bluuebunny/crossref_metadata_2025_split huggingface dataset:
Phosphorylation, disorder, and phase separation govern the behavior of Frequency in the fungal circadian clock
Authors: Tariq Daniyal , Maurici Nicole , Bartholomai Bradley M. , Chandrasekaran Siddarth , Dunlap Jay C. , Bah Alaji , Crane Brian R. 
Published: November 2022

AbstractCircadian clocks are composed of molecular oscillators that pace rhythms of gene expression to the diurnal cycle. Therein, transcriptional-translational negative feedback loops (TTFLs) generate oscillating levels of transcriptional repressor proteins that regulate their own gene expression. In the filamentous fungusNeurospora crassa,the proteinsFrequency (FRQ), theFRQ-interacting RNA helicase (FRH) andCasein-Kinase I (CK1) form theFFCcomplex that represses expression of genes activated by the White-Collar complex (WCC). A key question concerns how FRQ orchestrates molecular interactions at the core of the clock despite containing little predicted tertiary structure. We present the reconstitution and biophysical characterization of FRQ and the FFC in unphosphorylated and highly phosphorylated states. Site-specific spin labeling and pulse- dipolar ESR spectroscopy provides domain-specific structural details on the full-length, 989- residue intrinsically disordered FRQ and the FFC. FRQ contains a compact core that associates and organizes FRH and CK1 to coordinate their roles in WCC repression. FRQ phosphorylation increases conformational flexibility and alters oligomeric state but the changes in structure and dynamics are non-uniform. Full-length FRQ undergoes liquid-liquid phase separation (LLPS) to sequester FRH and CK1 and influence CK1 enzymatic activity. Although FRQ phosphorylation favors LLPS, LLPS feeds back to reduce FRQ phosphorylation by CK1 at higher temperatures. Live imaging ofNeurosporahyphae reveals FRQ foci characteristic of condensates near the nuclear periphery. Analogous clock repressor proteins in higher organisms share little position-specific sequence identity with FRQ; yet, they contain amino-acid compositions that promote LLPS. Hence, condensate formation may be a conserved feature of eukaryotic circadian clocks.
EukRibo: a manually curated eukaryotic 18S rDNA reference database to facilitate identification of new diversity
Authors: Berney Cédric , Henry Nicolas , Mahé Frédéric , Richter Daniel J. , de Vargas Colomban 
Published: November 2022

AbstractEukRibo is a manually curated, public reference database of small-subunit ribosomal RNA gene (18S rDNA) sequences of eukaryotes, specifically aimed at taxonomic annotation of high-throughput metabarcoding datasets. Unlike other reference databases of ribosomal genes, it is not meant to exhaustively capture all publicly available 18S rDNA sequences from the INSDC repositories, but to represent a subset of highly trustable sequences covering the whole known diversity of eukaryotes. EukRibo strives to include only sequences with verified, up-to-date taxonomic identifications, with a strong focus on protists, and relatively low genetic redundancy, to keep the database compact yet comprehensive. Environmental clone sequences representing previously identified novel diversity are accepted as reference sequences only if they have a precise lineage designation, useful for taxonomic annotation. EukRibo is part of a suite of public resources generated by the UniEuk project, which all follow a common taxonomic framework for maximal interoperability. The high level of taxonomic accuracy of EukRibo allows higher confidence in the taxonomic annotation of environmental metabarcodes, and should facilitate identification of new eukaryotic diversity at various taxonomic levels. The database is currently in version 2, and all versions are permanently stored and made available via the FAIR open platform Zenodo. It is our hope that EukRibo will help ongoing curation efforts of other 18S rDNA reference databases, and we welcome suggestions of corrections and new features to be included in subsequent versions.
A condensate forming tether for lariat debranching enzyme is defective in non-photosensitive trichothiodystrophy
Authors: Townley Brittany A. , Buerer Luke , Bacolla Albino , Rusanov Timur , Schmidt Nicolas , Srivatsan Sridhar N. , Clark Nathanial E. , Mansoori Fadhel , Sample Reilly A. , Brickner Joshua R. , McDonald Drew , Tsai Miaw-Sheue , Walter Matthew J. , Wozniak David F. , Holehouse Alex S. , Tainer John A. , Fairbrother William G. , Mosammaparast Nima 
Published: November 2022

SummaryThe pre-mRNA life cycle requires intron processing; yet, how intron processing defects influence splicing and gene expression is unclear. Here, we find TTDN1, which is frequently mutated in non-photosensitive trichothiodystrophy (NP-TTD), functionally links intron lariat processing to the spliceosome. The conserved TTDN1 C-terminal region directly binds lariat debranching enzyme DBR1, while its N-terminal intrinsically disordered region (IDR) binds the intron binding complex (IBC). The IDR forms condensatesin vitroand is needed for IBC interaction. TTDN1 loss causes significant intron lariat accumulation, as well as splicing and gene expression defects, mirroring phenotypes observed in NP-TTD patient cells.Ttdn1Δ/Δmice recapitulate intron processing defects and neurodevelopmental phenotypes seen in NP-TTD. A DBR1-IDR fusion recruits DBR1 to the IBC and circumvents the requirement for TTDN1, indicating this tethering role as its major molecular function. Collectively, our findings unveil key functional connections between lariat processing, splicing outcomes, and NP-TTD molecular pathology.
A stratagem for primary root elongation under moderate salt stress in the halophyteSchrenkiella parvula
Authors: Sekerci Keriman , Higashitani Nahoko , Ozgur Rengin , Uzilday Baris , Higashitani Atsushi , Turkan Ismail 
Published: November 2022

AbstractHalophytes are salt-tolerant plants that grow in soil or waters of high salinity.Schrenkiella parvulais one of the halophyte plants that grow around Tuz (Salt) Lake, TURKEY that can survive at 600 mM NaCl. Intriguingly,S. parvulabelongs to the same Brassicaceae family as the model plantArabidopsis thaliana, and its genome is 90% homologous to the Arabidopsis genome. Here, we performed proteomic analysis and physiological studies on the roots ofS. parvulaseedlings cultivated under a moderate salt condition at 100 mM NaCl. Surprisingly, under 100 mM NaCl conditions, the primary roots elongated much faster than under NaCl-free conditions, although up to 200 mM those were reduced. On the other hand, iso-osmotic mannitol did not promote primary root elongation, suggesting a specific response to NaCl. Epidermal cell elongation was promoted in the elongation zone, but meristem size and DNA replication were decreased. In addition, root hair formation and lateral root elongation were suppressed at moderate salinity. Compared withA. thaliana, the cell death and ROS increase of root tip meristem cells under 100 mM NaCl condition were significantly lower inS. parvulaseedlings. The size and starch content of sedimentary amyloplasts/statoliths in columella cells decreased, and gravitropism of primary roots was partially reduced. Gene expression analyses showed that the expression of auxin response and biosynthesis genesIAA1, IAA2, TAA1andYUC8were repressed and theSOS1gene was upregulated two-fold in roots grown under moderate salt conditions. Proteomic analysis showed that co-chaperone and activator of HSPs such as Hop2 and Aha1 domain-containing protein orthologs were upregulated. Moreover, several secondary metabolic process-related proteins, antioxidant proteins, stress response proteins and proline catabolic process-related proteins were also increased. In contrast, enzymes associated with root hair elongation and nucleotide and protein syntheses were downregulated. These changes in auxin-related physiological responses, root architecture, lower ROS signaling, and stress-related protein expression promote primary root penetration into lower-salinity deeper soils as an adaptation ofS. parvula.
kegg_pull: a Software Package for the RESTful Access and Pulling from The Kyoto Encyclopedia of Gene and Genomes
Authors: Huckvale Erik , Moseley Hunter N.B. 
Published: November 2022

AbstractBackgroundThe Kyoto Encyclopedia of Genes and Genomes (KEGG) provides organized genomic, biomolecular, and metabolic information and knowledge that is reasonably current and highly useful for a wide range of analyses and modeling. KEGG follows the principles of data stewardship to be findable, accessible, interoperable, and reusable (FAIR) by providing RESTful access to their database entries via their web-accessible KEGG API. However, the overall FAIRness of KEGG is often limited by the library and software package support available in a given programming language. While R library support for KEGG is fairly strong, Python library support has been lacking. Moreover, there is no software that provides extensive command line level support for KEGG access and utilization.ResultsWe present kegg_pull, a package implemented in the Python programming language that provides better KEGG access and utilization functionality than previous libraries and software packages. Not only does kegg_pull include an application programming interface (API) for Python programming, it also provides a command line interface (CLI) that enables language agnostic utilization of KEGG for a wide range of data analysis pipeline use-cases. As kegg_pull’s name implies, both the API and CLI provide versatile options for pulling (downloading and saving) an arbitrary (user defined) number of database entries from the KEGG API. Moreover, this functionality is implemented to efficiently utilize multiple central processing unit cores. Many options are provided to optimize fault-tolerant performance across a single or multiple processes, with recommendations provided based on extensive testing and practical network considerations.ConclusionsThe new kegg_pull package enables new flexible KEGG retrieval use cases not available in previous software packages. The most notable new feature that kegg_pull provides is its ability to robustly pull an arbitrary number of KEGG entries with a single API method or CLI command, including pulling an entire KEGG database. We provide recommendations to users for the most effective use of kegg_pull according to their network and computational circumstances.
Facemap: a framework for modeling neural activity based on orofacial tracking
Authors: Syeda Atika , Zhong Lin , Tung Renee , Long Will , Pachitariu Marius , Stringer Carsen 
Published: November 2022

AbstractRecent studies in mice have shown that orofacial behaviors drive a large fraction of neural activity across the brain. To understand the nature and function of these signals, we need better computational models to characterize the behaviors and relate them to neural activity. Here we developed Facemap, a framework consisting of a keypoint tracking algorithm and a deep neural network encoder for predicting neural activity. We used the Facemap keypoints as input for the deep neural network to predict the activity of ∼50,000 simultaneously-recorded neurons and in visual cortex we doubled the amount of explained variance compared to previous methods. Our keypoint tracking algorithm was more accurate than existing pose estimation tools, while the inference speed was several times faster, making it a powerful tool for closed-loop behavioral experiments. The Facemap tracker was easy to adapt to data from new labs, requiring as few as 10 annotated frames for near-optimal performance. We used Facemap to find that the neuronal activity clusters which were highly driven by behaviors were more spatially spread-out across cortex. We also found that the deep keypoint features inferred by the model had time-asymmetrical state dynamics that were not apparent in the raw keypoint data. In summary, Facemap provides a stepping stone towards understanding the function of the brainwide neural signals and their relation to behavior.
Machine learning-guided directed evolution for the development of small-molecule antibiotics originating from antimicrobial peptides
Authors: Zhang Heqian , Wang Yihan , Huang Pengtao , Zhu Yanran , Li Xiaojie , Chen Zhaoying , Liu Yu , Jiang Jiakun , Gao Yuan , Huang Jiaquan , Qin Zhiwei 
Published: November 2022

AbstractAntimicrobial peptides (AMPs) are valuable alternatives to traditional antibiotics that possess a variety of potent biological activities by exerting immunomodulatory effects to clear difficult-to-treat infections. Understanding the structure-activity relationships (SARs) of AMPs can direct the synthesis of desirable therapeutics. In this study, we use machine learning-guided directed evolution to develop the lipopolysaccharide-binding domain (LBD), which acts as a functional domain of anti-lipopolysaccharide factor (ALF), a family of AMPs, identified fromMarsupenaeus japonicus. We report the identification of LBDA-Das an output of this algorithm with the input of the original LBDMjsequence and show the NMR solution structure of LBDB, which possesses a circular extended structure with a disulfide crosslink in each terminus and two 310-helices and exhibits a broad antimicrobial spectrum. Scanning electron microscopy and transmission electron microscopy showed LBDBinduced the formation of a cluster of bacteria wrapped in a flexible coating that ruptured and consequently killed the bacteria. The co-injection of LBDBandVibrio alginolyticus, Staphylococcus aureusand another major pathogen in shrimp aquaculture white spot syndrome virusin vivoimproved the survival ofM. japonicus, indicating a promising therapeutic role of LBDBfor infectious disease. The findings of this study pave the way for the rational drug design of activity-enhanced peptide antibiotics.
The efficacy of chemotherapy is limited by intratumoural senescent cells that persist through the upregulation of PD-L2
Authors: Chaib Selim , López-Domínguez José Alberto , Lalinde Marta , Prats Neus , Marin Ines , Meyer Kathleen , Muñoz María Isabel , Aguilera Mònica , Mateo Lidia , Attolini Camille Stephan-Otto , Llanos Susana , Pérez-Ramos Sandra , Escorihuela Marta , Al-Shahrour Fatima , Cash Timothy P. , Tchkonia Tamara , Kirkland James L. , Arribas Joaquín , Serrano Manuel 
Published: November 2022

AbstractAnti-cancer therapies often result in a subset of surviving cancer cells that undergo therapy-induced senescence (TIS). Senescent cancer cells strongly modify the intratumoural microenvironment favoring immunosuppression and, thereby, tumour growth. An emerging strategy to optimise current therapies is to combine them with treatments that eliminate senescent cells. To this end, we undertook an unbiased proteomics approach to identify surface markers contributing to senescent cells immune evasion. Through this approach, we discovered that the immune checkpoint inhibitor PD-L2, but not PD-L1, is upregulated across multiple senescent human and murine cells. Importantly, blockade of PD-L2 strongly synergises with genotoxic chemotherapy, causing remission of solid tumours in mice. We show that PD-L2 inhibition prevents the persistence of chemotherapy-induced senescent cells, which exert cell-extrinsic immunomodulatory actions. In particular, upon chemotherapy, tumours deficient in PD-L2 fail to produce cytokines of the CXCL family, do not recruit myeloid-derived suppressor cells (MDSCs) and are eliminated in a CD8 T cell-dependent manner. We conclude that blockade of PD-L2 improves chemotherapy efficacy by reducing the intratumoural burden of senescent cells and their associated recruitment of immunosuppressive cells. These findings provide a novel strategy to exploit vulnerabilities arising in tumour cells as a result of therapy-induced damage and cellular senescence.
DeepOM: Single-molecule optical genome mapping via deep learning
Authors: Nogin Yevgeni , Detinis Zur Tahir , Margalit Sapir , Barzilai Ilana , Alalouf Onit , Ebenstein Yuval , Shechtman Yoav 
Published: November 2022

AbstractEfficient tapping into genomic information from a single microscopic image of an intact DNA molecule fragment is an outstanding challenge and its solution will open new frontiers in molecular diagnostics. Here, a new computational method for optical genome mapping utilizing Deep Learning is presented, termed DeepOM. Utilization of a Convolutional Neural Network (CNN), trained on simulated images of labeled DNA molecules, improves the success rate in alignment of DNA images to genomic references. The method is evaluated on acquired images of human DNA molecules stretched in nano-channels. The accuracy of the method is benchmarked against state-of-the-art commercial software Bionano Solve. The results show a significant advantage in alignment success rate for molecules shorter than 50 kb. DeepOM improves yield, sensitivity and throughput of optical genome mapping experiments in applications of human genomics and microbiology.
Measuring factors affecting honey bee attraction to soybeans using bioacoustics monitoring
Authors: Forrester Karlan C. , Lin Chia-Hua , Johnson Reed M. 
Published: November 2022

AbstractSoybean is an important agricultural crop around the world, and previous studies suggest that honey bees can be a component for optimizing soybean production through pollination. Determining when bees are present in soybean fields is critical for assessing pollination activity and identifying periods when bees are absent so that bee-toxic pesticides may be applied. There are currently several methods for detecting pollinator activity, but these existing methods have substantial limitations, including the bias of pan trappings against large bees and the limited duration of observation possible using manual techniques. This study aimed to develop a new method for detecting honey bees in soybean fields using bioacoustics monitoring. Microphones were placed in soybean fields to record the audible wingbeats of foraging bees. Foraging activity was identified using the wingbeat frequency of honey bees (234±13.9 Hz) through a combination of algorithmic and manual approaches. A total of 243 honey bees were detected over ten days of recording in four soybean fields. Bee activity was significantly greater in blooming fields than in non-blooming fields. Temperature had no significant effect on bee activity, but bee activity differed significantly between soybean varieties, suggesting that soybean attractiveness to honey bees is heavily dependent on varietal characteristics. Refinement of bioacoustics methods, particularly through incorporation of machine learning, could provide a practical tool for measuring activity of honey bees and other flying insects in soybeans as well as other crops and ecosystems.
Enteric Glial Cell Network Function is Required for Epithelial Barrier Restitution following Intestinal Ischemic Injury in the Early Postnatal Period
Authors: Ziegler Amanda L. , Erwin Sara , Caldwell Madison L. , Touvron Melissa S. , Pridgen Tiffany A. , Magness Scott T. , Odle Jack , Van Landeghem Laurianne , Blikslager Anthony T. 
Published: November 2022

ABSTRACTIschemic damage to the intestinal epithelial barrier, such as in necrotizing enterocolitis or small intestinal volvulus, is associated with higher mortality rates in younger patients. We have recently reported a powerful pig model to investigate these age-dependent outcomes in which mucosal barrier restitution is strikingly absent in neonates but can be rescued by direct application of homogenized mucosa from older, juvenile pigs by a yet-undefined mechanism. Within the mucosa, a postnatally developing network of enteric glial cells (EGC) is gaining recognition as a key regulator of the mucosal barrier. Therefore, we hypothesized that the developing EGC network may play an important role in coordinating intestinal barrier repair in neonates. Neonatal and juvenile jejunal mucosa recovering from surgically induced intestinal ischemia was visualized by scanning electron microscopy and the transcriptomic phenotypes were assessed by bulk RNA sequencing. EGC network density and gliosis were examined by gene set enrichment analysis, three-dimensional volume imaging and western blot and its function in regulating epithelial restitution assessedex vivoin Ussing chamber using the glia-specific inhibitor fluoroacetate, andin vivoby co-culture assay. Here we refine and elaborate our translational model, confirming a neonatal phenotype characterized by a complete lack of coordinated reparative signaling in the mucosal microenvironment. Further, we report important evidence that the subepithelial EGC network changes significantly over the early postnatal period and demonstrate that EGC function in close proximity to wounded intestinal epithelium is critical to intestinal barrier restitution following ischemic injury.NEW & NOTEWORTHYThis study refines a powerful translational pig model, defining an age-dependent relationship between enteric glia and the intestinal epithelium during intestinal ischemic injury and confirming an important role of the enteric glial cell activity in driving mucosal barrier restitution. This study suggests that targeting the enteric glial network could lead to novel interventions to improve recovery from intestinal injury in neonatal patients.
Label-guided seed-chain-extend alignment on annotated De Bruijn graphs
Authors: Mustafa Harun , Karasikov Mikhail , Ghiasi Nika Mansouri , Rätsch Gunnar , Kahles André 
Published: November 2022

AbstractExponential growth in sequencing databases has motivated scalable De Bruijn graph-based (DBG) indexing for searching these data, using annotations to label nodes with sample IDs. Low-depth sequencing samples correspond to fragmented subgraphs, complicating finding the long contiguous walks required for alignment queries. Aligners that target single-labelled subgraphs reduce alignment lengths due to fragmentation, leading to low recall for long reads. While some (e.g., label-free) aligners partially overcome fragmentation by combining information from multiple samples, biologically-irrelevant combinations in such approaches can inflate the search space or reduce accuracy.We introduce a new scoring model,multi-labelalignment(MLA), for annotated DBGs. MLA leverages two new operations: To promote biologically-relevant sample combinations,Label Changeincorporates more informative global sample similarity into local scores. To improve connectivity,Node Length Changedynamically adjusts the DBG node length during traversal. Our fast, approximate, yet accurate MLA implementation has two key steps: a single-label seed-chain-extendaligner (SCA) and amulti-labelchainer (MLC).SCAuses a traditional scoring model adapting recent chaining improvements to assembly graphs and provides a curated pool of alignments.MLCextracts seed anchors fromSCA’s alignments, produces multi-label chains using MLA scoring, then finally forms multi-label alignments. We show via substantial improvements in taxonomic classification accuracy that MLA produces biologically-relevant alignments, decreasing average weighted UniFrac errors by 63.1–66.8% and covering 45.5–47.4% (median) more long-read query characters than state-of-the-art aligners. MLA’s runtimes are competitive with label-combining alignment and substantially faster than single-label alignment.