bluuebunny/crossref_metadata_2025_split huggingface dataset:
Circadian clock genesBmal1andPer2in the nucleus accumbens are negative regulators of alcohol-drinking behavior in mice
Authors: Herrera J. , Button M. , Doherty-Haigh P. , Goldfarb C. , Quteishat N. , Amir S. , Schoettner K. 
Published: February 2023

ABSTRACTVoluntary alcohol consumption is influenced by a variety of environmental and genetic factors, including circadian clock genes. Even though their sex-specific role in alcohol drinking was identified through selective ablation ofBmal1andPer2from neurons of the mouse striatum, the contribution of specific striatal subregions to the observed drinking behavior remains unclear. Thus, alcohol intake and preference was investigated in male and female mice with a conditional knockout ofBmal1andPer2from cells in the nucleus accumbens (Nac). Mood- and anxiety-related behaviors were assessed prior to alcohol drinking to exclude potential confounding effects of the animal’s behavioral state on alcohol consumption. Alcohol consumption and preference were increased in male and female mice with a conditional knockout ofBmal1, whereas the same effect was only found in males with a deletion ofPer2. Because affective behaviors were only mildly influenced by the conditional gene knockouts, observed alcohol-drinking phenotypes can be directly associated with the Nac-specific clock gene deletion. The results thus suggest an inhibitory role ofBmal1andPer2in the Nac on alcohol consumption in male mice. In females, the inhibitory effect ofBmal1is strictly localized to the Nac, because striatal-wide deletion ofBmal1caused a suppression of alcohol consumption. This sex-dependent stimulatory effect ofBmal1on alcohol drinking is probably mediated through other striatal subregions such as the dorsal striatum.
Idioblasts accumulating anticancer alkaloids inCatharanthus roseusleaves are a unique cell type
Authors: Guedes Joana G. , Ribeiro Rogério , Carqueijeiro Inês , Guimarães Ana Luísa , Bispo Cláudia , Archer John , Azevedo Herlander , Fonseca Nuno A. , Sottomayor Mariana 
Published: February 2023

AbstractCatharanthus roseusleaves produce a range of monoterpenoid indole alkaloids (MIAs) that include low levels of the anticancer drugs vinblastine and vincristine. The MIA pathway displays a complex architecture spanning different subcellular and cell-type localizations and is under complex regulation. As a result, the development of strategies to increase the levels of the anticancer MIAs has remained elusive. The pathway involves mesophyll specialised idioblasts where the late unsolved biosynthetic steps are thought to occur. Here, protoplasts ofC. roseusleaf idioblasts were isolated by fluorescence-activated cell sorting, and their differential alkaloid and transcriptomic profiles were characterised. This involved the assembly of an improvedC. roseustranscriptome from short- and long-read data, IDIO+. It was observed thatC. roseusmesophyll idioblasts possess a distinctive transcriptomic profile associated with protection against biotic and abiotic stresses, and indicative that this cell type is a carbon sink, in contrast with surrounding mesophyll cells. Moreover, it is shown that idioblasts are a hotspot of alkaloid accumulation, suggesting that their transcriptome may hold the keys to the in-depth understanding of the MIA pathway and the success of strategies leading to higher levels of the anticancer drugs.HighlightCatharanthus mesophyll idioblasts are a hotspot of anticancer alkaloid accumulation. The idioblast transcriptome reveals commitment with stress responses and provides a roadmap towards the increase of anticancer alkaloid levels.
Variational Autoencoders for Generating Synthetic Tractography-Based Bundle Templates in a Low-Data Setting
Authors: Feng Yixue , Chandio Bramsh Q. , Thomopoulos Sophia I. , Chattopadhyay Tamoghna , Thompson Paul M. 
Published: February 2023

AbstractWhite matter tracts generated from whole brain tractography are often processed using automatic segmentation methods with standard atlases. Atlases are generated from hundreds of subjects, which becomes time-consuming to create and difficult to apply to all populations. In this study, we extended our prior work on using a deep generative model a Convolutional Variational Autoencoder - to map complex and data-intensive streamlines to a low-dimensional latent space given a limited sample size of 50 subjects from the ADNI3 dataset, to generate synthetic population-specific bundle templates using Kernel Density Estimation (KDE) on streamline embeddings. We conducted a quantitative shape analysis by calculating bundle shape metrics, and found that our bundle templates better capture the shape distribution of the bundles than the atlas data used in the original segmentation derived from young healthy adults. We further demonstrated the use of our framework for direct bundle segmentation from whole-brain tractograms.
MeCP2 Represses the Activity of Topoisomerase IIβ in Long Neuronal Genes
Authors: Nettles Sabin A. , Ikeuchi Yoshiho , Agwu Chibueze , Bonni Azad , Gabel Harrison W. 
Published: February 2023

SummaryA unique signature of neuronal transcriptomes is the high expression of the longest genes in the genome (e.g. >100 kilobases). These genes encode proteins with essential functions in neuronal physiology, and disruption of long gene expression has been implicated in neurological disorders. DNA topoisomerases resolve topological constraints that arise on DNA and facilitate the expression of long genes in neurons. Conversely, methyl-CpG binding protein 2 (MeCP2), which is disrupted in Rett syndrome, can act as a transcriptional repressor to downregulate the expression of long genes. The molecular mechanisms underlying the regulation of long genes by these factors are not fully understood, however, and whether or not they directly influence each other is not known. Here, we identify a functional interaction between MeCP2 and Topoisomerase II-beta (TOP2β) in neurons. We show that MeCP2 and TOP2β physically interactin vivoand map protein sequences sufficient for their physical interactionin vitro. We profile TOP2β activity genome-wide in neurons and detect enrichment at regulatory regions and gene bodies of long neuronal genes, including long genes regulated by MeCP2. Further, we find that knockdown and overexpression of MeCP2 leads to altered TOP2β activity at MeCP2-regulated genes. Our findings uncover a mechanism by which MeCP2 inhibits the activity of TOP2β at long genes in neurons and suggest that this mechanism is disrupted in neurodevelopment disorders caused by mutation of MeCP2.
Local microtubule and F-actin distributions fully determine the spatial geometry ofDrosophilasensory dendritic arbors
Authors: Nanda Sumit , Bhattacharjee Shatabdi , Cox Daniel N. , Ascoli Giorgio A. 
Published: February 2023

AbstractDendritic morphology underlies the source and processing of neuronal signal inputs. Morphology can be broadly described by two types of geometric characteristics. The first is dendrogram topology, defined by the length and frequency of the arbor branches; the second is spatial embedding, mainly determined by branch angles and tortuosity. We have previously demonstrated that microtubules and actin filaments are associated with arbor elongation and branching, fully constraining dendrogram topology. Here we relate the local distribution of these two primary cytoskeletal components with dendritic spatial embedding. We first reconstruct and analyze 167 sensory neurons from theDrosophilalarva encompassing multiple cell classes and genotypes. We observe that branches with higher microtubule concentration are overall straighter and tend to deviate less from the direction of their parent branch. F-actin displays a similar effect on the angular deviation from the parent branch direction, but its influence on branch tortuosity varies by class and genotype. We then create a computational model of dendritic morphology purely constrained by the cytoskeletal composition imaged from real neurons. The model quantitatively captures both spatial embedding and dendrogram topology across all tested neuron groups. These results suggest a common developmental mechanism regulating diverse morphologies, where the local cytoskeletal distribution can fully specify the overall emergent geometry of dendritic arbors.
A robust model for cell type-specific interindividual variation in single-cell RNA sequencing data
Authors: Chen Minhui , Dahl Andy 
Published: February 2023

AbstractThe development of single-cell RNA sequencing (scRNA-seq) offers opportunities to characterize cellular heterogeneity at unprecedented resolution. Although scRNA-seq has been widely used to identify and characterize gene expression variation across cell types and cell states based on their average gene expression profiles, most studies ignore variation across individual donors. Modelling this inter-individual variation could improve statistical power to detect cell type-specific biology and inform the genes and cell types that underlying complex traits. We therefore develop a new model to detect and quantify cell type-specific variation across individuals called CTMM (Cell Type-specific linear Mixed Model). CTMM operates on cell type-specific pseudobulk expression and is fit with efficient methods that scale to hundreds of samples. We use extensive simulations to show that CTMM is powerful and unbiased in realistic settings. We also derive calibrated tests for cell type-specific interindividual variation, which is challenging given the modest sample sizes in scRNA-seq data. We apply CTMM to scRNA-seq data from human induced pluripotent stem cells to characterize the transcriptomic variation across donors as cells differentiate into endoderm. We find that almost 100% of transcriptome-wide variability between donors is differentiation stage-specific. CTMM also identifies individual genes with statistically significant stage-specific variability across samples, including 61 genes that do not have significant stage-specific mean expression. Finally, we extend CTMM to partition interindividual covariance between stages, which recapitulates the overall differentiation trajectory. Overall, CTMM is a powerful tool to characterize a novel dimension of cell type-specific biology in scRNA-seq.
Stimulus representations in visual cortex shaped by spatial attention and microsaccades
Authors: Srinivasan Karthik , Lowet Eric , Gomes Bruno , Desimone Robert 
Published: February 2023

SUMMARY/ABSTRACTMicrosaccades (MSs) are commonly associated with spatially directed attention, but how they affect visual processing is still not clear. We studied MSs in a task in which the animal was randomly cued to attend to a target stimulus and ignore distractors, and it was rewarded for detecting a color change in the target. We found that the enhancement of firing rates normally found with attention to a cued stimulus was delayed until the first MS directed towards that stimulus. Once that MS occurred, attention to the target was engaged and there were persistent effects of attention on firing rates for the remainder of the trial. These effects were found in the superficial and deep layers of V4 as well as the lateral pulvinar and IT cortex. Although the tuning curves of V4 cells do not change depending on the locus of spatial attention, we found pronounced effects of MS direction on stimulus representations that persisted for the length of the trial in V4. In intervals following a MS towards the target in the RF, stimulus decoding from population activity was substantially better than in intervals following a MS away from the target. Likewise, turning curves of cells were substantially sharper following a MS towards the target in the RF. This sharpening appeared to result from both a “refreshing” of the initial transient sensory response to stimulus onset, and a magnification of the effects of attention in this condition. MSs to the target also enhanced the neuronal response to the behaviorally relevant target color change and led to faster reaction times. These results thus reveal a major link between spatial attention, object processing and its coordination with eye movements.
Leptomeningeal collaterals regulate reperfusion in ischemic stroke
Authors: Binder Nadine Felizitas , Amki Mohamad El , Glück Chaim , Middleham William , Reuss Anna Maria , Bertolo Adrien , Thurner Patrick , Deffieux Thomas , Handelsmann Hannah-Lea , Baumgartner Philipp , Orset Cyrille , Bethge Philipp , Kulcsar Zsolt , Aguzzi Adriano , Tanter Mickael , Vivien Denis , Wyss Matthias T. , Luft Andreas , Weller Michael , Weber Bruno , Wegener Susanne 
Published: February 2023

AbstractRecanalization is the mainstay of ischemic stroke treatment. However, even with timely clot removal, many stroke patients recover poorly. Leptomeningeal collaterals (LMCs) are pial anastomotic vessels with yet unknown functions. Utilizing a thrombin-based mouse model of stroke and the gold standard fibrinolytic treatment rt-PA, we here show that LMCs play a critical role in preserving vascular function in ischemic territories. We applied laser speckle contrast imaging, ultrafast ultrasound, and two-photon microscopy, to show that after thrombolysis, LMCs allow for gradual reperfusion resulting in small infarcts. On the contrary, in mice with poor LMCs, distal segments of recanalized arteries collapse and deleterious hyperemia causes hemorrhage and mortality. Accordingly, in stroke patients with poor collaterals undergoing thrombectomy, rapid reperfusion resulted in hemorrhagic transformation and unfavorable recovery. Thus, we identify LMCs as key components regulating reperfusion after stroke. Future therapeutic interventions should aim to enhance collateral function, allowing for gradual reperfusion of ischemic tissues after stroke.
Cyclic peptide structure prediction and design using AlphaFold
Authors: Rettie Stephen A. , Campbell Katelyn V. , Bera Asim K. , Kang Alex , Kozlov Simon , De La Cruz Joshmyn , Adebomi Victor , Zhou Guangfeng , DiMaio Frank , Ovchinnikov Sergey , Bhardwaj Gaurav 
Published: February 2023

ABSTRACTDeep learning networks offer considerable opportunities for accurate structure prediction and design of biomolecules. While cyclic peptides have gained significant traction as a therapeutic modality, developing deep learning methods for designing such peptides has been slow, mostly due to the small number of available structures for molecules in this size range. Here, we report approaches to modify the AlphaFold network for accurate structure prediction and design of cyclic peptides. Our results show this approach can accurately predict the structures of native cyclic peptides from a single sequence, with 36 out of 49 cases predicted with high confidence (pLDDT > 0.85) matching the native structure with root mean squared deviation (RMSD) less than 1.5 Å. Further extending our approach, we describe computational methods for designing sequences of peptide backbones generated by other backbone sampling methods and forde novodesign of new macrocyclic peptides. We extensively sampled the structural diversity of cyclic peptides between 7–13 amino acids, and identified around 10,000 unique design candidates predicted to fold into the designed structures with high confidence. X-ray crystal structures for seven sequences with diverse sizes and structures designed by our approach match very closely with the design models (root mean squared deviation < 1.0 Å), highlighting the atomic level accuracy in our approach. The computational methods and scaffolds developed here provide the basis for custom-designing peptides for targeted therapeutic applications.
Screening in serum-derived medium reveals differential response to compounds targeting metabolism
Authors: Abbott Keene L. , Ali Ahmed , Casalena Dominick , Do Brian T. , Ferreira Raphael , Cheah Jaime H. , Soule Christian K. , Deik Amy , Kunchok Tenzin , Schmidt Daniel R. , Renner Steffen , Honeder Sophie E. , Wu Michelle , Chan Sze Ham , Tseyang Tenzin , Greaves Daniel , Hsu Peggy P. , Ng Christopher W. , Zhang Chelsea J. , Farsidjani Ali , Gramatikov Iva Monique T. , Matheson Nicholas J. , Lewis Caroline A. , Clish Clary B. , Rees Matthew G. , Roth Jennifer A. , Griner Lesley Mathews , Muir Alexander , Auld Douglas S. , Heiden Matthew G. Vander 
Published: February 2023

SUMMARYA challenge for screening new candidate drugs to treat cancer is that efficacy in cell culture models is not always predictive of efficacy in patients. One limitation of standard cell culture is a reliance on non-physiological nutrient levels to propagate cells. Which nutrients are available can influence how cancer cells use metabolism to proliferate and impact sensitivity to some drugs, but a general assessment of how physiological nutrients affect cancer cell response to small molecule therapies is lacking. To enable screening of compounds to determine how the nutrient environment impacts drug efficacy, we developed a serum-derived culture medium that supports the proliferation of diverse cancer cell lines and is amenable to high-throughput screening. We used this system to screen several small molecule libraries and found that compounds targeting metabolic enzymes were enriched as having differential efficacy in standard compared to serum-derived medium. We exploited the differences in nutrient levels between each medium to understand why medium conditions affected the response of cells to some compounds, illustrating how this approach can be used to screen potential therapeutics and understand how their efficacy is modified by available nutrients.
Modular Tissue-in-a-CUBE Platform to Model Blood-brain-Barrier (BBB) and Brain Interaction
Authors: Koh Isabel , Hagiwara Masaya 
Published: February 2023

AbstractWith the advent of increasingly sophisticated organoids, there is growing demand for technology to replicate the interactions between multiple tissues or organs. This is challenging to achieve, however, due to the varying culture conditions of the different cell types that make up each tissue. Current methods often require complicated microfluidic setups, but fragile tissue samples tend not to fare well with rough handling. Furthermore, the more complicated the human system to be replicated, the more difficult the model becomes to operate. Here, we present the development of a multi-tissue chip platform that takes advantage of the modularity and convenient handling ability of the CUBE device. We first developed a blood-brain barrier (BBB)-in-a-CUBE by layering astrocytes, pericytes, and brain microvascular endothelial cells in the CUBE, and confirmed the expression and function of important tight junction and transporter proteins in the BBB model. Then, we demonstrated the application of integrating Tissue-in-a-CUBE with a chip in simulating the testing of the permeability of a drug through the blood-brain barrier (BBB) to the brain and its effect on treating brain cancer. We anticipate that this platform can be adapted for use with organoids to build complex human systemsin vitroby the combination of multiple simple CUBE units.
Descriptive pan-cancer genetic analysis of disulfidptosis-related gene set
Authors: Liu Hengrui , Tang Tao 
Published: February 2023

AbstractBackgroundA recent study has identified a novel programmed cell death pathway, termed disulfidoptosis, which is based on disulfide proteins. This discovery provides new insight into the mechanisms of cell death and may have implications for therapeutic strategies targeting cell death pathways. This study aimed to evaluate the pan-cancer genomics and clinical association of disulfidptosis and disulfidptosis-related cell death genes, including SLC7A11, NADPH, INF2, CD2AP, PDLIM1, ACTN4, MYH9, MYH10, IQGAP1, FLNA, FLNB, TLN1, MYL6, ACTB, DSTN, and CAPZB.MethodsUsing multi-omics profiling data, this study provides a comprehensive and systematic characterization of disulfidptosis genes across more than 9000 samples of over 30 types of cancer.ResultsFLNA and FLNB were the two most frequently mutated disulfidptosis cell death genes in cancer. UCEC and SKCM were the two cancer types that have the highest mutation rates while the mutation of ACTN4 was associated with worse survival of CESC and ESCA. Breast cancer was potentially affected by disulfidptosis because its subtypes are different in disulfidptosis gene expression. Similarly, KIRC might also be associated with disulfidptosis.). Additionally, the association of disulfidptosis-related cell death genes with survival was analyzed, with MESO and LGG as the top cancer types with survival associated with disulfidptosis cell death genes. The correlation between CNV and survival across multiple cancer types found that UCEC, KIRP, LGG, and KIRC were the top cancer types where the CNV level was associated with survival. There was a negative correlation between expression and methylation for most of the genes and there was only a slight correlation between methylation levels and survival of cancer in LGG. About half of the disulfidptosis-related cell death proteins were associated with the activation of EMT. Disulfidptosis genes were correlated to immune cell infiltration levels in cancers. Multiple compounds were identified as potential drugs that might be affected by disulfidptosis-related cell death for future study.ConclusionDisulfidptosis cell death genes are potentially involved in many cancer types and can be developed as candidates for cancer diagnosis, prognosis, and therapeutic biomarkers.
Delving into theBacillus cereusgroup biosynthetic gene clusters cosmos: a comparative-genomics-based classification framework
Authors: Belaouni Hadj Ahmed , Yekkour Amine , Zitouni Abdelghani , Meklat Atika 
Published: February 2023

AbstractBackgroundIn this study, theBacillussp. strain BH32 (a plant-beneficial bacterial endophyte) and its closest non-typeBacillus cereusgroup strains were used to study the organization, conservation, and diversity of biosynthetic gene clusters (BGCs) among this group to propose a classification framework of gene cluster families (GCFs) among this intricate group. A dataset consisting of 17 genomes was used in this study. Genomes were annotated using PROKKA ver.1.14.5. The web tool antiSMASH ver. 5.1.2 was used to predict the BGCs profiles of each strain, with a total number of 198 BGCs. The comparison was made quantitatively based on a BGCs counts matrix comprising all the compared genomes and visualized using the Morpheus tool. The constitution, distribution, and evolutionary relationships of the detected BGCs were further analyzed using a manual approach based on a BLASTp analysis (using BRIG ver. 0.95); a phylogenetic analysis of the concatenated BGCs sequences to highlight the evolutionary relationships; and the conservation, distribution and the genomic co-linearity of the studied BGCs using Mauve aligner ver. 2.4.0. Finally, the BIG-SCAPE/CORASON automated pipeline was used as a complementary strategy to investigate the gene cluster families (GCFs) among theB. cereusgroup.ResultsBased on the manual approach, we identified BGCs conserved across the studied strains with very low variation and interesting singletons BGCs. Moreover, we highlighted the presence of two major BGCs synteny blocks (named “synteny blockA” and “synteny blockB”), each composed of conserved homologous BGCs among theB. cereusgroup. For the automatic approach, we identified 23 families among the different BGCs classes of theB. cereusgroup, named using a rational basis. The proposed manual and automatic approaches proved to be in harmony and complete each other, for the study of BGCs among the selected genomes.ConclusionUltimately, we propose a framework for an expanding classification of theB. cereusgroup BGCs, based on a set of reference BGCs reported in this work.