bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multiplexed competition in a synthetic squid light organ microbiome using barcode-tagged gene deletions
Authors: Burgos Hector L. , Burgos Emanuel F. , Steinberger Andrew J. , Suen Garret , Mandel Mark J. 
Published: August 2020

AbstractBeneficial symbioses between microbes and their eukaryotic hosts are ubiquitous and have widespread impacts on host health and development. The binary symbiosis between the bioluminescent bacteriumVibrio fischeriand its squid hostEuprymna scolopesserves as a model system to study molecular mechanisms at the microbe-animal interface. To identify colonization factors in this system, our lab previously conducted a global transposon insertion sequencing (INSeq) screen and identified over 300 putative novel squid colonization factors inV. fischeri. To pursue mechanistic studies on these candidate genes, we present an approach to quickly generate barcode-tagged gene deletions and perform high-throughput squid competition experiments with detection of the proportion of each strain in the mixture by barcode sequencing (BarSeq). Our deletion approach improves on previous techniques based on splicing-by-overlap extension PCR (SOE-PCR) andtfoX-based natural transformation by incorporating a randomized barcode that results in unique DNA sequences within each deletion scar. Amplicon sequencing of the pool of barcoded strains before and after colonization faithfully reports on known colonization factors and provides increased sensitivity over colony counting methods. BarSeq enables rapid and sensitive characterization of the molecular factors involved in establishing theVibrio-squid symbiosis and provides a valuable tool to interrogate the molecular dialogue at microbe-animal host interfaces.ImportanceBeneficial microbes play essential roles in the health and development of their hosts. However, the complexity of animal microbiomes and general genetic intractability of their symbionts have made it difficult to study the coevolved mechanisms for establishing and maintaining specificity at the microbe-animal host interface. Model symbioses are therefore invaluable for studying the mechanisms of beneficial microbe-host interactions. Here we present a combined barcode-tagged deletion and BarSeq approach to interrogate the molecular dialogue that ensures specific and reproducible colonization of the Hawaiian bobtail squid byVibrio fischeri. The ability to precisely manipulate the bacterial genome, combined with multiplex colonization assays, will accelerate the use of this valuable model system for mechanistic studies of how environmental microbes—both beneficial and pathogenic—colonize specific animal hosts.
Hidden layers of density dependence in consumer feeding rates
Authors: Stouffer Daniel B. , Novak Mark 
Published: August 2020

AbstractFunctional responses relate a consumer’s feeding rates to variation in its abiotic and biotic environment, providing insight into consumer behavior and fitness, and underpinning population and food-web dynamics. Despite their broad relevance and long-standing history, we show here that the types of density dependence found in classic resource- and consumer-dependent functional-response models equate to strong and often untenable assumptions about the independence of processes underlying feeding rates. We first demonstrate mathematically how to quantify non-independence between feeding and consumer interference and between feeding on multiple resources. We then analyze two large collections of functional-response datasets to show that non-independence is pervasive and borne out in previously-hidden forms of density dependence. Our results provide a new lens through which to view variation in consumer feeding rates and disentangle the biological underpinnings of species interactions in multi-species contexts.
Nanolipoprotein mediated Her2 protein transfection induces malignant transformation in human breast acinar cultures
Authors: He Wei , Evans Angela C. , Coleman Matthew , Robertson Claire 
Published: August 2020

AbstractHer2 overexpression is associated with an aggressive form of breast cancer and malignant transformation. We sought to determine if a nano-carrier system could introduce Her2 protein to non-malignant cells and determine the effects on cell phenotype and transcriptome. With stimulation with Her2-NLPs, we observed uptake of Her2 protein and a decreased probability of individual non-malignant cells forming polar growth arrested acinar-like structures. The NLP delivery system alone or Her2-NLPs plus trastuzumab showed no effect on acinar organization rate. Transcriptomics revealed essentially no effect of empty NLPs versus untreated cells whereas Her2-NLPs versus either untreated or empty NLP treated cells revealed upregulation of several factors associated with breast cancer. Pathway analysis also suggested that known nodes downstream of Her2 were activated in response to Her2-NLP treatment. This suggests that Her2-NLPs are sufficient for malignant transformation of non-malignant cells and that this system offers a new model for studying cell surface receptor signaling without genomic modification or transformation techniques.
Assessment of research ethics education offerings of pharmacy master programs: a qualitative content analysis
Authors: Ahmed Wesam S. , Nebeker Camille 
Published: August 2020

AbstractThe importance of research ethics (RE) training has led academic and funding institutions to require that students, trainees, and faculty obtain such training at various stages of their careers. Despite the increasing awareness of the value RE education offers, this training requirement is absent in Jordan. We aimed to assess RE education offerings of pharmacy master programs in Jordan and compare with the top-ranked pharmacy graduate programs globally. Therefore, a list of universities that offer research-based pharmacy master programs was created. Each program was evaluated for the inclusion of RE education. A qualitative content analysis approach based on inductive reasoning and latent analysis was followed to analyze the data. Results of the study showed a lack of appropriate RE education for graduate-level pharmacy programs in Jordan with only 40% of the programs partially discuss selected topics related to RE. Regarding pharmacy graduate programs globally, 10% offer a standalone RE course, 40% offer some discussions related to RE, another 10% do not offer RE education in any form, and the remaining 40% of the programs were difficult to assess due to lack of sufficient information available online. Based on the findings of this study, training in RE is tends to be lacking in pharmacy graduate programs in Jordan and globally, with a greater lack in Jordan than globally. There is a need to incorporate formal RE education into programs that do not offer this type of instruction. Programs that formally touch on some aspects of RE need to expand the scope of topics to include more RE-related themes. Integrating a standalone RE course into pharmacy graduate programs is highly encouraged.
“Myosin XI drives polarized growth by vesicle clustering and local enrichment of F-actin inPhyscomitrium (Physcomitrella) patens”
Authors: Galotto Giulia , Wisanpitayakorn Pattipong , Bibeau Jeffrey P. , Liu Yen-Chun , Simpson Parker J. , Tüzel Erkan , Vidali Luis 
Published: August 2020

ABSTRACTIn tip-growing plant cells, growth results from myosin XI and F-actin mediated deposition of cell wall polysaccharides contained in secretory vesicles. Previous evidence showed that myosin XI anticipates F-actin accumulation at the cell’s tip, suggesting a mechanism where vesicle clustering via myosin XI promotes F-actin polymerization. To evaluate this model, we used a conditional loss-of-function strategy by generatingPhyscomitrium (Physcomitrella) patensplants harboring a myosin XI temperature-sensitive allele. We found that loss of myosin XI function alters tip cell morphology, vacuolar homeostasis, and cell viability, but not following F-actin depolymerization. Importantly, our conditional loss-of-function analysis shows that myosin XI clusters and directs vesicles at the tip of the cell, which induces F-actin polymerization, increasing F-actin’s local concentration. Our findings support the role of myosin XI in vesicle clustering and F-actin organization, necessary for tip growth, and deepen our understanding of additional myosin XI functions.
Facilitation and biodiversity jointly drive mutualistic networks
Authors: Losapio Gianalberto , Hasday Elizabeth Norton , Espadaler Xavier , Germann Christoph , Ortiz-Sánchez Francisco Javier , Pont Adrian , Sommaggio Daniele , Schöb Christian 
Published: August 2020

ABSTRACTFacilitation by nurse plants increases understorey diversity and supports ecological communities. In turn, biodiversity shapes ecological networks and enhances ecosystem functioning. However, whether and how facilitation and increased biodiversity jointly influence community structure and ecosystem functioning remains unclear.We performed a field experiment disentangling the relative contribution of nurse plants and increasing understorey plant diversity in driving pollination interactions. Both the presence of nurse shrubs as well as increased understorey plant diversity increased pollinator diversity and visitation rates. While nurse and understorey diversity effects on pollinator visitation rates did not interact, the effects of increasing understorey plant diversity on pollinator diversity were stronger in the absence than in the presence of shrubs, meaning that nurse shrubs attenuated the effects of high understorey diversity and buffered the effects of low understorey diversity.We also found positive complementarity effects among understorey species as well as complementarity between nurse plants and understorey species at high diversity. Results also indicate negative selection effects, suggesting that species with generally few pollinators benefit the most in the polyculture, while a species (possibly the nurse plant) with generally lots of pollinators does not. The corresponding changes in pollination networks with the experimental treatments were due to both changes in the frequency of visits and turnover in pollinator community composition.SynthesisPlant–plant facilitative systems, where a nurse plant increases understorey plant diversity, are common in stressful environments. Here, we show that these facilitative systems positively influence mutualistic interactions with pollinators via both direct nurse effects and indirect positive effects of increasing plant diversity.Conserving and supporting nurse plant systems is crucial not only for maintaining plant diversity but also for supporting ecosystem functions and services.
An Integrative Analysis of the Age-Associated Genomic, Transcriptomic and Epigenetic Landscape across Cancers
Authors: Chatsirisupachai Kasit , Lesluyes Tom , Paraoan Luminita , Van Loo Peter , de Magalhães João Pedro 
Published: August 2020

AbstractAge is the most important risk factor for cancer, as cancer incidence and mortality increase with age. However, how molecular alterations in tumours differ among patients of different age remains largely unexplored. Here, using data from The Cancer Genome Atlas, we comprehensively characterised genomic, transcriptomic and epigenetic alterations in relation to patients’ age across cancer types. We showed that tumours from older patients present an overall increase in genomic instability, somatic copy-number alterations (SCNAs) and somatic mutations. Age-associated SCNAs and mutations were identified in several cancer-driver genes across different cancer types. The largest age-related genomic differences were found in gliomas and endometrial cancer. We identified age-related global transcriptomic changes and demonstrated that these genes are controlled by age-associated DNA methylation changes. This study provides a comprehensive view of age-associated alterations in cancer and underscores age as an important factor to consider in cancer research and clinical practice.
Stapled peptides based on Human Angiotensin-Converting Enzyme 2 (ACE2) potently inhibit SARS-CoV-2 infection in vitro
Authors: Curreli Francesca , Victor Sofia M B , Ahmed Shahad , Drelich Aleksandra , Tong Xiaohe , Tseng Chien-Te K , Hillyer Christopher D. , Debnath Asim K 
Published: August 2020

AbstractSARS-CoV-2 uses human angiotensin-converting enzyme 2 (ACE2) as the primary receptor to enter host cells and initiate the infection. The critical binding region of ACE2 is a ∼30 aa long helix. Here we report the design of four stapled peptides based on the ACE2 helix, which is expected to bind to SARS-CoV-2 and prevent the binding of the virus to the ACE2 receptor and disrupt the infection. All stapled peptides showed high helical contents (50-94% helicity). On the contrary, the linear control peptide NYBSP-C showed no helicity (19%). We have evaluated the peptides in a pseudovirus based single-cycle assay in HT1080/ACE2 and human lung cells A549/ACE2, overexpressing ACE2. Three of the four stapled peptides showed potent antiviral activity in HT1080/ACE2 (IC50: 1.9 – 4.1 µM) and A549/ACE2 cells (IC50: 2.2 – 2.8 µM). The linear peptides NYBSP-C and the double-stapled peptide StRIP16, used as controls, showed no antiviral activity. Most significantly, none of the stapled peptides show any cytotoxicity at the highest dose tested. We also evaluated the antiviral activity of the peptides by infecting Vero E6 cells with the replication-competent authentic SARS-CoV-2 (US_WA-1/2020). NYBSP-1 was the most efficient preventing the complete formation of cytopathic effects (CPEs) at an IC100 17.2 µM. NYBSP-2 and NYBSP-4 also prevented the formation of the virus-induced CPE with an IC100 of about 33 µM. We determined the proteolytic stability of one of the most active stapled peptides, NYBSP-4, in human plasma, which showed a half-life (T1/2) of >289 min.
Population modeling with machine learning can enhance measures of mental health
Authors: Dadi Kamalaker , Varoquaux Gaël , Houenou Josselin , Bzdok Danilo , Thirion Bertrand , Engemann Denis 
Published: August 2020

AbstractBackgroundBiological aging is revealed by physical measures,e.g., DNA probes or brain scans. Instead, individual differences in mental function are explained by psychological constructs, e.g., intelligence or neuroticism. These constructs are typically assessed by tailored neuropsychological tests that build on expert judgement and require careful interpretation. Could machine learning on large samples from the general population be used to build proxy measures of these constructs that do not require human intervention?ResultsHere, we built proxy measures by applying machine learning on multimodal MR images and rich sociodemographic information from the largest biomedical cohort to date: the UK Biobank. Objective model comparisons revealed that all proxies captured the target constructs and were as useful, and sometimes more useful than the original measures for characterizing real-world health behavior (sleep, exercise, tobacco, alcohol consumption). We observed this complementarity of proxy measures and original measures when modeling from brain signals or sociodemographic data, capturing multiple health-related constructs.ConclusionsPopulation modeling with machine learning can derive measures of mental health from brain signals and questionnaire data, which may complement or even substitute for psychometric assessments in clinical populations.Key PointsWe applied machine learning on more than 10.000 individuals from the general population to define empirical approximations of health-related psychological measures that do not require human judgment.We found that machine-learning enriched the given psychological measures via approximation from brain and sociodemographic data: Resulting proxy measures related as well or better to real-world health behavior than the original measures.Model comparisons showed that sociodemographic information contributed most to characterizing psychological traits beyond aging.
Role of FMRP in rapid antidepressant effects and synapse regulation
Authors: Heaney Chelcie F. , Namjoshi Sanjeev V. , Uneri Ayse , Bach Eva C. , Weiner Jeffrey L. , Raab-Graham Kimberly F. 
Published: August 2020

AbstractRapid antidepressants are novel treatments for major depressive disorder (MDD) and work by blocking N-methyl-aspartate receptors (NMDAR), which, in turn, activate the protein synthesis pathway regulated by mechanistic/mammalian target of rapamycin complex 1 (mTORC1). Our recent work demonstrates that the RNA-binding protein Fragile X Mental Retardation Protein (FMRP) is downregulated in dendrites upon treatment with a rapid antidepressant. Here, we show that the behavioral effects of the rapid antidepressant Ro-25-6981 require FMRP expression, and treatment promotes differential mRNA binding to FMRP in an mTORC1-dependent manner. Further, these mRNAs are identified to regulate transsynaptic signaling. Using a novel technique, we show that synapse formation underlying the behavioral effects of Ro-25-6981 requires GABABR-mediated mTORC1 activity in WT animals. Finally, we demonstrate that in an animal model that lacks FMRP expression and has clinical relevance for Fragile X Syndrome (FXS), GABABR activity is detrimental to the effects of Ro-25-6981. These effects are rescued with the combined therapy of blocking GABABRs and NMDARs, indicating that rapid antidepressants alone may not be an effective treatment for people with comorbid FXS and MDD.
Genome-wide methylation prediction of biological age using reproducing kernel Hilbert spaces and Bayesian ridge regressions
Authors: Roudbar Mahmoud Amiri , Momen Mehdi , Mousavi Seyedeh Fatemeh , Ardestani Siavash Salek , Lopes Fernando Brito , Gianola Daniel , Khatib Hasan 
Published: August 2020

ABSTRACTThe use of DNA methylation signatures to predict chronological age and the aging rate is of interest in many fields, including disease prevention and treatment, forensics, and anti-aging medicine. Although a large number of methylation markers have been found to be significantly associated with age, most age-prediction methods use a small number of markers selected based on either previously published studies or datasets containing methylation information. Here, we implemented reproducing kernel Hilbert spaces (RKHS) regression and ridge regression model in a Bayesian framework that utilized phenotypic and methylation profiles simultaneously to predict chronological age. We used over 450,000 CpG sites from the whole blood of a large cohort of 4,409 human individuals with a range of 10-101 years of age. Models were fitted using adjusted and un-adjusted methylation measurements for cell heterogeneity. Non-adjusted methylation scores delivered a significantly higher prediction accuracy than adjusted methylation data, with a correlation between age and predicted age of 0.98 and a root-mean-square error (RMSE) of 3.54 years in non-adjusted data, 0.90 (correlation) and 7.16 (RMSE) years in adjusted data. Reducing the number of predictors through subset selection improved predictive power with a correlation of 0.98 and an RMSE of 2.98 years in the RKHS model. We found distinct global methylation patterns, with significant hypermethylation in CpG islands and hypomethylation in other CpG types including CpG shore, shelf, and open sea (p < 5e-06). Epigenetic drift seemed to be a widespread phenomenon as more than 97% of the age-associated methylation sites had heteroscedasticity. Apparent methylomic aging rate (AMAR) had a sex-specific pattern, with an increase in AMAR in females with age compared to males.
NOise Reduction with DIstribution Corrected (NORDIC) PCA in dMRI with complex-valued parameter-free locally low-rank processing
Authors: Moeller Steen , Pisharady Pramod Kumar , Ramanna Sudhir , Lenglet Christophe , Wu Xiaoping , Dowdle Logan , Yacoub Essa , Uğurbil Kamil , Akçakaya Mehmet 
Published: August 2020

AbstractDiffusion-weighted magnetic resonance imaging (dMRI) has found great utility for a wide range of neuroscientific and clinical applications. However, high-resolution dMRI, which is required for improved delineation of fine brain structures and connectomics, is hampered by its low signal-to-noise ratio (SNR). Since dMRI relies on the acquisition of multiple different diffusion weighted images of the same anatomy, it is well-suited for denoising methods that utilize correlations across the image series to improve the apparent SNR and the subsequent data analysis. In this work, we introduce and quantitatively evaluate a comprehensive framework, NOise Reduction with Distribution Corrected (NORDIC) PCA method for processing dMRI. NORDIC uses low-rank modeling of g-factor-corrected complex dMRI reconstruction and non-asymptotic random matrix distributions to remove signal components which cannot be distinguished from thermal noise. The utility of the proposed framework for denoising dMRI is demonstrated on both simulations and experimental data obtained at 3 Tesla with different resolutions using human connectome project style acquisitions. The proposed framework leads to substantially enhanced quantitative performance for estimating diffusion tractography related measures and for resolving crossing fibers as compared to a conventional/state-of-the-art dMRI denoising method.HighlightsWe propose a framework, NORDIC, for denoising complex valued dMRI data using Gaussian statisticsThe effectiveness of the proposed denoising method is distinguished by the ability to remove only signal which cannot be distinguished from thermal noiseThe proposed method outperforms a state-of-art method for denoising dMRI in terms of fiber orientation dispersionQuantitative evaluation of NORDIC across different resolutions and SNR using human connectome type acquisitions and analysis shows up to 6 fold improvement in apparent SNR for 0.9mm whole brain dMRI at 3T.
A generalist lifestyle allows rareGardnerellaspp. to persist at low levels in the vaginal microbiome
Authors: Khan Salahuddin , Vancuren Sarah J. , Hill Janet E. 
Published: August 2020

AbstractGardnerellaspp. are considered a hallmark of bacterial vaginosis, a dysbiosis of the vaginal microbiome. There are four cpn60 sequence-based subgroups within the genus (A, B, C, and D), and thirteen genome species have been defined recently.Gardnerellaspp. co-occur in the vaginal microbiome with varying abundance, and these patterns are shaped by a resource-dependent, exploitative competition, which affects the growth rate of subgroup A, B, and C negatively. The growth rate of rarely abundant subgroup D, however, increases with the increasing number of competitors, negatively affecting the growth rate of others. We hypothesized that a nutritional generalist lifestyle and minimal niche overlap with the other, more abundantGardnerellaspp. facilitate the maintenance of subgroup D in the vaginal microbiome through negative-frequency dependent selection. Using 40 whole genome sequences from isolates representing all four subgroups we found that they could be distinguished based on content of their predicted proteomes. Proteins associated with carbohydrate and amino acid uptake and metabolism were significant contributors to the separation of subgroups. Subgroup D isolates had significantly more of their proteins assigned to amino acid metabolism than the other subgroups. Subgroup D isolates were also significantly different from others in terms of number and type of carbon sources utilized in a phenotypic assay, while the other three could not be distinguished. Overall, the results suggest that a generalist lifestyle and lack of niche overlap with otherGardnerellaspp. leads to subgroup D being favoured by negative-frequency dependent selection in the vaginal microbiome.