bluuebunny/crossref_metadata_2025_split huggingface dataset:
Modelling Emergence ofWolbachiaToxin-Antidote Protein Functions with an Evolutionary Algorithm
Authors: Beckmann John , Gillespie Joe , Tauritz Daniel 
Published: March 2023

AbstractEvolutionary algorithms (EAs) simulate Darwinian evolution and adeptly mimic natural evolution. Most EA applications in biology encode high levels of abstraction in top-down ecological population models. In contrast, our research merges protein alignment algorithms from bioinformatics into codon based EAs that simulate molecular protein string evolution from the bottom up. We apply our EA to reconcile a problem in the field ofWolbachiainduced cytoplasmic incompatibility (CI).Wolbachiais a microbial endosymbiont that lives inside insect cells. CI is conditional insect sterility that operates as a toxin antidote (TA) system. Although, CI exhibits complex phenotypes not fully explained under a single discrete model. We instantiate in-silico genes that control CI, CI factors (cifs), as strings within the EA chromosome. We monitor the evolution of their enzymatic activity, binding, and cellular localization by applying selective pressure on their primary amino acid strings. Our model helps rationalize why two distinct mechanisms of CI induction might coexist in nature. We find that nuclear localization signals (NLS) and Type IV secretion system signals (T4SS) are of low complexity and evolve fast, whereas binding interactions have intermediate complexity, and enzymatic activity is the most complex. Our model predicts that as ancestral TA systems evolve into eukaryotic CI systems, the placement of NLS or T4SS signals can stochastically vary, imparting effects that might impact CI induction mechanics. Our model highlights how preconditions, genetic diversity, and sequence length can bias evolution ofcifstowards one mechanism or another.
Video-rate three-photon imaging in deepDrosophilabrain based on a single Cr:forsterite oscillator
Authors: Chou Lu-Ting , Wu Shao-Hsuan , Hung Hao-Hsuan , Jang Je-Chi , Chen Chung-Ming , Chang Ting-Chen , Lin Wei-Zhong , Chu Li-An , Sun Chi-Kuang , Kärtner Franz X. , Ivanov Anatoly A. , Chu Shi-Wei , Chia Shih-Hsuan 
Published: March 2023

SUMMARYWe have demonstrated 30-Hz three-photon imaging using a single 24-MHz mode-locked Cr:forsterite oscillator with a center wavelength at 1260 nm. By managing the dispersion distribution in the resonator using double-chirped mirrors, we have produced 32-fs pulses with 22-nJ pulse energy. Using the oscillator as a driving source, we have realized multi-color three-photon images using a GFP-labeledDrosophilabrain and an AF647-labeled mouse brain. To demonstrate the capability of deep-tissue imaging, we have obtained a 10-times higher SBR from the three-photon images than the two-photon results at different depths in a GFP-labeledDrosophilabrain dissection. Furthermore, we have shown the impact of excitation pulse width on three-photon deep-tissue imaging. Our results indicate the superiority of using shorter pulses for deeper-tissue imaging, especially in theDrosophilabrain. In addition, we have recorded the three-photon calcium imagingin vivofrom theDrosophilamushroom body in response to external electric shocks. We believe our demonstration provides a robust approach for high-speed three-photon microscopy applications, especially for intravital investigations in theDrosophilabrain.
High-altitude hypoxia exposure inhibits erythrophagocytosis by inducing macrophage ferroptosis in the spleen
Authors: Yang Wan-ping , Li Mei-qi , Ding Jie , Li Jia-yan , Wu Gang , Liu Bao , Gao Yu-qi , Wang Guo-hua , Luo Qian-qian 
Published: March 2023

AbstractHigh-altitude polycythemia (HAPC) is a chronic condition prevalent in individuals residing at high altitudes (HA), characterized by an augmented production of red blood cells (RBCs) due to hypoxic conditions. Despite its prevalence, the pathophysiological basis and molecular mechanisms driving HAPC remain largely unelucidated. In our study, we utilized a mouse model exposed to hypobaric hypoxia (HH), replicating the environmental conditions experienced at 6000 m above sea level, coupled within vitroanalysis of primary splenic macrophages under 1% O2to investigate these mechanisms. Our findings revealed that HH exposure significantly stimulates erythropoiesis, leading to erythrocytosis. This was accompanied by a notable sequence of splenic changes, initially characterized by splenic contraction, which subsequently progressed to splenomegaly over 14 days. A key observation was the impairment on the capacity of spleen to process RBCs, primarily attributed to a reduction in splenic macrophages located in the red pulp. Extended HH treatment over 7 and 14 days precipitated increased iron mobilization and the onset of ferroptosis within the spleen. This was evidenced by altered expression levels of iron metabolism and ferroptosis-related proteins, paralleling gene expression patterns observed in human peripheral blood mononuclear cells. Single-cell sequencing of splenic tissue post-HH exposure demonstrated a marked decrease in macrophage populations after 7 days. Our study further disclosed a significant increase in RBCs retention in the spleen following HH exposure, likely a consequence of diminished red pulp macrophages (RPMs) and erythrophagocytosis. This hypothesis was corroborated through comprehensive analyses involving flow cytometry, histological staining, and immunostaining, which collectively provided a detailed understanding of RBCs dynamics under HH conditions.In vitroanalyses substantiated the decline in primary splenic macrophages and induction of ferroptosis under hypoxic treatment, effects that were relieved by pre-treatment with the ferroptosis inhibitor ferrostatin-1. Collectively, our data suggest that HH exposure initiates splenic ferroptosis, leading primarily to a decrease in RPMs. This decrease potentially impacts erythrophagocytosis, contributing to increased RBCs retention and subsequent splenomegaly. Such changes could potentially foster continuous RBCs production and accelerate the progress of HAPC. In conclusion, our study highlights the important role of the spleen and splenic macrophages in the pathogenesis of HAPC, providing crucial insights into the disease progression and potential therapeutic targets.
Conditionalin vivodeletion of LYN kinase has little effect on aBRCA1loss-of-function-associated mammary tumour model
Authors: Tornillo Giusy , Warrington Lauren , Kendrick Howard , Higgins Adam T. , Hay Trevor , Beck Sam , Smalley Matthew J. 
Published: March 2023

AbstractLYN kinase is expressed in BRCA1 loss-of-function-dependent mouse mammary tumours, in the cells of origin of such tumours, and in human breast cancer. Suppressing LYN kinase activity in BRCA1-defective cell lines, as well as inin vitrocultures ofBrca1-null mouse mammary tumours, is deleterious to their growth. Here, we have examined the interaction between LYN kinase and BRCA1 loss-of-function in anin vivomouse mammary tumour model, using conditional knockoutBrca1andLynalleles. Comparison ofBrca1tumour cohorts showed little difference in mammary tumour formation between animals that were wild type, heterozygous or homozygous for the conditionalLynallele, although this was confounded by factors including incompleteLynrecombination in some tumours. RNAseq analysis demonstrated that tumours with high levels ofLyngene expression had a slower doubling time, but this was not correlated with levels of LYN staining in tumour cells themselves. Rather, highLynexpression and slower tumour growth were likely a result of B-cell infiltration. The multifaceted role of LYN means it is likely to present difficulties as a therapeutic target in breast cancer.
Analysis of evolutionary dynamics and clonal architecture in prostate cancer
Authors: Conway Jake R. , Tewari Alok K. , Camp Sabrina Y. , Han Seunghun , Crowdis Jett , He Meng Xiao , Nyame Yaw A. , AlDubayan Saud H. , Schultz Nikolaus , Szallasi Zoltan , Pomerantz Mark M. , Freedman Matthew L. , Fong Lawrence , Nelson Peter S. , Brown Myles , Salari Keyan , Allen Eliezer Van 
Published: March 2023

AbstractThe extent to which clinical and genomic characteristics associate with prostate cancer clonal architecture, tumor evolution, and therapeutic response remains unclear. Here, we reconstructed the clonal architecture and evolutionary trajectories of 845 prostate cancer tumors with harmonized clinical and molecular data. We observed that tumors from patients who self-reported as Black had more linear and monoclonal architectures, despite these men having higher rates of biochemical recurrence. This finding contrasts with prior observations relating polyclonal architecture to adverse clinical outcomes. Additionally, we utilized a novel approach to mutational signature analysis that leverages clonal architecture to uncover additional cases of homologous recombination and mismatch repair deficiency in primary and metastatic tumors and link the origin of mutational signatures to specific subclones. Broadly, prostate cancer clonal architecture analysis reveals novel biological insights that may be immediately clinically actionable and provide multiple opportunities for subsequent investigation.Statement of significanceTumors from patients who self-reported as Black demonstrate linear and monoclonal evolutionary trajectories yet experience higher rates of biochemical recurrence. In addition, analysis of clonal and subclonal mutational signatures identifies additional tumors with potentially actionable alterations such as deficiencies in mismatch repair and homologous recombination.
SMASH: Scalable Method for Analyzing Spatial Heterogeneity of genes in spatial transcriptomics data
Authors: Seal Souvik , Bitler Benjamin G. , Ghosh Debashis 
Published: March 2023

AbstractIn high-throughput spatial transcriptomics (ST) studies, it is of great interest to identify the genes whose level of expression in a tissue covaries with the spatial location of cells/spots. Such genes, also known as spatially variable genes (SVGs), can be crucial to the biological understanding of both structural and functional characteristics of complex tissues. Existing methods for detecting SVGs either suffer from huge computational demand or significantly lack statistical power. We propose a non-parametric method termed SMASH that achieves a balance between the above two problems. We compare SMASH with other existing methods in varying simulation scenarios demonstrating its superior statistical power and robustness. We apply the method to four ST datasets from different platforms revealing interesting biological insights.
On the limits to invasion prediction using coexistence outcomes
Authors: Deng Jie , Taylor Washington , Levin Simon A. , Saavedra Serguei 
Published: March 2023

AbstractThe dynamics of ecological communities in nature are typically characterized by probabilistic processes involving invasion dynamics. Because of technical challenges, however, the majority of theoretical and experimental studies have focused on coexistence dynamics. Therefore, it has become central to understand the extent to which coexistence outcomes can be used to predict analogous invasion outcomes relevant to systems in nature. Here, we study the limits to this predictability under a geometric and probabilistic Lotka-Volterra framework. We show that while survival probability in coexistence dynamics can be fairly closely translated into colonization probability in invasion dynamics, the translation is less precise between community persistence and community augmentation, and worse between exclusion probability and replacement probability. These results provide a guiding and testable theoretical framework regarding the translatability of outcomes between coexistence and invasion outcomes when communities are represented by Lotka-Volterra dynamics under environmental uncertainty.
A Single-Nucleus Atlas of Seed-to-Seed Development in Arabidopsis
Authors: Lee Travis A. , Nobori Tatsuya , Illouz-Eliaz Natanella , Xu Jiaying , Jow Bruce , Nery Joseph R. , Ecker Joseph R. 
Published: March 2023

SUMMARYExtensive studies of the reference plant Arabidopsis have enabled a deep understanding of tissues throughout development, yet a census of cell types and states throughout development is lacking. Here, we present a single-nucleus transcriptome atlas of seed-to-seed development employing over 800,000 nuclei, encompassing a diverse set of tissues across ten developmental stages, with spatial transcriptomic validation of the dynamic seed and silique. Cross-organ analyses revealed transcriptional conservation of cell types throughout development and heterogeneity within individual cell types influenced by organ-of-origin and developmental timing, including groups of transcription factors, suggesting gatekeeping by transcription factor activation. This atlas provides a resource for the study of cell type specification throughout the development continuum and a reference for stimulus-response and genetic perturbations at the single-cell resolution.
Mapping the neutralizing specificity of human anti-HIV serum by deep mutational scanning
Authors: Radford Caelan E. , Schommers Philipp , Gieselmann Lutz , Crawford Katharine H. D. , Dadonaite Bernadeta , Yu Timothy C. , Dingens Adam S. , Overbaugh Julie , Klein Florian , Bloom Jesse D. 
Published: March 2023

AbstractUnderstanding the specificities of human serum antibodies that broadly neutralize HIV can inform prevention and treatment strategies. Here we describe a deep mutational scanning system that can measure the effects of combinations of mutations to HIV envelope (Env) on neutralization by antibodies and polyclonal serum. We first show that this system can accurately map how all functionally tolerated mutations to Env affect neutralization by monoclonal antibodies. We then comprehensively map Env mutations that affect neutralization by a set of human polyclonal sera known to target the CD4-binding site that neutralize diverse strains of HIV. The neutralizing activities of these sera target different epitopes, with most sera having specificities reminiscent of individual characterized monoclonal antibodies, but one sera targeting two epitopes within the CD4 binding site. Mapping the specificity of the neutralizing activity in polyclonal human serum will aid in assessing anti-HIV immune responses to inform prevention strategies.
Stereotypical hippocampal clustering predicts navigational success in virtualized real-world environments
Authors: Ozubko Jason D. , Campbell Madelyn , Verhayden Abigail , Demetri Brooke , Brady Molly , Brunec Iva 
Published: March 2023

AbstractStructural differences along the long-axis of the hippocampus have long been believed to underlie meaningful functional differences, such as the granularity of information processing. Recent findings show that data-driven parcellations of the hippocampus sub-divide the hippocampus into a 10-cluster map with anterior-medial, anterior-lateral, and posteroanterior-lateral, middle, and posterior components. We tested whether task and experience could modulate this clustering using a spatial learning experiment where subjects were trained to virtually navigate a novel neighborhood in a Google Street View-like environment over a two-week period. Subjects were scanned while navigating routes early in training and at the end of their two-week training. Using the 10-cluster map as the ideal template, we find that subjects who eventually learn the neighborhood well have hippocampal cluster-maps consistent with the ideal—even on their second day of learning—and their cluster mappings do not change over the two week training period. However, subjects who eventually learn the neighborhood poorly begin with hippocampal cluster-maps inconsistent with the ideal, though their cluster mappings become more stereotypical by the end of the two week training. Interestingly this improvement seems to be route specific as even after some early improvement, when a new route is navigated participants’ hippocampal maps revert back to less stereotypical organization. We conclude that hippocampal clustering is not dependent solely on anatomical structure, and instead is driven by a combination of anatomy, task, and importantly, experience. Nonetheless, while hippocampal clustering can change with experience, efficient navigation depends on functional hippocampal activity clustering in a stereotypical manner, highlighting optimal divisions of processing along the hippocampal anterior-posterior and medial-lateral-axes.
MIDASim: a fast and simple simulator for realistic microbiome data
Authors: He Mengyu , Zhao Ni , Satten Glen A. 
Published: March 2023

AbstractBackgroundAdvances in sequencing technology has led to the discovery of associations between the human microbiota and many diseases, conditions, and traits. With the increasing availability of microbiome data, many statistical methods have been developed for studying these associations. The growing number of newly developed methods highlights the need for simple, rapid, and reliable methods to simulate realistic microbiome data, which is essential for validating and evaluating the performance of these methods. However, generating realistic microbiome data is challenging due to the complex nature of microbiome data, which feature correlation between taxa, sparsity, overdispersion, and compositionality. Current methods for simulating microbiome data are deficient in their ability to capture these important features of microbiome data, or can require exorbitant computational time.MethodsWe develop MIDASim (MIcrobiomeDAtaSimulator), a fast and simple approach for simulating realistic microbiome data that reproduces the distributional and correlation structure of a template microbiome dataset. MIDASim is a two-step approach. The first step generates correlated binary indicators that represent the presence-absence status of all taxa, and the second step generates relative abundances and counts for the taxa that are considered to be present in step 1, utilizing a Gaussian copula to account for the taxon-taxon correlations. In the second step, MIDASim can operate in both a nonparametric and parametric mode. In the nonparametric mode, the Gaussian copula uses the empirical distribution of relative abundances for the marginal distributions. In the parametric mode, an inverse generalized gamma distribution is used in place of the empirical distribution.ResultsWe demonstrate improved performance of MIDASim relative to other existing methods using gut and vaginal data. MIDASim showed superior performance by PER-MANOVA and in terms of alpha diversity and beta dispersion in either parametric or nonparametric mode. We also show how MIDASim in parametric mode can be used to assess the performance of methods for finding differentially abundant taxa in a compositional model.ConclusionsMIDASim is easy to implement, flexible and suitable for most microbiome data simulation situations. MIDASim has three major advantages. First, MIDASim performs better in reproducing the distributional features of real data compared to other methods at both presence-absence level and relative-abundance level. MIDASim-simulated data are more similar to the template data than competing methods, as quantified using a variety of measures. Second, MIDASim makes few distributional assumptions for the relative abundances, and thus can easily accommodate complex distributional features in real data. Third, MIDASim is computationally efficient and can be used to simulate large microbiome datasets.
Quadratic trends: a morphometric tool both old and new
Authors: Bookstein Fred L. 
Published: March 2023

AbstractThe original exposition of the method of “Cartesian transformations” in D’Arcy Thompson’s great essayOn Growth and Formof 1917 is still its most cited. But generations of theoretical biologists have struggled ever since to invent a biometric method aligning that approach with the comparative anatomist’s ultimate goal of inferring bio-logically meaningful hypotheses from empirical geometric patterns. Thirty years ago our community converged on a common data resource, samples of landmark configurations, and a currently popular biometric toolkit for this purpose, the “morphometric synthesis,” that combines Procrustes shape coordinates with thin-plate spline renderings of their various multivariate statistical comparisons. But because both tools algebraically disarticulate the landmarks in the course of a linear multivariate analysis, they have no access to the actual anatomical information conveyed by the arrangements and adjacencies of these locations as they combine in pairs or higher numbers into substructures. This paper explores a geometric approach circumventing these fundamental difficulties: an explicit statistical methodology for the simplest nonlinear patterning of these comparisons at their largest scale, their fits by what Sneath (1967) called quadratic trend surfaces. After an initial quadratic regression of target configurations on a template, the proposed method ignores individual shape coordinates completely, replacing them by a close reading of the regression coefficients accompanied by several new diagrams, notably the exhaustive summary of each regression by an unfamiliar biometric ellipse, its circuit of second-order directional derivatives. These novel trend coordinates, directly visualizable in their own coordinate plane, do not reduce to any of the usual Procrustes or thin-plate summaries. The geometry and algebra of these second-derivative ellipses seem a serviceable first approximation for applications in evo-devo studies and elsewhere. Two examples are offered, one the classic growth data set of Vilmann neurocranial octagons and the other the Marcus group’s data set of midsagittal cranial landmarks over most of the orders of the mammals. Each analysis yields startling new findings inaccessible to the current GMM toolkit. A closing discussion suggests a variety of ways by which innovations in this spirit might burst the current strait-jacket of Procrustes coordinates and thin-plate splines that together so severely constrain the conversion of landmark locations into understanding across our science.
Understanding Complex Trait Susceptibilities and Ethnical Diversity in a Sample of 4,145 Russians Through Analysis of Clinical and Genetic Data
Authors: Usoltsev Dmitrii , Kolosov Nikita , Rotar Oxana , Loboda Alexander , Boyarinova Maria , Moguchaya Ekaterina , Kolesova Ekaterina , Erina Anastasia , Tolkunova Kristina , Rezapova Valeriia , Melnik Olesya , Freylikhman Olga , Paskar Nadezhda , Alieva Asiiat , Baranova Elena , Bazhenova Elena , Beliaeva Olga , Vasilyeva Elena , Kibkalo Sofia , Skitchenko Rostislav , Babenko Alina , Sergushichev Alexey , Dushina Alena , Lopina Ekaterina , Basyrova Irina , Libis Roman , Duplyakov Dmitrii , Cherepanova Natalya , Donner Kati , Laiho Paivi , Kostareva Anna , Konradi Alexandra , Shlyakhto Evgeny , Palotie Aarno , Daly Mark J. , Artomov Mykyta 
Published: March 2023

AbstractThe population of Russia consists of more than 150 local ethnicities. The ethnic diversity and geographic origins, which extend from eastern Europe to Asia, make the population uniquely positioned to investigate the shared properties of inherited disease risks between European and Asian ethnicities.We present the analysis of genetic and phenotypic data from a cohort of 4,145 individuals collected in three metro areas in western Russia. We show the presence of multiple admixed ancestry clusters spanning from primarily European to Asian and high identity-by-descent sharing with the Finnish population. As a result, there was notable enrichment of Finnish-specific variants in Russia. We illustrate the utility of Russian-descent cohorts for discovery of novel population-specific genetic associations, as well as replication of previously identified associations that were thought to be population-specific in other cohorts.Finally, we provide access to a database of GWAS results for 465 unique phenotypes and allele frequencies.