bluuebunny/crossref_metadata_2025_split huggingface dataset:
DNA methylation analysis of amplicons from individuals exposed to maternal tobacco use during pregnancy, and offspring conduct problems in childhood and adolescence
Authors: Noble Alexandra J. , Pearson John F. , Noble Alasdair D. , Boden Joseph M. , Horwood L. John , Kennedy Martin A. , Osborne Amy J. 
Published: July 2020

AbstractMaternal tobacco smoking during pregnancy is a large driver of health inequalities and a higher prevalence of conduct problem has been observed in exposed offspring. Further, maternal tobacco use during pregnancy can also alter offspring DNA methylation. However, currently, limited molecular evidence have been found to support this observation. Thus we aim to examine the association between maternal tobacco use in pregnancy and whether offspring Conduct problems is mediated by tobacco exposure-induced via DNA methylation differences. Understanding the etiology of the causal link will be crucial in the early identification and treatment of CP in children and adolescents. DNA was sourced from the Christchurch Health and Development Study, a longitudinal birth cohort studied for over 40 years in New Zealand. Bisulfite-based amplicon sequencing of 10 loci known to play a role in neurodevelopment, or with associations with CP phenotypes, was undertaken. We identified nominally significant differential DNA methylation at specific CpG sites inCYP1A1, ASH2LandMEF2Cin individuals with Conduct problems who were exposed to tobaccoin utero.We conclude that environmentally-induced DNA methylation differences could play a role in the observed link between maternal tobacco use during pregnancy and childhood/adolescent Conduct problems However, larger sample sizes are needed to produce an adequate amount of power to investigate this interaction further.
Stability of the pH-Dependent Parallel-Stranded d(CGA) Motif
Authors: Luteran E. M. , Kahn J. D. , Paukstelis P. J. 
Published: July 2020

ABSTRACTNon-canonical DNA structures that retain programmability and structural predictability are increasingly being used in DNA nanotechnology applications, where they offer versatility beyond traditional Watson-Crick interactions. The d(CGA) triplet repeat motif is structurally dynamic and can transition between parallel-stranded homo-base paired duplex and anti-parallel unimolecular hairpin in a pH-dependent manner. Here, we evaluate the thermodynamic stability and nuclease sensitivity of oligonucleotides composed of the d(CGA) motif and several structurally related sequence variants. These results show that the structural transition resulting from decreasing the pH is accompanied by both a significant energetic stabilization and decreased nuclease sensitivity as unimolecular hairpin structures are converted to parallel-stranded homo-base paired duplexes. Furthermore, the stability of the parallel-stranded duplex form can be altered by changing the 5′-nucleobase of the d(CGA) triplet and the frequency and position of the altered triplets within long stretches of d(CGA) triplets. This work offers insight into the stability and versatility of the d(CGA) triplet repeat motif and provides constraints for using this pH-adaptive structural motif for creating DNA-based nanomaterials.STATEMENT OF SIGNIFICANCEThis article addresses the stability of the d(CGA) triplet motif and variants in solution. Our study reveals changes in thermodynamic stability and nuclease resistance in response to pH. The identity of the 5′-nucleobase within each triplet and the position and frequency of different triplets within stretches of d(CGA) triplets can tune parallel-stranded duplex stability. This tunability can be used for nanotechnological applications where the specificity of the 5′-nucleobase pairing interaction is used to order of long stretches of d(CGA) triplets. These results can inform the rational design of pH-sensitive structurally switchable DNA-based nanomaterials.
Heart Snapshot: a broadly validated smartphone measure of VO2max for collection of real world data
Authors: Webster Dan E. , Tummalacherla Meghasyam , Higgins Michael , Wing David , Ashley Euan , Kelly Valerie E. , McConnell Michael V. , Muse Evan D. , Olgin Jeff , Mangravite Lara , Godino Job , Kellen Michael , Omberg Larsson 
Published: July 2020

AbstractExpanding access to precision medicine will increasingly require that patient biometrics can be measured in remote care settings. VO2max, the maximum volume of oxygen usable during intense exercise, is one of the most predictive biometric risk factors for cardiovascular disease, frailty, and overall mortality.1,2However, VO2max measurements are rarely performed in clinical care or large-scale epidemiologic studies due to the high cost, participant burden, and need for specialized laboratory equipment and staff.3,4To overcome these barriers, we developed two smartphone sensor-based protocols for estimating VO2max: a generalization of a 12-minute run test (12-MRT) and a submaximal 3-minute step test (3-MST). In laboratory settings, Lins concordance for these two tests relative to gold standard VO2max testing waspc=0.66 for 12-MRT andpc=0.61 for 3-MST. Relative to “silver standards”5(Cooper/Tecumseh protocols), concordance waspc=0.96 andpc=0.94, respectively. However, in remote settings, 12-MRT was significantly less concordant with gold standard (pc=0.25) compared to 3-MST (pc=0.61), though both had high test-retest reliability (ICC=0.88 and 0.86, respectively). These results demonstrate the importance of real-world evidence for validation of digital health measurements. In order to validate 3-MST in a broadly representative population in accordance with theAll of UsResearch Program6for which this measurement was developed, the camera-based heart rate measurement was investigated for potential bias. No systematic measurement error was observed that corresponded to skin pigmentation level, operating system, or cost of the phone used. The smartphone-based 3-MST protocol, here termedHeart Snapshot, maintained fidelity across demographic variation in age and sex, across diverse skin pigmentation, and between iOS and Android implementations of various smartphone models. The source code for these smartphone measurements, along with the data used to validate them,6are openly available to the research community.
Simultaneous quantification of mRNA and protein in single cells reveals post-transcriptional effects of genetic variation
Authors: Brion Christian , Lutz Sheila , Albert Frank W. 
Published: July 2020

AbstractTrans-acting DNA variants may specifically affect mRNA or protein levels of genes located throughout the genome. However, prior work comparedtrans-acting loci mapped in studies performed separately or with limited statistical power. Here, we developed a CRISPR-based system for simultaneous quantification of mRNA and protein of a given gene via dual fluorescent reporters in single, live cells of the yeastSaccharomyces cerevisiae. In large populations of recombinant cells from a cross between two genetically divergent strains, we mapped 86trans-acting loci affecting the expression of ten genes. Less than 20% of these loci had concordant effects on mRNA and protein of the same gene. Most loci influenced protein but not mRNA of a given gene. One such locus harbored a premature stop variant in theYAK1kinase gene that had specific effects on protein or mRNA of dozens of genes. These results demonstrate complex, post-transcriptional genetic effects on gene expression.One sentence summaryA CRISPR-based dual reporter assay enables genetic mapping of DNA variants that specifically affect mRNA or protein levels intrans.
A free boundary mechanobiological model of epithelial tissues
Authors: Tambyah Tamara A. , Murphy Ryan J. , Buenzli Pascal R. , Simpson Matthew J. 
Published: July 2020

AbstractIn this study, we couple intracellular signalling and cell–based mechanical properties to develop a novel free boundary mechanobiological model of epithelial tissue dynamics. Mechanobiological coupling is introduced at the cell level in a discrete modelling framework, and new reaction–diffusion equations are derived to describe tissue–level outcomes. The free boundary evolves as a result of the underlying biological mechanisms included in the discrete model. To demonstrate the accuracy of the continuum model, we compare numerical solutions of the discrete and continuum models for two different signalling pathways. First, we study the Rac–Rho pathway where cell– and tissue–level mechanics are directly related to intracellular signalling. Second, we study an activator–inhibitor system which gives rise to spatial and temporal patterning related to Turing patterns. In all cases, the continuum model and free boundary condition accurately reflect the cell–level processes included in the discrete model.
A combined microphysiological-computational omics approach in dietary protein evaluation
Authors: Jochems Paulus G.M. , Keusters Willem R. , America Antoine H.P. , Rietveld Pascale C.S. , Bastiaan-Net Shanna , Ariëns Renata M.C. , Tomassen Monic M.M. , Lewis Fraser , Li Yang , Westphal Koen G.C. , Garssen Johan , Wichers Harry J. , van Bergenhenegouwen Jeroen , Masereeuw Rosalinde 
Published: July 2020

AbstractThe ever-growing world population puts pressure on food security. To tackle this, waste stream proteins and novel protein sources need to be evaluated for nutritional value, which requires information on digesta peptide composition in comparison to established protein sources and coupling to biological parameters. Here, we present a novel combined experimental and computational approach comparing seventeen protein sources with cow’s whey protein (WPC) as benchmark.In vitrodigestion was followed by proteomics analysis and statistical model clustering based on Bayesian Information Criterion. Next, we incorporated functional protein data after evaluating the effects of eighteen protein digests on intestinal barrier integrity, viability, brush border enzyme activity and immune parameters using a bioengineered intestine. Our data show that a holistic approach allows evaluating a dietary protein’s potential for delivery of bioactive peptides, where protein source (animal, plant or novel source-derived) does not seem to be the driving force for clustering.
Highly Sensitive Detection ofCampylobacter spp.in Chicken Meat using a Silica Nanoparticle Enhanced Dot Blot DNA Biosensor
Authors: Vizzini Priya , Manzano Marisa , Farre Carole , Meylheuc Thierry , Chaix Carole , Ramarao Nalini , Vidic Jasmina 
Published: July 2020

AbstractPaper-based DNA biosensors are powerful tools in point-of-care diagnostics since they are affordable, portable, user-friendly, rapid and robust. However, their sensitivity is not always as high as required to enable DNA quantification. To improve the response of standard dot blots, we have applied a new enhancement strategy that increases the sensitivity of assays based on the use of biotinylated silica-nanoparticles (biotin-Si-NPs). After immobilization of a genomicCampylobacterDNA onto a paper membrane, and addition of a biotinylated-DNA detection probe, hybridization was evidenced using streptavidin-conjugated to horseradish peroxidase (HRP) in the presence of luminol and H2O2. Replacement of the single biotin by the biotin-Si-NPs boosted on average a 30 fold chemiluminescent read-out of the biosensor. Characterization of biotin-Si-NPs onto a paper with immobilized DNA was done using a scanning electron microscope. A limit of detection of 3 pg/μL of DNA, similar to the available qPCR kits, is achieved, but it is cheaper, easier and avoids inhibition of DNA polymerase by molecules from the food matrices. We demonstrated that the new dot blot coupled to biotin-Si-NPs successfully detectedCampylobacterfrom naturally contaminated chicken meat, without needing a PCR step. Hence, such an enhanced dot blot paves the path to the development of a portable and multiplex paper based platform for point-of-care screening of chicken carcasses forCampylobacter.Graphical abstract
Peopling of Tibet Plateau and multiple waves of admixture of Tibetans inferred from both modern and ancient genome-wide data
Authors: Wang Mengge , Zou Xing , Ye Hui-Yuan , Wang Zheng , Liu Yan , Liu Jing , Wang Fei , Yao Hongbin , Chen Pengyu , Tao Ruiyang , Wang Shouyu , Wei Lan-Hai , Tang Renkuan , Wang Chuan-Chao , He Guanglin 
Published: July 2020

AbstractArcheologically attested human occupation on the Tibet Plateau (TP) can be traced back to 160 thousand years ago (kya, Xiahe) via archaic people and 30~40 kya via anatomically modern human in Nwya Devu. However, the past human movements and peopling of the TP keep in its infancy in the modern/ancient DNA studies. Here, we performed the first modern/ancient genomic meta-analysis among 3,017 Paleolithic to present-day eastern Eurasian genomes (2,444 modern individuals from 183 populations (including 98 Ü-Tsang/Ando/Kham Tibetans) and 573 ancients (including 161 Chinese ancients first meta-analyzed here)). Closer genetic connection between ancient-modern highland Tibetans and lowland island/coastal Neolithic northern East Asians was identified, reflecting the main ancestry of high-altitude Tibeto-Burman speakers originated from the ancestors of Houli/Yangshao/Longshan ancients in the middle and lower Yellow River basin, consistent with the common North-China origin of Sino-Tibetan language and dispersal pattern of millet farmers. Although the shared common northern East Asian lineage between Tibetans and lowland East Asians, we still identified genetic differentiation between Highlanders and lowland northern East Asians, the former harboring more deeply diverged Hoabinhian/Onge ancestry and the latter possessing more modern Neolithic southern East Asian and Siberian ancestry, which suggested the co-existence of Paleolithic and Neolithic ancestries in modern and Neolithic East Asian Highlanders. Tibetans from Ü-Tsang/Ando/Kham Tibetan regions showed strong population stratifications consistent with their cultural backgrounds and geographic terrains (showed as barriers for human movements): stronger Chokhopani affinity in Ü-Tsang Tibetans, more western Eurasian ancestry in Ando and greater Neolithic southern East Asian ancestry in Kham Tibetan. Modern combined ancient genomes documented multiple waves of human migrations in TP past: the first layer of local Hunter-Gatherer mixed with Qijia Farmer arose the Chokhopani-associated Proto-Tibetan-Burman, admixture with the additional genetic materials from the western Eurasian steppe, Yellow River and Yangtze River respectively gave rise to modern Ando, Ü-Tsang and Kham Tibetans.
Can we improve slow learning in cerebellar patients?
Authors: Hulst Thomas , Mamlins Ariels , Frens Maarten , Chang Dae-In , Göricke Sophia L. , Timmann Dagmar , Donchin Opher 
Published: July 2020

AbstractCerebellar patients are impaired in motor adaptation. Further, motor adaptation can be divided into a fast component and a slow component, and the cerebellum is known to be especially crucial for the slow component. We tested whether the cerebellar deficit in motor adaptation can be ameliorated by training paradigms targeting slow learning using four visuomotor tasks: standard, gradual, overlearning and long intertrial intervals. We measured slow learning in patients and age-matched controls using a standard paradigm developed for reaching movements by Smith in 2006. The paradigm quantifies slow learning as the magnitude of spontaneous recovery of a previously learned and washed-out adaptation. Cerebellar patients had slower learning and reached a lower level of final adaptation, as seen in previous studies. Nevertheless, both groups had robust spontaneous recovery. Moreover, spontaneous recovery was increased in both groups in the overlearning paradigm with no significant difference between them. Computational modeling suggested that increased spontaneous recovery in the Control group reflects a changed slow adaptation system. That is, in the overlearning in controls, the slow system forgot more slowly and had a slower response to errors. In contrast, the same modeling suggests that no such change in the slow system occurred in the Cerebellar group. Rather, increased spontaneous recovery in this group seems to be the result of greater accumulated slow adaptation in the overlearning. We used our modeling results to predict that overlearning should have slower adaptation in the counterperturbation. Modeling further suggested we would not see these difference in the cerebellar patients. Follow-up analysis confirmed these model predictions. Taken together, our results imply that residual slow learning in cerebellar patients is expressed during increased training trials, but the primary cerebellar deficit is not improved.
From Chemoproteomic-Detected Amino Acids to Genomic Coordinates: Insights into Precise Multi-omic Data Integration
Authors: Palafox Maria F. , Arboleda Valerie A. , Backus Keriann M. 
Published: July 2020

ABSTRACTThe integration of proteomic, transcriptomic, and genetic-variant annotation data will improve our understanding genotype-phenotype associations. Due, in part, to challenges associated with accurate inter-database mapping, such multi-omic studies have not extended to chemoproteomics, a method that measure the intrinsic reactivity and potential ‘druggability’ of nucleophilic amino acid side chains. Here, we evaluated two mapping approaches to match chemoproteomic-detected cysteine and lysine residues with their genetic coordinates. Our analysis reveals that databases update cycles and reliance on stable identifiers can lead to pervasive misidentification of labeled residues. Enabled by this examination of mapping strategies, we then integrated our chemoproteomic data within silicogenerated predictions of genetic variant pathogenicity, which revealed that codons of highly reactive cysteines are enriched for genetic variants that are predicted to be more deleterious. Our study provides a roadmap for more precise inter-database comparisons and points to untapped opportunities to improve the predictive power of pathogenicity scores and to advance prioritization of putative druggable sites through integration of predictions of pathogenicity with chemoproteomic datasets.
Low cell number proteomic analysis using in-cell protease digests reveals a robust signature for cell cycle state classification
Authors: Van Kelly , al-Rawi Aymen , Lewis David , Kustatscher Georg , Ly Tony 
Published: July 2020

AbstractComprehensive proteome analysis of rare cell phenotypes remains a significant challenge. We report a method for low cell number mass spectrometry (MS)-based proteomics using protease digestion of mildly formaldehyde-fixed cellsin cellulo, which we call the ‘in-cell digest’. We combined this with AMPL (Averaged MS1 Precursor Library Matching) to quantitatively characterise proteomes from low cell numbers of human lymphoblasts. 4,500 proteins were detected from 2,000 cells and 2,500 proteins were quantitated from 200 lymphoblasts. The ease of sample processing and high sensitivity makes this method exceptionally suited for the proteomic analysis of rare cell states, including immune cell subsets and cell cycle subphases.To demonstrate the method, we characterised the proteome changes across 16 cell cycle states isolated from an asynchronous TK6 human lymphoblast culture, avoiding synchronization. States included late mitotic cells present at extremely low frequency. We identified 119 pseudoperiodic proteins (PsPs) that vary across the cell cycle. Clustering of the PsPs showed abundance patterns consistent with ‘waves’ of protein degradation in late S, at the G2&M border, mid-mitosis and at mitotic exit. These clusters were distinguished by significant differences in predicted nuclear localization and interaction with the APC/C. The dataset also identifies putative APC/C substrates in mitosis and the temporal order in which they are targeted for degradation.We demonstrate that a protein signature made of these 119 high confidence cell cycle regulated proteins can be used to perform unbiased classification of proteomes into cell cycle states. We applied this signature to 296 proteomes that encompass a range of quantitation methods, cell types, and experimental conditions. The analysis confidently assigns a cell cycle state for 49 proteomes, including correct classification for proteomes from synchronized cells. We anticipate this robust cell cycle protein signature will be crucial for classifying cell states in single cell proteomes.
Prediction ofBurkholderia pseudomalleiDsbA substrates identifies potential virulence factors and vaccine targets
Authors: Vezina Ben , Petit Guillaume A. , Martin Jennifer L. , Halili Maria A. 
Published: July 2020

AbstractIdentification of bacterial virulence factors is critical for understanding disease pathogenesis, drug discovery and vaccine development. In this study we used two approaches to predict virulence factors ofBurkholderia pseudomallei, the Gram-negative bacterium that causes melioidosis.B. pseudomalleiis naturally antibiotic resistant and there are no melioidosis vaccines. To identifyB. pseudomalleiprotein targets for drug discovery and vaccine development, we chose to search for substrates of theB. pseudomalleiperiplasmic disulfide bond forming protein A (DsbA). DsbA introduces disulfide bonds into extra-cytoplasmic proteins and is essential for virulence in many Gram-negative organism, includingB. pseudomallei. The first approach to identifyB. pseudomalleiDsbA virulence factor substrates was a large-scale genomic analysis of 511 uniqueB. pseudomalleidisease-associated strains. This yielded 4,496 core gene products, of which we hypothesise 263 are DsbA substrates. Manual curation of the 263 mature proteins yielded 73 associated with disease pathogenesis or virulence. These were screened for structural homologues to predict potential B-cell epitopes. In the second approach, we searched theB. pseudomalleigenome for homologues of the more than 90 known DsbA substrates in other bacteria. Using this approach, we identified 15 potentialB. pseudomalleiDsbA virulence factor substrates. Two putativeB. pseudomalleivirulence factors were identified by both methods: homologues of PenI family β-lactamase and of succinate dehydrogenase flavoprotein subunit. These two proteins could serve as high priority targets for futureB. pseudomalleivirulence factor characterization.
The major genetic risk factor for severe COVID-19 is inherited from Neandertals
Authors: Zeberg Hugo , Pääbo Svante 
Published: July 2020

AbstractA recent genetic association study (Ellinghauset al.2020) identified a gene cluster on chromosome 3 as a risk locus for respiratory failure in SARS-CoV-2. Recent data comprising 3,199 hospitalized COVID-19 patients and controls reproduce this and find that it is the major genetic risk factor for severe SARS-CoV-2 infection and hospitalization (COVID-19 Host Genetics Initiative). Here, we show that the risk is conferred by a genomic segment of ~50 kb that is inherited from Neandertals and occurs at a frequency of ~30% in south Asia and ~8% in Europe.