bluuebunny/crossref_metadata_2025 huggingface dataset:
DyScore: A Boosting Scoring Method with Dynamic Properties for Identifying True Binders and Non-binders in Structure-based Drug Discovery
Authors: Li Yanjun , Zhou Daohong , Zheng Guangrong , Li Xiaolin , Wu Dapeng , Yuan Yaxia
Published: October 2021

The accurate prediction of protein-ligand binding affinity is critical for the success of computer-aided drug discovery. However, the accuracy of current scoring functions is usually unsatisfactory due to their rough approximation or sometimes even omittance of many factors involved in protein-ligand binding. For instance, the intrinsic dynamic of the protein-ligand binding state is usually disregarded in scoring function because these rapid binding affinity prediction approaches are only based on a representative complex structure of the protein and ligand in the binding state. That is, the dynamic protein-ligand binding complex ensembles are simplified as a static snapshot in calculation. In this study, two novel features were proposed for characterizing the dynamic properties of protein-ligand binding based on the static structure of the complex, which is expected to be a valuable complement to the current scoring functions. The two features demonstrate the geometry-shape matching between a protein and a ligand as well as the dynamic stability of protein-ligand binding. We further combined these two novel features with several classical scoring functions to develop a binary classification model called DyScore that uses the Extreme Gradient Boosting algorithm to classify compound poses as binders or non-binders. We have found that DyScore achieves state-of-the-art performance in distinguishing active and decoy ligands on both enhanced DUD dataset and external test sets with both proposed novel features showing significant contributions to the improved performance. Especially, DyScore exhibits superior performance on early recognition, a crucial requirement for success in virtual screening andde novodrug design. The standalone version of DyScore and Dyscore-MF are freely available to all at:https://github.com/YanjunLi-CS/dyscore

Key Points

Two novel binding features were proposed for characterizing the dynamic properties of protein-ligand binding only based on a static snapshot of complex.

Based on the XGBoost machine learning method, the DyScore recognition model was proposed to accurately classify compound binding poses as binders or non-binders. DyScore consistently outperforms all the state-of-the-art published models on three different metrics by a large margin.

DyScore showed superior performance in early recognition with an average of 73.3% success rate for the top three ranked compounds for each protein target.

The standalone version of DyScore and DyScore-MF are freely available to all at:https://github.com/YanjunLi-CS/dyscore

TOC
PepSeA: Peptide Sequence Alignment and Visualization Tools to Enable Lead Optimization
Authors: Baylon Javier L. , Ursu Oleg , Muzdalo Anja , Wassermann Anne Mai , Adams Gregory L , Spale Martin , Mejzlik Petr , Gromek Anna , Pisarenko Viktor , Hancharyk Dzianis , Jenkins Esteban , Bednar David , Chang Charlie , Clarova Kamila , Glick Meir , Bitton Danny A.
Published: October 2021

Therapeutic peptides offer potential advantages over small molecules in terms of selectivity, affinity, and their ability to target “undruggable” proteins that are associated with a wide range of pathologies. Despite their importance, there are currently no adequate molecular design capabilities that inform medicinal chemistry decisions on peptide programs. More specifically, SAR (Structure-Activity Relationship) analysis and visualization of linear, cyclic, and cross-linked peptides containing non-natural motifs, which are widely used in drug discovery. To bridge this gap, we developed PepSeA (Peptide Sequence Alignment and Visualization), an open-source, freely available package of sequence-based tools (https://github.com/Merck/PepSeA). PepSeA enables multi-sequence alignment of non-natural amino acids and enhanced HELM (Hierarchical Editing Language for Macromolecules) visualization. Via stepwise SAR analysis of a ChEMBL peptide dataset, we demonstrate PepSeA’s power to accelerate decision making in lead optimization campaigns in pharmaceutical settings. PepSeA represents an initial attempt to expand cheminformatics capabilities for therapeutic peptides and to enable rapid and more efficient design–make–test cycles.
In vivo MR spectroscopy reflects synapse density in a Huntington’s disease mouse model
Authors: Zarate Nicole , Gundry Katherine , Yu Dahyun , Casby Jordan , Eberly Lynn E , Öz Gülin , Gomez-Pastor Rocio
Published: October 2021

Striatal medium spiny neurons are highly susceptible in Huntington’s disease (HD), resulting in progressive synaptic perturbations that lead to neuronal dysfunction and death. Non-invasive imaging techniques, such as proton magnetic resonance spectroscopy (1H-MRS), are used in HD mouse models and patients with HD to monitor neurochemical changes associated with neuronal health. However, the association between brain neurochemical alterations and synaptic dysregulation is unknown, limiting our ability to monitor potential treatments that may affect synapse function. We conducted in vivo longitudinal 1H-MRS in the striatum followed by ex-vivo analyses of excitatory synapse density of two synaptic circuits disrupted in HD, thalamo-striatal (T-S) and cortico-striatal (C-S) pathways, to assess the relationship between neurochemical alterations and changes in synapse density. We used the zQ175(Tg/0) HD mouse model as well as zQ175 mice lacking one allele of CK2α’(zQ175(Tg/0):CK2α’(+/−)), a kinase previously shown to regulate synapse function in HD. Longitudinal analyses of excitatory synapse density showed early and sustained reduction in T-S synapses in zQ175 mice, preceding C-S synapse depletion, which was rescued in zQ175:CK2α’(+/−). Changes in T-S and C-S synapses were accompanied by progressive alterations in numerous neurochemicals between WT and HD mice. Linear regression analyses showed C-S synapse number positively correlated with 1H-MRS-measured levels of GABA while T-S synapse number positively correlated with levels of alanine, phosphoethanolamine and lactate, and negatively correlated with total creatine levels.

These associations suggest that these neurochemical concentrations measured by 1H-MRS may facilitate monitoring circuit-specific synaptic dysfunction in the zQ175 mouse model and in other HD pre-clinical studies.

Significance Statement

The pathogenic events of many neurodegenerative diseases including HD are triggered by reductions in number of synapses. Therefore, in vivo measures that reflect synapse number represent a powerful tool to monitor synaptic changes in numerous brain disorders. In this study, we showed that non-invasive in vivo1H-MRS reflects excitatory synapse number in the striatum of the zQ175 mouse model of HD. The combination of longitudinal 1H-MRS and immunofluorescence synapse detection revealed that distinct neurochemical levels significantly correlated with different striatal glutamatergic synaptic input pathways, suggesting that 1H-MRS could distinguish circuit-dependent synapse changes in HD. These results provide potential neurochemical biomarkers to monitor synaptic changes in future pre-clinical trials with HD models.
Inferring Deep Brain Stimulation Induced Short-term Synaptic Plasticity Using Novel Dual Optimization Algorithm
Authors: Ghadimi Alireza , Steiner Leon Amadeus , Popovic Milos R. , Milosevic Luka , Lankarany Milad
Published: October 2021

Experimental evidence in both human and animal studies demonstrated that deep brain stimulation (DBS) can induce short-term synaptic plasticity (STP) in the stimulated nucleus. Given that DBS-induced STP may be connected to the therapeutic effects of DBS, we sought to develop an appropriate computational predictive model that infers the dynamics of STP in response to DBS at different frequencies. Existing methods for estimating STP – either model-based or model-free approaches – require access to pre-synaptic spiking activity. However, in the context of DBS, extracellular stimulation (e.g. DBS) can be used to elicit presynaptic activations directly. We present a model-based approach that integrates multiple individual frequencies of DBS-like electrical stimulation as pre-synaptic spikes and infers parameters of the Tsodyks-Markram (TM) model from post-synaptic currents of the stimulated nucleus. By distinguishing between the steady-state and transient responses of the TM model, we develop a novel dual optimization algorithm that infers the model parameters in two steps. First, the TM model parameters are calculated by integrating multiple frequencies of stimulation to estimate the steady state response of post-synaptic current through a closed-form analytical solution. The results of this step are utilized as the initial values for the second step in which a non-derivative optimization algorithm is used to track the transient response of the post-synaptic potential across different individual frequencies of stimulation. Moreover, we apply our algorithm to empirical data recorded from acute rodent brain slices of the subthalamic nucleus (STN) during DBS-like stimulation to infer dynamics of STP for inhibitory synaptic inputs.
Warming in the land of the midnight sun: breeding birds may suffer greater heat stress at high- vs low-Arctic sites
Authors: O’Connor Ryan S. , Pogam Audrey Le , Young Kevin G. , Love Oliver P. , Cox Christopher J. , Roy Gabrielle , Robitaille Francis , Elliott Kyle H. , Hargreaves Anna L. , Choy Emily S. , Gilchrist H. Grant , Berteaux Dominique , Tam Andrew , Vézina François
Published: October 2021

Rising global temperatures are expected to increase reproductive costs for wildlife as greater thermoregulatory demands interfere with essential breeding activities such as parental care. However, predicting the temperature threshold where reproductive performance is negatively impacted remains a significant hurdle. Using a novel thermoregulatory polygon approach, we predicted the threshold temperature at which an Arctic songbird–the snow bunting (Plectrophenax nivalis)–would need to reduce activity and perform below the 4-times basal metabolic rate (BMR) required to sustain nestling provisioning to avoid overheating. We then compared this threshold to operative temperatures recorded at high (82°N) and low (64°N) Arctic sites to estimate how heat constraints translate into site-specific impacts on sustained activity level. We predict buntings would become behaviourally constrained at operative temperatures above 11.7°C, whereupon they must reduce provisioning rates to maintain thermal balance. Low Arctic sites had larger fluctuations in solar radiation, producing consistent daily periods when operative temperatures exceeded 11.7°C. However, high-latitude birds faced entire, consecutive days where parents would not be able to sustain required provisioning rates. These data indicate that Arctic warming is likely already disrupting the breeding performance of cold-specialist birds, but also suggests counterintuitive and severe negative impacts of warming at high-latitude breeding locations.
A simple strategy for sample annotation error detection in cytometry datasets
Authors: Smithmyer Megan E , Wiedeman Alice E , Skibinski David A.G. , Savage Adam K. , Acosta-Vega Carolina , Scheiding Sheila , Gersuk Vivian H. , Long S. Alice , Buckner Jane H. , Speake Cate
Published: October 2021

Mislabeling samples or data with the wrong participant information can impact study integrity and lead investigators to draw inaccurate conclusions. Quality control to prevent these types of errors is commonly embedded into the analysis of genomic datasets, but a similar identification strategy is not standard for cytometric data. Here, we present a method for detecting sample identification errors in cytometric data using expression of HLA class I alleles. We measured HLA-A*02 and HLA-B*07 expression in 3 longitudinal samples from 41 participants using a 33-marker CyTOF panel designed to identify major immune cell types. 3/123 samples (2.4%) showed HLA allele expression that did not match their longitudinal pairs. Furthermore, these same three samples’ cytometric signature did not match qPCR HLA class I allele data, suggesting that they were accurately identified as mismatches. We conclude that this technique is useful for detecting sample labeling errors in cytometric analyses of longitudinal data. This technique could also be used in conjunction with another method, like GWAS or PCR, to detect errors in cross-sectional data. We suggest widespread adoption of this or similar techniques will improve the quality of clinical studies that utilize cytometry.
LungCancer3D: A Comprehensive Database for Integrating Lung Cancer Chromatin Architecture with Other Multi-omics
Authors: Wu Xinyu , Jiang Anlan , Wang Jixin , Song Shiyang , Xu Yaping , Tang Qian , Zhang Shirong , Xia Bing , Chen Xueqin , Ma Shenglin , Liu Jian
Published: October 2021

With the breakthrough of chromatin conformation capture technologies in recent years, the importance of three-dimensional (3D) genome structure in gene expression, cell function regulation, disease occurrence, and development has been gradually recognized. To provide a comprehensive visualization of chromatin architecture and other multi-omics data for lung cancer research, we have constructed a comprehensive database, LungCancer3D (http://www.lungcancer3d.net). This web-based tool focuses on displaying human lung cancer-related HiC data along with a variety of other publicly available data, such as RNA-seq, scRNA-seq, ATAC-seq, ChIP-seq, DNA methylation, DNA mutation, and copy number variations. Researchers can visualize these diverse multi-omics data directly through the genome browser and discover how the genes expression is regulated at diverse levels. For example, we have demonstrated that the high expression level of C-MYC in lung cancer may be caused by the distant enhancer introduced by the de novo chromatin loops in lung cancer cells to bind the C-MYC promoter. The integrated multi-omics analyses through the LungCancer3D website can reveal the mechanisms underlying lung cancer development and provide potential targets for lung cancer therapy.
Three water restriction schedules used in rodent behavioral tasks transiently impair growth and differentially evoke a stress hormone response without causing dehydration
Authors: Vasilev Dmitrii , Havel Daniel , Liebscher Simone , Slesiona-Kuenzel Silvia , Logothetis Nikos K. , Schenke-Layland Katja , Totah Nelson K.
Published: October 2021

Water restriction is commonly used to motivate rodents to perform behavioral tasks; however, its on hydration and stress hormone levels are unknown. Here, we report daily body weight and bi-weekly packed red blood cell volume and corticosterone in adult male rats across 80 days for three commonly used water restriction schedules. We also assessed renal adaptation to water restriction using post-mortem histological evaluation of renal medulla. A control group received ad libitum water. After one week of water restriction, rats on all restriction schedules resumed similar levels of growth relative to the control group. Nominal hydration was observed, and water restriction did not drive renal adaptation. An intermittent restriction schedule was associated with an increase in corticosterone relative to the control group. Our results suggest that the water restriction schedules used here will maintain welfare in rats. However, intermittent restriction evokes a stress response which could affect behavioral and neurobiological results. Our results also suggest that stable motivation in behavioral tasks may only be achieved after one week of restriction.
Seizure Onset Zone Identification Using Phase-Amplitude Coupling and Multiple Machine Learning Approaches for Interictal Electrocorticogram
Authors: Miao Yao , Iimura Yasushi , Sugano Hidenori , Fukumori Kosuke , Tanaka Toshihisa
Published: October 2021

Automatic seizure onset zone (SOZ) localization using interictal electrocorticogram (ECoG) improves the diagnosis and treatment of patients with medically refractory epilepsy. This study aimed to investigate the characteristics of phase-amplitude coupling (PAC) extracted from interictal ECoG and the feasibility of PAC served as a promising biomarker for SOZ identification. We employed the mean vector length modulation index approach on the 20-s ECoG window to calculate PAC features between low-frequency rhythms (0.5–24 Hz) and high frequency oscillations (HFOs) (80–560 Hz). We used statistical measures to test the significant difference in PAC between SOZ and non-seizure onset zone (NSOZ). To overcome the drawback of handcraft feature engineering, we established novel machine learning models to automatically learn the characteristics of PAC features obtained and classify them to identify SOZ. Besides, to conquer the imbalance of datasets, we introduced novel feature-wise/class-wise re-weighting strategies in conjunction with classifiers. In addition, we proposed the time-series nest cross-validation to provide more accurate and unbiased evaluations for this model. Seven patients with focal cortical dysplasia were included in this study. The experiment results not only illustrate that the significant coupling at band pairs of slow waves and HFOs exists in the SOZ when compared with the NSOZ but also indicate the effectiveness of PAC features and the proposed models with better classification performance.
Loss of p16INK4a in neuroblastoma cells induces shift to an immature state with mesenchymal characteristics and increases sensitivity to EGFR inhibitors
Authors: Schubert Nil A. , van Hooff Sander R. , Schild Linda , Ober Kimberley , Hortensius Marjolein , van den Handel Kim , Essing Anke H.W. , Koopmans Bianca , Boeije Manon , Proost Natalie , van de Ven Marieke , Jansky Selina , Stainczyk Sabine A. , Toprak Umut H. , Westermann Frank , Eising Selma , Molenaar Jan J. , van den Boogaard Marlinde L.
Published: October 2021

Homozygous inactivation of the CDKN2A locus is one of the most common genomic aberrations in human cancer. The locus codes for two unrelated and distinctly regulated proteins: p14ARF and p16INK4a, which inhibit MDM2 and CDK4/6, respectively. Loss of CDKN2A is also a recurrent event in relapsed neuroblastoma, a childhood tumour that arises from neural crest cells. To examine the consequences of the loss of the two distinct gene transcripts in neuroblastoma, we used the CRISPR-Cas9 system to knockout p14, p16 and p14+p16 in SY5Y cells. RNA sequencing of the transcriptome revealed a striking shift towards an immature Schwann cell precursor-like phenotype with mesenchymal characteristics, specifically in the p16 and p14+p16 knockouts. High-throughput drug screening of p16 and p14+p16 knockout clones identified a large increase in sensitivity to EGFR inhibitors. On protein level, we were able to confirm that EGFR pathway activation is higher in p14+p16 knockout cells and that treatment with the EGFR inhibitor afatinib resulted in higher levels of apoptosis. Afatinib also reduced tumour growth in vivo in xenografts transplanted with p14+p16 knockout SY5Y cells. Overall, our study suggests that CDKN2A deletion in neuroblastoma relates to a phenotypic shift towards a more progenitor like state and increases sensitivity to EGFR inhibitors.
An iTSC-derived placental model of SARS-CoV-2 infection reveals ACE2-dependent susceptibility in syncytiotrophoblasts
Authors: Chen J , Neil JA , Tan JP , Rudraraju R , Mohenska M , Sun YBY , Sun G , Zhou Y , Li Y , Drew D , Pymm P , Tham WH , Rossello FJ , Nie G , Liu X , Subbarao K , Polo JM
Published: October 2021

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection causing coronavirus disease 2019 (COVID-19) has caused a global health crisis. The primary site of infection is in the respiratory tract but the virus has been associated with a variety of complications involving the gastrointestinal and cardiovascular systems. Since the virus affects a variety of tissue types, there has been interest in understanding SARS-CoV-2 infection in early development and the placenta. ACE2 and TMPRSS2, two genes that are critical for SARS-CoV-2 virus entry are expressed in placenta-specific cell types including extravillous trophoblasts (EVTs) and especially, syncytiotrophoblasts (STs). The potential of SARS-CoV-2 to infect these placental cells and its effect on placental development and function is still unclear. Furthermore, it is crucial to understand the possible mechanism of vertical transmission of SARS-CoV-2 through the placenta. Here, we developed an in vitro model of SARS-CoV-2 infection of placental cell types using induced trophoblast stem cells (iTSCs). This model allowed us to show that STs but not EVTs are infected. Importantly, infected STs lack the expression of key differentiation genes, lack typically observed differentiated morphology and produce significantly lower human chorionic gonadotropin (HCG) compared to non-infected controls. We also show that an anti-ACE2 antibody prevents SARS-CoV-2 infection and restores normal ST differentiation and function. We highlight the establishment of a platform to study SARS-CoV-2 infection in early placental cell types, which will facilitate investigation of antiviral therapy to protect the placenta during early pregnancy and development.
Tree-based Correlation Screen and Visualization for Exploring Phenotype-Cell Type Association in Multiple Sample Single-Cell RNA-Sequencing Experiments
Authors: Zhang Boyang , Ji Zhicheng , Ji Hongkai
Published: October 2021

Single-cell RNA-seq experiments with multiple samples are increasingly used to discover cell types and their molecular features that may influence samples’ phenotype (e.g. disease). However, analyzing and visualizing the complex cell type-phenotype association remains nontrivial. TreeCorTreat is an open source R package that tackles this problem by using a tree-based correlation screen to analyze and visualize the association between phenotype and transcriptomic features and cell types at multiple cell type resolution levels. With TreeCorTreat, one can conveniently explore and compare different feature types, phenotypic traits, analysis protocols and datasets, and evaluate the impacts of potential confounders.
In Vivo MRI of Endogenous Remyelination in a Nonhuman Primate Model of Multiple Sclerosis
Authors: Lee Nathanael J. , Sati Pascal , Ha Seung-Kwon , Luciano Nicholas J. , Roy Snehashis , Ineichen Benjamin , Leibovitch Emily C. , Yen Cecil C. , Pham Dzung L. , Silva Afonso C. , Johnson Mac , Jacobson Steven , Reich Daniel S.
Published: October 2021

Remyelination is crucial for recovery from inflammatory demyelination in multiple sclerosis (MS). Investigating remyelination in vivo using magnetic resonance imaging (MRI) is difficult in MS, where collecting serial short-interval scans is challenging. Using experimental autoimmune encephalomyelitis (EAE) in common marmosets, a model of MS that recapitulates focal cerebral MS lesions, we investigated whether remyelination can be detected and characterized noninvasively. In 6 animals followed with multisequence 7-tesla MRI, 36 focal lesions, classified as demyelinated or remyelinated based on signal intensity on proton density-weighted images, were subsequently assessed with histopathology. Remyelination occurred in 5 of 6 marmosets and 51% of lesions. Radiological-pathological comparison showed high sensitivity (88%) and specificity (90%) for detecting remyelination by in vivo MRI. This study demonstrates the prevalence of spontaneous remyelination in marmoset EAE and the ability of in vivo MRI to detect it, with implications for preclinical testing of pro-remyelinating agents and translation to clinical practice.
H3K9me1/2 methylation limits the lifespan ofC. elegans
Authors: Huang Meng , Hong Minjie , Zhu Chengming , Chen Di , Chen Xiangyang , Guang Shouhong , Feng Xuezhu
Published: October 2021

Histone methylation plays crucial roles in the development, gene regulation and maintenance of stem cell pluripotency in mammals. Recent work shows that histone methylation is associated with aging, yet the underlying mechanism remains unclear. In this work, we identified a class of histone 3 lysine 9 mono-/dimethyltransferase genes (met-2, set-6, set-19, set-20, set-21, set-32andset-33), mutations in which induce synergistic lifespan extension in the long-lived DAF-2 (IGF-1 receptor) mutant inC. elegans. These histone methyltransferase plusdaf-2double mutants not only exhibited an average lifespan nearly three times that of wild-type animals and a maximal lifespan of approximately 100 days, but also significantly increased resistance to oxidative and heat stress. Synergistic lifespan extension depends on the transcription factor DAF-16 (FOXO). mRNA-seq experiments revealed that the mRNA levels of class I DAF-16 target genes, which are activated by DAF-16, were further elevated in the double mutants. Among these genes,F35E8.7, nhr-62, sod-3, asm-2andY39G8B.7are required for the lifespan extension of thedaf-2;set-21double mutant. In addition, treatingdaf-2animals with the H3K9me1/2 methyltransferase G9a inhibitor also extends lifespan and increases stress resistance. Therefore, investigation of DAF-2 and H3K9me1/2 methyltransferase deficiency-mediated synergistic longevity will contribute to a better understanding of the molecular mechanisms of aging and therapeutic applications.
MPDB: a unified multi-domain protein structure database integrating structural analogue detection
Authors: Peng Chun-Xiang , Zhou Xiao-Gen , Xia Yu-Hao , Zhang Yang , Zhang Gui-Jun
Published: October 2021

With the development of protein structure prediction methods and biological experimental determination techniques, the structure of single-domain proteins can be relatively easier to be modeled or experimentally solved. However, more than 80% of eukaryotic proteins and 67% of prokaryotic proteins contain multiple domains. Constructing a unified multi-domain protein structure database will promote the research of multi-domain proteins, especially in the modeling of multi-domain protein structures. In this work, we develop a unified multi-domain protein structure database (MPDB). Based on MPDB, we also develop a server with two functional modules: (1) the culling module, which filters the whole MPDB according to input criteria; (2) the detection module, which identifies structural analogues of the full-chain according to the structural similarity between input domain models and the protein in MPDB. The module can discover the potential analogue structures, which will contribute to high-quality multi-domain protein structure modeling.
Natural killer-like B cells promote Th17 cell differentiation and exacerbate rheumatoid arthritis
Authors: Wang Ping , Song Jing , Bai Mingxin , Zheng Xi , Xie Yang , Tang Yundi , Li Xin , Fang Xiangyu , Jia Yuan , Ren Limin , Ye Hua , Su Yin , Wang Shuo , Li Zhanguo , Hu Fanlei
Published: October 2021

B cells are important participants in the pathogenesis of rheumatoid arthritis (RA). Besides classical B cells, novel B cell subsets are continually to be identified in recent years. Natural killer-like B (NKB) cells, a newly recognized B cell subset, are proved to be actively involved in the anti-infection immunity. However, their role in RA and the potential mechanism remain elusive. Here, we showed that NKB cells were expanded dramatically in collagen-induced arthritis (CIA) mice, demonstrating dynamic changes during the disease progression. These cells promoted CD4+ effector T cell proliferation and Th17 cell differentiation in vitro, while adoptive transfer of these cells exacerbated the arthritis severity of CIA mice. RNA Sequencing revealed that NKB cells displayed distinct differential gene expression profile under RA circumstance, potential perpetuating the disease progression. Moreover, the frequencies of NKB cells were significantly increased in RA patients, positively correlated with the clinical and immunological features. After effective therapy, these cells could be recovered to normal levels. Taken together, our results preliminarily revealed the pathogenic role of NKB cells in RA by promoting Th17 proinflammatory responses. Targeting these cells might provide potential therapeutic strategies for this persistent disease.
T Cell Receptor Non-Equilibrium Kinetics
Authors: Rollins Zachary A. , Faller R. , George Steven C.
Published: October 2021

An atomic-scale mechanism describing the role of mechanosensing in T Cell Receptor (TCR) recognition of peptides in the binding groove of the peptide-major histocompatibility complex (pMHC) may inform the design of novel TCRs for immunotherapies. Using steered molecular dynamic simulations, our study demonstrates that mutations to peptides in the binding groove of the pMHC – which are known to discretely alter the T cell response to an antigen – influence MHC conformation and thus the overall strength of the TCR-pMHC bond including duration and length under constant load. Moreover, physiochemical features of the TCR-pMHC dynamic bond strength, such as hydrogen bonds and Lennard-Jones contacts, correlate with the immunogenic response elicited by the specific peptide in the MHC groove. Thus, formation of transient TCR-pMHC bonds is a characteristic of immunogenic peptides and is mediated by stabilized interactions.x
The Ribb-osome: Ribbon boosts ribosomal protein gene expression to coordinate organ form and function
Authors: Loganathan Rajprasad , Levings Daniel C. , Kim Ji Hoon , Wells Michael B. , Chiu Hannah , Wu Yifan , Slattery Matthew , Andrew Deborah J.
Published: October 2021

Cell growth is well defined for the late (post-embryonic) stages of development, but evidence for early (embryonic) cell growth during post-mitotic morphogenesis is quite limited. Here, we identify early cell growth as a key characteristic of tubulogenesis in the Drosophila embryonic salivary gland (SG). A BTB/POZ domain nuclear factor, Ribbon (Rib), mediates this early cell growth. Rib binds the transcription start site of nearly every SG-expressed ribosomal protein gene (RPG) and is required for full expression of all RPGs tested. Rib binding to RPG promoters in vitro is weak and not sequence-specific, suggesting that specificity is achieved through co-factor interactions. Consistent with this hypothesis, we demonstrate Rib’s ability to physically interact with each of the three known contributors to RPG transcription. Surprisingly, Rib-dependent early cell growth in another tubular organ—the embryonic trachea—is not mediated by direct RPG transcription. These findings support a model of early cell growth sustained by transcriptional regulatory networks customized for organ form and function.
How far to build it before they come? Analyzing the use of the Field of Dreams hypothesis to bull kelp restoration
Authors: Arroyo-Esquivel Jorge , Baskett Marissa L. , McPherson Meredith , Hastings Alan
Published: October 2021

In restoration ecology, the Field of Dreams Hypothesis posits that restoration efforts that create a suitable environment could lead to eventual recovery of the remaining aspects of the ecosystem through natural processes. Natural processes following partial restoration has lead to ecosystem recovery in both terrestrial and aquatic systems. However, understanding the efficacy of a “field of dreams” approach requires comparison of different approaches to partial restoration in terms of spatial, temporal, and ecological scale to what would happen with more comprehensive restoration efforts. We explore the relative effect of partial restoration and ongoing recovery on restoration efficacy with a dynamical model based on temperate rocky reefs in Northern California. We analyze our model for both the ability and rate of bull kelp forest recovery under different restoration strategies. We compare the efficacy of a partial restoration approach with a more comprehensive restoration effort by exploring how kelp recovery likelihood and rate change with varying intensities of urchin removal and kelp outplanting over different time periods and spatial scales. We find that, for the case of bull kelp forests, setting more favorable initial conditions for kelp recovery through implementing both urchin harvesting and kelp outplanting at the start of the restoration project has a bigger impact on the kelp recovery rate than applying restoration efforts through a longer period of time. Therefore partial restoration efforts, in terms of spatial and temporal scale, can be significantly more effective when applied across multiple ecological scales in terms of both the capacity and rate of achieving the target outcomes.
Influenza virus replication in cardiomyocytes drives heart dysfunction and fibrosis
Authors: Kenney Adam D. , Aron Stephanie L. , Gilbert Clara , Kumar Naresh , Chen Peng , Eddy Adrian , Zhang Lizhi , Zani Ashley , Vargas-Maldonado Nahara , Speaks Samuel , Kawahara Jeffrey , Denz Parker J. , Dorn Lisa , Accornero Federica , Ma Jianjie , Zhu Hua , Rajaram Murugesan V.S. , Cai Chuanxi , Langlois Ryan A. , Yount Jacob S.
Published: October 2021

Cardiac dysfunction is a common extrapulmonary complication of severe influenza virus infection. Prevailing models propose that influenza-associated heart dysfunction is indirectly triggered by cytokine mediated cardiotoxicity downstream of the inflamed lung, rather than by direct infection of cardiac tissue. To test the etiology of cardiac dysfunction resulting from influenza virus infection, we generated a novel recombinant H1N1 influenza A virus that was attenuated in cardiomyocytes by incorporation of target sequences for miRNAs expressed specifically in that cell type (miR133b and miR206). Compared with control virus, mice infected with the miR-targeted virus had significantly reduced heart viral titers, confirming cardiac attenuation of viral replication. The miR-targeted virus, however, was fully replicative and inflammatory in lungs when compared to control virus, and induced similar systemic weight loss. The miR-targeted virus induced considerably lower levels of cardiac arrhythmia, fibrosis, and inflammation, compared with control virus, in mice lacking interferon induced transmembrane protein 3 (IFITM3), which serve as the only available model for severe influenza-associated cardiac pathology. We conclude that robust replication of virus in the heart is required for pathology even when lung inflammation is severe. Indeed, we show that human stem cell-derived cardiomyocytes are susceptible to influenza virus infection. This work establishes a fundamental new paradigm in which influenza virus damages the heart through direct infection of cardiomyocytes.
Selfing-outcrossing as a gradient, not a dichotomy: propensity for selfing varies within a population of hermaphroditic animals
Authors: Felmy Anja , Streiff Alena B. , Jokela Jukka
Published: October 2021

For mating-system evolution, individual-level variation is essential. In self-compatible hermaphrodites, individuals may vary in their lifetime propensity for selfing, which consists of individual and environmental components. According to the reproductive assurance hypothesis explaining partial selfing, a key environmental factor is mate availability, which fluctuates with population density.

We quantified individual variation in selfing propensity in a hermaphroditic snail by manipulating mate availability, recording mating behaviour, estimating selfing rates from progeny arrays, and measuring female lifetime fitness. We found substantial among-individual variation in selfing propensity, including pure outcrossers, pure selfers, and two types of plastic individuals. This variation only manifested in the laboratory; for the highly dense field population, data suggest full outcrossing. Meanwhile, experimental levels of mate availability (lowversusmoderate) neither significantly affected selfing propensities nor selfing rates.

Instead, selfing propensities had an individual, environment-independent component. Our results imply that selfing propensities are partially heritable and, when selected on, cause mean selfing rates to evolve. We propose that genetic variation in selfing propensities offers a reconciliation between the reproductive assurance hypothesis and its limited empirical support in animals: distributions of selfing propensities vary temporally and spatially, thus obscuring the relationship between population density and realised selfing rates.
Widespread redundancy in -omics profiles of cancer mutation states
Authors: Crawford Jake , Christensen Brock C. , Chikina Maria , Greene Casey S.
Published: October 2021

In studies of cellular function in cancer, researchers are increasingly able to choose from many -omics assays as functional readouts. Choosing the correct readout for a given study can be difficult, and which layer of cellular function is most suitable to capture the relevant signal may be unclear. In this study, we consider prediction of cancer mutation status (presence or absence) from functional -omics data as a representative problem. Since functional signatures of cancer mutation have been identified across many data types, this problem presents an opportunity to quantify and compare the ability of different -omics readouts to capture signals of dysregulation in cancer. The TCGA Pan-Cancer Atlas contains genetic alteration data including somatic mutations and copy number variants (CNVs), as well as several -omics data types. From TCGA, we focus on RNA sequencing, DNA methylation arrays, reverse phase protein arrays (RPPA), microRNA, and somatic mutational signatures as -omics readouts.

Across a collection of genes recurrently mutated in cancer, RNA sequencing tends to be the most effective predictor of mutation state. Surprisingly, we found that for many of the genes we considered, one or more other data types are approximately equally effective predictors. Performance was more variable between mutations than it was between data types for the same mutation, and there was often little difference between the top data types. We also found that combining data types into a single multi-omics model provided little or no improvement in predictive ability over the best individual data type. Based on our results, for the design of studies focused on the functional outcomes of cancer mutations, there are often multiple -omics types that can serve as effective readouts, although gene expression seems to be a reasonable default option.
Single-molecule imaging suggests compact and spliceosome dependent organization of long introns
Authors: Adivarahan Srivathsan , Kalhara Abeykoon A.M.S. , Zenklusen Daniel
Published: October 2021

Intron removal from pre-mRNAs is a critical step in the processing of RNA polymerase II transcripts, required to create translation competent mRNAs. In humans, introns account for large portions of the pre-mRNA, with intronic sequences representing about 95% of most pre-mRNA. Intron length varies considerably; introns can be as short as a few to hundreds of thousands of nucleotides in length. How nascent long intronic RNA is organized during transcription to facilitate the communication between 5’ and 3’ splice-sites required for spliceosome assembly however is still poorly understood. Here, we use single-molecule fluorescent RNA in situ hybridization (smFISH) to investigate the spatial organization of co- and post-transcriptional long introns in cells. Using two long introns within the POLA1 pre-mRNA as a model, we show that introns are packaged into compact assemblies, and when fully transcribed, are organized in a looped conformation with their ends in proximity. This organization is observed for nascent and nucleoplasmic pre-mRNAs and requires spliceosome assembly, as disruption of U2 snRNP binding results in introns with separated 5’ and 3’ ends. Moreover, interrogating the spatial organization of partially transcribed co-transcriptional POLA1 intron 35 indicates that the 5’ splice site is maintained proximal to the 3’ splice site during transcription, supporting a model that 5’ splice site tethering to the elongating polymerase might contribute to spliceosome assembly at long introns. Together, our study reveals details of intron and pre-mRNA organization in cells and provides a tool to investigate mechanisms of splicing for long introns.
Telescoping bimodal latent Dirichlet allocation to identify expression QTLs across tissues
Authors: Gewirtz Ariel DH , Townes F William , Engelhardt Barbara E
Published: October 2021

Expression quantitative trait loci (eQTLs), or single nucleotide polymorphisms (SNPs) that affect average gene expression levels, provide important insights into context-specific gene regulation. Classic eQTL analyses use one-to-one association tests, which test gene-variant pairs individually and ignore correlations induced by gene regulatory networks and linkage disequilibrium. Probabilistic topic models, such as latent Dirichlet allocation, estimate latent topics for a collection of count observations. Prior multi-modal frameworks that bridge genotype and expression data assume matched sample numbers between modalities. However, many data sets have a nested structure where one individual has several associated gene expression samples and a single germline genotype vector. Here, we build a telescoping bimodal latent Dirichlet allocation (TBLDA) framework to learn shared topics across gene expression and genotype data that allows multiple RNA-sequencing samples to correspond to a single individual’s genotype. By using raw count data, our model avoids possible adulteration via normalization procedures. Ancestral structure is captured in a genotype-specific latent space, effectively removing it from shared components. Using GTEx v8 expression data across ten tissues and genotype data, we show that the estimated topics capture meaningful and robust biological signal in both modalities, and identify associations within and across tissue types. We identify 53,358 cis-eQTLs and 1,173 trans-eQTLs by conducting eQTL mapping between the most informative features in each topic. Our TBLDA model is able to identify associations using raw sequencing count data when the samples in two separate data modalities are matched one-to-many, as is often the case in biological data.
Whole-genome sequence and methylome profiling of the almond (Prunus dulcis [Mill.] D.A.Webb) cultivar ‘Nonpareil’
Authors: D’Amico-Willman Katherine M. , Ouma Wilberforce Z. , Meulia Tea , Sideli Gina M. , Gradziel Thomas M. , Fresnedo-Ramírez Jonathan
Published: October 2021

Almond (Prunus dulcis [Mill.] D.A. Webb) is an economically important, specialty nut crop grown almost exclusively in the United States. Breeding and improvement efforts worldwide have led to the development of key, productive cultivars, including ‘Nonpareil,’ which is the most widely grown almond cultivar. Thus far, genomic resources for this species have been limited, and a whole-genome assembly for ‘Nonpareil’ is not currently available despite its economic importance and use in almond breeding worldwide. We generated a 615.89X coverage genome sequence using Illumina, PacBio, and optical mapping technologies. Gene prediction revealed 27,487 genes using MinION Oxford nanopore and Illumina RNA sequencing, and genome annotation found that 68% of predicted models are associated with at least one biological function. Further, epigenetic signatures of almond, namely DNA cytosine methylation, have been implicated in a variety of phenotypes including self-compatibility, bud dormancy, and development of non-infectious bud failure. In addition to the genome sequence and annotation, this report also provides the complete methylome of several key almond tissues, including leaf, flower, endocarp, mesocarp, fruit skin, and seed coat. Comparisons between methylation profiles in these tissues revealed differences in genome-wide weighted percent methylation and chromosome-level methylation enrichment. The raw sequencing data are available on NCBI Sequence Read Archive, and the complete genome sequence and annotation files are available on NCBI Genbank. All data can be used without restriction.
Jaagsiekte sheep retrovirus infection induces changes in microRNA expression in the ovine lung
Authors: Garcia Maria Contreras , Karagianni Anna E. , Vasoya Deepali , Jayaraman Siddharth , Lin Yao-Tang , Wood Ann R. , Dagleish Mark P. , Cousens Chris , Watson Mick , Grey Finn E. , Griffiths David J.
Published: October 2021

Ovine pulmonary adenocarcinoma (OPA) is an infectious neoplastic lung disease of sheep caused by jaagsiekte sheep retrovirus. OPA is an important veterinary problem and is also a valuable large animal model for human lung adenocarcinoma. JSRV infects type 2 alveolar epithelial cells in the lung and induces the growth of tumors, but little is known about the molecular events that lead to the activation of oncogenic pathways in infected cells. MicroRNAs (miRNAs) are small RNA molecules of approximately 22 nucleotides with important roles in regulating gene expression in eukaryotes and with well-established roles in cancer. Here we used small-RNA sequencing to investigate the changes in miRNA expression that occur in JSRV-infected ovine lung. After filtering out low abundance miRNAs, we identified expression of 405 miRNAs, 32 of which were differentially expressed in JSRV-infected lung compared to mock-inoculated control lung. Highly upregulated miRNAs included miR-182, miR-183, miR-96 and miR-135b, which have also been associated with oncogenic changes in human lung cancer. Network analysis of genes potentially targeted by the deregulated miRNAs identified their involvement in pathways known to be dysregulated in OPA. We found no evidence to support the existence of miRNAs encoded by JSRV. This study provides the first information on miRNA expression in OPA and identifies a number of targets for future studies into the role of these molecules in the pathogenesis of this unique veterinary model for human lung adenocarcinoma.

IMPORTANCE

Ovine pulmonary adenocarcinoma is a neoplastic lung disease of sheep caused by jaagsiekte sheep retrovirus (JSRV). OPA is a significant welfare and economic concern for sheep producers and is a valuable large animal model for human lung adenocarcinoma. MicroRNAs are small RNA molecules of approximately 22 nucleotides with important functions in regulating gene expression in eukaryotes and with well-established roles in cancer. In this study, we examined the changes in microRNA expression that occur in the lung in response to JSRV infection. We identified differential expression of a number of host-encoded microRNAs in infected tissue, including microRNAs with roles in human cancer. We found no evidence that JSRV encodes a microRNA. This study provides new insights on the cellular response to JSRV infection in the ovine lung, which will inform future studies into the pathogenesis of OPA in sheep and its use as a model for human lung adenocarcinoma.