bluuebunny/crossref_metadata_2025_split huggingface dataset:
Trade-offs, trade-ups, and high mutational parallelism underlie microbial adaptation to extreme feast/famine
Authors: Behringer Megan G. , Ho Wei-Chin , Miller Samuel F , Worthan Sarah B. , Cen Zeer , Stikeleather Ryan , Lynch Michael 
Published: October 2023

AbstractMicrobes are robust organisms capable of rapidly adapting to complex stress, enabling the colonization of harsh environments. In nature, microbes are regularly challenged by starvation, which is a particularly complex stress because resource limitation often co-occurs with changes in pH, osmolarity, and toxin accumulation created by metabolic waste. Often overlooked are the additional complications introduced by eventual resource replenishment as successful microbes must withstand rapid environmental shifts before swiftly capitalizing on replenished resources to avoid invasion by competing species. To understand how microbes navigate trade-offs between growth and survival, ultimately adapting to thrive in environments with extreme fluctuations, we experimentally evolved 16Escherichia colipopulations for 900 days to repeated feast/famine cycles of 100-day starvation before resource replenishment. Using longitudinal population-genomic analysis, we found that evolution in response to extreme feast/famine is characterized by narrow adaptive trajectories with high mutational parallelism and notable mutational order. Genetic reconstructions reveal that early mutations result in trade-offs for biofilm and motility but trade-ups for growth and survival, as these mutations conferred correlated advantages during both short-term and long-term culture. Our results demonstrate how microbes can navigate the adaptive landscapes of regularly fluctuating conditions and ultimately follow mutational trajectories that confer benefits across diverse environments.
The Maintenance of Deleterious Variation in Wild Chinese Rhesus Macaques
Authors: Steux Camille , Szpiech Zachary A. 
Published: October 2023

AbstractUnderstanding how deleterious variation is shaped and maintained in natural populations is important in conservation and evolutionary biology, as decreased fitness caused by these deleterious mutations can potentially lead to an increase in extinction risk. It is known that demographic processes can influence these patterns. For example, population bottlenecks and inbreeding increase the probability of inheriting identical-by-descent haplotypes from a recent common ancestor, creating long tracts of homozygous genotypes called runs of homozygosity (ROH), which have been associated with an accumulation of mildly deleterious homozygotes. Counter intuitively, positive selection can also maintain deleterious variants in a population through genetic hitchhiking.Here we analyze the whole genomes of 79 wild Chinese rhesus macaques across five sub-species and characterize patterns of deleterious variation with respect to ROH and signals of recent positive selection. We show that the fraction of homozygotes occurring in long ROH is significantly higher for deleterious homozygotes than tolerated ones, whereas this trend is not observed for short and medium ROH. This confirms that inbreeding, by generating these long tracts of homozygosity, is the main driver of the high burden of homozygous deleterious alleles in wild macaque populations. Furthermore, we show evidence that homozygous LOF variants are being purged. Next, we identify 7 deleterious variants at high frequency in regions putatively under selection near genes involved with olfaction and other processes.Our results shed light on how evolutionary processes can shape the distribution of deleterious variation in wild non-human primates.SignificanceOur results offer insights into the relationship between demographic and evolutionary processes and the maintenance of deleterious alleles in wild rhesus macaques. We demonstrate how inbreeding and recent positive selection can contribute to the maintenance of deleterious variants in wild non-human primate populations. Given that deleterious variation can reduce individuals reproductive fitness and contribute to extinction risks, this study is particularly relevant in the context of conservation of wild endangered species.
Dissecting glial scar formation by spatial point pattern and topological data analysis
Authors: Manrique-Castano Daniel , Bhaskar Dhananjay , ElAli Ayman 
Published: October 2023

AbstractGlial scar formation represents a fundamental response to central nervous system (CNS) injury. It is mainly characterized by a well-defined spatial rearrangement of reactive astrocytes and microglia. The mechanisms underlying glial scar formation have been extensively studied, yet quantitative descriptors of the spatial arrangement of reactive glial cells remain limited. Here, we present a novel approach using point pattern analysis (PPA) and topological data analysis (TDA) to quantify spatial patterns of reactive glial cells after experimental ischemic stroke in mice. We provide open and reproducible tools usingRandJuliato quantify spatial intensity, cell covariance and conditional distribution, cell-to-cell interactions, and short/long-scale arrangement, which collectively disentangle the arrangement patterns of the glial scar. This approach unravels a substantial divergence in the distribution of reactive astrocytes and microglia after injury that conventional analysis methods cannot fully characterize. PPA and TDA are valuable tools for studying the complex spatial arrangement of reactive glia and other nervous cells following CNS injuries and have potential applications for evaluating glial-targeted restorative therapies.
Unleashing the secrets of plant-fungal interactions using a transformation-free confocal staining technique that supports AI-assisted quantitative analysis
Authors: Nelson Ashley C. , Kariyawasam Gayan , Wyatt Nathan A. , Li Jinling , Haueisen Janine , Stukenbrock Eva H. , Borowicz Pawel , Liu Zhaohui , Friesen Timothy L. 
Published: October 2023

AbstractLaser scanning confocal microscopy’s ability to generate high-contrast 3D images has become essential to studying plant-fungal interactions. Techniques such as visualization of native fluorescence, fluorescent protein tagging of microbes, GFP/RFP-fusion proteins, and fluorescent labelling of plant and fungal proteins have been widely used to aid in these investigations. Use of fluorescent proteins have several pitfalls including variability of expressionin plantaand the requirement of gene transformation. Here we used the unlabeled pathogensParastagonospora nodorum,Pyrenophora teresf.teres, andCercospora beticolainfecting wheat, barley, and sugar beet respectively, to show the utility of a staining and imaging technique that uses propidium iodide (PI), which stains RNA and DNA, and wheat germ agglutinin labeled with fluorescein isothiocyanate (WGA-FITC), which stains chitin, to visualize fungal colonization of plants. This method relies on the use of KOH to remove the cutin layer of the leaf, increasing its permeability. This permeability allows the staining solution to penetrate and efficiently bind to its targets, resulting in a consistent visualization of cellular structures. We have also used this staining technique in conjunction with machine learning to analyze fungal volume, which indicates the fitness of the pathogenin planta, as well as quantifying nuclear breakdown, an early indicator of programmed cell death (PCD). This technique is simple to use, robust, consistent across host species, and can be applied to any plant-fungal interaction. Therefore, this technique can be used to characterize model systems as well as non-model interactions where transformation is not routine.
Detecting and quantifying heterogeneity in susceptibility using contact tracing data
Authors: Tuschhoff Beth M. , Kennedy David A. 
Published: October 2023

AbstractThe presence of heterogeneity in susceptibility, differences between hosts in their likelihood of becoming infected, can fundamentally alter disease dynamics and public health responses, for example, by changing the final epidemic size, the duration of an epidemic, and even the vaccination threshold required to achieve herd immunity. Yet, heterogeneity in susceptibility is notoriously difficult to detect and measure, especially early in an epidemic. Here we develop a method that can be used to detect and estimate heterogeneity in susceptibility given contact by using contact tracing data, which is typically collected early in the course of an outbreak. This approach provides the capability, given sufficient data, to estimate and account for the effects of this heterogeneity before they become apparent during an epidemic. It additionally provides the capability to analyze the wealth of contact tracing data available for previous epidemics and estimate heterogeneity in susceptibility for disease systems in which it has never been estimated previously. The premise of our approach is that highly susceptible individuals become infected more often than less susceptible individuals, and so individuals not infected after appearing in contact networks should be less susceptible than average. This change in susceptibility can be detected and quantified when individuals show up in a second contact network after not being infected in the first. To develop our method, we simulated contact tracing data from artificial populations with known levels of heterogeneity in susceptibility according to underlying discrete or continuous distributions of susceptibilities. We analyzed this data to determine the parameter space under which we are able to detect heterogeneity and the accuracy with which we are able to estimate it. We found that our power to detect heterogeneity increases with larger sample sizes, greater heterogeneity, and intermediate fractions of contacts becoming infected in the discrete case or greater fractions of contacts becoming infected in the continuous case. We also found that we are able to reliably estimate heterogeneity and disease dynamics. Ultimately, this means that contact tracing data alone is sufficient to detect and quantify heterogeneity in susceptibility.
Predicting Small Molecule Ligand – RNA Binding Pocket Binding Modes Using Metadynamics
Authors: Bai Zhixue , Chen Alan 
Published: October 2023

ABSTRACTUnderstanding the structural dynamics of how small molecule ligand recognize its RNA binding pocket is always a crucial determinant in pharmaceutical research. Molecular dynamics (MD) simulation is often used to interpretate this process at atomic resolution. However, the insurmountable high energy barriers in the binding pathway results in the nonergodic dynamics for unbiased MD sampling. To address this limitation, we applied well-tempered metadynamics coupled with upper wall restrain in this work, therefore providing an novel modeling approach for sampling the multiple state transitions during this binding process and probing the most energy favorable binding modes through two-dimensional free energy landscape reconstructed by incorporating couple possible hydrogen binding interactions between small molecule ligand and its RNA binding pocket as collective variables (CVs). Our computational predictions of binding modes for all five cases studied are in quantitative agreement with structures solved by X-ray crystallography or NMR with RMSD less than 2.0 Å. In addition, we presented the first molecular dynamics binding pathway and binding mechanism for the three cases of in vitro selected RNA aptamer. Our study demonstrated that metadynamics can be applied to effectively sampling state transitions of ligand binding events. By coupling with upper wall restrain, we have enabled fast free energy profile calculation and binding mode prediction for small molecule-RNA binding process, facilitating RNA-ligand binding investigation. This method therefore could be much-needed in computer-aided drug design pipelines of RNA-targeted small molecule compounds.Abstract Figure
A Systematic Review of Evidence Behind the CDC Guidelines for Indoor Lightning Safety
Authors: Brown Elissa , Haslam Alyson , Prasad Vinay 
Published: October 2023

AbstractObjectiveTo assess the evidence underlying the Centers for Disease Control and Prevention (CDC) indoor safety guidance for lightning storms.DesignSystematic Review of peer-reviewed literature.SettingGoogle Scholar, PubMed, and Web of Science (through 2023).ParticipantsReports of indoor death or injury from lightning strike.Main outcome measuresThe number of deaths and injuries from lightning-related activities.ResultsA majority of the 15 articles identified were retrospective reviews of data from death certificates, medical records, and newspaper reports; 5 articles were based on single case reports. Reports of injuries from lightning while indoors are exceedingly rare; death from lightning while indoors is essentially non-existent in modern times. No evidence exists that supports the given advice.ConclusionsCurrent U.S. lightning avoidance tips may inadvertently portray indoor spaces as unsafe, despite their protective advantage. Guidelines should place less emphasis on indoor situations and highlight controllable risks, such as behavior in outdoor and recreation situations.
Daytime broadcast spawning in crypticPocilloporaspecies at Mo’orea, French Polynesia
Authors: Harnay P , Turner AM , Burgess SC , Putnam HM 
Published: October 2023

AbstractKnowledge of when corals release gametes is fundamentally important for understanding reef ecology and evolution, but further research is needed to document patterns at the species level and in a broader range of taxa. In Mo’orea (17°32′S 149°50′W), French Polynesia, when corals were decimated by crown-of-thorns and a cyclone between 2007-2010,Pocillopora spp.recruitment primarily drove reef recovery over the following decade. Furthermore, recent research has identified that the Pocillopora community is composed of six morphologically-cryptic species. Spawning times at the genetically-verified species level at Mo’orea are undocumented in the scientific literature. To address this gap, we conducted in situ surveys ofPocillopora spp.over a total of 89 days during September 2022 - January 2023 and October 2023 - January 2024. For corals observed spawning, we used molecular analysis of mtORF and PocHistone markers to identify corals to species. We documented the synchronized lagoon level spawning ofP. meandrina2-3 days following the full moon in December 2022 (06:16-06:32, 06:21-06:35), and of a few colonies in October of 2023 (06:22-06:38) and a single colony in November 2022 (06:32). In contrast, sister speciesP. verrucosaandP. tuahiniensisspawned around the new moons in November and December of 2023. These species’ spawning overlapped one day after the new moon, butP. verrucosatended to release on the new moon and earlier in the day (∼05:45 - 06:15), whereasP. tuahiniensistended to release 1 - 3 days after the new moon and later in the day (∼06:30 - 06:50), We observed only one colony ofP. cf. effusaspawning (+3 days after new moon ∼06:30 - 06:50). Collectively, these first reported observations provide an initial documentation ofPocilloporaspawning in Mo’orea (to our knowledge), expanding on indigenous knowledge and increasing capacity to study the essential, yet environmentally sensitive, process of coral reproduction for critical reef building species in French Polynesia.
Afanc: a Metagenomics Tool for Variant Level Disambiguation of NGS Datasets
Authors: Morris Arthur V. , Price Anna , Connor Tom 
Published: October 2023

AbstractGenomics is amongst the most powerful tools available for mounting a clinical response to infectious disease. The accurate and precise taxonomic evaluation of pathogens is essential when building a picture of pathogenicity, virulence, transmission, and drug resistance. Carrying out such profiling in a high throughput manner necessitates the development of reliable bioinformatic tools. Here we present Afanc, a novel metagenomic profiler which is sensitive down to species and strain level taxa, and capable of elucidating the complex pathogen profile of compound datasets. We compared Afanc against currently available cutting edge profilers using 3 datasets: single species read sets simulated from the full Mycobacteriaceae taxonomic landscape; compound read sets containing multiple Mycobacteriaceae species and variants; and real data covering the majority of theM. tuberculosislineage taxonomic space. Afanc outperformed all profilers, both generic and Mycobacteriaceae specific, across all tested fields. As a species agnostic profiler, we predict that Afanc will be of great utility when carrying out highly specific and sensitive pathogen profiling of clinical datasets. Such analyses are essential in advising both the clinical response to an individual disease case, and in forming the foundation of epidemiological surveys.
Bacteroidesis increased in an autism cohort and induces autism-relevant behavioral changes in mice in a sex-dependent manner
Authors: Carmel Julie , Ghanayem Nasreen , Mayouf Rasha , Saleev Natalia , Chaterjee Ipsita , Getselter Dmitriy , Tiknonov Evgeny , Turjeman Sondra , Shaalan Mounia , Khatib Saleh , Kuzminsky Alla , Kevtani-Friedman Neta , Kronos Tanya , Bretler Tali , Koren Omry , Elliott Evan 
Published: October 2023

AbstractAutism Spectrum Disorder (ASD) is a neurodevelopmental condition which is defined by decreased social communication and the presence of repetitive or stereotypic behaviors. Recent evidence has suggested that the gut-brain axis may be important in neurodevelopment in general and may play a role in ASD in particular. Here, we present a study of the gut microbiome in 96 individuals diagnosed with ASD in Israel, compared to 42 neurotypical individuals. We determined differences in alpha and beta diversity in the microbiome of individuals with ASD and demonstrated that the phylum Bacteroidetes and genusBacteroideswere the most significantly over-represented in individuals with ASD. To understand the possible functional significance of these changes, we treated newborn mice withBacteroides fragilisat birth.B. fragilis-treated male mice displayed social behavior dysfunction, increased repetitive behaviors and gene expression dysregulation in the prefrontal cortex, while female mice did not display behavioral deficits. These findings suggest that overabundance ofBacteroides, particularly in early life, may have functional consequences for individuals with ASD.
Serum Lipidome Profiling Reveals a Distinct Signature of Ovarian Cancer in Korean Women
Authors: Sah Samyukta , Bifarin Olatomiwa O. , Moore Samuel G. , Gaul David A. , Chung Hyewon , Cho Hanbyoul , Cho Chi-Heum , Kim Jae-Hoon , Kim Jaeyeon , Fernández Facundo M. 
Published: October 2023

AbstractDistinguishing ovarian cancer (OC) from other gynecological malignancies remains a critical unmet medical need with significant implications for patient survival. However, non-specific symptoms along with our lack of understanding of OC pathogenesis hinder its diagnosis, preventing many women from receiving appropriate medical assistance. Accumulating evidence suggests a link between OC and deregulated lipid metabolism. Most studies, however, are limited by small sample size, particularly for early-stage cases. Furthermore, racial/ethnic differences in OC survival and incidence have been reported, yet most of the studies consist largely of non-Hispanic white women or women with European ancestry. Studies of more diverse racial/ethnic populations are needed to make OC diagnosis and prevention more inclusive. Here, we profiled the serum lipidome of 208 OC, including 93 patients with early-stage OC, and 117 non-OC (other gynecological malignancies) patients of Korean descent. Serum samples were analyzed with a high-coverage liquid chromatography high-resolution mass spectrometry platform, and lipidome alterations were investigatedviastatistical and machine learning approaches. Results show that lipidome alterations unique to OC were present in Korean women as early as when the cancer is localized, and those changes increase in magnitude as the diseases progresses. Analysis of relative lipid abundances revealed specific patterns for various lipid classes, with most classes showing decreased abundance in OC in comparison to other gynecological diseases. Machine learning methods selected a panel of 17 lipids that discriminated OC from non-OC cases with an AUC of 0.85 for an independent test set. This study provides a systemic analysis of lipidome alterations in human OC, specifically in Korean women, emphasizing the potential of circulating lipids in distinguishing OC from non-OC conditions.
Cohesin distribution alone predicts chromatin organization in yeast via conserved-current loop extrusion
Authors: Yuan Tianyu , Yan Hao , Li Kevin C. , Surovtsev Ivan , King Megan C. , Mochrie Simon G. J. 
Published: October 2023

AbstractInhomogeneous patterns of enhanced chromatin-chromatin contacts within 10-100 kb-sized regions of the genome are a generic feature of chromatin spatial organization. These features, termed topologically associating domains (TADs), have led to the loop extrusion factor (LEF) model, where TADs arise from loop extrusion by cohesin complexes. Currently, our ability to model TADs relies on the observation that in vertebrates TAD boundaries are correlated with DNA sequences that bind CTCF, which therefore is inferred to block loop extrusion. However, although TADs feature prominently in their Hi-C maps, non-vertebrate eukaryotes either do not express CTCF or show few TAD boundaries that correlate with CTCF sites. In all of these organisms, the counterparts of CTCF remain unknown, frustrating comparisons between Hi-C data and simulations. To extend the LEF model across the tree of life, here, we propose theconserved-current loop extrusion (CCLE) modelthat interprets loop-extruding cohesin as a nearly-conserved probability current. From cohesin ChIP-seq data alone, we thus derive a position-dependent loop extrusion rate, allowing for a modified paradigm for loop extrusion, that goes beyond solely discrete, localized barriers to also include loop extrusion rates that vary more continuously across the genome. To demonstrate its utility in organisms lacking CTCF, we applied the CCLE model to the Hi-C maps of interphaseSchizosaccharomyces pombe, as well as to those of meiotic and mitoticSaccharomyces cerevisiae. In all cases, even though their Hi-C maps appear quite different, the model accurately predicts the TAD-scale Hi-C maps. It follows that loop extrusion by cohesin is indeed the primary mechanism underlying TADs in these systems. CCLE allows us to obtain loop extrusion parameters such as the LEF density and processivity, which compare well to independent estimates. The model also provides new insights intoin vivoLEF composition and function.
Calcium Sulfate Microparticle Size Modification for Improved Alginate Hydrogel Fabrication and Its Application in 3D Cell Culture
Authors: Kim Joo Ho , Iyer Siddharth , Tessman Christian , Lakshman Shashank Vummidi , Kang Heemin , Gu Luo 
Published: October 2023

AbstractCalcium ion-crosslinked alginate hydrogels are widely used as a materials system for investigating cell behavior in 3D environmentsin vitro. Suspensions of calcium sulfate particles are often used as the source of Ca2+to control the rate of gelation. However, the instability of calcium sulfate suspensions can increase chances of reduced homogeneity of the resulting gel and requires researcher’s proficiency. Here, we show that ball-milled calcium sulfate microparticles with smaller sizes can create more stable crosslinker suspensions than unprocessed or simply autoclaved calcium sulfate particles. In particular, 15 µm ball-milled calcium sulfate microparticles result in gels that are more homogeneous with a balanced gelation rate, which facilitates fabrication of gels with consistent mechanical properties and reliable performance for 3D cell culture. Overall, these microparticles represent an improved method for alginate hydrogel fabrication that can increase experimental reliability and quality for 3D cell culture.