bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dual long-axis reorganization of hippocampus in youth
Authors: Zeng Debin , Li Qiongling , Li Deyu , He Yirong , Dong Xiaoxi , Li Shaoxian , Bi Shenghan , Liao Xuhong , Zhao Tengda , Chen Xiaodan , Xia Yunman , Lei Tianyuan , Sun Lianglong , Men Weiwei , Wang Yanpei , Wang Daoyang , Hu Mingming , Pan Zhiying , Tan Shuping , Gao Jia-Hong , Qin Shaozheng , Tao Sha , Dong Qi , He Yong , Zuo Xi-Nian , Li Shuyu 
Published: November 2023

AbstractThe reorganization of human hippocampus, especially its interaction with cortex, remains largely undefined in youth. The organization of a single hippocampal long-axis has been predominantly characterized as monotonic1–6, despite recent indications of nonmonotonic features in neuron density7and geometric eigenmodes8. While the human cortical hierarchy has been well recognized for significant developmental and evolutionary advantages9–12, hippocampus has been typically considered an evolutionarily conserved brain structure1,13,14, and overlooked regarding its integrative role of cortical hierarchical processing during development. Here, we corroborated the presence and significance of a dual long-axis representation of the hippocampal connectome and geometry including both linear and quadratic gradients along its long-axis in youth. This finding was robust across two independent large-scale developmental cohorts. Charting development of the dual long-axis gradients underscored their specific contributions to the cortical hierarchy maturation from the frontoparietal and salience/ventral attention networks. The observed developmental variability in spontaneous brain activities in youth parallels the gradients of myelin content. During childhood through adolescence to early adulthood, the hippocampus reorganized the dual long-axis by gradually relaxing its geometric constraints on the intrinsic network organization of cortical spontaneous activity for refined executive functions. Molecular processes underlying such reorganization of the dual long-axis in hippocampus are linked to neural growth, stress hormone regulation, and neuroactive signaling. Our findings enrich the understanding of hippocampal-cortical reorganizational principles across structural, functional, and molecular dimensions as well as its maturation, and define the plasticity distribution within the human hippocampus at systems level, holding potentials to enhance and translate neurodevelopment and neuropsychiatric healthcare.
Chikungunya virus infection disrupts MHC-I antigen presentation via nonstructural protein 2
Authors: Ware Brian C. , Parks M. Guston , Morrison Thomas E. 
Published: November 2023

ABSTRACTInfection by chikungunya virus (CHIKV), a mosquito-borne alphavirus, causes severe polyarthralgia and polymyalgia, which can last in some people for months to years. Chronic CHIKV disease signs and symptoms are associated with the persistence of viral nucleic acid and antigen in tissues. Like humans and nonhuman primates, CHIKV infection in mice results in the development of robust adaptive antiviral immune responses. Despite this, joint tissue fibroblasts survive CHIKV infection and can support persistent viral replication, suggesting that they escape immune surveillance. Here, using a recombinant CHIKV strain encoding a chimeric protein of VENUS fused to a CD8+T cell epitope, SIINFEKL, we observed a marked loss of both MHC class I (MHC-I) surface expression and antigen presentation by CHIKV-infected joint tissue fibroblasts. Bothin vivoandex vivoinfected joint tissue fibroblasts displayed reduced cell surface levels of H2-Kband H2-DbMHC proteins while maintaining similar levels of other cell surface proteins. Mutations within the methyl transferase-like domain of the CHIKV nonstructural protein 2 (nsP2) increased MHC-I cell surface expression and antigen presentation efficiency by CHIKV-infected cells. Moreover, expression of WT nsP2 alone, but not nsP2 with mutations in the methyltransferase-like domain, resulted in decreased MHC-I antigen presentation efficiency. MHC-I surface expression and antigen presentation could be rescued by replacing VENUS-SIINFEKL with SIINFEKL tethered to β2-microglobulin in the CHIKV genome, which bypasses the need for peptide processing and TAP-mediated peptide transport into the endoplasmic reticulum. Collectively, this work suggests that CHIKV escapes the surveillance of antiviral CD8+T cells, in part, by nsP2-mediated disruption of MHC-I antigen presentation.AUTHOR SUMMARYArthritogenic alphaviruses, including chikungunya virus (CHIKV), are re-emerging global public health threats with no approved vaccines or antiviral therapies. Infection with these viruses causes debilitating musculoskeletal disease for months to years that is associated with the persistence of viral RNA and antigen. Prior studies using a mouse model found that CD8+T cells, which recognize viral peptides in the context of major histocompatibility class I (MHC-I) displayed on the surface of infected cells, have a limited role in the control and clearance of CHIKV infection in joint-associated tissues, suggesting that CHIKV infected cells evade these critical effectors of the anti-viral immune response. Here, we show that MHC-I antigen presentation is inefficient in CHIKV-infected joint tissue fibroblasts, and that a protein encoded by CHIKV and produced in infected cells, nonstructural protein 2 (nsP2), disrupts the surface display of MHC-I molecules and antigen recognition of infected cells by CD8+T cells. Our findings support a role for CHIKV nsP2 in the evasion of the CD8+T cell response and establishment of persistent infection.
Human Endogenous Retrovirus Expression is Dynamically Regulated in Parkinson’s Disease
Authors: Gordevičius Juozas , Goralski Thomas , Bergsma Alexis , Parham Andrea , Kuhn Emily , Meyerdirk Lindsay , McDonald Mitch , Milčiūtė Milda , Putten Elizabeth Van , Marshall Lee , Brundin Patrik , Brundin Lena , Labrie Viviane , Henderson Michael , Pospisilik John Andrew 
Published: November 2023

SUMMARYParkinson’s disease (PD) is a progressive, debilitating neurodegenerative disease that afflicts approximately every 1000th individual. Recently, activation of genomic transposable elements (TE) has been suggested as a potential driver of PD onset. However, it is unclear where, when, and to what extent TEs are dysregulated in PD. Here, we performed a multi-tissue transcriptional analysis of multiple patient cohorts and identified TE transcriptional activation as a hallmark of PD. We find that PD patients exhibit up-regulation primarily of human endogenous retrovirus (HERV) transcripts in prefrontal cortex tissue, prefrontal neurons as well as in blood, and we demonstrate that TE activation in the blood is highest at the time of PD diagnosis. Supporting a potentially causal association between ERV dysregulation and PD heterogeneity, reduced gene dosage of the TE repressor Trim28 triggers transcriptional changes highly correlated to those measured in animal models of synucleinopathy (PFF-injection), and importantly, to those exhibited by patients themselves. These data identify ERV up-regulation as a common feature of central and peripheral PD etiology, and highlight potential roles for Trim28-dependent TEs in stratifying and monitoring PD and treatment compliance.
Is M1-L121E a good mimic on microbial rhodopsin? A viewpoint from excited-state dynamics
Authors: Li Gaoshang , Meng Jiajia , Yu Shuang , Bai Xiaolu , Dai Jin , Song Yin , Peng Xubiao , Zhao Qing 
Published: November 2023

AbstractMicrobial rhodopsin, an important photoreceptor protein, has been widely used in several fields, such as optogenetics, biotechnology, and biodevicesetc. However, current microbial rhodopsins are all transmembrane proteins, which both complicates the investigation on the photoreaction mechanism and limits their further applications. Therefore, a suitable mimic for microbial rhodopsin can not only provide a better model for understanding the mechanism, but also can extend the applications. The human protein CRABPII turns out to be a good template for design mimics on rhodopsin, due to the convenience in synthesis and the stability after mutations. Recently, Geigeret al.designed a new CRABPII-based mimic M1-L121E on microbial rhodopsin with the correct 13-cis (13C) isomerization after irritation. However, it still remains a question how similar it is compared with the natural microbial rhodopsin, in particular in the aspect of the photoreaction dynamics. In this article, we investigated the excited-state dynamics of this mimic by measuring its transient absorption spectra. Our results reveal that there are two components in the solution of mimic M1-L121E at PH=8, known as protonated Schiff base (PSB) and unprotonated Schiff base (USB) states. In both states, the photoreaction process from 13-cis (13C) to all-trans (AT) is faster than that from the inverse direction. In addition, the photoreaction process in PSB state is faster than that in the USB state. In the end, we compared the isomerization time of the PSB state with the properties of the microbial rhodopsin, and confirmed that the mimic M1-L121E indeed captures the main feature of the rhodopsin and is a good model of microbial rhodopsin in the photoreaction dynamics. However, our results also reveal significant differences in the excited-state dynamics of the mimic relative to the natural microbial rhodopsin, including the slower PSB isomerization rates in both 13C-AT and AT-13C directions, as well as the unusual USB photoreaction dynamics at PH=8. Such unique properties have not been observed in the natural rhodopsin, which could further deepen the understanding in photoreaction mechanism of the photosensitive proteins.
Machine learning-based exploration, expansion and definition of the atropopeptide family of ribosomally synthesized and posttranslationally modified peptides
Authors: Biermann Friederike , Tan Bin , Breitenbach Milena , Nanudorn Pakjira , Kakumu Yuya , Dimitrova Yoana , Walker Allison S. , Ueoka Reiko , Helfrich Eric J. N. 
Published: November 2023

AbstractRibosomally synthesized and posttranslationally modified peptides (RiPPs) constitute a diverse class of natural products. Atropopeptides are a recent addition to the fast-growing number of RiPP families. Characterized members of the peptide family feature a particular intricate three-dimensional shape. Here we developed AtropoFinder, a machine learning-based algorithm to chart the biosynthetic landscape of the atropopeptides. AtropoFinder identified more than 650 atropopeptide biosynthetic gene clusters (BGCs). Through bioinformatics and modeling analyses, we pinpointed crucial motifs and residues in leader and core peptide sequences, prompting a refined definition of the atropopeptide RiPP family. Our study revealed that a substantial subset of atropopeptide BGCs harbors multiple tailoring genes, thus suggesting a broader structural diversity than previously anticipated. To verify AtropoFinder, we heterologously expressed four atropopeptide BGCs, which resulted in the identification of novel atropopeptides with varying peptide lengths, number and type of modifications. Most notably, our study resulted in the characterization of an atropopeptide that is more extensively modified than previously identified members, resulting in an even more rigid 3-dimensional shape. Moreover, one characterized atropopeptide BGC encoding a single P450 is involved in the biosynthesis of two peptides with the same sequence but distinct and non-overlapping modification patterns. This work expands the atropopeptide chemical space, advances our understanding of atropopeptide biosynthesis and underscores the potential of machine learning in uncovering the uncharted biosynthetic diversity encoded in RiPP biosynthetic blueprints.
Using developmental dynamics for evolutionary prediction and control
Authors: Milocco Lisandro , Uller Tobias 
Published: November 2023

AbstractUnderstanding, predicting, and controlling the phenotypic consequences of genetic and environmental change is essential to many areas of fundamental and applied biology. In evolutionary biology, the generative process of development is a major source of organismal evolvability that constrains or facilitates adaptive change by shaping the distribution of phenotypic variation that selection can act upon. While the complex interactions between genetic and environmental factors during development may appear to make it impossible to infer the consequences of perturbations, the persistent observation that many perturbations result in similar phenotypes indicates that there is a logic to what variation is generated. Here, we show that a general representation of development as a dynamical system can reveal this logic. We build a framework that allows to predict the phenotypic effects of perturbations, and conditions for when the effects of perturbations of different origin are concordant. We find that this concordance is explained by two generic features of development, namely the dynamical dependence of the phenotype on itself and the fact that all perturbations must be funneled by the same developmental process. We apply our theoretical results to classical models of development and show that it can be used to predict the evolutionary response to selection using information of plasticity, and to accelerate evolution in a desired direction. The framework we introduce provides a way to quantitatively interchange perturbations, opening a new avenue of perturbation design to control the generation of variation, and thus evolution.
Predmoter - Cross-species prediction of plant promoter and enhancer regions
Authors: Kindel Felicitas , Triesch Sebastian , Schlüter Urte , Randarevitch Laura Alexandra , Reichel-Deland Vanessa , Weber Andreas P.M. , Denton Alisandra K. 
Published: November 2023

AbstractMotivationThe identification ofcis-regulatory elements (CREs) is crucial for the analysis of gene regulatory networks in plants. Several next generation sequencing (NGS)-based methods were developed to identify CREs. However, these methods can be time-consuming and costly. They also involve creating sequencing libraries for the entire genome. Since many research efforts only focus on specific genomic loci, this presents a considerable expenditure. Computational prediction of the outputs of specialized NGS methods to analyze CREs, like Assay for Transposase Accessible Chromatin using sequencing (ATAC-seq), would significantly cut costs and time investment. Yet, no such method is available to date.ResultsWe present Predmoter, a deep neural network able to predict base-wise ATAC-seq and histone Chromatin immunoprecipitation DNA-sequencing (ChIP-seq) read coverage for plant genomes. Predmoter uses only the DNA sequence as input. We evaluated our model on two plant genomes, the genome of the dicotArabidopsis thalianaand of the monocotOryza sativa. We trained our models on 10 species with publicly available ATAC-seq data and 15 species with ChIP-seq data. Our best models showed accurate predictions in peak positions and the overall pattern of peaks for ATAC- and Histone H3 trimethylated at lysine 4 (H3K4me3) ChIP-seq. Annotating putatively accessible chromatin regions provides valuable input for the identification of CREs. In conjunction with otherin silicodata, such as predicted binding affinities for transcription factors (TFs), this can significantly narrow down the search space to a manageable number of experimentally verifiable DNA-protein interaction pairs.Availability and ImplementationThe source code for Predmoter is available at:https://github.com/weberlab-hhu/Predmoteralong with documentation for installation and usage. Predmoter uses a single-command inference, Predmoter.py, for both training and prediction. Predmoter takes a fasta file as input and outputs an h5 file and optionally bigWig and bedGraph files.HighlightPredmoter will help identifying CREs and so gaining further insight into gene regulatory networks in plants.
Robust spatiotemporal organization of mitotic events in mechanically perturbedC. elegansembryos
Authors: Borne Vincent , Weiss Matthias 
Published: November 2023

ABSTRACTEarly embryogenesis of the nematodeCaenorhabditis elegansprogresses in an autonomous fashion within a protective chitin eggshell. Cell division timing and the subsequent, mechanically guided positioning of cells is virtually invariant between individuals, especially before gastrulation. Here, we have challenged this stereotypical developmental program in early stages by mechanically perturbing the embryo, without breaking its eggshell. Compressing embryos to about 2/3 of their unperturbed diameter only resulted in markedly slower cell divisions. In contrast, compressing embryos to half of their native diameter frequently resulted in a loss of cytokinesis, yielding a non-natural syncytium that still allowed for multiple divisions of nuclei. Although the orientation of mitotic axes was strongly altered in the syncytium, key features of division timing and spatial arrangement of nuclei remained surprisingly similar to unperturbed embryos in the first few division cycles. This suggests that few, very robust mechanisms provide a basic and resilient program for safeguarding the early embryogenesis ofC. elegans.STATEMENT OF SIGNIFICANCEEarly embryogenesis of the nematodeCaenorhabditis elegansprogresses in an autonomous fashion within a protective chitin eggshell. Cell division timing and cell positioning seemingly runs on autopilot, yielding a stereotypical development. Compressive forces, a potential hazard in the nematode’s native habitat, may jeopardize this. We show that compressing embryos to 2/3 of their native diameter results in markedly slower cell divisions but leaves the early embryonic program otherwise intact. Further compression of embryos impairs the formation of new cells while nuclei still divide in a common cytoplasm (’syncytium’) with basic features of division timing and spatial arrangement being surprisingly similar to unperturbed embryos. This suggests that few robust mechanisms provide a basic program for the early embryonic autopilot.
Localization of Spatially Extended Brain Sources by Flexible Alternating Projection (Flex-AP)
Authors: Hecker Lukas , Giri Amita , Pantazis Dimitrios , Adler Amir 
Published: November 2023

ABSTRACTMagnetoencephalography (MEG) and electroencephalography (EEG) are widely employed techniques for thein-vivomeasurement of neural activity with exceptional temporal resolution. Modeling the neural sources underlying these signals is of high interest for both neuroscience research and pathology. The method of Alternating Projection (AP) was recently shown to outperform the well-established recursively applied and projected multiple signal classification (RAP-MUSIC) algorithm. In this work, we further enhanced AP to allow for source extent estimation, a novel approach termed flexible extent AP (FLEX-AP). We found that FLEX-AP achieves significantly lower errors for spatially coherent sources compared to AP, RAP-MUSIC, and the corresponding extension, FLEX-RAP-MUSIC. We also found an advantage for discrete dipoles under forward modeling errors encountered in real-world scenarios. Together, our results indicate that the FLEX-AP method can unify dipole fitting and distributed source imaging into a single algorithm with promising accuracy.
Integrating single-cell RNA-seq datasets with substantial batch effects
Authors: Hrovatin Karin , Moinfar Amir Ali , Zappia Luke , Lapuerta Alejandro Tejada , Lengerich Ben , Kellis Manolis , Theis Fabian J. 
Published: November 2023

AbstractIntegration of single-cell RNA-sequencing (scRNA-seq) datasets has become a standard part of the analysis, with conditional variational autoencoders (cVAE) being among the most popular approaches. Increasingly, researchers are asking to map cells across challenging cases such as cross-organs, species, or organoids and primary tissue, as well as different scRNA-seq protocols, including single-cell and single-nuclei. Current computational methods struggle to harmonize datasets with such substantial differences, driven by technical or biological variation. Here, we propose to address these challenges for the popular cVAE-based approaches by introducing and comparing a series of regularization constraints.The two commonly used strategies for increasing batch correction in cVAEs, that is Kullback–Leibler divergence (KL) regularization strength tuning and adversarial learning, suffer from substantial loss of biological information. Therefore, we adapt, implement, and assess alternative regularization strategies for cVAEs and investigate how they improve batch effect removal or better preserve biological variation, enabling us to propose an optimal cVAE-based integration strategy for complex systems. We show that using a VampPrior instead of the commonly used Gaussian prior not only improves the preservation of biological variation but also unexpectedly batch correction. Moreover, we show that our implementation of cycle-consistency loss leads to significantly better biological preservation than adversarial learning implemented in the previously proposed GLUE model. Additionally, we do not recommend relying only on the KL regularization strength tuning for increasing batch correction, as it removes both biological and batch information without discriminating between the two. Based on our findings, we propose a new model that combines VampPrior and cycle-consistency loss. We show that using it for datasets with substantial batch effects improves downstream interpretation of cell states and biological conditions. To ease the use of the newly proposed model, we make it available in the scvi-tools package as an external model named sysVI. Moreover, in the future, these regularization techniques could be added to other established cVAE-based models to improve the integration of datasets with substantial batch effects.
LncPlankton V1.0: a comprehensive collection of plankton long non-coding RNAs
Authors: Debit Ahmed , Vincens Pierre , Bowler Chris , de Carvalho Helena Cruz 
Published: November 2023

ABSTRACTLong considered as transcriptional noise, long non-coding RNAs (lncRNAs) are emerging as central, regulatory molecules in a multitude of eukaryotic species, from plants to animals to fungi. Yet, our knowledge about the occurrence of these molecules in the marine environment, namely in planktonic protists, is still elusive. To fill this gap of knowledge we developed LncPlankton v1.0, which is the first comprehensive database of marine plankton lncRNAs. By integrating the predictions derived from ten distinctive coding potential prediction tools in a majority voting setting, we identified 2,210,359 lncRNAs distributed across 414 marine plankton species from over nine different phyla. A user-friendly, open-access web interface for the exploration of the database was implemented (https://www.lncplankton.bio.ens.psl.eu/). We believe LncPlankton v1.0 will serve as a rich resource for studies of lncRNAs that will contribute to small- and large-scale analyses in a wide range of marine plankton species and allow comparative analysis well beyond the marine environment.