bluuebunny/crossref_metadata_2025_split huggingface dataset:
Endosome positioning coordinates spatially selective GPCR signaling
Authors: Willette Blair K.A. , Tsvetanova Nikoleta G. 
Published: July 2022

AbstractG protein-coupled receptors (GPCRs), a class of critical regulators of mammalian physiology, can initiate unique functional responses depending on the subcellular compartment of their activation. Yet, how endosomal receptors transduce location-biased outcomes remains poorly understood. Efforts to uncover the mechanistic basis of compartmentalized GPCR signaling have largely focused on the biochemical aspect of this regulation through dissection of the relevant factors. Here, we assess the biophysical positioning of receptor-containing endosomes as an alternative salient mechanism coordinating the transduction of spatially biased responses. We focus on the prototypical beta2-adrenergic receptor (β2-AR), which preferentially mediates transcriptional reprogramming via cyclic AMP (cAMP) production from early endosomes. We overcome a technical challenge that has hindered the direct assessment of the role of endosome positioning in this paradigm by devising a strategy to selectively and rapidly redistribute endosomes ‘on command’ in intact cells without perturbing their biochemical composition. Next, we present two complementary optical readouts that enable robust measurements of bulk- and gene-specific GPCR/cAMP-dependent transcription with single-cell resolution. We then combine these readouts with rapid endosome relocalization to establish that increasing endosome distance from the nucleus inhibits the initiation of the endosome-dependent response. Lastly, we demonstrate a prominent mechanistic role of phosphodiesterase (PDE)-mediated cAMP hydrolysis in this process. Our study, therefore, illuminates a novel mechanism regulating GPCR function by identifying endosome positioning as a principal mediator of spatially selective receptor signaling.SummaryG protein-coupled receptors (GPCRs) orchestrate essential aspects of mammalian physiology. GPCR function is tightly controlled by endocytic trafficking, where the ligand-activated receptor engages arrestins and clathrin machinery and is subsequently internalized into endosomal compartments1. While the endosome-associated receptor pool was classically presumed to be functionally inactive, it is now clear that receptors can also signal from endosomes2-4. Moreover, endosomal receptors can initiate cellular responses that are distinct from those activated at the plasma membrane. Transcriptional reprogramming was one of the first location-biased GPCR responses to be identified and shown to be stimulated from intracellular receptors5, 6. Since then, compartmentalized signaling has been implicated in the transduction of distinct phosphosignaling7, 8 and in the coordination of unique physiologies and drug actions8-17. Yet, how the endosome selectively facilitates these responses compared to other subcellular compartments remains unclear.
The mammalian forelimb diversity as a morphological gradient of increasing evolutionary versatility
Authors: Rothier Priscila S. , Fabre Anne-Claire , Clavel Julien , Benson Roger , Herrel Anthony 
Published: July 2022

AbstractVertebrate limb morphology often reflects the environment, due to variation in locomotor requirements and other ecological traits. However, proximal and distal limb segments may evolve differently to each other, reflecting an anatomical gradient of functional specialization that has been suggested to be impacted by the timing of bone condensation during ontogeny. Here we explore whether the temporal sequence of bone condensation predicts variation in the capacity of evolution to generate morphological diversity between proximal and distal forelimb segments across more than 600 species of mammals. Our findings are consistent with the hypothesis that late developing distal limb elements should display greater morphological variation than more proximal limb elements, which condense earlier during morphogenesis. Distal limb elements, belonging to the autopod, not only exhibit higher diversity of form, but are also more integrated and, on average, show greater evolutionary versatility than intermediate and upper limb segments. Our findings indicate that the macroevolutionary patterns of proximal and distal limb segments are not the same, suggesting that strong functional selection, combined with the higher potential of development to generate variation in more distal limb structures, facilitate the evolution of high autopodial disparity in mammals.
Emergent dynamics of adult stem cell lineages from single nucleus and single cell RNA-Seq ofDrosophilatestes
Authors: Raz Amelie A. , Vida Gabriela S. , Stern Sarah R. , Mahadevaraju Sharvani , Fingerhut Jaclyn M. , Viveiros Jennifer M. , Pal Soumitra , Grey Jasmine R. , Grace Mara R. , Berry Cameron W. , Li Hongjie , Janssens Jasper , Saelens Wouter , Shao Zhantao , Hu Chun , Yamashita Yukiko M. , Przytycka Teresa M. , Oliver Brian , Brill Julie A. , Krause Henry M. , Matunis Erika L. , White-Cooper Helen , DiNardo Stephen , Fuller Margaret T. 
Published: July 2022

AbstractProper differentiation of sperm from germline stem cells, essential for production of the next generation, requires dramatic changes in gene expression that drive remodeling of almost all cellular components, from chromatin to organelles to cell shape itself. Here we provide a single nucleus and single cell RNA-seq resource covering all of spermatogenesis inDrosophilastarting from in-depth analysis of adult testis single nucleus RNA-seq (snRNA-seq) data from the Fly Cell Atlas (FCA) study (Liet al., 2022). With over 44,000 nuclei and 6,000 cells analyzed, the data provide identification of rare cell types, mapping of intermediate steps in differentiation, and the potential to identify new factors impacting fertility or controlling differentiation of germline and supporting somatic cells. We justify assignment of key germline and somatic cell types using combinations of known markers,in situhybridization, and analysis of extant protein traps. Comparison of single cell and single nucleus datasets proved particularly revealing of dynamic developmental transitions in germline differentiation. To complement the web-based portals for data analysis hosted by the FCA, we provide datasets compatible with commonly used software such as Seurat and Monocle. The foundation provided here will enable communities studying spermatogenesis to interrogate the datasets to identify candidate genes to test for functionin vivo.
A Model of Hippocampal Replay Driven by Experience and Environmental Structure Facilitates Spatial Learning
Authors: Diekmann Nicolas , Cheng Sen 
Published: July 2022

AbstractReplay of neuronal sequences in the hippocampus during resting states and sleep play an important role in learning and memory consolidation. Consistent with these functions, replay sequences have been shown to obey current spatial constraints. Nevertheless, replay does not necessarily reflect previous behavior and can construct never-experienced sequences. Here we propose a stochastic replay mechanism that prioritizes experiences based on three variables: 1. Experience strength, 2. experience similarity, and 3. inhibition of return. Using this prioritized replay mechanism to train reinforcement learning agents leads to far better performance than using random replay. Its performance is close to the state-of-the-art, but computationally intensive, algorithm by Mattar & Daw (2018). Importantly, our model reproduces diverse types of replay because of the stochasticity of the replay mechanism and experience-dependent differences between the three variables. In conclusion, a unified replay mechanism generates diverse replay statistics and is efficient in driving spatial learning.
Nicotine-mediated rescue of α-synuclein toxicity requires synaptic vesicle glycoprotein 2
Authors: Olsen Abby L. , Clemens Sabrina G. , Feany Mel B. 
Published: July 2022

AbstractBackgroundParkinson’s disease (PD) is characterized by α-synuclein aggregation and loss of dopamine (DA) neurons in the substantia nigra. Risk of PD arises due to a combination of genetic and environmental factors, which may interact, termed gene-environment (GxE) interactions. An inverse association between smoking and risk of PD is well-established, and a previous genome-wide GxE interaction study identified genetic variation in the synaptic-vesicle glycoprotein 2C (SV2C) locus as an important mediator of the degree to which smoking is inversely associated with PD.ObjectiveWe sought to determine the mechanism of the smoking-SV2C interaction in a Drosophila model of PD.MethodsFlies expressing human α-synuclein in all neurons develop the hallmarks of PD, including motor dysfunction, loss of DA neurons, and formation of α-synuclein inclusions. We assessed the effects of increasing doses of nicotine on these parameters of neurodegeneration, in the presence or absence of SV2 knockdown.Resultsα-synuclein-expressing flies treated with nicotine had improvement in locomotion, DA neuron counts, and in α-synuclein aggregation. However, in α-synuclein-expressing flies in which Drosophila orthologs of SV2 were knocked down, nicotine failed to rescue neurodegeneration.ConclusionsThis work confirms a GxE interaction between nicotine and SV2, defines a role for this interaction in α-synuclein proteostasis, and suggests that future clinical trials on nicotine should consider genetic variation in SV2C. Further, this provides proof of concept that our model can be used for mechanistic study of GxE, paving the way for investigation of additional GxE interactions or identification of novel GxE.
Using transfer learning and dimensionality reduction techniques to improve generalisability of machine-learning predictions of mosquito ages from mid-infrared spectra
Authors: Mwanga Emmanuel P. , Siria Doreen J. , Mitton Joshua , Mshani Issa H. , Jimenez Mario Gonzalez , Selvaraj Prashanth , Wynne Klaas , Baldini Francesco , Okumu Fredros O. , Babayan Simon A. 
Published: July 2022

AbstractAccurate prediction of mosquito population age structures can improve the evaluation of mosquito-targeted interventions since old mosquitoes are more likely to transmit malaria than young ones. Mid-infrared spectroscopy (MIRS) reveals age-associated variation in the biochemical composition of the mosquito cuticle, which can then be used to train machine learning (ML) models to predict mosquito ages. However, these MIRS-ML models are not always generalisable across different mosquito populations. Here, we investigated whether dimensionality reduction applied to the MIRS input data and transfer learning could improve the generalisability of MIRS-ML predictions for mosquito ages. We reared adults of the malaria vector, Anopheles arabiensis, in two insectaries (Ifakara, Tanzania and Glasgow, UK). The heads and thoraces of female mosquitoes of two age classes (1-9 day-olds and 10-17 day-olds) were scanned using an attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectrometer (4000 cm-1 to 400 cm-1). The dimensionality of the spectra data was reduced using unsupervised principal component analysis (PCA) or t-distributed stochastic neighbour embedding (t-SNE), and then the spectra were used to train deep learning (DL) and standard machine learning (ML) classifiers. Transfer learning was also evaluated for improving the computational cost of the models when predicting mosquito age classes from new populations. Model accuracies for predicting the age of test mosquitoes from the same insectary as the training samples reached 99% for DL and 92% for ML, but did not generalise to a different insectary, achieving only 46% and 48% for ML for DL, respectively. Dimensionality reduction did not improve the model generalisability between locations but reduced computational time up to 5-fold. However, transfer learning by updating pre-trained models with 2% of mosquitoes from the alternate location brought both DL and standard ML model performance to ~98% accuracy for predicting mosquito age classes in the alternative insectary. Combining dimensionality reduction and transfer learning can reduce computational costs and improve the transferability of both deep learning and standard machine learning models for predicting the age of mosquitoes. Future studies could investigate the optimal quantities and diversity of training data necessary for transfer learning, and implications for broader generalisability to unseen datasets.
Rhizospheric miRNAs affect the plant microbiota
Authors: Middleton Harriet , Dozois Jessica Ann , Monard Cécile , Daburon Virginie , Clostres Emmanuel , Tremblay Julien , Combier Jean-Philippe , Yergeau Étienne , El Amrani Abdelhak 
Published: July 2022

AbstractRecently, small RNAs have been shown to play important roles in cross-kingdom communication, notably in plant-pathogen relationships. Plant miRNAs were even shown to regulate gene expression in the gut microbiota. But what impact do they have on the plant microbiota? Here we hypothesized that plant miRNAs can be found in the rhizosphere of plants, where they are taken up by rhizosphere bacteria, influencing their gene expression, thereby shaping the rhizosphere bacterial community. We found plant miRNAs in the rhizosphere ofArabidopsis thalianaandBrachypodium distachyon. These plant miRNAs were also found in rhizosphere bacteria, and fluorescent synthetic miRNAs were taken up by cultivated bacteria. A mixture of five plant miRNAs modulated the expression of more than a hundred genes inVariovorax paradoxus, whereas no effect was observed inBacillus mycoides. Similarly, whenV. paradoxuswas grown in the rhizosphere ofArabidopsisthat overexpressed a miRNA, it changed its gene expression profile. The rhizosphere bacterial communities ofArabidopsismutants that were impaired in their miRNA or small RNA pathways differed from wildtype plants. Similarly, bacterial communities ofArabidopsisoverexpressing specific miRNAs diverged from control plants. Finally, the growth and the abundance of specific ASVs of a simplified soil community were affected by exposure to a mixture of synthetic plant miRNAs. Taken together, our results support a paradigm shift in plant-bacteria interactions in the rhizosphere, adding miRNAs to the plant tools shaping microbial assembly.
Dual scRNA-Seq analysis reveals rare and uncommon parasitized cell populations in chronic L. donovani infection
Authors: Karagiannis Konstantinos , Gannavaram Sreenivas , Verma Chaitenya , Bhattacharya Parna , Nakhasi Hira L , Satoskar Abhay 
Published: July 2022

AbstractAlthough phagocytic cells are documented targets of Leishmania parasites, it is unclear whether these parasites can infect other cell types. In this study, we describe a computational approach that exploits scRNA-seq to simultaneously analyze the transcriptomic signatures of the host cell and to identify rare and uncommon cells that harbor Leishmania donovani in the spleen and bone marrow. Individual cells were annotated as parasitized based on the presence of L. donovani transcripts that were detected with high accuracy. This unbiased approach allowed identification of heterogenous parasitized cell populations that cannot be detected by conventional methods. Consistent with previous studies, analysis of spleen cells isolated from L. donovani infected mice revealed inflammatory monocytes as the dominant parasitized cells. In addition, megakaryocytes, basophils, and NK cells were found to be the rare cells infected in the spleen. Unexpectedly, hematopoietic stem cells (HSCs), not known to be phagocytic, were the dominant cells parasitized cell in the bone marrow. In addition, eosinophils, megakaryocytes, and basal cells were the rare bone marrow cells found to be infected. scRNA-seq analysis revealed known phagocytic receptors FcγR and CD93 are expressed on HSCs. In vitro studies using purified HSCs showed that these cells can phagocytize L. donovani. Parasitized HSCs were also detectable in the bone marrow of mouse infected with L donovani.. This unbiased dual scRNA-seq approach enables identification of rare and uncommon parasitized cells that could be involved in pathogenesis, persistence, and protective immunity. Further, such approach could be used to study pathogenesis of other infectious agents.
Protein complexes in cells by AI-assisted structural proteomics
Authors: O‘Reilly Francis J. , Graziadei Andrea , Forbrig Christian , Bremenkamp Rica , Charles Kristine , Lenz Swantje , Elfmann Christoph , Fischer Lutz , Stülke Jörg , Rappsilber Juri 
Published: July 2022

SummaryAccurately modeling the structures of proteins and their complexes using artificial intelligence is revolutionizing molecular biology. Experimental data enables a candidate-based approach to systematically model novel protein assemblies. Here, we use a combination of in-cell crosslinking mass spectrometry, cofractionation mass spectrometry (CoFrac-MS) to identify protein-protein interactions in the model Gram-positive bacteriumBacillus subtilis. We show that crosslinking interactions prior to cell lysis reveals protein interactions that are often lost upon cell lysis. We predict the structures of these protein interactions and others in theSubtiWiki database with AlphaFold-Multimer and, after controlling for the false-positive rate of the predictions, we propose novel structural models of 153 dimeric and 14 trimeric protein assemblies. Crosslinking MS data independently validates the AlphaFold predictions and scoring. We report and validate novel interactors of central cellular machineries that include the ribosome, RNA polymerase and pyruvate dehydrogenase, assigning function to several uncharacterized proteins. Our approach uncovers protein-protein interactions inside intact cells, provides structural insight into their interaction interface, and is applicable to genetically intractable organisms, including pathogenic bacteria.
Dynamic states of cervical epithelia during pregnancy and epithelial barrier disruption
Authors: Cooley Anne , Madhukaran ShanmugaPriyaa , Stroebele Elizabeth , Caraballo Mariano Colon , Wang Lei , Hon Gary C. , Mahendroo Mala 
Published: July 2022

ABSTRACTThe cervical epithelium undergoes continuous changes in proliferation, differentiation, and function that are critical before pregnancy to ensure fertility and during pregnancy to provide a physical and immunoprotective barrier for pregnancy maintenance. Barrier disruption can lead to the ascension of pathogens that elicit inflammatory responses and preterm birth. Here, we identify cervical epithelial subtypes in nonpregnant, pregnant, and in-labor mice using single-cell transcriptome and spatial analysis. We identify heterogeneous subpopulations of epithelia displaying spatial and temporal specificity. Notably, two goblet cell subtypes with distinct transcriptional programs and mucosal networks were dominant in pregnancy. Untimely basal cell proliferation and goblet cells with diminished mucosal integrity characterize barrier dysfunction in mice lacking hyaluronan. These data demonstrate how the cervical epithelium undergoes continuous remodeling to maintain dynamic states of homeostasis in pregnancy and labor, and provide a framework to understand perturbations in epithelial health and host-microbe interactions that increase the risk of premature birth.
Shifted Reverse PAGE: a novel approach based on structure switching for the discovery of riboswitches and aptamers
Authors: Devinck Aurélie , Boutet Emilie , Ouellet Jonathan , Rouag Rihab , Sellamuthu Balasubramanian , Perreault Jonathan 
Published: July 2022

AbstractRiboswitches are regulatory sequences composed of an aptamer domain capable of binding a ligand and an expression platform that allows the control of the downstream gene expression based on a conformational change. Current bioinformatic methods for their discovery have various limitations. To circumvent this, we developed an experimental technique to discover new riboswitches called SR-PAGE (Shifted Reverse Polyacrylamide Gel Electrophoresis). A ligand-based regulatory molecule is recognized by exploiting the conformational change of the sequence following binding with the ligand within a native polyacrylamide gel. Known riboswitches were tested with their corresponding ligands to validate our method. SR-PAGE was imbricated within an SELEX to enrich switching RNAs from a TPP riboswitch-based degenerate library to change its binding preference from TPP to thiamine. The SR-PAGE technique allows performing a large screening for riboswitches, search in several organisms and test more than one ligand simultaneously.
Maf Family Transcription Factors are Required for Nutrient Uptake in the Neonatal Gut
Authors: Bara Anne M. , Chen Lei , Ma Celina , Underwood Julie , Moreci Rebecca S. , Sumigray Kaelyn , Sun Tongyu , Diao Yarui , Verzi Michael , Lechler Terry 
Published: July 2022

AbstractThere are fundamental differences in the way that neonatal and adult intestines absorb nutrients. In adults, macromolecules are efficiently broken down into simpler molecular components in the lumen of the small intestine, then absorbed. In contrast, neonates are thought to rely more on bulk intake of nutrients and subsequent degradation in the lysosome. Here, we identify the Maf family transcription factors, MafB and cMaf, as markers of terminally-differentiated intestinal enterocytes throughout life. The expression of these factors is regulated by HNF4α/γ, master regulators of the enterocyte cell fate. Loss of Maf factors results in a neonatal-specific failure to thrive and loss of bulk uptake of nutrients. RNA-Seq and CUT&RUN analyses defined an endo-lysosomal program as being downstream of these transcription factors. We demonstrate major transcriptional changes in metabolic pathways, including fatty acid oxidation and increases in peroxisome number in response to loss of Mafs. Finally, we show that deletion of Blimp1, which represses adult enterocyte genes in the neonatal gut, shows highly overlapping changes in gene expression and similar defects in nutrient uptake. This work defines transcriptional regulators that are necessary for bulk uptake in neonatal enterocytes.