bluuebunny/crossref_metadata_2025_split huggingface dataset:
A multimodal iPSC platform for cystic fibrosis drug testing
Authors: Berical Andrew , Lee Rhianna E. , Lu Junjie , Beermann Mary Lou , LeSeur Jake A. , Mithal Aditya , Thomas Dylan , Ranallo Nicole , Peasley Megan , Stuffer Alex , Harrington Jan , Coote Kevin , Hurley Killian , McNally Paul , Mostovslavsky Gustavo , Mahoney John , Randell Scott H. , Hawkins Finn J. 
Published: June 2021

AbstractCystic fibrosis (CF) is a monogenic lung disease caused by dysfunction of the cystic fibrosis transmembrane regulator (CFTR) anion channel, resulting in significant morbidity and mortality. The progress in elucidating the role of the CFTR channel using established animal and cell-based models led to the recent discovery of effective CFTR modulators for most individuals with CF. However, a subset of individuals with CF do not respond to these modulators and there is an urgent need to develop novel therapeutic strategies. In this study, we assembled a panel of iPSCs derived from individuals with common or rare variants representative of three distinct classes of CFTR dysfunction. To measure CFTR function in patient-specific iPSCs we adapted two establishedin vitroassays of CFTR function to iPSC-derived airway cells. In both a 3-D spheroid assay using forskolin-induced swelling as well as planar cultures composed of polarized mucociliary airway epithelial cells, we quantified CFTR baseline function and response to CFTR modulators and detected genotype-specific differences. Our results demonstrate the potential of the human iPSC platform as a research tool to study cystic fibrosis and in particular accelerate therapeutic development for CF caused by rare mutations.
Protective role of the Atg8 homologue Gabarapl1 in regulating cardiomyocyte glycophagy in diabetic heart disease
Authors: Mellor Kimberley M. , Varma Upasna , Koutsifeli Parisa , Curl Claire L. , Janssens Johannes V. , Daniels Lorna J. , Bernasochi Gabriel B. , Raaijmakers Antonia J.A. , Benson Victoria L. , Chan Eleia J. , Annandale Marco , Li Xun , Nursalim Yohanes , Ip Wendy T.K. , Taylor David J. , Raedschelders Koen , Stotland Aleksandr , Robinson Aaron E. , Mills Richard J. , Lamberts Regis R. , Powell Kim L. , O’Brien Terence J. , Katare Rajesh , Chandramouli Chanchal , Ritchie Rebecca H. , Lim Shiang Y. , Parton Robert G. , Hu Xinli , Bell James R. , Porrello Enzo R. , Hudson James E. , Xiao Rui-Ping , Van Eyk Jennifer E. , Gottlieb Roberta A. , Delbridge Lea M.D. 
Published: June 2021

SummaryDiabetic heart disease is highly prevalent and characterized by diastolic dysfunction. The mechanisms of diabetic heart disease are poorly understood and no targeted therapies are available. Here we show that the diabetic myocardium (type 1 and type 2) is characterized by marked glycogen elevation and ectopic cellular localization - a paradoxical metabolic pathology given suppressed cardiomyocyte glucose uptake in diabetes. We demonstrate involvement of a glycogen-selective autophagy pathway (‘glycophagy’) defect in mediating this pathology. Genetically manipulated deficiency of Gabarapl1, an Atg8 autophagy homologue, induces cardiac glycogen accumulation and diastolic dysfunction. Stbd1, the Gabarapl1 cognate autophagosome partner is identified as a unique component of the early glycoproteome response to hyperglycemia in cardiac, but not skeletal muscle. Cardiac-targeted in vivo Gabarapl1 gene delivery normalizes glycogen levels, diastolic function and cardiomyocyte mechanics. These findings reveal that cardiac glycophagy is a key metabolic homeostatic process perturbed in diabetes that can be remediated by Gabarapl1 intervention.
Structure of the human FERRY Rab5 effector complex
Authors: Quentin Dennis , Schuhmacher Jan S. , Klink Björn U. , Lauer Jeni , Shaikh Tanvir R. , Huis in ’t Veld Pim J. , Welp Luisa M. , Urlaub Henning , Zerial Marino , Raunser Stefan 
Published: June 2021

AbstractLong-range mRNA transport is crucial for the spatio-temporal regulation of gene expression, and its malfunction leads to neurological disorders. The pentameric FERRY Rab5 effector complex is the molecular link between mRNA and early endosomes in mRNA intracellular distribution. Here, we determine the cryo-EM structure of the human FERRY complex, composed of Fy-1 to Fy-5. The structure reveals a clamp-like architecture, where two arm-like appendages of Fy-2 and a Fy-5 dimer, protrude from the central Fy-4 dimer. The coiled-coil domains of Fy-2 are flexible and project into opposite directions from the core. While the Fy-2 C-terminal coiled-coil acts as binding region for Fy-1/3 and Rab5, both coiled-coils and Fy-5 concur to bind mRNA. Mutations causing truncations of Fy-2 in patients with neurological disorders impair Rab5 binding or FERRY complex assembly. Thus, Fy-2 serves as a binding hub connecting all five complex subunits and mediating the binding to mRNA and early endosomes via Rab5. The FERRY structure provides novel mechanistic insights into long-distance mRNA transport.
The interplay between host biogeography and phylogeny in structuring diversification of the feather louse genusPenenirmus
Authors: Johnson Kevin P. , Weckstein Jason D. , Herrera Stephany Virrueta , Doña Jorge 
Published: June 2021

ABSTRACTParasite diversification is influenced by many of the same factors that affect speciation of free-living organisms, such as biogeographic barriers. However, the ecology and evolution of the host lineage also has a major impact on parasite speciation. Here we explore the interplay between biogeography and host-association on the pattern of diversification in a group of ectoparasitic lice (Insecta: Phthiraptera:Penenirmus) that feeds on the feathers of woodpeckers, barbets, and honeyguides (Piciformes) and some songbirds (Passeriformes). We use whole genome sequencing of 41 ingroup and 12 outgroup samples to develop a phylogenomic dataset of DNA sequences from a reference set of 2,395 single copy ortholog genes, for a total of nearly four million aligned base positions. The phylogenetic trees resulting from both concatenated and gene-tree/species-tree coalescent analyses were nearly identical and highly supported. These trees recovered the genusPenenirmusas monophyletic and identified several major clades, which tended to be associated with one major host group. However, cophylogenetic analysis revealed that host-switching was a prominent process in the diversification of this group. This host-switching generally occurred within single major biogeographic regions. We did, however, find one case in which it appears that a rare dispersal event by a woodpecker lineage from North America to Africa allowed its associated louse to colonize a woodpecker in Africa, even though the woodpecker lineage from North America never became established there.
SRF-CLICAL: an approach for patient risk stratification using random forest models
Authors: Simao Felipe A. , Hieta Reija , Pulman Jane A. , Madonna Gabriele , Ascierto Paolo Antonio , Lewensohn Rolf , Masucci Giuseppe V. 
Published: June 2021

AbstractAn important part of good clinical care is identifying which patients have a high likelihood of experiencing adverse outcomes. Similarly, due to the significant impact cancer treatment can have on a patient’s quality of life, it is also important to properly identify which patients are likely to benefit from more aggressive treatment options. As such, models for predictive risk stratification can be extremely useful in clinical decision making. In this paper, we present, Survival Random Forest-Clinical Categorization Algorithm (SRF-CLICAL), a new method for patient risk stratification using random forests for survival, regression and classification. As a proof of concept, we demonstrate this method on two different cohorts of cancer patients.
Super.Complex: A supervised machine learning pipeline for molecular complex detection in protein-interaction networks
Authors: Palukuri Meghana V. , Marcotte Edward M. 
Published: June 2021

AbstractCharacterization of protein complexes, i.e. sets of proteins assembling into a single larger physical entity, is important, as such assemblies play many essential roles in cells such as gene regulation. From networks of protein-protein interactions, potential protein complexes can be identified computationally through the application of community detection methods, which flag groups of entities interacting with each other in certain patterns. Most community detection algorithms tend to be unsupervised and assume that communities are dense network subgraphs, which is not always true, as protein complexes can exhibit diverse network topologies. The few existing supervised machine learning methods are serial and can potentially be improved in terms of accuracy and scalability by using better-suited machine learning models and parallel algorithms. Here, we present Super.Complex, a distributed, supervised AutoML-based pipeline for overlapping community detection in weighted networks. We also propose three new evaluation measures for the outstanding issue of comparing sets of learned and known communities satisfactorily. Super.Complex learns a community fitness function from known communities using an AutoML method and applies this fitness function to detect new communities. A heuristic local search algorithm finds maximally scoring communities, and a parallel implementation can be run on a computer cluster for scaling to large networks. On a yeast protein-interaction network, Super.Complex outperforms 6 other supervised and 4 unsupervised methods. Application of Super.Complex to a human protein-interaction network with ~8k nodes and ~60k edges yields 1,028 protein complexes, with 234 complexes linked to SARS-CoV-2, the COVID-19 virus, with 111 uncharacterized proteins present in 103 learned complexes. Super.Complex is generalizable with the ability to improve results by incorporating domain-specific features. Learned community characteristics can also be transferred from existing applications to detect communities in a new application with no known communities. Code and interactive visualizations of learned human protein complexes are freely available at: https://sites.google.com/view/supercomplex/super-complex-v3-0.
Probing interplays between human XBP1u translational arrest peptide and 80S ribosome
Authors: Palma Francesco Di , Decherchi Sergio , Pardo-Avila Fátima , Succi Sauro , Levitt Michael , Heijne Gunnar von , Cavalli Andrea 
Published: June 2021

AbstractThe ribosome stalling mechanism is a crucial biological process; yet its atomistic underpinning is still elusive. In this framework, the XBP1u translational arrest peptide (AP) plays a central role in regulating the Unfolded Protein Response (UPR) in eukaryotic cells. Here, we report multi-microseconds all atom molecular dynamics simulations designed to probe the interactions between the XBP1u AP and the mammalian ribosome exit tunnel, both for the wild type AP and for four mutant variants of different arrest potency. Enhanced sampling simulations allow investigating the AP release process of the different variants shedding light on this complex mechanism. The present outcomes are in qualitative/quantitative agreement with available experimental data. In conclusion, we provide an unprecedented atomistic picture of this biological process and clear-cut insights into the key AP-ribosome interactions.
Spatial transcriptomics using combinatorial fluorescence spectral and lifetime encoding, imaging and analysis
Authors: Vu Tam , Vallmitjana Alexander , Gu Joshua , La Kieu , Xu Qi , Flores Jesus , Zimak Jan , Shiu Jessica , Hosohama Linzi , Wu Jie , Douglas Christopher , Waterman Marian , Ganesan Anand , Hedde Per Niklas , Gratton Enrico , Zhao Weian 
Published: June 2021

AbstractMultiplexed mRNA profiling in the spatial context provides important new information enabling basic research and clinical applications. Unfortunately, most existing spatial transcriptomics methods are limited due to either low multiplexing or assay complexity. Here, we introduce a new spatialomics technology, termed Multi Omic Single-scan Assay with Integrated Combinatorial Analysis (MOSAICA), that integrates in situ labeling of mRNA and protein markers in cells or tissues with combinatorial fluorescence spectral and lifetime encoded probes, spectral and time-resolved fluorescence imaging, and machine learning-based target decoding. This technology is the first application combining the biophotonic techniques, Spectral and Fluorescence Lifetime Imaging and Microscopy (FLIM), to the field of spatial transcriptomics. By integrating the time dimension with conventional spectrum-based measurements, MOSAICA enables direct and highly-multiplexed in situ spatial biomarker profiling in a single round of staining and imaging while providing error correction removal of background autofluorescence. We demonstrate mRNA encoding using combinatorial spectral and lifetime labeling and target decoding and quantification using a phasor-based image segmentation and machine learning clustering technique. We then showcase MOSAICA’s multiplexing scalability in detecting 10-plex targets in fixed colorectal cancer cells using combinatorial labeling of only five fluorophores with facile error-correction and removal of autofluorescent moieties. MOSAICA’s analysis is strongly correlated with sequencing data (Pearson’s r = 0.9) and was further benchmarked using RNAscope™and LGC Stellaris™. We further apply MOSAICA for multiplexed analysis of clinical melanoma Formalin-Fixed Paraffin-Embedded (FFPE) tissues that have a high degree of tissue scattering and intrinsic autofluorescence, demonstrating the robustness of the approach. We then demonstrate simultaneous co-detection of protein and mRNA in colorectal cancer cells. MOSAICA represents a simple, versatile, and scalable tool for targeted spatial transcriptomics analysis that can find broad utility in constructing human cell atlases, elucidating biological and disease processes in the spatial context, and serving as companion diagnostics for stratified patient care.
Single-cell Chromatin Accessibility and Lipid Profiling Reveals a Metabolic Shift in Adipocytes Induced by Bariatric Surgery
Authors: Harlan Blaine , Park Hui Gyu , Spektor Roman , Cummings Bethany , Thomas Brenna J. , Soloway Paul D. 
Published: June 2021

AbstractObesity promotes type 2 diabetes and cardiometabolic pathologies. Vertical sleeve gastrectomy (VSG) is used to treat obesity resulting in long-term weight loss and health improvements that precede weight loss; however, the mechanisms underlying the immediate benefits remain incompletely understood. Because adipose plays a crucial role in energy homeostasis and utilization, we hypothesized that VSG exerts its influences, in part, by modulating adipose functional states. We applied single-cell ATAC sequencing and lipid profiling to inguinal and epididymal adipose depots from mice that received sham surgery or VSG. We observed depot-specific cellular composition and chromatin accessibility patterns that were altered by VSG. Specifically, accessibility at Scd1, a fatty acid desaturase, was substantially reduced after VSG in mature adipocytes of inguinal but not epididymal depots. This was accompanied by reduced accumulation of SCD1-produced unsaturated fatty acids. Given these findings and reports that reductions in Scd1 attenuate obesity and insulin resistance and that unsaturated fatty acids stimulate glucose uptake, storage, and oxidation, our results suggest VSG exerts its beneficial effects through modifications of fatty acid profiles mediated by Scd1.
Regulatory approved monoclonal antibodies contain framework mutations predicted from human antibody repertoires
Authors: Petersen Brian M. , Ulmer Sophia A. , Rhodes Emily R. , Gutierrez Gonzalez Matias F , Dekosky Brandon J , Sprenger Kayla G , Whitehead Timothy A. 
Published: June 2021

AbstractMonoclonal antibodies (mAbs) are an important class of therapeutics used to treat cancer, inflammation, and infectious diseases. Identifying highly developable mAb sequences in silico could greatly reduce the time and cost required for therapeutic mAb development. Here, we present position-specific scoring matrices (PSSMs) for antibody framework mutations developed using natural human antibody repertoire sequences. Our analysis shows that natural human antibody repertoire-based PSSMs are consistent across individuals and demonstrate high correlations between related germlines. We show that mutations in existing therapeutic antibodies can be accurately predicted solely from natural human antibody sequence data. mAbs developed using humanized mice had more human-like FR mutations than mAbs originally developed by hybridoma technology. A quantitative assessment of entire framework regions of therapeutic antibodies revealed that there may be potential for improving the properties of existing therapeutic antibodies by incorporating additional mutations of high frequency in natural human antibody repertoires. In addition, high frequency mutations in natural human antibody repertoires were predicted in silico to reduce immunogenicity in therapeutic mAbs due to the removal of T cell epitopes. Several therapeutic mAbs were identified to have common, universally high-scoring framework mutations, and molecular dynamics simulations revealed the mechanistic basis for the evolutionary selection of these mutations. Our results suggest that natural human antibody repertoires may be useful as predictive tools to guide mAb development in the future.
Witnessing the structural evolution of an RNA enzyme
Authors: Portillo Xavier , Huang Yu-Ting , Breaker Ronald R , Horning David P , Joyce Gerald F 
Published: June 2021

AbstractAn RNA polymerase ribozyme that has been the subject of extensive directed evolution efforts has attained the ability to synthesize complex functional RNAs, including a full-length copy of its own evolutionary ancestor. During the course of evolution, the catalytic core of the ribozyme has undergone a major structural rearrangement, resulting in a novel tertiary structural element that lies in close proximity to the active site. Through a combination of site-directed mutagenesis, structural probing, and deep sequencing analysis, the trajectory of evolution was seen to involve the progressive stabilization of the new structure, which provides the basis for improved catalytic activity of the ribozyme. Multiple paths to the new structure were explored by the evolving population, converging upon a common solution. Tertiary structural remodeling of RNA is known to occur in nature, as evidenced by the phylogenetic analysis of extant organisms, but this type of structural innovation had not previously been observed in an experimental setting. Despite prior speculation that the catalytic core of the ribozyme had become trapped in a narrow local fitness optimum, the evolving population has broken through to a new fitness locale, suggesting that further improvement of polymerase activity may be achievable.
SNAREs and Synaptotagmin cooperatively determine the Ca2+ sensitivity of neurotransmitter release in fixed stoichiometry modules
Authors: McDargh Zachary A. , O’Shaughnessy Ben 
Published: June 2021

AbstractNeurotransmitter release is accomplished by a multi-component machinery including the membrane-fusing SNARE proteins and Ca2+-sensing Synaptotagmin molecules. However, the Ca2+ sensitivity of release was found to increase or decrease with more or fewer SNARE complexes at the release site, respectively, while the cooperativity is unaffected (Acuna et al., 2014; Arancillo et al., 2013), suggesting that there is no simple division of labor between these two components. To examine the mechanisms underlying these findings, we developed molecular dynamics simulations of the neurotransmitter release machinery, with variable numbers of Synaptotagmin molecules and assembled SNARE complexes at the release site. Ca2+ uncaging simulations showed that increasing the number of SNARE complexes at fixed stoichiometric ratio of Synaptotagmin to SNAREs increased the Ca2+ sensitivity without affecting the cooperativity. The physiological cooperativity of ~4-5 was reproduced with 2-3 Synaptotagmin molecules per SNARE complex, suggesting that Synaptotagmin and SNAREs cooperate in fixed stoichiometry modules. In simulations of action potential-evoked release, increased numbers of Synaptotagmin-SNARE modules increased release probability, consistent with experiment. Our simulations suggest that the final membrane fusion step is driven by SNARE complex-mediated entropic forces, and by vesicle-tethering forces mediated by the long Synaptotagmin linker domains. In consequence, release rates are increased when more SNARE complexes and Synaptotagmin monomers are present at the fusion site.
Profiling Myxococcus xanthus swarming phenotypes through mutation and environmental variation
Authors: Ritchie Linnea J. , Curtis Erin M. , Murphy Kimberly A. , Welch Roy D. 
Published: June 2021

AbstractMyxococcus xanthus is a bacterium that lives on surfaces as a predatory biofilm called a swarm.As a growing swarm feeds on prey and expands, it displays dynamic multicellular patterns such as traveling waves called ripples and branching protrusions called flares. The rate at which a swarm expands across a surface, and the emergence of the coexisting patterns, are all controlled through coordinated cell movement. M. xanthus cells move using two motility systems known as Adventurous (A) and Social (S). Both are involved in swarm expansion and pattern formation. In this study, we describe a set of M. xanthus swarming genotype-to-phenotype associations that include both genetic and environmental perturbations. We identified new features of the swarming phenotype; recorded and measured swarm expansion using time-lapse microscopy; and compared the impact of mutation on different surfaces. These observations and analyses have increased our ability to discriminate between swarming phenotypes and provided context that allowed us to identify some phenotypes as improbable ‘outliers’ within the M. xanthus swarming phenome.ImportanceMyxococcus xanthus grows on surfaces as a predatory biofilm called a swarm. A feeding swarm expands by moving over and consuming prey bacteria. In the laboratory, a swarm is created by spotting cell suspension onto nutrient agar in lieu of prey. The cells quickly settle on the surface and the new swarm then expands radially. An assay that measures the expansion rate of a swarm of mutant cells is the first, and sometimes only, measurement used to decide whether a particular mutation impacts swarm motility. We have broadened the scope of this assay by increasing the accuracy of measurements and reintroducing prey, resulting in new identifiable and quantifiable features that can be used to improve genotype-to-phenotype associations.