bluuebunny/crossref_metadata_2025_split huggingface dataset:
Transcriptomic sexual conflict at two evolutionary timescales revealed by experimental evolution inCaenorhabditis elegans
Authors: Kasimatis Katja R. , Willis John H. , Sedore Christine A. , Phillips Patrick C. 
Published: August 2023

ABSTRACTSex-specific regulation of gene expression is the most plausible way for generating sexually differentiated phenotypes from an essentially shared genome. However, since genetic material is shared, sex-specific selection in one sex can have an indirect response in the other sex. From a gene expression perspective, this tethered response can move one sex away from their wildtype expression state and impact potentially many gene regulatory networks. Here, using experimental evolution in the model nematodeCaenorhabditis elegans,we explore the coupling of direct sexual selection on males with the transcriptomic response in males and females over microevolutionary timescales to uncover the extent to which post-insemination reproductive traits share a genetic basis between the sexes. We find that differential gene expression evolved in a sex-specific manner in males, while in females indirect selection causes an evolved response. Almost all differentially expressed genes were downregulated in both evolved males and females. Moreover, 97% of significantly differentially expressed genes in males and 69% of significantly differentially expressed genes in females have wildtype female-biased expression profile. Changes in gene expression profiles were likely driven throughtrans-acting pathways that are shared between the sexes. We found no evidence that the core dosage compensation machinery was impacted by experimental evolution. Together these data suggest a de-feminization of the male transcriptome and masculinization of the female transcriptome driven by direct selection on male sperm competitive ability. Our results indicate that on short evolutionary timescales sexual selection can generate putative sexual conflict in expression space.
Alternating polarity integrates chemical and mechanical cues to drive tissue morphogenesis
Authors: Osterfield Miriam 
Published: August 2023

AbstractThe spatial patterning of molecules within a sheet of cells directs morphogenesis in many epithelial tissues. InScaptodrosophilafollicle cells, Par3/Bazooka and aPKC were previously shown to localize to a set of cell edges destined to elongate and form the base of each eggshell dorsal appendage. This study establishes that the mechanism underlying this localization pattern is an alternating, in-plane polarity of the cells. A candidate screen identified several potential molecular players, whose epistatic relationships were then examined using a custom culture assay. These experiments demonstrated that positive feedback between actin polymerization and PI4P production leads to polarization of these cells individually, while mechanical force coordinates polarization among these cells. This work adds to the growing evidence for a role of mechanics in cell polarity, and also provides an example where morphological differences between species can be understood at the level of changes in fundamental cell biological processes.SummaryInScaptodrosophila, the alternating (left, right, left) polarization in a row of cells drives the formation of up to eight eggshell respiratory filaments. This study uncovers the underlying pathway, which integrates chemical signaling through actin and PI4P with mechanical force.
Data-Driven 3D Shape Analysis Reveals Cell Shape-Fate Relationships in Zebrafish Lateral Line Neuromasts
Authors: Hewitt Madeleine N. , Cruz Iván A. , Raible David W. 
Published: August 2023

AbstractCell shape is a powerful readout of cell state, fate, and function. With the advent of sophisticated microscopes, image segmentation algorithms, and numerical shape representations, it is becoming more feasible to study cell shape in developing tissues. However, few studies have analyzed cell shape in three dimensions in living, intact organisms. Here, we took advantage of the favorable imaging qualities of zebrafish lateral line neuromasts to generate a dataset of high resolution images with labeled cells and nuclei. Using a custom Python-based workflow, we performed semi-automated, 3D cell and nucleus segmentation. We then used spherical harmonics and principal components analysis to distill neuromast cell and nuclear shape variation into several interpretable, biologically meaningful parameters. We found that neuromast cell and nuclear shapes vary with cell location and identity. The distinction between hair cells and support cells was discrete and accounted for much of the variation in neuromast cell and nucleus shape, which allowed us to train classifiers to predict hair cell identity from cell and nucleus shape features. Using markers for support cell subpopulations, we found that support cell subtypes also had different shapes from each other; however, shape features did not distinguish as sharply between support cell subtypes, suggesting that support cells vary continuously in shape. To investigate the effects of genetic perturbation that results in loss of a cell type on neuromast cell shape, we examinedatoh1amutants that lack hair cells. We found that neuromasts fromatoh1amutants lacked the cell shape phenotype associated with hair cells, but did not exhibit a mutant-specific cell shape. Our results demonstrate the utility of using 3D cell shape features to characterize, compare, and classify cells in a living, developing organism.
Comprehensive analyses of 1771 transcriptome from seven tissues enhance genetic and biological interpretations of maize complex traits
Authors: Lei Mengyu , Si Huan , Zhu Mingjia , Han Yu , Liu Wei , Dai Yifei , Ji Yan , Liu Zhengwen , Hao Fan , Hao Ran , Zhao Jiarui , Ye Guoyou , Zan Yanjun 
Published: August 2023

AbstractBy analyzing 1771 RNA-seq datasets from seven tissues in a maize diversity panel, we explored the landscape of multi-tissue transcriptome variation and evolution patterns of tissue-specific genes, and built a comprehensive multi-tissue gene regulation atlas to understand the genetic regulation of maize complex trait. Using transcriptome-wide association analysis, we linked tissue-specific expression variation of 45 genes to variation of 11 agronomic traits. Through integrative analyses of tissue-specific gene regulatory variation with genome-wide association studies, we detected relevant tissue types and candidate genes for a number of agronomic traits, including leaf during the day for anthesis-silking interval (GRMZM2G093210), leaf during the day for kernel Zeinoxanthin level (GRMZM2G143202), and root for ear height (GRMZM2G700665), highlighting the contribution from tissue-specific gene expression to variation of agronomic trait. Our findings provide novel insights into the genetic and biological mechanisms underlying complex traits in maize, and the multi-tissue regulatory atlas serves as a primary source for biological interpretation, functional validation, and genomic improvement of maize.
Modeling Single Cell Trajectory Using Forward-Backward Stochastic Differential Equations
Authors: Zhang Kevin , Zhu Junhao , Kong Dehan , Zhang Zhaolei 
Published: August 2023

AbstractRecent advances in single-cell sequencing technology have provided opportunities for mathematical modeling of dynamic developmental processes at the single-cell level, such as inferring developmental trajectories. Optimal transport has emerged as a promising theoretical framework for this task by computing pairings between cells from different time points. However, optimal transport methods have limitations in capturing nonlinear trajectories, as they are static and can only infer linear paths between endpoints. In contrast, stochastic differential equations (SDEs) offer a dynamic and flexible approach that can model non-linear trajectories, including the shape of the path. Nevertheless, existing SDE methods often rely on numerical approximations that can lead to inaccurate inferences, deviating from true trajectories. To address this challenge, we propose a novel approach combining forward-backward stochastic differential equations (FBSDE) with a refined approximation procedure. Our FBSDE model integrates the forward and backward movements of two SDEs in time, aiming to capture the underlying dynamics of single-cell developmental trajectories. Through comprehensive benchmarking on multiple scRNA-seq datasets, we demonstrate the superior performance of FBSDE compared to other methods, high-lighting its efficacy in accurately inferring developmental trajectories.
Nuclear translocation of LINE-1 encoded ORF1p alters nuclear envelope integrity and disrupts nucleocytoplasmic transport in human neurons
Authors: Znaidi Rania , Massiani-Beaudoin Olivia , Mailly Philippe , Monnet Héloïse ,   The Brainbank Neuro-CEB Neuropathology Network, Joshi Rajiv L. , Fuchs Julia 
Published: August 2023

AbstractLINE-1 retrotransposons are emerging as possible culprits in neurodegenerative diseases. However, the molecular mechanisms underlying the pathogenic role of LINE-1 and their encoded proteins ORF1p and ORF2p are still not completely understood. While the endonuclease and reverse transcriptase activities of ORF2p have been associated with DNA damage and inflammation, no pathogenic role has yet been assigned to ORF1p. Using a neuronal model of oxidative stress displaying increased LINE-1 expression, we report here that ORF1p stress-dependently translocated into the nucleus, localized to the nuclear envelope and directly interacted with nuclear import proteins, nuclear pore complex components and the inner nuclear lamina. Stress-dependent targeting of nuclear envelope components by ORF1p altered nuclear envelope integrity, disrupted nucleocytoplasmic transport and induced heterochromatin destructuration, features associated with neurodegenerative diseases and aging. Neurons of post-mortem Parkinson disease (PD) patients and non-PD affected controls expressed ORF1p and nuclear ORF1p levels correlated with altered nuclear shape in PD. Overexpression of ORF1p in neurons in the absence of stress recapitulated nuclear envelope dysfunctions and increased nuclear ORF1p levels correlated with a loss of nuclear circularity. Stress-induced nuclear alterations were restored by blocking ORF1p nuclear import or by the small molecule remodelin. This study thus reveals a retrotransposition- and ORF2p- independent pathogenic action of ORF1p at the nuclear envelope and points to ORF1p as a novel target for neuroprotection.
Pancreatic islet α cell function and proliferation requires the arginine transporter SLC7A2
Authors: Spears Erick , Stanley Jade E. , Shou Matthew , Yin Linlin , Li Xuan , Dai Chunhua , Bradley Amber , Sellick Katelyn , Poffenberger Greg , Coate Katie C. , Shrestha Shristi , Jenkins Regina , Sloop Kyle W. , Wilson Keith T. , Attie Alan D. , Keller Mark P. , Chen Wenbiao , Powers Alvin C. , Dean E. Danielle 
Published: August 2023

AbstractInterrupting glucagon signaling decreases gluconeogenesis and the fractional extraction of amino acids by liver from blood resulting in lower glycemia. The resulting hyperaminoacidemia stimulates α cell proliferation and glucagon secretion via a liver-α cell axis. We hypothesized that α cells detect and respond to circulating amino acids levels via a unique amino acid transporter repertoire. We found thatSlc7a2ISLC7A2is the most highly expressed cationic amino acid transporter in α cells with its expression being three-fold greater in α than β cells in both mouse and human. Employing cell culture, zebrafish, and knockout mouse models, we found that the cationic amino acid arginine and SLC7A2 are required for α cell proliferation in response to interrupted glucagon signaling. Ex vivoandin vivoassessment of islet function inSlc7a2−/−mice showed decreased arginine-stimulated glucagon and insulin secretion. We found that arginine activation of mTOR signaling and induction of the glutamine transporter SLC38A5 was dependent on SLC7A2, showing that both’s role in α cell proliferation is dependent on arginine transport and SLC7A2. Finally, we identified single nucleotide polymorphisms inSLC7A2associated with HbA1c. Together, these data indicate a central role for SLC7A2 in amino acid-stimulated α cell proliferation and islet hormone secretion.
Plant allometry derived from Metabolic Scaling Theory and segregated by tissue functionality
Authors: Sopp S. , Valbuena R. 
Published: August 2023

AbstractPlant allometry is key for determining the role of forests in global carbon cycles, through the calculation of tree biomass using proxy measurements such as tree diameters or heights. Metabolic Scaling Theory (MST) considers the general principles that underpin allometry, but MST scaling relationships have been challenged on their lack of fit to empirical data and global applicability. Many authors have thus optimised their model forms for statistical performance over theory based approaches. We postulated that MST scaling is applicable only to the proportion of plant tissue with supportive functionality, meaning that as plants evolved tissues of specialized conductive functionality (e.g vessels) their allometry progressed into more complex relationships. Our generalised MST (gMST) models were thus created by considering conductive lumen as unsupportive area, and consequentially removing it from the original MST 2/3 scaling. According to this principle, we deducted generalized gMST relationships with mechanistically deducted coefficients. We found that the gMST height-diameter scaling outperformed current state of the art equations that are widely used within the tropics and that the model performed well across all tested ecoregions. Furthermore, the proposed aboveground biomass models performed similarly to widely used models in the literature within the tropics. The results presented indicate that the further development of generalised allo-metric models remains a research priority given the importance of assessing and monitoring global forest carbon fluxes. The height-diameter models presented can thus be of much use to the wider community in further refining carbon stock estimates globally, providing a universally applicable theoretical framework.
Chemotherapeutic regulation of the ROS/MondoA-dependent TXNIP/GDF15 axis; and derivation of a new organoid metric as a predictive biomarker
Authors: Deng Jinhai , Pan Teng , Hong Yourae , Liu Zaoqu , Zhou Xingang , An Zhengwen , Li Lifeng , Alfano Giovanna , Li Gang , Dolcetti Luigi , Evans Rachel , Vicencio Jose M , Vlckova Petra , Chen Yue , Monypenny James , De Carvalho Gomes Camila Araujo , Ng Kenrick , McCarthy Caitlin , Yang Xiaoping , Hu Zedong , Porter Joanna C. , Tape Christopher J , Yin Mingzhu , Rodriguez-Justo Manuel , Tejpar Sabine , Beatson Richard , Ng Tony 
Published: August 2023

AbstractChemotherapy, the standard of care treatment for cancer patients with advanced disease, has been increasingly recognised to activate host immune responses to produce durable outcomes. Here, in colorectal adenocarcinoma (CRC) we identify chemotherapy-induced Thioredoxin Interacting Protein (TXNIP),a MondoA-dependent tumor suppressor gene, as a negative regulator of Growth/Differentiation Factor 15 (GDF15). GDF15 is a negative prognostic factor in CRC and promotes the differentiation of regulatory T cells (Tregs), through CD48 ligation. Intriguingly, multiple models including patient-derived tumor organoids demonstrate that loss of TXNIP/GDF15 axis functionality is associated with advanced disease or chemotherapeutic resistance, with transcriptomic or proteomic GDF15/TXNIP ratios showing potential as a prognostic biomarker. These findings illustrate a potentially common pathway where chemotherapy-induced epithelial stress drives local immune remodelling for patient benefit, with disruption of this pathway seen in refractory or advanced cases.
Design of a Biohybrid Materials Circuit with Binary Decoder Functionality
Authors: Mohsenin Hasti , Wagner Hanna J. , Rosenblatt Marcus , Kemmer Svenja , Drepper Friedel , Huesgen Pitter , Timmer Jens , Weber Wilfried 
Published: August 2023

AbstractSynthetic biology applies concepts from electrical engineering and information processing to endow cells with computational functionality. Transferring the underlying molecular components into materials and wiring them according to topologies inspired by electronic circuit boards has yielded materials systems that perform selected computational operations. However, the limited functionality of available building blocks is restricting the implementation of advanced information-processing circuits into materials. Here, we engineer a set of protease-based biohybrid modules the bioactivity of which can either be induced or inhibited. Guided by a quantitative mathematical model and following a design-build-test-learn cycle, we wire the modules according to circuit topologies inspired by electronic signal decoders, a fundamental motif in information processing. We design a 2-input/4-output binary decoder for the detection of two small molecules in a material framework that could perform regulated outputs in form of distinct protease activities. The here demonstrated smart material system is strongly modular and could be used for biomolecular information processing for example in advanced biosensing or drug delivery applications.
Pharmacophoric-based ML model to filter candidate E3 ligands and predict E3 Ligase binding probabilities
Authors: Karki Reagon , Gadiya Yojana , Shetty Simran , Gribbon Phillip , Zaliani Andrea 
Published: August 2023

AbstractAmong the plethora of E3 Ligases, only a few have been utilized for the novel PROTAC technology. However, extensive knowledge of the preparation of E3 ligands and their utilization for PROTACs is already present in several databases. Here we provide, together with an analysis of functionalized E3 ligands, a comprehensive list of trained ML models to predict the probability to be an E3 ligase binder. We compared the different algorithms based on the different description schemes used and identified that the pharmacophoric-based ML approach was the best. Due to the peculiar pharmacophores present in E3 ligase binders and the presence of an explainable model, we were able to show the capability of our ErG model to filter compound libraries for fast virtual screening or focused library design. A particular focus was also given to target E3 ligase prediction and to find a subset of candidate E3 ligase binders within known public and commercial compound collections.
Asexual lineages of a cosmopolitan pest aphid are associated with different climatic niches
Authors: Godefroid Martin , Meynard Christine N , Clamens Anne-Laure , Popkin Megan , Jousselin Emmanuelle 
Published: August 2023

ABSTRACTAsexual lineages often exhibit broader distributions and can thrive in extreme habitats compared to their sexual counterparts. Two hypotheses have been proposed to explain this phenomenon. The general-purpose genotype model posits that selection favours a few versatile asexual genotypes with wide environmental tolerance, enabling their long-term persistence across diverse conditions. Conversely, the frozen niche variation model suggests that selection favours specialised genotypes with minimal niche overlap among them and their sexual relatives, potentially leading to competition-driven exclusion of both sexual and asexual relatives. To investigate these hypotheses, we examined ecological niche differentiation among six globally distributed obligate asexual lineages of the cosmopolitan aphid pest,Brachycaudus helichrysi. We initially investigated the presence of different endosymbionts across clones, as endosymbionts play a major role in aphid niche differentiation. Subsequently, we conducted multivariate analyses to explore climatic niche divergence among clones. We provide evidence for climatic niche specialisation in asexual lineages, which is not related to variations in endosymbiont associations. Therefore, despite their apparent global distribution,B. helichrysiclones exhibit characteristics of specialised genotypes, which aligns with the frozen niche variation hypothesis. This study represents the first comprehensive evidence of climatic adaptation in aphid superclones, providing novel insights into their global distribution.
Differences in Conformational Sampling and Intrinsic Electric Fields Drive Ion Binding in Telomeric and TERRA G-Quadruplexes
Authors: Polêto Marcelo D. , Lemkul Justin A. 
Published: August 2023

AbstractThe formation of G-quadruplexes (GQs) occurs in guanine-rich sequences of DNA and RNA, producing highly stable and structurally diverse noncanonical nucleic acid structures. GQs play crucial roles in regulating transcription, translation, and replication; and maintaining the genome, among others, thus changes to their structures can lead to diseases such as cancer. Previous studies using polarizable molecular dynamics simulations have shown differences in ion binding properties between telomeric and TERRA GQs despite architectural similarities. Here, we used volume-based metady-namics and repulsive potential simulations in conjunction with polarizable force fields to quantify the impact of ion binding on GQ dynamics and ion binding free energies. Furthermore, we describe how GQs exert electric fields on their surroundings to link dynamics with variations in electronic structure. Our findings provide new insights into the energetic, physical, and conformational properties of GQs and expose subtle, but important, differences between DNA and RNA GQs with the same fold.
Long duration environmental biosensing by recording analyte detection in DNA using recombinase memory
Authors: Kalvapalle Prashant Bharadwaj , Sridhar Swetha , Silberg Jonathan J. , Stadler Lauren B. 
Published: August 2023

ABSTRACTMicrobial biosensors that convert environmental information into real-time visual outputs are limited in their sensing abilities in complex environments, such as soil and wastewater. Alternative reporter outputs are needed that stably record the presence of analytes. Here, we test the performance of recombinase-memory biosensors that sense a sugar (arabinose) and a microbial communication molecule (3-oxo-C12- homoserine lactone) over 8 days (∼70 generations) following analyte exposure. These biosensors use analyte sensing to trigger the expression of a recombinase which flips a segment of DNA, creating a genetic memory, and initiates fluorescent protein expression. The initial designs failed over time due to unintended DNA flipping in the absence of the analyte and loss of the flipped state after exposure to the analyte. Biosensor performance was improved by decreasing recombinase expression, removing the fluorescent protein output, and using qPCR to read out stored information. Application of memory biosensors in wastewater isolates achieved memory of analyte exposure in an uncharacterizedPseudomonasisolate. By returning these engineered isolates to their native environments, recombinase-memory systems are expected to enable longer duration andin situinvestigation of microbial signaling, community shifts, and gene transfer beyond the reach of traditional environmental biosensors.IMPORTANCELiving microbial sensors can monitor chemicals and biomolecules in the environment in real-time, but they remain limited in their ability to function on the week, month, and year timescales. To determine if environmental microbes can be programmed to record the detection of analytes over longer timescales, we evaluated whether the sensing of a microbial signaling molecule could be recorded through a DNA rearrangement. We show that off-the-shelf DNA memory is suboptimal for long-duration information storage, use iterative design to enable robust functioning over more than a week, and demonstrate DNA memory in an uncharacterized wastewaterPseudomonasisolate. Memory biosensors will be useful for monitoring the role of quorum sensing in wastewater biofilm formation, and variations of this design are expected to enable studies of ecological processesin situthat are currently challenging to monitor using real-time biosensors and analytical instruments.