bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dimerization of rhomboid protease RHBDL2 in lipid membranes addressed by FRET with MC simulations
Authors: Škerle J. , Humpolíčková J. , Rampírová P. , Poláchová E. , Adámková L. , Suchánková A. , Jakubec D. , Strisovsky K. 
Published: March 2018

AbstractMany membrane proteins are thought to function as oligomers, but measuring membrane protein dimerization in native lipid membranes is particularly challenging. Förster resonance energy transfer (FRET) and fluorescence correlation spectroscopy (FCS) are non-invasive, optical methods of choice that have been applied to the analysis of dimerization of single-spanning membrane proteins. The effects inherent to such two-dimensional systems, such as excluded volume of polytopic transmembrane proteins, proximity FRET, and rotational diffusion of fluorophore dipoles, complicate interpretation of FRET data and have not been typically accounted for. Here, using FRET and FCS we introduce methods to measure surface protein density and to estimate kappa squared, and we use Monte Carlo simulations of the FRET data to account for the proximity FRET effect occurring in confined 2D environments. We then use FRET and FCS to analyze the dimerization of human rhomboid protease RHBDL2 in its native lipid membranes. While previous reports have proposed that rhomboid proteases dimerize and this allosterically activates them, we find no evidence for stable oligomers of RHBDL2 in lipid membranes of human cells. This indicates that the rhomboid transmembrane core may be intrinsically monomeric. Finally, our findings will find use in the application of FRET and FCS for the analysis of oligomerization of transmembrane proteins in lipid membranes.
Monitoring Unfolding of Titin I27 single- and bi-Domain with High-Pressure NMR Spectroscopy
Authors: Herrada I. , Barthe P. , Van Heusden M. , DeGuillen K , Mammri L , Delbecq S. , Rico F. , Roumestand C. 
Published: March 2018

ABSTRACTA complete description of the pathways and mechanisms of protein folding requires a detailed structural and energetic characterization of the folding energy landscape. Simulations, when corroborated by experimental data yielding global information on the folding process, can provide this level of insight. Molecular Dynamics (MD) has been associated often to force spectroscopy experiments to decipher the unfolding mechanism of titin Ig-like single- or multi-domain, the giant multi-modular protein from sarcomere, yielding information on the sequential events during titin unfolding under stretching. Here, we used high-pressure NMR to monitor the unfolding of titin I27 Ig-like single-domain and tandem. Since this method brings residue-specific information on the folding process, it can provide quasi-atomic details on this process, without the help of MD simulations. Globally, the results of our high-pressure analysis are in agreement with previous results obtained by the association of experimental measurements and MD simulation and/or protein engineering, although the intermediate folding state caused by the early detachment of the AB ß-sheet, often reported in previous works based on MD or force spectroscopy, cannot be detected. On the other hand, the A’G parallel ß-sheet of the ß-sandwich has been confirmed as the Achilles heel of the 3D scaffold: its disruption yields complete unfolding, with very similar characteristics (free energy, unfolding volume, kinetics constant rates) for the two constructs.
Beta diversity patterns derived from island biogeography theory
Authors: Lu Muyang , Vasseur David , Jetz Walter 
Published: March 2018

AbstractThe Theory of Island Biogeography (TIB) has been successful in predicting alpha diversity patterns such as species-area relationships and species-abundance distributions. Although beta diversity (i.e. the dissimilarity of community composition) has long been recognized as an important element of the TIB and is crucial for understanding community assembly processes, it has never been formally incorporated into the theory. Here we derive theoretical predictions for the expected pairwise beta diversity values under a species-level neutral scenario where all species have equal colonization and extinction rates. We test these predictions for the avian community composition of 42 islands (and 93 species) in the Thousand Island Lake, China. We find that alpha diversity patterns alone do not distinguish a species-level neutral model from a non-neutral model. In contrast, beta diversity patterns clearly reject a species-level neutral model. We suggest that the presented theoretical integration beta diversity offers a powerful path for testing the presence of neutral processes in ecology and biogeography.
Adaptation to local climate in a multi-trait space: evidence from silver fir (Abies albaMill.) populations across a heterogeneous environment
Authors: Csilléry Katalin , Ovaskainen Otso , Sperisen Christoph , Widmer Alex , Gugerli Felix 
Published: March 2018

AbstractAttempts to identify and understand selection pressures responsible for local adaptation are central to evolutionary research. We tested whether populations of silver fir (Abies albaMill.), sampled across a heterogeneous environment, have more strongly diverged at quantitative traits than expected from genetic drift. We genotyped 387 trees from 19 Swiss populations at 374 single-nucleotide polymorphisms (SNPs) to estimate their demographic distances, and used these to generate a null expectation for divergence in a multi-trait space including morphology and life-history traits obtained from a published common garden trial. Local soil and historical climate data were used to identify the selective environment of the source populations. Our results revealed a strong selection on height driven by temperature: trees from warm sites evolved to become taller than those from cooler sites. The evolution of growth rate, growth duration and bud break were correlated, and populations evolved towards two extreme strategies, “start early and grow slow” or “start late and grow fast”, driven by precipitation seasonality. We conclude that local climate has shaped the morphology and life-history of silver fir populations since they recolonized the Alps. Our methodology provides a show-case for empirical evaluation of adaptive evolutionary strategies combining genetic data and common gardens.
Reductions in Retrieval Competition Predict the Benefit of Repeated Testing
Authors: Rafidi Nicole S. , Hulbert Justin C. , Pacheco Paula , Norman Kenneth A. 
Published: March 2018

AbstractRepeated testing leads to improved long-term memory retention compared to repeated study, but the mechanism underlying this improvement remains controversial. In this work, we test the hypothesis that retrieval practice benefits subsequent recall by reducing competition from related memories. This hypothesis implies that the degree of reduction in competition between retrieval practice attempts should predict subsequent memory for practiced items. To test this prediction, we collected electroencephalography (EEG) data across two sessions. In the first session, participants practiced selectively retrieving exemplars from superordinate semantic categories (high competition), as well as retrieving the names of the superordinate categories from exemplars (low competition). In the second session, participants repeatedly studied and were tested on Swahili-English vocabulary. One week after session two, participants were again tested on the vocabulary. We trained a within-subject classifier on the data from session one to distinguish high and low competition states.We then used this classifier to measure competition across multiple retrieval practice attempts in the second session. The degree to which competition decreased for a given vocabulary word predicted whether that item was subsequently remembered in the third session. These results are consistent with the hypothesis that repeated testing improves retention by reducing competition.
Peptidoglycan precursor synthesis along the sidewall of pole-growing mycobacteria
Authors: García-Heredia Alam , Pohane Amol Arunrao , Melzer Emily S. , Carr Caleb R. , Fiolek Taylor J. , Rundell Sarah R. , Lim Hoong Chuin , Wagner Jeffrey , Morita Yasu S. , Swarts Benjamin M. , Carr Caleb R. , Siegrist M. Sloan 
Published: March 2018

Abstractd-amino acid probes label cell wall peptidoglycan at both the poles and sidewall of pole-growing mycobacteria. Since peptidoglycan assembly along the cell periphery could provide a rapid, growth-independent means by which to edit the cell wall, we sought to clarify the precise metabolic fates of these probes.d-amino acid monopeptides were incorporated into peptidoglycan byl,d-transpeptidase remodeling enzymes to varying extents. Dipeptides were incorporated into cytoplasmic precursors. While dipeptide-marked peptidoglycan synthesis at the poles was associated with cell elongation, synthesis along the periphery was highly responsive to cell wall damage. Our observations suggest a post-expansion role for peptidoglycan assembly along the mycobacterial sidewall and provide a conceptual framework for understanding cell wall robustness in the face of polar growth.
Glucocorticoid receptor gene polymorhisms and breast cancer: significant association in cancerous tissue samples from Turkish patients
Authors: Akyildiz Gürkan , Akkіprіk Mustafa , Özer Ayşe , Kaya Handan , Güllüoğlu Bahadіr M. , Aral Cenk 
Published: March 2018

AbstractBackground and Aims: Glucocorticoid receptor (GR) has been postulated to serve an important role in normal breast and breast carcinoma. On the other hand, studies on its common polymorphisms with breast cancer are very limited. In this study, we aimed to assess the presence and frequency of 4 common polymorphisms of the GR gene in the cancerous tissue samples from breast cancer patients in the Turkish population and compare them with healthy individuals. Methods: DNA samples from 86 Turkish female breast cancer patients and 86 healthy controls analysed for BclI, Tth111I, N363S and ER22/23EK polymorphisms of GR gene by PCR-RFLP. Results: N363S polymorphism was not observed in study samples. Frequency of BclI polymorphism did not differ between cases and controls but it associated with family history of cancer. The polymorphic allele frequency of Tth111I and ER22/23EK was found to be higher in cases compared to healthy samples (p<0.05). Also, a haplotype containing polymorphic variants of these two polymorphisms found to be associated with breast cancer. Conclusion: The data presented here suggest that polymorphisms of GR gene may be an important risk factor for breast cancer predisposition.
A unifying framework for summary statistic imputation
Authors: Wu Yue , Eskin Eleazar , Sankararaman Sriram 
Published: March 2018

AbstractImputation has been widely utilized to aid and interpret the results of Genome-Wide Association Studies(GWAS). Imputation can increase the power to identify associations when the causal variant was not directly observed or typed in the GWAS. There are two broad classes of methods for imputation. The first class imputes the genotypes at the untyped variants given the genotypes at the typed variants and then performs a statistical test of association at the imputed variants. The second class of methods, summary statistic imputation, directly imputes the association statics at the untyped variants given the association statistics observed at the typed variants. This second class of methods is appealing as it tends to be computationally efficient while only requiring the summary statistics from a study while the former class requires access to individual-level data that can be difficult to obtain. The statistical properties of these two classes of imputation methods have not been fully understood. In this paper, we show that the two classes of imputation methods are equivalent,i.e., have identical asymptotic multivariate normal distributions with zero mean and minor variations in the covariance matrix, under some reasonable assumptions. Using this equivalence, we can understand the effect of imputation methods on power. We show that a commonly employed modification of summary statistic imputation that we term summary statistic imputation with variance re-weighting generally leads to a loss in power. On the other hand, our proposed method, summary statistic imputation without performing variance re-weighting, fully accounts for imputation uncertainty while achieving better power.
Surveillance of CKD epidemiology in the US – a joint analysis of NHANES and KEEP
Authors: Myers OB , Pankratz VS , Norris KC , Vassalotti JA , Unruh M , Argyropoulos C 
Published: March 2018

AbstractChronic Kidney Disease (CKD), is highly prevalent in the United States. Epidemiological systems for surveillance of CKD rely on data that are based solely on the NHANES survey, which does not include many patients with the most severe and less frequent forms of CKD. We investigated the feasibility of estimating CKD prevalence from the large-scale community disease detection Kidney Early Evaluation and Program (KEEP, n = 127,149). We adopted methodologies from the field of web surveys to address the self-selection bias inherent in KEEP. Primary outcomes studied were CKD Stage 3-5 (estimated glomerular filtration rate [eGFR] <60 mL/min/1.73m2, and CKD Stage 4-5 (eGFR <30 mL/min/1.73m2). The unweighted prevalence of Stage 4-5 CKD was higher in KEEP (1.00%, 95%CI: 0.94-1.05%) than in NHANES (0.51%, 95% CI: 0.43-0.59%). Application of a selection model with IPW of variables related to demographics, recruitment and socio-economic factors resulted in estimates similar to NHANES (0.55%, 95% CI: 0.50-0.60%). Weighted prevalence of Stages 3-5 CKD in KEEP was 6.45% (95% CI: 5.70 7.28%) compared to 6.73% (95% CI: 6.30-7.19%) for NHANES. Application of methodologies that address the self-selection bias in the KEEP program may allow the use of this large, geographically diverse dataset for CKD surveillance.
Effects of exclusive breastfeeding on infant gut microbiota: a meta-analysis across studies and populations
Authors: Ho Nhan T. , Li Fan , Lee-Sarwar Kathleen A. , Tun Hein M. , Brown Bryan , Pannaraj Pia S. , Bender Jeffrey M. , Azad Meghan B. , Thompson Amanda L. , Weiss Scott T. , Azcarate-Peril M. Andrea , Litonjua Augusto A. , Kozyrskyj Anita L. , Jaspan Heather B. , Aldrovandi Grace M. , Kuhn Louise 
Published: March 2018

AbstractLiterature regarding the differences in gut microbiota between exclusively breastfed (EBF) and non-EBF infants is meager with large variation in methods and results. We performed a meta-analysis of seven studies (a total of 1825 stool samples from 684 infants) to investigate effects of EBF compared to non-EBF on infant gut microbiota across different populations. In the first 6 months of life, overall bacterial diversity, gut microbiota age, relative abundances of Bacteroidetes and Firmicutes and microbial-predicted pathways related to carbohydrate metabolism were consistently increased; while relative abundances of pathways related to lipid, vitamin metabolism and detoxification were decreased in non-EBF vs. EBF infants. The perturbation in microbial-predicted pathways associated with non-EBF was larger in infants delivered by C-section than delivered vaginally. Longer duration of EBF mitigated diarrhea-associated gut microbiota dysbiosis and the effects of EBF persisted after 6 months of age. These consistent findings across vastly different populations suggest that one of the mechanisms of short and long-term benefits of EBF may be alteration in gut microbes.
Classification of early and late stage Liver Hepatocellular Carcinoma patients from their genomics and epigenomics profiles
Authors: Kaur Harpreet , Bhalla Sherry , Raghava GPS 
Published: March 2018

AbstractBackgroundLiver Hepatocellular Carcinoma (LIHC) is the second major cancer worldwide, responsible for millions of premature deaths every year. Prediction of clinical staging is vital to implement optimal therapeutic strategy and prognostic prediction in cancer patients. However, to date, no method has been developed for predicting stage of LIHC from genomic profile of samples.ResultsIn current study, in silico models have been developed for classifying LIHC patients in early and late stage using RNA expression and DNA methylation data. The Cancer Genome Atlas (TCGA) dataset contains 173 early and 177 late stage samples of LIHC, was extensively analysed to identify differentially expressed RNA transcripts and methylated CpG sites that can discriminate early and late stages of LIHC samples with high precision. Naive Bayes model developed using 51 features that combine 21 CpG methylation sites and 30 RNA transcripts achieved maximum MCC 0.58 with accuracy 78.87% on validation dataset. Further, we also analysed genomics and epigenomics profiles of normal and LIHC samples and developed model to classify LIHC samples with AUROC 0.99. In addition, multiclass models developed for classifying samples in normal, early and late stage of cancer and achieved accuracy of 76.54% and AUROC of 0.86.ConclusionOur study reveals stage prediction of LIHC samples with high accuracy based on genomics and epigenomics profiling is a challenging task in comparison to classification of LIHC and normal samples. Comprehensive analysis, differentially expressed RNA transcripts, methylated CpG sites in LIHC samples and prediction models are available from CancerLSP ( http://webs.iiitd.edu.in/raghava/cancerlsp/).
Complementary responses of morphology and physiology enhance the stand‐scale production of a model invasive species under elevated CO2 and nitrogen
Authors: Mozdzer Thomas J. , Caplan Joshua S. 
Published: March 2018

Abstract

Elevated atmospheric carbon dioxide (eCO2) concentrations and nitrogen (N) enrichment are known to enhance plant productivity and invasion. However, the implications of their interactive effects for plant productivity are not well understood, especially at the stand scale, presumably because morphological and physiological responses to these global change factors are rarely studied together in the field or assessed at the stand level.

We first determined how leaf‐level morphological and physiological traits responded to factorial combinations of ambient and elevated CO2 and N. We collected trait data from the model invasive species Phragmites australis (common reed) that were measured over 3 years in a long‐term global change field experiment. We then combined the trait data and additional descriptions of P. australis canopies in a simulation model of carbon assimilation to determine how morphology and physiology contribute to P. australis’ stand‐scale productivity.

At the leaf level, we found that light‐saturated rates of photosynthesis were strongly stimulated by eCO2 (37%) and that this effect was enhanced by increasing salinity. N had a smaller effect (17% stimulation) on physiological responses than eCO2, but leaf morphological traits responded primarily to N; plant height increased by 27% and leaf area increased by 47%.

Stand‐scale simulations demonstrated that that morphological and physiological adjustments induced approximately additive responses when P. australis experienced both eCO2 and N enrichment. The simulations also indicated that morphological changes (which were primarily associated with canopy size) influenced stand‐scale carbon assimilation more than physiological changes. Moreover, 97% of the N response was due to changes in morphology, whereas 62% of the eCO2 response was caused by physiological shifts.

Our analysis indicates that morphological and physiological trait responses to elevated CO2 and nitrogen are likely to enhance the productivity of P. australis in complementary ways, potentially accelerating its invasion in North America. Furthermore, our data suggest that changes in morphological traits may have a greater influence on carbon gain than leaf‐level physiology under near‐future environmental conditions. Our study also highlights the importance of accounting for both morphological and physiological responses when attempting to infer global change responses from leaf‐level data.

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Variation in home‐field advantage and ability in leaf litter decomposition across successional gradients
Authors: Veen G. F. (Ciska) , Keiser Ashley D. , van der Putten Wim H. , Wardle David A. 
Published: March 2018

Abstract

It is increasingly recognized that interactions between plants and soil (a)biotic conditions can influence local decomposition processes. For example, decomposer communities may become specialized in breaking down litter of plant species that they are associated with, resulting in accelerated decomposition, known as “home‐field advantage” (HFA). Also, soils can vary inherently in their capacity to degrade organic compounds, known as “ability.” However, we have a poor understanding how environmental conditions drive the occurrence of HFA and ability.

Here, we studied how HFA and ability change across three types of successional gradients: coastal sand dunes (primary succession), inland drift sands (primary succession) and ex‐arable fields (secondary succession). Across these gradients, litter quality (i.e. nutrient, carbon and lignin contents) increases with successional time for coastal dunes and decreases for the other two gradients.

We performed a 12‐months reciprocal litter transplant experiment under greenhouse conditions using soils and litters collected from early‐, mid‐ and late‐successional stages of each gradient.

We found that HFA and ability did not consistently shift with successional stage for all gradients, but were instead specific for each type of successional gradient. In coastal dunes, HFA was positive for early‐successional litter, in drift, sands it was negative for mid‐successional litter, and for ex‐arable fields, HFA increased with successional time. Ability of decomposer communities was highest in mid‐successional stages for coastal dunes and drift sands, but for ex‐arable fields, ability decreased throughout with successional time. High HFA was related to high litter C content and soil and organic matter content in soils and to low litter and soil nutrient concentrations. Ability did not consistently occur in successional stages with high or low litter quality.

Synthesis. Our findings show that specific environmental conditions, such as changes in litter or soil quality, along environmental gradients can shape the influence of HFA and ability on decomposition. In sites with strong HFA or ability, interactions between plants, litter and decomposer communities will be important drivers of nutrient cycling and hence have the potential to feedback to plant growth.

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