bluuebunny/crossref_metadata_2025_split huggingface dataset:
Seasonality of the estrus cycle in laboratory mice under constant conditions
Authors: Reichard Tess M. , Miller Caitlin H. , Yang Jay , Sheehan Michael J. 
Published: September 2024

AbstractSeasonality governs every aspect of life in the natural environment. Controlled laboratory settings are intended to keep animals under a constant set of environmental cues with no seasonality. However, prior research suggests that seasonal variation may exist despite aseasonal lab environments. Here, we examined if seasonal reproductive variation was present in a laboratory mouse strain (C57BL/6J) under standard laboratory housing conditions. We found that female C57BL/6J mice exhibited reproductive seasonality mirroring the outside environment, in a controlled “simulated summer” environment. In the winter and spring, females have longer ovulating phases (proestrus and estrus), compared to the fall. Females similarly experience lengthier complete cycles in the spring, with the most rapid cycling occurring in the fall. Additionally, females spent more time in ovulating phases across seasons than previously reported. Laboratory mice are sensitive to external seasonal changes, despite their local environment being light, temperature, and humidity controlled. This may be due to the detection of an unidentified external cue providing information about external seasonal changes. These findings represent just one example of how seasonality may impact mouse physiology in laboratory settings, emphasizing the need to account for such influences in biomedical research.
Data-Independent Acquisition Mass Spectrometry as a Tool for Metaproteomics: Interlaboratory Comparison Using a Model Microbiome
Authors: Rajczewski Andrew T. , Alfredo Blakeley-Ruiz J. , Meyer Annaliese , Vintila Simina , McIlvin Matthew R. , Van Den Bossche Tim , Searle Brian C. , Griffin Timothy J. , Saito Mak A. , Kleiner Manuel , Jagtap Pratik D. 
Published: September 2024

AbstractMass spectrometry (MS)-based metaproteomics is used to identify and quantify proteins in microbiome samples, with the frequently used methodology being Data-Dependent Acquisition mass spectrometry (DDA-MS). However, DDA-MS is limited in its ability to reproducibly identify and quantify lower abundant peptides and proteins. To address DDA-MS deficiencies, proteomics researchers have started using Data-Independent Acquisition Mass Spectrometry (DIA-MS) for reproducible detection and quantification of peptides and proteins. We sought to evaluate the reproducibility and accuracy of DIA-MS metaproteomic measurements relative to DDA-MS using a mock community of known taxonomic composition. Artificial microbial communities of known composition were analyzed independently in three laboratories using DDA- and DIA-MS acquisition methods. DIA-MS yielded more protein and peptide identifications than DDA-MS in each laboratory. In addition, the protein and peptide identifications were more reproducible in all laboratories and provided an accurate quantification of proteins and taxonomic groups in the samples. We also identified some limitations of current DIA tools when applied to metaproteomic data, highlighting specific needs to improve DIA tools enabling analysis of metaproteomic datasets from complex microbiomes. Ultimately, DIA-MS represents a promising strategy for MS-based metaproteomics due to its large number of detected proteins and peptides, reproducibility, deep sequencing capabilities, and accurate quantitation.
Estimation of demography and mutation rates from one million haploid genomes
Authors: Schraiber Joshua G. , Spence Jeffrey P. , Edge Michael D. 
Published: September 2024

AbstractAs genetic sequencing costs have plummeted, datasets with sizes previously un-thinkable have begun to appear. Such datasets present new opportunities to learn about evolutionary history, particularly via rare alleles that record the very recent past. However, beyond the computational challenges inherent in the analysis of many large-scale datasets, large population-genetic datasets present theoretical problems. In particular, the majority of population-genetic tools require the assumption that each mutant allele in the sample is the result of a single mutation (the “infinite sites” assumption), which is violated in large samples. Here, we present DR EVIL, a method for estimating mutation rates and recent demographic history from very large samples. DR EVIL avoids the infinite-sites assumption by using a diffusion approximation to a branching-process model with recurrent mutation. The branching-process approach limits the method to rare alleles, but, along with recent results, renders tractable likelihoods with recurrent mutation. We show that DR EVIL performs well in simulations and apply it to rare-variant data from a million haploid samples, identifying a signal of mutation-rate heterogeneity within commonly analyzed classes and predicting that in modern sample sizes, most rare variants at sites with high mutation rates represent the descendants of multiple mutation events.
Cohesin-mediated chromatin remodeling controls the differentiation and function of conventional dendritic cells
Authors: Adams Nicholas M. , Galitsyna Aleksandra , Tiniakou Ioanna , Esteva Eduardo , Lau Colleen M. , Reyes Jojo , Abdennur Nezar , Shkolikov Alexey , Yap George S. , Khodadadi-Jamayran Alireza , Mirny Leonid A. , Reizis Boris 
Published: September 2024

AbstractThe cohesin protein complex extrudes chromatin loops, stopping at CTCF-bound sites, to organize chromosomes into topologically associated domains, yet the biological implications of this process are poorly understood. We show that cohesin is required for the post-mitotic differentiation and function of antigen-presenting dendritic cells (DCs), particularly for antigen cross-presentation and IL-12 secretion by type 1 conventional DCs (cDC1s)in vivo. The chromatin organization of DCs was shaped by cohesin and the DC-specifying transcription factor IRF8, which controlled chromatin looping and chromosome compartmentalization, respectively. Notably, optimal expression of IRF8 itself required CTCF/cohesin-binding sites demarcating theIrf8gene. During DC activation, cohesin was required for the induction of a subset of genes with distal enhancers. Accordingly, the deletion of CTCF sites flanking theIl12bgene reduced IL-12 production by cDC1s. Our data reveal an essential role of cohesin-mediated chromatin regulation in cell differentiation and functionin vivo, and its bi-directional crosstalk with lineage-specifying transcription factors.
Isolating the Direct Effects of Growth Hormone on Lifespan and Metabolism
Authors: Lasher Alexander Tate , Liu Kaimao , Fitch Michael , Sun Liou Y. 
Published: September 2024

SummaryPrior studies show that disrupting somatotropic axis components extends laboratory mouse lifespan, but confounding effects of additional genes and hormones obscure the specific impact of growth hormone (GH) on longevity. We address this issue by using mice with a specific knockout of the GH gene, revealing that disrupting GH alone substantially increases lifespan. The longevity effects are accompanied by altered metabolic fuel utilization, directly linking GH action to aging mechanisms.
SMoRe GloS: An efficient and flexible framework for inferring global sensitivity of agent-based model parameters
Authors: Bergman Daniel R. , Jackson Trachette , Jain Harsh Vardhan , Norton Kerri-Ann 
Published: September 2024

ABSTRACTAgent-based models (ABMs) have become essential tools for simulating complex biological, ecological, and social systems where emergent behaviors arise from the interactions among individual agents. Quantifying uncertainty through global sensitivity analysis is crucial for assessing the robustness and reliability of ABM predictions. However, most global sensitivity methods demand substantial computational resources, making them impractical for highly complex models. Here, we introduce SMoRe GloS (SurrogateModeling forRecapitulatingGlobalSensitivity), a novel, computationally efficient method for performing global sensitivity analysis of ABMs. By leveraging explicitly formulated surrogate models, SMoRe GloS allows for comprehensive parameter space exploration and uncertainty quantification without sacrificing accuracy. We demonstrate our method’s flexibility by applying it to two biological ABMs: a simple 2D cell proliferation assay and a complex 3D vascular tumor growth model. Our results show that SMoRe GloS is compatible with simpler methods like the Morris one-at-a-time method, and more computationally intensive variance-based methods like eFAST. SMoRe GloS accurately recovered global sensitivity indices in each case while achieving substantial speedups, completing analyses in minutes. In contrast, direct implementation of eFAST amounted to several days of CPU time for the complex ABM. Remarkably, our method also estimates sensitivities for ABM parameters representing processes not explicitly included in the surrogate model, further enhancing its utility. By making global sensitivity analysis feasible for computationally expensive models, SMoRe GloS opens up new opportunities for uncertainty quantification in complex systems, allowing for more in depth exploration of model behavior, thereby increasing confidence in model predictions.
Machine Learning-based Predictions of Spatial Metabolic Profiles Demonstrate the Impact of Morphology on Astrocytic Energy Metabolism
Authors: Papavasileiou Paris , Farina Sofia , Koronaki Eleni D. , Boudouvis Andreas G. , Bordas Stéphane P.A. , Skupin Alexander 
Published: September 2024

AbstractThis work introduces a machine learning framework that allows the investigation of the influence of reaction centers on the metabolic state of astrocyte cells. The proposed ML framework takes advantage of spatial astrocyte metabolic data stemming from numerical simulations for different reaction center configurations and allows for the following: (i) Discovery of cell groups of similar metabolic states and investigation of the reaction center configuration within each group. This approach allows for an analysis of the importance of the specific location of the reaction centers for a potentially critical metabolic state of the cell. (ii) Qualitative prediction of the energetic state of the cell (based on [ATP]: [ADP]) and quantitative prediction of the metabolic state of the cell by predicting the spatial average concentration of the metabolites or the complete spatial metabolic profile within the cell. (iii) Finally, the framework allows for the post hoc analysis of the developed quantitative predictive models using a SHAP approach to investigate the influence of the reaction center positions for further support of the insights drawn in steps (i)-(iii). Following the implementation of the framework, we observe that a uniform mitochondrial distribution within the cell results in the most robust energetic cell state. On the contrary, realizations of polarized mitochondrial distributions exhibit the worst overall cell health. Furthermore, we can make accurate qualitative predictions regarding cell health (accuracy= 0.9515,recall= 0.9753) and satisfactory predictions for the spatial average concentration and spatial concentration profiles of most of the metabolites involved. The techniques proposed in this study are not restricted to the dataset used. They can be easily used in other datasets that include findings from various metabolic computational models.
Robust RNA Secondary Structure Prediction with a Mixture of Deep Learning and Physics-based Experts
Authors: Qiu Xiangyun 
Published: September 2024

ABSTRACTA mixture of experts (MoE) approach is developed to mitigate poor out-of-distribution (OOD) generalization of deep learning (DL) models for single-sequence-based prediction of RNA secondary structure. The main idea is to use DL models for in-distribution (ID) test sequences to take advantage of their superior ID performances, while relying on physics-based models for OOD sequences to ensure robust predictions. One key ingredient of the pipeline, named MoEFold2D, is automated ID/OOD detection via consensus analysis of an ensemble of DL model predictions without accessing training data during inference. Specifically, motivated by the clustered distribution of known RNA structures, a collection of distinct DL models is trained by iteratively leaving one cluster out. Each DL model hence serves as an expert on all but one cluster in the training data. Consequently, for an ID sequence, all but one DL model makes accurate predictions consistent with one another, while an OOD sequence yields highly inconsistent predictions among all DL models. Consensus analysis of DL predictions categorizes test sequences as ID or OOD. ID sequences are then predicted by averaging the DL models in consensus, and OOD sequences are predicted using physics-based models. Instead of remediating generalization gaps with alternative approaches such as transfer learning and sequence alignment, MoEFold2D circumvents unpredictable ID-OOD gaps and combines the strengths of DL and physics-based models to achieve accurate ID and robust OOD predictions.
Acute tuft cell ablation induces malabsorption and alterations in secretory and immune cell lineages in small intestine
Authors: Momoh Michael , Adeniran Francisca , Ramos Cynthia , DelGiorno Kathleen E. , Seno Hiroshi , Roland Joseph T. , Kaji Izumi 
Published: September 2024

ABSTRACTBackground & AimsIntestinal tuft cells have recently been the interest of studies in several human gastrointestinal diseases. However, the impact of tuft cell deletion on intestinal physiological functions are not fully understood. This study investigated the effects of acute tuft cell loss on nutrient absorption and cell lineage differentiation.MethodsTuft cell deletion was induced inDCLK1-IRES-GFP-CreERT2/+;Rosa-DTA(DCLK1-DTA) mice by a single tamoxifen injection concomitant with littermate controls. Intestinal tissues were analyzed two-, four-, or seven-days post tamoxifen injection.ResultsDCLK1-DTA mice showed significantly shortened small intestinal length and body weight loss on day 4. Impaired activities of Na+-dependent glucose transporter 1 (SGLT1) and cystic fibrosis transmembrane regulator (CFTR) were observed in Ussing chamber experiments. Tissue immunostaining revealed a transient deletion of intestinal and biliary tuft cells, which was maximal on day 4 and recovered by day 7. On day 4 post tamoxifen, cholecystokinin (CCK)+ enteroendocrine cell numbers were increased particularly in the ileum. Correlated with the tuft cell reduction, the frequency of mislocalized Paneth cells, which were co-labeled by Paneth and goblet cell markers, was increased in the villus regions. In the lamina propria, fewer mast cells and leukocytes were found in the day 4 DCLK1-DTA mice than in controls.ConclusionAblation of intestinal tuft cells may induce nutrient malabsorption through alterations in epithelial cell proliferation and differentiation along with changes in mucosal defense response. These observations elucidate a new role for tuft cells in regulating intestinal absorption and mucosal regeneration.
BCR ligation selectively inhibits IgE class switch recombination
Authors: Wade-Vallance Adam K. , Yang Zhiyong , Libang Jeremy B. , Krishnapura Ananya R. , Jung James B. , Matcham Emily W. , Robinson Marcus J. , Allen Christopher D. C. 
Published: September 2024

AbstractMechanisms that restrict class switch recombination (CSR) to IgE limit the subsequent production of IgE antibodies and therefore the development of allergic disease. Mice with impaired B cell receptor (BCR) signaling have significantly increased IgE responses, consistent with a role for BCR signaling in IgE regulation. While prior work focused on BCR signaling in IgE-expressing cells to explain these findings, it has been reported that BCR signaling can reduce CSR. Therefore, we investigated the possibility that IgE CSR might be particularly sensitive to inhibition by BCR signaling in unswitched B cells. We found that immunization of mice with high-affinity antigen resulted in reduced representation of IgE-expressing cells among germinal center B cells and plasma cells relative to a low-affinity antigen. Mechanistic experiments with cultured mouse B cells demonstrated that BCR ligands selectively inhibited IgE CSR in a dose-, affinity-, and avidity-dependent manner. Signaling via Syk was required for the inhibition of IgE CSR following BCR stimulation, whereas inhibition of the PI3K subunit p110δ increased IgE CSR independently of BCR ligation. The inhibition of IgE CSR by BCR ligands synergized with IL-21 or TGFβ1. BCR ligation also inhibited CSR to IgE in human tonsillar B cells, and this inhibition was also synergistic with IL-21. These findings establish that IgE CSR is uniquely susceptible to inhibition by BCR signaling in mouse and human B cells, with important implications for the regulation and pathogenesis of allergic disease.
Examination of INPP5A in uveal melanoma uncovers novel calcium transients
Authors: Onken Michael D. , Kaltenbronn Kevin M. , Makepeace Carol M. , Piggott Kisha D. , Blumer Kendall J. 
Published: September 2024

AbstractUveal melanoma is a highly aggressive intraocular cancer that metastasizes in about half of patients whereupon it is inexorably fatal. Uveal melanomas (UM) are distinct from other melanomas because they are driven by constitutively activating mutation in the heterotrimeric G protein alpha subunits Gq (GNAQ) and G11 (GNA11). This results in constitutive production of inositol trisphosphate (IP3) by phospholipase C-beta downstream of Gq/11. In normal cells, increased IP3 causes calcium release from the endoplasmic reticulum, which would be cytotoxic if maintained chronically, but UM cells are able to survive constitutive IP3 production. INPP5A, which dephosphorylates and thus inactivates IP3, is highly upregulated in UM cells compared to other melanomas and another study has shown that INPP5A is necessary for UM cell survival. To understand the mechanism of calcium regulation in response to IP3, we collected single-cell calcium measurements and found that UM cells driven by constitutively active Gq/11 produce spontaneous calcium transients. These calcium oscillations are not seen in any other melanoma cell lines unless induced by an agonist, but they are present in patient UM tumor samples. Moreover, these calcium oscillations are lost in UM cells treated with the Gq/11 inhibitor FR900359, demonstrating their dependence on constitutive Gq/11 activity. We found that the INPP5A inhibitor YU144369 causes significant changes in calcium oscillations in UM cells, demonstrating a role for INPP5A in this system. INPP5A is tethered to membranes by C-terminal prenylation and palmitoylation, suggesting that localization may play a role in INPP5A regulation of IP3 levels. GFP-tagged INPP5A was localized to plasma membrane, nuclear envelop, endoplasmic reticulum, and lysosomes. Mutation of the palmitoylation site significantly reduced localization to the plasma membrane, while mutation of the prenylation site resulted in purely nucleoplasmic localization of INPP5A. These results demonstrate a role of palmitoylation in the regulation of INPP5A localization and mobilization in UM cells.
Placozoan secretory cell types implicated in feeding, innate immunity and regulation of behavior
Authors: Mayorova Tatiana D. , Koch Thomas Lund , Kachar Bechara , Jung Jae Hoon , Reese Thomas S. , Smith Carolyn L. 
Published: September 2024

AbstractPlacozoa are millimeter-sized, flat, irregularly shaped ciliated animals that crawl on surfaces in warm oceans feeding on biofilms, which they digest externally. They stand out from other animals due to their simple body plans. They lack organs, body cavities, muscles and a nervous system and have only seven broadly defined morphological cell types, each with a unique distribution. Analyses of single cell transcriptomes of four species of placozoans revealed greater diversity of secretory cell types than evident from morphological studies, but the locations of many of these new cell types were unknown and it was unclear which morphological cell types they represent. Furthermore, there were contradictions between the conclusions of previous studies and the single cell RNAseq studies. To address these issues, we used mRNA probes for genes encoding secretory products expressed in different metacells inTrichoplax adhaerensto localize cells in whole mounts and in dissociated cell cultures, where their morphological features could be visualized and identified. The nature and functions of their secretory granules were further investigated with electron microscopic techniques and by imaging secretion in live animals during feeding episodes. We found that two cell types participate in disintegrating prey, one resembling a lytic cell type in mammals and another combining features of zymogen gland cells and enterocytes. We identified secretory epithelial cells expressing glycoproteins or short peptides implicated in defense. We located seven peptidergic cell types and two types of mucocytes. Our findings reveal mechanisms that placozoans use to feed and protect themselves from pathogens and clues about neuropeptidergic signaling. We compare placozoan secretory cell types with cell types in other animal phyla to gain insight about general evolutionary trends in cell type diversification, as well as pathways leading to the emergence of synapomorphies.
Halogenated cholesterol alters the phase behavior of ternary lipid membranes
Authors: Mehta Deeksha , Crumley Elizabeth K. , Lou Jinchao , Best Michael D. , Waxham M. Neal , Heberle Frederick A. 
Published: September 2024

AbstractEukaryotic plasma membranes exhibit nanoscale lateral lipid heterogeneity, a feature that is thought to be central to their function. Studying these heterogeneities is challenging since few biophysical methods are capable of detecting domains at sub-micron length scales. We recently showed that cryogenic electron microscopy (cryo-EM) can directly image nanoscale liquid-liquid phase separation in extruded liposomes due to its ability to resolve the intrinsic thickness and electron density differences of ordered and disordered phases. However, the intensity contrast between these phases is poor compared to conventional fluorescence microscopy and is thus both a limiting factor and a focal point for optimization. Because the fundamental source of intensity contrast is the spatial variation in electron density within the bilayer, lipid modifications aimed at selectively increasing the electron density of one phase might enhance the ability to resolve coexisting phases. To this end, we investigated model membrane mixtures of DPPC/DOPC/cholesterol in which one hydrogen of cholesterol’s C19 methyl group was replaced by an electron-rich halogen atom (either bromine or iodine). We characterized the phase behavior as a function of composition and temperature using fluorescence microscopy, FRET, and cryo-EM. Our data suggest that halogenated cholesterol variants distribute approximately evenly between liquid-ordered and liquid-disordered phases and are thus ineffective at enhancing the intensity difference between them. Furthermore, replacing more than half of the native cholesterol with halogenated cholesterol variants dramatically reduces the size of membrane domains. Our results reinforce how small changes in sterol structure can have a large impact on the lateral organization of membrane lipids.