bluuebunny/crossref_metadata_2025_split huggingface dataset:
A phosphorylation switch regulates RAB6 function during mitosis
Authors: Jimenez Ana Joaquina , Bousquet Hugo , Bardin Sabine , Perez Franck , Goud Bruno , Miserey Stéphanie 
Published: January 2023

AbstractRAB GTPases are key regulators of membrane trafficking in eukaryotic cells. In addition to their role in interphase, several RAB proteins, including Golgi-associated RAB6, have mitotic functions. The aim of this study was to investigate how the interphasic and mitotic functions of RAB6 could be regulated. Since phosphorylation is a key regulatory process in mitosis, we looked for specific mitotic phosphorylation of RAB6 using a phospho-proteomic approach. We found that RAB6 is phosphorylated at position S52 by the mitotic kinase Pololike kinase 1 (Plk1) in mitosis. Phosphorylated RAB6 localizes at the spindle poles from prophase to anaphase. In metaphase, we observed RAB6A-positive structures containing Mad1 and Mad2 moving along the mitotic spindle via the dynein-dynactin complex. We provide evidence that phosphorylation impairs RAB6A binding to some of its known partners, including p150Gluedand Bicaudal-D2. In addition, the overexpression of RAB6A phospho-mutants lead to mitosis and cytokinesis defects. Our results suggest that a cycle of RAB6 phosphorylation/dephosphorylation is required for cell division.
The macrophage genetic cassette inr/dtor/pvf2 is a nutritional status checkpoint for developmental timing
Authors: Juarez-Carreño Sergio , Geissmann Frederic 
Published: January 2023

SummaryA small number of signaling molecules, used reiteratively, control differentiation programs, but the mechanisms that adapt developmental timing to environmental cues are less understood. We report here that a macrophageinr/dtor/pvf2genetic cassette is a developmental timing checkpoint inDrosophila, which either licenses or delays biosynthesis of the steroid hormone in the endocrine gland and metamorphosis according to the larval nutritional status. Insulin-Receptor/dTor signaling in macrophages is required and sufficient for production of the PDGF/VEGF family growth factor Pvf2, which turns on transcription of the sterol biosynthesis Halloween genes in the prothoracic gland via its receptor Pvr. In response to a starvation event or genetic manipulation, low Pvf2 signal delays steroid biosynthesis until it becomes Pvr-independent, thereby prolonging larval growth before pupation. The significance of this developmental timing checkpoint for host fitness is illustrated by the observation that it regulates the size of the pupae and adult flies.One sentence summaryA macrophage Inr/dtor/pvf2 cassette is a nutritional status checkpoint that controls developmental timing via steroid hormone biosynthesis in the endocrine gland.
Functional genomic analysis of adult and pediatric brain tumor isolates
Authors: Hoellerbauer Pia , Biery Matt C. , Arora Sonali , Rao Yiyun , Girard Emily J. , Mitchell Kelly , Dighe Pratiksha , Kufeld Megan , Kuppers Daniel A. , Herman Jacob A. , Holland Eric C. , Soroceanu Liliana , Vitanza Nicholas A. , Olson James M. , Pritchard Justin R. , Paddison Patrick J. 
Published: January 2023

AbstractBackgroundAdult and pediatric tumors display stark differences in their mutation spectra and chromosome alterations. Here, we attempted to identify common and unique gene dependencies and their associated biomarkers among adult and pediatric tumor isolates using functional genetic lethal screens and computational modeling.MethodsWe performed CRISRP-Cas9 lethality screens in two adult glioblastoma (GBM) tumor isolates and five pediatric brain tumor isolates representing atypical teratoid rhabdoid tumors (ATRT), diffuse intrinsic pontine glioma, GBM, and medulloblastoma. We then integrated the screen results with machine learning-based gene-dependency models generated from data from >900 cancer cell lines.ResultsWe found that >50% of candidate dependencies of 280 identified were shared between adult GBM tumors and individual pediatric tumor isolates. 68% of screen hits were found as nodes in our network models, along with shared and tumor-specific predictors of gene dependencies. We investigated network predictors associated with ADAR, EFR3A, FGFR1 (pediatric-specific), and SMARCC2 (ATRT-specific) gene dependency among our tumor isolates.ConclusionsThe results suggest that, despite harboring disparate genomic signatures, adult and pediatric tumor isolates share a preponderance of genetic dependences. Further, combining data from primary brain tumor lethality screens with large cancer cell line datasets produced valuable insights into biomarkers of gene dependency, even for rare cancers.Importance of the StudyOur results demonstrate that large cancer cell lines data sets can be computationally mined to identify known and novel gene dependency relationships in adult and pediatric human brain tumor isolates. Gene dependency networks and lethality screen results represent a key resource for neuro-oncology and cancer research communities. We also highlight some of the challenges and limitations of this approach.
Harnessing antimicrobial peptide genes to expedite disease-resistant enhancement in aquaculture: Transgenesis and genome editing
Authors: Wang Jinhai , Cheng Yu 
Published: January 2023

AbstractNumerous studies have demonstrated that genome editing and transgenesis by integrating vector-engineered antimicrobial peptide genes (AMGs) is effective to modulate the fish’s innate immune system. To generalize the knowledge of AMG application in aquaculture, here we recruited 540 data entries from a pool of empirical studies, which included 18 peer-reviewed publications and spanning 12 diseases. We systematically re-processed and re-analyzed these data by harnessing a cross-disease meta-analysis. On aggregate, AMG-genetic engineering aimed at enhancing disease resistance was shown to decrease the number of colony-forming units of bacteria, improve lysozyme activity, increase the post-infection survival rates, and alter the expression of AMGs and immune-related genes in aquatic animals. Furthermore, the AMG-pathogen combating activity was triggered within two hours after infection and lasted 48 hours, and the overexpression of AMGs was dominant in the spleen and skin, followed by the kidney and liver during this period. Typically, regardless of the type of AMGs, the synergistic expression of AMGs with IL, IKβ, TGFβ, C3b and TLR in AMG-integrated fish contributed to activating inflammatory/immune responses against pathogens. In addition, innovative CRISPR/Cas9-mediated systems enabling the site-directed knock-in of foreign genes at multiple loci were presented and prospected for disease-resistant enhancement in combination with other favorable fish-producing traits, including fast-growing, sterility, and enriched fatty acid. Altogether, our findings indicated that AMGs as transgenes have substantial potential to modulate the fish’s innate immune system and accelerate disease-resistant enhancement combined with genetic engineering.
Phenotypic subtyping via contrastive learning
Authors: Gorla Aditya , Sankararaman Sriram , Burchard Esteban , Flint Jonathan , Zaitlen Noah , Rahmani Elior 
Published: January 2023

AbstractDefining and accounting for subphenotypic structure has the potential to increase statistical power and provide a deeper understanding of the heterogeneity in the molecular basis of complex disease. Existing phenotype subtyping methods primarily rely on clinically observed heterogeneity or metadata clustering. However, they generally tend to capture the dominant sources of variation in the data, which often originate from variation that is not descriptive of the mechanistic heterogeneity of the phenotype of interest; in fact, such dominant sources of variation, such as population structure or technical variation, are, in general, expected to be independent of subphenotypic structure. We instead aim to find a subspace with signal that is unique to a group of samples for which we believe that subphenotypic variation exists (e.g., cases of a disease). To that end, we introduce Phenotype Aware Components Analysis (PACA), a contrastive learning approach leveraging canonical correlation analysis to robustly capture weak sources of subphenotypic variation. In the context of disease, PACA learns a gradient of variation unique to cases in a given dataset, while leveraging control samples for accounting for variation and imbalances of biological and technical confounders between cases and controls. We evaluated PACA using an extensive simulation study, as well as on various subtyping tasks using genotypes, transcriptomics, and DNA methylation data. Our results provide multiple strong evidence that PACA allows us to robustly capture weak unknown variation of interest while being calibrated and well-powered, far superseding the performance of alternative methods. This renders PACA as a state-of-the-art tool for definingde novosubtypes that are more likely to reflect molecular heterogeneity, especially in challenging cases where the phenotypic heterogeneity may be masked by a myriad of strong unrelated effects in the data.Code AvailabilityPACA is available as an open source R package on GitHub:https://github.com/Adigorla/PACA
ViralConsensus: A fast and memory-efficient tool for calling viral consensus genome sequences directly from read alignment data
Authors: Moshiri Niema 
Published: January 2023

AbstractMotivationIn viral molecular epidemiology, reconstruction of consensus genomes from sequence data is critical for tracking mutations and variants of concern. However, as the number of samples that are sequenced grows rapidly, compute resources needed to reconstruct consensus genomes can become prohibitively large.ResultsViralConsensus is a fast and memory-efficient tool for calling viral consensus genome sequences directly from read alignment data. ViralConsensus is orders of magnitude faster and more memory-efficient than existing methods. Further, unlike existing methods, ViralConsensus can pipe data directly from a read mapper via standard input and performs viral consensus calling on-the-fly, making it an ideal tool for viral sequencing pipelines.AvailabilityViralConsensus is freely available athttps://github.com/niemasd/ViralConsensusas an open-source software project.Contactniema@ucsd.eduSupplementary informationSupplementary data are available online.
Caspase-4 dimerisation and D289 auto-processing elicits an interleukin-1β converting enzyme
Authors: Chan Amy H. , Vezyrgiannis Kassandra , Von Pein Jessica B. , Wang Xiaohui , Labzin Larisa I , Boucher Dave , Schroder Kate 
Published: January 2023

AbstractThe non-canonical inflammasome is a signalling complex critical for cell defence against cytosolic Gram-negative bacteria. A key step in the human non-canonical inflammasome pathway involves unleashing the proteolytic activity of caspase-4 within this complex. Caspase-4 induces inflammatory responses by cleaving gasdermin-D (GSDMD) to initiate pyroptosis, although the molecular mechanisms that activate caspase-4 and govern its capacity to cleave substrates are poorly defined. Caspase-11, the murine counterpart of caspase-4, acquires protease activity within the non-canonical inflammasome by forming a dimer that self-cleaves at D285 to directly cleave GSDMD. These cleavage events trigger signalling via the NLRP3-ASC-caspase-1 axis, leading to downstream cleavage of the pro-interleukin-1β (pro-IL-1β) cytokine precursor. Here, we show that caspase-4 first dimerises then self-cleaves at two sites – D270 and D289 – in the interdomain linker to acquire full proteolytic activity, cleave GSDMD and induce cell death. Surprisingly, caspase-4 dimerisation and self-cleavage at D289 generates a caspase-4 p34/p9 protease species that directly cleaves pro-IL-1β, resulting in its maturation and secretion independently of the NLRP3 inflammasome in primary human myeloid and epithelial cells. Our study thus elucidates the key molecular events that underpin signalling by the caspase-4 inflammasome, and identifies IL-1β as a natural substrate of caspase-4.
Graph Convolutional Learning of Multimodal Brain Connectome Data for Schizophrenia Classification
Authors: Ghosh Sanjay , Bhargava Eshan , Lin Chieh-Te , Nagarajan Srikantan S. 
Published: January 2023

ABSTRACTThe long term goal of this work is to develop powerful tools for brain network analysis in order to study structural and functional connectivity abnormalities in psychiatric disorders like schizophrenia. Graph convolutional neural networks (GCNN) are quite effective for learning complex discriminate features in graph-structured data. Here, we explore the GCNN to learn the discriminating features in multimodal human brain connectomes for the purpose of schizophrenia disorder classification. In particular, we train and validate a network using both structural connectivity graphs obtained from diffusion tensor imaging data and functional connectivity from functional magnetic resonance imaging data.We compare the GCNN method with a support vector machine based classifier and other popular classification benchmarks. We demonstrate that the proposed graph convolution method has the best performance compared to existing benchmarks with F1 scores of 0.75 for schizophrenia classification. This demonstrates the potential of this approach for multimodal diagnosis and prognosis in mental health disorders.
Genomic evolution of non-small cell lung cancer patient-derived xenograft models
Authors: Hynds Robert E. , Huebner Ariana , Pearce David R. , Akarca Ayse U. , Moore David A. , Ward Sophia , Gowers Kate H.C. , Karasaki Takahiro , Hill Mark S. , Bakir Maise Al , Wilson Gareth A. , Pich Oriol , Sivakumar Monica , Aissa Assma Ben , Grönroos Eva , Chandrasekharan Deepak , Kolluri Krishna K. , Towns Rebecca , Wang Kaiwen , Cook Daniel E. , Bosshard-Carter Leticia , Naceur-Lombardelli Cristina , Rowan Andrew J. , Veeriah Selvaraju , Litchfield Kevin , Quezada Sergio A. , Janes Sam M. , Jamal-Hanjani Mariam , Marafioti Teresa ,   TRACERx Consortium, McGranahan Nicholas , Swanton Charles 
Published: January 2023

ABSTRACTPatient-derived xenograft (PDX) models of cancer, developed through injection of patient tumour cells into immunocompromised mice, have been widely adopted in preclinical studies, as well as in precision oncology approaches. However, the extent to which PDX models represent the underlying genetic diversity of a patient’s tumour and the extent of on-going genomic evolution in PDX models are incompletely understood, particularly in the context of heterogeneous cancers such as non-small cell lung cancer (NSCLC). To investigate the depiction of intratumour heterogeneity by PDX models, we derived 47 new subcutaneous multi-region PDX models from 22 patients with primary NSCLC enrolled in the clinical longitudinal cohort study TRACERx. By analysing whole exome sequencing data from primary tumours and PDX models, we find that PDX establishment creates a genomic bottleneck, with 76% of PDX models being derived from a single primary tumour subclone. Despite this, multiple primary tumour subclones were capable of PDX establishment in regional PDX models, indicating that PDX libraries derived from multiple tumour regions can capture intratumour heterogeneity. Acquisition of somatic mutations continued during PDX model expansion, and was associated with APOBEC- or mismatch repair deficiency-induced mutational signatures in a subset of models. Overall, while NSCLC PDX models retain truncal genomic alterations, the absence of subclonal heterogeneity representative of the primary tumour is a major limitation. Our results emphasise the importance of characterising and monitoring intratumour heterogeneity in the context of pre-clinical cancer studies.
The Cortical Representation of Language Timescales is Shared between Reading and Listening
Authors: Chen Catherine , Dupré la Tour Tom , Gallant Jack L. , Klein Dan , Deniz Fatma 
Published: January 2023

AbstractLanguage comprehension involves integrating low-level sensory inputs into a hierarchy of increasingly high-level features. Prior work studied brain representations of different levels of the language hierarchy, but has not determined whether these brain representations are shared between written and spoken language. To address this issue, we analyzed fMRI BOLD data recorded while participants read and listened to the same narratives in each modality. Levels of the language hierarchy were operationalized astimescales, where each timescale refers to a set of spectral components of a language stimulus. Voxelwise encoding models were used to determine where different timescales are represented across the cerebral cortex, for each modality separately. These models reveal that between the two modalities timescale representations are organized similarly across the cortical surface. Our results suggest that, after low-level sensory processing, language integration proceeds similarly regardless of stimulus modality.
Ultra-fast genome-wide inference of pairwise coalescence times
Authors: Schweiger Regev , Durbin Richard 
Published: January 2023

AbstractThe pairwise sequentially Markovian coalescent (PSMC) algorithm and its extensions infer the coalescence time of two homologous chromosomes at each genomic position. This inference is utilized in reconstructing demographic histories, detecting selection signatures, genome-wide association studies, constructing ancestral recombination graphs and more. Inference of coalescence times between each pair of haplotypes in a large dataset is of great interest, as they may provide rich information about the population structure and history of the sample.We introduce a new method,Gamma-SMC, which is>14 times faster than current methods. To obtain this speed up, we represent the posterior coalescence time distributions succinctly as a Gamma distribution with just two parameters; while in PSMC and its extensions, these are held as a vector over discrete intervals of time. Thus, Gamma-SMC has constant time complexity per site, without dependence on a number of discrete time states. Additionally, due to this continuous representation, our method is able to infer times spanning many orders of magnitude, and as such is robust to parameter misspecification. We describe how this approach works, illustrate its performance on simulated and real data, and use it to study recent positive selection in the 1000 Genomes Project dataset.
MYC enhancer invasion promotes prognostic cancer type-specific gene programs through an epigenetic switch
Authors: Jakobsen Simon T. , Jensen Rikke AM. , Ravnsborg Tina , Vaagenso Christian D. , Einarsson Hjorleifur , Madsen Maria S. , Andersson Robin , Jensen Ole N. , Siersbæk Rasmus 
Published: January 2023

AbstractThe transcription factor MYC is overexpressed in most cancers, where it drives multiple hallmarks of cancer progression. MYC is known to promote oncogenic transcription by binding to active promoters. In addition, MYC has also been shown to invade distal enhancers when expressed at oncogenic levels, but this enhancer binding has been proposed to have low gene-regulatory potential. Here, we demonstrate that MYC enhancer binding directly promotes cancer type-specific gene programs predictive of poor patient prognosis. MYC induces transcription of enhancer RNA through recruitment of RNAPII, rather than regulating RNAPII pause-release as is the case at promoters. This is mediated by MYC-induced H3K9 demethylation by KDM3A and acetylation by GCN5, leading to enhancer-specific BRD4 recruitment through its bromodomains, which facilitates RNAPII recruitment. Thus, we propose that MYC drives prognostic cancer type-specific gene programs by promoting RNAPII recruitment to enhancers through induction of an epigenetic switch.
Transcription factors mediating regulation of photosynthesis
Authors: Halpape Wiebke , Wulf Donat , Verwaaijen Bart , Stasche Anna Sophie , Zenker Sanja , Sielemann Janik , Tschikin Sebastian , Viehöver Prisca , Sommer Manuel , Weber Andreas P. M. , Delker Carolin , Eisenhut Marion , Bräutigam Andrea 
Published: January 2023

AbstractPhotosynthesis by which plants convert carbon dioxide to sugars using the energy of light is fundamental to life as it forms the basis of nearly all food chains. Surprisingly, our knowledge about its transcriptional regulation remains incomplete. Effort for its agricultural optimization have mostly focused on post-translational regulatory processes1–3but photosynthesis is regulated at the post-transcriptional4and the transcriptional level5. Stacked transcription factor mutations remain photosynthetically active5,6and additional transcription factors have been difficult to identify possibly due to redundancy6or lethality. Using a random forest decision tree-based machine learning approach for gene regulatory network calculation7we determined ranked candidate transcription factors and validated five out of five tested transcription factors as controlling photosynthesisin vivo. The detailed analyses of previously published and newly identified transcription factors suggest that photosynthesis is transcriptionally regulated in a partitioned, non-hierarchical, interlooped network.
APOBEC3F is the main source of editing identified during the 2022 outbreak of human monkeypox virus
Authors: Suspène Rodolphe , Raymond Kyle A. , Boutin Laetitia , Guillier Sophie , Lemoine Frédéric , Ferraris Olivier , Tournier Jean-Nicolas , Iseni Frédéric , Simon-Lorière Etienne , Vartanian Jean-Pierre 
Published: January 2023

AbstractOn May 6, 2022, a powerful outbreak of monkeypox virus (MPXV) had been reported outside of Africa, with many continuing new cases being reported around the world. Analysis of mutations among the two different lineages present in the 2021 and 2022 outbreaks revealed the presence of G->A mutations occurring in the 5’GpA context, indicative of APOBEC3 cytosine deaminase activity. By using a sensitive PCR (3D-PCR) method allowing differential amplification of AT-rich DNA, we demonstrate that G->A hypermutated MPXV genomes can be recovered experimentally from APOBEC3 transfection followed by MPXV infection. Here, among the 7 human APOBEC3 cytidine deaminases (A3A-A3C, A3DE, A3F-A3H), only APOBEC3F was capable of extensively deaminating cytidine residues in MPXV genomes. Hyperedited genomes were also recovered in ~42% of analyzed patients, indicating that editing is part of the natural cycle of MPXV infection. Moreover, we demonstrate that substantial repair of these mutations occurs. Upon selection, corrected G->A mutations escaping drift loss contribute to the MPXV evolution observed in the current epidemics. Thus, stochastic or transient overexpression ofAPOBEC3Fgene exposes the MPXV genome to a broad spectrum of mutations that may be modeling the mutational landscape after multiple cycles of viral replication.