bluuebunny/crossref_metadata_2025_split huggingface dataset:
Characterizing RNA-binding Ligands on Structures, Chemical Information, Binding Affinity and Drug-likeness
Authors: Fan Cong , Wang Xin , Ling Tianze , Zhao Huiying 
Published: January 2022

ABSTRACTRecent studies suggest RNAs playing essential roles in many cell activities and act as promising drug targets. However, limited development has been achieved in detecting RNA-ligand interactions. To guide the discovery of RNA-binding ligands, it is necessary to characterize them comprehensively. We established a database, RNALID that collects RNA-ligand interactions validated by low-throughput experiment. RNALID contains 358 RNA-ligand interactions. Comparing to other databases, 94.5% of ligands in RNALID are completely or partially novel collections, and 51.78% have novel two-dimensional (2D) structures. The ligand structure analysis indicated that multivalent ligands (MV), ligands binding with cellular mRNA (mRNA), ligands binding with RNA from virus (vRNA) and ligands binding with RNA containing repetitive sequence (rep RNA) are more structurally conserved in both 2D and 3D structures than other ligand types. Binding affinity analysis revealed that interactions between ligands and rep RNA were significantly stronger (two-tailed MW-U test P-value = 0.012) than the interactions between ligands and non-rep RNAs; the interactions between ligands and vRNA were significantly stronger (two-tailed MW-U test P-value = 0.012) than those between ligands and mRNA. Drug-likeness analysis indicated that small molecule (SM) ligands binding with non-rep RNA or vRNA may have higher probability to be drugs than other types of ligands. Comparing ligands in RNALID to FDA-approved drugs and ligands without bioactivity indicated that RNA-binding ligands are different from them in chemical properties, structural properties and drug-likeness. Thus, characterizing the RNA-ligand interactions in RNALID in multiple respects provides new insights into discovering and designing druggable ligands binding with RNA.KEY POINTSWe established a database, RNALID, by collecting RNA-ligand interactions validated by low-throughput experiments, which contains 358 RNA-ligand interactions, and 94.5% of them are completely or partially novel collections.Ligands in RNALID were divided into fourteen types, and were analyzed on chemical properties, spatial properties, binding affinity and drug-likeness. Small molecule (SM) ligands binding with non-repeat RNA or virus RNA were indicated having higher probability to be drugs than other types of ligands.Ligands in RNALID were different from protein-binding ligands and ligands without bioactivity in chemical properties, structural properties and drug-likeness.
Resonant fluctuations of selection pressure exponentially accelerate fitness valley crossing
Authors: Salvo Mario E. Di , Reynolds Kimberly A. , Lin Milo M. 
Published: January 2022

AbstractTwo functional protein sequences can sometimes be separated by a fitness valley - a series of low or non-functional intermediate mutations that must be traversed to reach a more optimal or refined function. Time-varying selection pressure modulates evolutionary sampling of such valleys. Yet, how the amplitude and frequency of fluctuating selection influence the rate of protein evolution is poorly understood. Here, we derive a simple equation for the time-dependent probability of crossing a fitness valley as a function of evolutionary parameters: valley width, protein size, mutation rate, and selection pressure. The equation predicts that, under low selection pressure, the valley crossing rate is magnified by a factor that depends exponentially on valley width. However, after a characteristic time set by the evolutionary parameters, the rate rapidly decays. Thus, there is an optimal frequency of selection-pressure fluctuations that maximizes the rate of protein optimization. This result is reminiscent of the resonance frequency in mechanical systems. The equation unites empirical and theoretical results that were previously disconnected, and is consistent with time-dependent in vitro and clinical data. More generally, these results suggest that seasonal and climate oscillations could synchronously drive protein evolution at the resonant frequency across a range of organism hosts and timescales. This theory could also be applied to optimize de novo protein evolution in laboratory directed evolution using time-varying protocols.
Interpreting tree ensemble machine learning models with endoR
Authors: Ruaud Albane , Pfister Niklas , Ley Ruth E , Youngblut Nicholas D 
Published: January 2022

BackgroundTree ensemble machine learning models are increasingly used in microbiome science as they are compatible with the compositional, high-dimensional, and sparse structure of sequence-based microbiome data. While such models are often good at predicting phenotypes based on microbiome data, they only yield limited insights into how microbial taxa or genomic content may be associated. Results: We developed endoR, a method to interpret a fitted tree ensemble model. First, endoR simplifies the fitted model into a decision ensemble from which it then extracts information on the importance of individual features and their pairwise interactions and also visualizes these data as an interpretable network. Both the network and importance scores derived from endoR provide insights into how features, and interactions between them, contribute to the predictive performance of the fitted model. Adjustable regularization and bootstrapping help reduce the complexity and ensure that only essential parts of the model are retained. We assessed the performance of endoR on both simulated and real metagenomic data. We found endoR to infer true associations with more or comparable accuracy than other commonly used approaches while easing and enhancing model interpretation. Using endoR, we also confirmed published results on gut microbiome differences between cirrhotic and healthy individuals. Finally, we utilized endoR to gain insights into components of the microbiome that predict the presence of human gut methanogens, as these hydrogen-consumers are expected to interact with fermenting bacteria in a complex syntrophic network. Specifically, we analyzed a global metagenome dataset of 2203 individuals and confirmed the previously reported association betweenMethanobacteriaceaeandChristensenellales. Additionally, we observed thatMethanobacteriaceaeare associated with a network of hydrogen-producing bacteria. Conclusion: Our method accurately captures how tree ensembles use features and interactions between them to predict a response. As demonstrated by our applications, the resultant visualizations and summary outputs facilitate model interpretation and enable the generation of novel hypotheses about complex systems. An implementation of endoR is available as an open-source R-package on GitHub (https://github.com/leylabmpi/endoR).
Understanding drivers of phylogenetic clustering and terminal branch lengths distribution in epidemics of Mycobacterium tuberculosis
Authors: Menardo Fabrizio 
Published: January 2022

AbstractDetecting factors associated with transmission is important to understand disease epidemics, and to design effective public health measures. Clustering and terminal branch lengths (TBL) analyses are commonly applied to genomic data sets of Mycobacterium tuberculosis (MTB) to identify sub-populations with increased transmission. Here, I used a simulation-based approach to investigate what epidemiological processes influence the results of clustering and TBL analyses, and whether difference in transmission can be detected with these methods. I simulated MTB epidemics with different dynamics (latency, infectious period, transmission rate, basic reproductive number R0, sampling proportion, and molecular clock), and found that all these factors, except the length of the infectious period and R0, affect the results of clustering and TBL distributions. I show that standard interpretations of this type of analyses ignore two main caveats: 1) clustering results and TBL depend on many factors that have nothing to do with transmission, 2) clustering results and TBL do not tell anything about whether the epidemic is stable, growing, or shrinking. An important consequence is that the optimal SNP threshold for clustering depends on the epidemiological conditions, and that sub-populations with different epidemiological characteristics should not be analyzed with the same threshold. Finally, these results suggest that different clustering rates and TBL distributions, that are found consistently between different MTB lineages, are probably due to intrinsic bacterial factors, and do not indicate necessarily differences in transmission or evolutionary success.
The rosy future paradox: Positive future thinking without task relevance enhances negative biases and anxiety for aversive events
Authors: Montijn Nicole D. , Gerritsen Lotte , van Son Dana , Engelhard Iris. M. 
Published: January 2022

ABSTRACTExpectations have an important role in guiding behavior and the interpretation of novel information, but can contain negative biases such as is the case in anxiety disorders. Positive future thinking may provide an accessible way to attenuate these negatively biases. However, much is still unclear about the optimal form of such positive interventions, and it is unknown if the effects go beyond subjective experience. Here, we used a positive future thinking intervention to adapt the way a stressful event is experienced. Participants imagined either task-relevant (N = 21) or irrelevant (N = 21) positive future events before being subjected to the Trier Social Stress Task, or did not receive the intervention (N= 20). We recorded resting state EEG during the anticipation and recovery phases of the TSST to assess intervention and trait anxiety related differences in the level of frontal delta-beta coupling, which is considered a neurobiological substrate of emotion regulation. Results show that the intervention reduces event-related stress and anxiety, and increases social fixation behavior and task performance, but only if future thinking is task relevant. Paradoxically, task-irrelevant positive future thoughts enhance negative perceptual biases and stress reactivity. This increase in stress reactivity in the task-irrelevant group was corroborated by the elevated levels frontal delta-beta coupling during event anticipation, especially for those with high trait anxiety. This suggests an increased demand for emotion regulation following the task-irrelevant intervention, possibly due to the contextual incongruence between positive imagery and the stressor. Together, these results show that positive future thinking can mitigate the negative emotional, behavioral and neurobiological consequences of a stressful event, but that it should not be applied indiscriminately. Task-relevant positive future thinking can be an accessible way to boost efficacy of exposure therapy for pathological anxiety, and can help people deal with negative anticipation in daily life.
Reduced interferon antagonism but similar drug sensitivity in Omicron variant compared to Delta variant SARS-CoV-2 isolates
Authors: Bojkova Denisa , Widera Marek , Ciesek Sandra , Wass Mark N. , Michaelis Martin , Cinatl Jindrich 
Published: January 2022

AbstractThe SARS-CoV-2 Omicron variant is currently causing a large number of infections in many countries. A number of antiviral agents are approved or in clinical testing for the treatment of COVID-19. Despite the high number of mutations in the Omicron variant, we here show that Omicron isolates display similar sensitivity to eight of the most important anti-SARS-CoV-2 drugs and drug candidates (including remdesivir, molnupiravir, and PF-07321332, the active compound in paxlovid), which is of timely relevance for the treatment of the increasing number of Omicron patients. Most importantly, we also found that the Omicron variant displays a reduced capability of antagonising the host cell interferon response. This provides a potential mechanistic explanation for the clinically observed reduced pathogenicity of Omicron variant viruses compared to Delta variant viruses.
In planta transcriptomics reveals conflicts between pattern-triggered immunity and the AlgU sigma factor regulon
Authors: Wang Haibi , Lovelace Amelia , Smith Amy , Kvitko Brian H. 
Published: January 2022

AbstractIn previous work, we determined the transcriptomic impacts of flg22 pre-induced Pattern Triggered Immunity (PTI) in Arabidopsis thaliana on the pathogen Pseudomonas syringae pv. tomato DC3000 (Pto). During PTI exposure we observed expression patterns in Pto reminiscent of those previously observed in a Pto algU mutant. AlgU is a conserved extracytoplasmic function sigma factor which has been observed to regulate over 950 genes in Pto in vitro. We sought to identify the AlgU regulon in planta.and which PTI-regulated genes overlapped with AlgU-regulated genes. In this study, we analyzed transcriptomic data from RNA-sequencing to identify the AlgU in planta regulon and its relationship with PTI. Our results showed that approximately 224 genes are induced by AlgU, while another 154 genes are downregulated by AlgU in Arabidopsis during early infection. Both stress response and virulence-associated genes were induced by AlgU, while the flagellar motility genes are downregulated by AlgU. Under the pre-induced PTI condition, more than half of these AlgU-regulated genes have lost induction/suppression in contrast to naïve plants, and almost all function groups regulated by AlgU were affected by PTI.
The ESKAPE mobilome contributes to the spread of antimicrobial resistance and CRISPR-mediated conflict between mobile genetic elements
Authors: Botelho João , Cazares Adrian , Schulenburg Hinrich 
Published: January 2022

AbstractMobile genetic elements (MGEs) mediate the shuffling of genes among organisms. They contribute to the spread of virulence and antibiotic resistance genes in human pathogens, such as the particularly problematic group of ESKAPE pathogens, including Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter sp. Here, we performed the first systematic analysis of MGEs, including plasmids, prophages, and integrative and conjugative/mobilizable elements (ICEs/IMEs), in the ESKAPE pathogens. We characterized over 1700 complete ESKAPE genomes and found that different MGE types are asymmetrically distributed across these pathogens. While some MGEs are capable of exchanging DNA beyond the genus (and phylum) barrier, most horizontal gene transfer (HGT) events are restricted by phylum or genus. We show that the MGEs proteome is involved in diverse functional processes and distinguish widespread proteins within the ESKAPE context. Moreover, anti-CRISPRs and antimicrobial resistance (AMR) genes are overrepresented in the ESKAPE mobilome. Our results also underscore species-specific trends shaping the number of MGEs, AMR, and virulence genes across pairs of conspecific ESKAPE genomes with and without CRISPR-Cas systems. Finally, we found that CRISPR targets vary according to MGE type: while plasmid and prophage CRISPRs almost exclusively target other plasmids and prophages, respectively, ICEs/IME CRISPRs preferentially target prophages. Overall, our study highlights the general importance of the ESKAPE mobilome in contributing to the spread of AMR and mediating conflict among MGEs.
Visual search training benefits from the integrative effect of enhanced covert attention and optimized overt eye movements
Authors: Zhang Qi , Huang Zhibang , Li Liang , Li Sheng 
Published: January 2022

AbstractTraining serves as an effective approach to improve visual search performance when the target does not automatically pop out from the distractors. In the present study, we trained participants on a conjunction visual search task and examined the training effects in behavior and eye movement. The results of Experiments 1 to 4 showed that training improved behavioral performance and reduced the number of saccades and overall scanning time. Training also increased the search initiation time before the first saccade and the proportion of trials in which the participants correctly identified the target without any saccade, but these effects were modulated by stimulus’ parameters. In Experiment 5, we simultaneously recorded eye movements and EEG signals and the results revealed significant N2pc components after the stimulus onset (i.e., stimulus-locked) and before the first saccade (i.e., saccade-locked) when the search target was the trained one. These N2pc components can be considered as the neural signatures for the enhanced covert attention to the trained target. Together with the training-induced increase in functional visual field, these mechanisms could support the beneficial effects of increased search initiation time and reduced number of saccades. These findings suggest that visual search training enhanced covert attention to target and optimized overt eye movements to facilitate search performance.
Seed-competent tau monomer initiates pathology in PS19 tauopathy mice
Authors: Mirbaha Hilda , Chen Dailu , Mullapudi Vishruth , Terpack Sandi Jo , White Charles L. , Joachimiak Lukasz A. , Diamond Marc I. 
Published: January 2022

AbstractTau aggregation into ordered assemblies causes myriad neurodegenerative tauopathies. We previously reported that tau monomer exists in either inert (Mi) or seed-competent (Ms) conformational ensembles, and that Ms encodes strains, which are biologically active, self-propagating assemblies. We have previously isolated Ms from tauopathy brains, but it is unknown if disease begins with Ms formation followed by fibril assembly, or if Ms derives from fibrils and is an epiphenomenon. Consequently, we studied a tauopathy mouse model (PS19) that expresses full-length human (1N4R) tau containing a disease-associated mutation (P301S). Using tau repeat domain biosensor cells, we detected insoluble tau seeding activity at 2 months. We found insoluble tau protein assemblies by immunoblot at 3 months. We next immunopurified monomer from mice aged 1-6 weeks using size exclusion chromatography. We detected soluble seeding activity at 4 weeks, before insoluble material or larger assemblies, with assemblies ranging from n=1-3 tau units. By 5 and 6 weeks, large soluble assemblies had formed. This indicated the first detectable pathological forms of tau were Ms. We next tested for post-translational modifications of tau monomer from 1-6 weeks. We detected no phosphorylation unique to Ms in PS19 or Alzheimer’s disease brain. We conclude that tauopathy begins with formation of Ms monomer, whose activity is phosphorylation-independent. Ms self-assembles to form oligomers before it forms insoluble fibrils. The conversion of tau monomer from Mi to Ms thus constitutes the first detectable step in the initiation of tauopathy in this mouse model, with obvious implications for origins of disease in humans.
Wetland loss in the Ñeembucú Wetlands Complex, Paraguay, using remote sensing
Authors: O’Leary Frances 
Published: January 2022

AbstractSouth American wetlands are of global importance, yet limited delineation and monitoring restricts informed decision-making around the drivers of wetland loss. A growing human population and increasing demand for agricultural products has driven wetland loss and degradation in the Neotropics. Understanding of wetland dynamics and land use change can be gained through wetland monitoring. The Ñeembucú Wetlands Complex is the largest wetland in Paraguay, lying within the Paraguay-Paraná-La Plata River system. This study aims to use remotely sensed data to map land cover between 2006 and 2021, quantify wetland change over the 15-year study period and thus identify land cover types vulnerable to change in the Ñeembucú Wetlands Complex. Forest, dryland vegetation, vegetated wetland and open water were identified using Random Forest supervised classifications trained on visual inspection data and field data. Annual change of −0.34, 4.95, −1.65, 0.40 was observed for forest, dryland, vegetated wetland and open water, respectively. Wetland and forest conversion is attributed to agricultural and urban expansion. With ongoing pressures on wetlands, monitoring will be a key tool for addressing change and advising decision-making around development and conservation of valuable ecosystem goods and services in the Ñeembucú Wetlands Complex.
Testing a theoretical framework for the environment-species abundance paradigm: a new approach to the Abundant Centre Hypothesis
Authors: Maitra Alakananda , Pandit Rohan , Mungee Mansi , Athreya Ramana 
Published: January 2022

AbstractThe linkage between environment, a species’ fitness and its abundance is central to the theory of evolution. So far, all studies of this linkage have been heuristic and empirical due to an inability to determine fitness either experimentally (independent of abundance) or theoretically (from species-environment interaction). One category of such studies involves the Abundant Centre Hypothesis which posits that a species’ abundance rises to a maximum at the centre of its range. We argue that the confusing mix of results from ACH studies arises from ignoring the central premise that the abundance distribution cannot be independent of the environment. First, we employed a theoretical framework to identify an environmental context (an elevational transect; 200-2800 m in the eastern Himalayas) likely to favour ACH. We then improved upon some previously identified conceptual and methodological shortcomings of ACH studies. Using systematically collected bird data (245 species; 15867 records) from that transect we found that the community average abundance profile is symmetric, as expected by ACH. Notwithstanding which, the abundance profiles of individual species showed a small degree of asymmetry which was correlated with elevation. This elevational dependence may be due to the hard elevational limits at the lower and upper ends of the mountain, as expected from theoretical considerations. We also showed that the average abundance profile shape is close to gaussian, while ruling out uniform and inverted-quadratic shapes. This work demonstrates that selecting a particular category of environmental contexts can help in integrating theoretical tools into a field dominated by empirical studies. Such a union should spur the development of more detailed and testable theoretical models for better insights in an important field.
Engineering Protein Activity into Off-the-Shelf DNA Devices
Authors: Sekhon Harsimranjit , Loh Stewart N. 
Published: January 2022

AbstractDNA-based devices are relatively straightforward to design by virtue of their predictable folding, but they lack biological activity. Conversely, protein-based devices offer a myriad of biological functions but are much more difficult to design due to their complex folding. This study bridges the fields of DNA engineering and protein engineering to generate a protein switch that is activated by a specific DNA sequence. A single protein switch, engineered from nanoluciferase using the alternate frame folding mechanism and herein called nLuc-AFF, is paired with different DNA technologies to create a biosensor for a DNA or RNA sequence of choice, sensors for serotonin and ATP, and a computational device that processes two DNA inputs. nLuc-AFF is a genetically-encoded, ratiometric, blue/green-luminescent biosensor whose output can be quantified by cell phone camera. nLuc-AFF is not falsely activated by decoy DNA and it retains full ratiometric readout in 100 % serum. The design approach can be applied to other proteins and enzymes to convert them into DNA-activated switches.