bluuebunny/crossref_metadata_2025 huggingface dataset:
Utilizing tumor microenvironment microbial profiles and host gene expressions for survival subtyping in diverse types of cancers
Authors: Zhang Haohong , Cheng Mingyue , Ji Lei , Ning Kang
Published: May 2023

The tumor microbiome, a complex community of microbes found in tumors, has been found to be linked to cancer development, progression, and treatment outcome. However, it remains a bottleneck in distangling the relationship between the tumor microbiome and patient survival. In this study, we aimed to decode this complex relationship by developing ASD-cancer (autoencoder-based subtypes detector for cancer), a semi-supervised deep learning framework that could extract survival-related features from tumor microbiome and transcriptome data, and identify patients’ survival subtypes. By using samples from The Cancer Genome Atlas database, we identified two statistically distinct survival subtypes across all 20 types of cancer. Our framework provided improved risk-stratification (e.g., for Liver hepatocellular carcinoma, LIHC, log-rank test,P= 8.12E-6) compared to PCA (e.g., for LIHC, log-rank test,P= 0.87), predicted survival subtypes accurately, and identified biomarkers for survival subtypes. Additionally, we identified potential interactions between microbes and genes that may play roles in survival. For instance, in LIHC,Arcobacter,Methylocella, andIsoptericolamay regulate host survival through interactions with host genes enriched in the HIF-1 signaling pathway, indicating these species as potential therapy targets. Further experiments on validation dataset have also supported these patterns. Collectively, ASD-cancer has enabled accurate survival subtyping and biomarker discovery, which could facilitate personalized treatment for a broad-spectrum types of cancers.
Molecular Evolution and Interaction of 14-3-3 Proteins with H+-ATPases in Plant Abiotic Stresses
Authors: Jiang Wei , He Jing , Babla Mohammad , Wu Ting , Tong Tao , Riaz Adeel , Zeng Fanrong , Qin Yuan , Chen Guang , Deng Fenglin , Chen Zhong-Hua
Published: May 2023

Environmental stresses severely affect plant growth and crop productivity. Regulated by 14-3-3 proteins (14-3-3s), H+-ATPases (AHA) are important proton pumps that can induce diverse secondary transport via channels and co-transporters for the abiotic stress response of plants. Many studies demonstrated the roles of 14-3-3s and AHAs in coordinating the processes of plant growth, phytohormone signaling, and stress responses. However, the molecular evolution of 14-3-3s and AHAs has not been summarized in parallel with insights across multiple plant species. Here, we review the roles of 14-3-3s and AHAs in cell signaling to enhance plant responses to diverse environmental stresses. We analyzed the molecular evolution of key proteins that are associated with 14-3-3s and AHAs in plant growth and hormone signaling. The results revealed evolution, duplication, contraction, and expansion of 14-3-3s and AHAs in green plants. We also discussed the stress-specific expression of those14-3-3sandAHAsin a eudicot (Arabidopsis thaliana), a monocot (Hordeum vulgare) and a moss (Physcomitrium patens) under abiotic stresses. We propose that 14-3-3s and H+-ATPases respond to abiotic stresses through many important targets and signaling components of phytohormones, which could be promising to improve plant tolerance to single or multiple environmental stresses.

Highlight

We review the response and adaptation of 14-3-3s and AHAs to diverse environmental stimuli and we analyze the evolutionary features and molecular functions of 14-3-3s and AHAs.
Fibroblast-specific inflammasome activation predisposes to atrial fibrillation
Authors: Li Luge , Coarfa Cristian , Yuan Yue , Abu-Taha Issam , Wang Xiaolei , Song Jia , Koirala Amrit , Grimm Sandra L , Kamler Markus , Mullany Lisa K , Tallquist Michelle , Nattel Stanley , Dobrev Dobromir , Li Na
Published: May 2023

Background

Recent work has shown that the NLR-family-pyrin-domain-containing 3 (NLRP3) inflammasome is expressed in cardiomyocytes and when specifically activated causes atrial electrical remodeling and arrhythmogenicity. Whether the NLRP3-inflammasome system is functionally important in cardiac fibroblasts (FBs) remains controversial. In this study, we sought to uncover the potential contribution of FB NLRP3-inflammasome signaling to the control of cardiac function and arrhythmogenesis.

Methods

Digital-PCR was performed to determine the expression of NLRP3-pathway components in FBs isolated from human biopsy samples of AF and sinus rhythm patients. NLRP3-system protein expression was determined by immunoblotting in atria of canines with electrically maintained AF. Using the inducible, resident fibroblast (FB)-specific Tcf21-promoter-Cre system (Tcf21iCre as control), we established a FB-specific knockin (FB-KI) mouse model with FB-restricted expression of constitutively active NLRP3. Cardiac function and arrhythmia susceptibility in mice were assessed by echocardiography, programmed electrical stimulation, and optical mapping studies.

Results

NLRP3 and IL1B were upregulated in atrial FBs of patients with persistent AF. Protein levels of NLRP3, ASC, and pro-Interleukin-1β were increased in atrial FBs of a canine AF model. Compared with the control mice, FB-KI mice exhibited enlarged left atria (LA) and reduced LA contractility, a common determinant of AF. The FBs from FB-KI mice were more transdifferentiated, migratory, and proliferative compared to the FBs from control mice. FB-KI mice showed increased cardiac fibrosis, atrial gap junction remodeling, and reduced conduction velocity, along with increased AF susceptibility. These phenotypic changes were supported by single nuclei (sn)RNA-seq analysis, which revealed enhanced extracellular matrix remodeling, impaired communication among cardiomyocytes, and altered metabolic pathways across multiple cell types.

Conclusions

Our results show that the FB-restricted activation of the NLRP3-inflammasome system leads to fibrosis, atrial cardiomyopathy, and AF. Activation of NLRP3-inflammasome in resident FBs exhibits cell-autonomous function by increasing the activity of cardiac FBs, fibrosis, and connexin remodeling. This study establishes the NLRP3-inflammasome as a novel FB-signaling pathway contributing to AF pathogenesis.
How accurately can one predict drug binding modes using AlphaFold models?
Authors: Karelina Masha , Noh Joseph J. , Dror Ron O.
Published: May 2023

Computational prediction of protein structure has been pursued intensely for decades, motivated largely by the goal of using structural models for drug discovery. Recently developed machine learning methods such as AlphaFold 2 (AF2) have dramatically improved protein structure prediction, with reported accuracy approaching that of experimentally determined structures. To what extent do these advances translate to an ability to predict more accurately how drugs and drug candidates bind to their target proteins? Here we carefully examine the utility of AF2 protein structure models for predicting binding poses of drug-like molecules at the largest class of drug targets, the G protein–coupled receptors. We find that AF2 models capture binding pocket structures much more accurately than traditional homology models, with errors nearly as small as differences between structures of the same protein determined experimentally with different ligands bound. Strikingly, however, the accuracy of ligand binding poses predicted by computational docking to AF2 models is not significantly higher than when docking to traditional homology models and is much lower than when docking to structures determined experimentally without these ligands bound. These results have important implications for all those who might use predicted protein structures for drug discovery.
Elucidating disease-associated mechanisms triggered by pollutants via the epigenetic landscape using large-scale ChIP-Seq data
Authors: Zou Zhaonan , Yoshimura Yuka , Yamanishi Yoshihiro , Oki Shinya
Published: May 2023

Background

Despite well-documented effects on human health, the action modes of environmental pollutants are incompletely understood. Although transcriptome-based approaches are widely used to predict associations between chemicals and disorders, the molecular cues regulating pollutant-derived gene expression changes remain unclear. Therefore, we developed a data-mining approach, termed “DAR-ChIPEA,” to identify transcription factors (TFs) playing pivotal roles in the action modes of pollutants.

Methods

Large-scale public ChIP-Seq data (human,n= 15,155; mouse,n= 13,156) were used to predict TFs that are enriched in the pollutant-induced differentially accessible genomic regions (DARs) obtained from epigenome analyses (ATAC-Seq). The resultant pollutant–TF matrices were then cross-referenced to a repository of TF–disorder associations to account for pollutant modes of action. We subsequently evaluated the performance of the proposed method using a chemical perturbation dataset to compare the outputs of the DAR-ChIPEA and our previously developed differentially expressed gene (DEG)-ChIPEA methods using pollutant-induced DEGs as input. We then adopted the proposed method to predict disease-associated mechanisms triggered by pollutants.

Results

The proposed approach outperformed other methods using the area under the receiver operating characteristic curve score. The mean score of the proposed DAR-ChIPEA was significantly higher than that of our previously described DEG-ChIPEA (0.7287 vs. 0.7060;Q= 5.278 × 10−42; two-tailed Wilcoxon rank-sum test). The proposed approach further predicted TF-driven modes of action upon pollutant exposure, indicating that (1) TFs regulating Th1/2 cell homeostasis are integral in the pathophysiology of tributyltin-induced allergic disorders; (2) fine particulates (PM2.5) inhibit the binding of C/EBPs, Rela, and Spi1 to the genome, thereby perturbing normal blood cell differentiation and leading to immune dysfunction; and (3) lead induces fatty liver by disrupting the normal regulation of lipid metabolism by altering hepatic circadian rhythms.

Conclusion

Highlighting genome-wide chromatin change upon pollutant exposure to elucidate the epigenetic landscape of pollutant responses outperformed our previously described method that focuses on gene-adjacent domains only. Our approach has the potential to reveal pivotal TFs that mediate deleterious effects of pollutants, thereby facilitating the development of strategies to mitigate damage from environmental pollution.
MyeloDB: A multi-omics resource for Multiple Myeloma
Authors: Kumar Ambuj , Kumar Keerthana Vinod , Kundal Kavita , Sengupta Avik , R Kunjulakshmi , Kumar Rahul
Published: May 2023

Multiple myeloma (MM) is a common type of blood cancer affecting plasma cells originating from the lymphoid B-cell lineage. It accounts for about 10% of all haematological malignancies and can cause significant end-organ damage. The emergence of genomic technologies such as next-generation sequencing and gene expression analysis has opened new possibilities for early detection of multiple myeloma and identification of personalized treatment options. However, there remain significant challenges to overcome in MM research, including integrating multi-omics data, achieving a comprehensive understanding of the disease, and developing targeted therapies and biomarkers. The extensive data generated by these technologies presents another challenge for data analysis and interpretation. To bridge this gap, we have developed a multi-omics open-access database called MyeloDB. It includes gene expression profiling, high throughput CRISPR-Cas9 screens, drug sensitivity resources profile, and biomarkers. MyeloDB contains 47 expression profiles, 3 methylation profiles comprising a total of 5630 patient samples and 15 biomarkers which were reported in previous studies. In addition to this, MyeloDB can provide significant insight of gene mutations in MM on drug sensitivity. Furthermore, users can download the datasets and conduct their own analyses. Utilizing this database, we have identified five novel genes i.e.,CBFB, MANF, MBNL1, SEPHS2andUFM1as potential drug targets for MM. We hope MyeloDB will serve as a comprehensive platform for researchers and foster novel discoveries in MM. MyeloDB is freely accessible at: (https://project.iith.ac.in/cgntlab/myelodb/)
Dismantling cognitive-behavioural therapy for chronic insomnia in adults with or without comorbidities: a systematic review and component network meta-analysis
Authors: Furukawa Yuki , Sakata Masatsugu , Yamamoto Ryuichiro , Nakajima Shun , Kikuchi Shino , Inoue Mari , Ito Masami , Noma Hiroku , Takashina Hikari Nishimura , Funada Satoshi , Ostinelli Edoardo G. , Furukawa Toshi A. , Efthimiou Orestis , Perlis Michael
Published: May 2023

Background

Chronic insomnia disorder is highly prevalent, disabling and costly. Cognitive-behavioural therapy for insomnia (CBT-I) is recommended as the first-line treatment. CBT-I may contain various educational, cognitive and behavioural strategies delivered in a range of formats, but the effect of each component remains unclear.

Methods

We performed a systematic review and component network meta-analysis (cNMA) of CBT-I trials for chronic insomnia. We searched PubMed, CENTRAL, PsycINFO and ICTRP for randomised controlled trials published from database inception to 14thMay 2022, comparing any form of CBT-I against each other or a control condition for chronic insomnia disorder in adults (aged ≥18 years). We included insomnia both with and without comorbidities. Concomitant treatments were allowed if they were equally distributed among the arms. Two independent reviewers identified components, extracted data, and assessed trial quality. Primary outcome of interest in this study was treatment efficacy (remission defined as reaching a satisfactory state at endpoint measured by any validated self-reported scale) at post-treatment. (PROSPERO; CRD42022324233)

Findings

We identified 226 trials, including 29,982 participants. Mean age was 45·7 years and 71% were women. The results suggests that critical components of CBT-I are cognitive restructuring (incremental odds ratio[iOR] 1·63 [95% confidence interval 1·25 to 2·14]), sleep restriction (iOR 1·44 [1·00 to 2·06]) and stimulus control (iOR 1·44 [1·00 to 2·07]) Sleep hygiene education was not essential (iOR 1·05 [0·79 to 1·38]) and relaxation procedures may be counterproductive (iOR 0·81 [0·64 to 1·03]). Face-to-face, therapist-led program was found to be most beneficial (iOR 1·86 [1·21to 2·85]). The overall risk of bias was low in 8% of the trials, some concerns in 56%, and high in 36%.

Interpretation

This cNMA suggests that effective and efficient CBT-I packages can include cognitive restructuring, sleep restriction and stimulus control, but not relaxation.

Funding

None.
Defining the Subtypes of Long COVID and Risk Factors for Prolonged Disease
Authors: Resendez Skyler , Brown Steven H. , Ruiz H. Sebastian , Rangan Prahalad , Nebeker Jonathan R. , Montella Diane , Elkin Peter L.
Published: May 2023

Importance

There have been over 759 million confirmed cases of COVID-19 worldwide. A significant portion of these infections will lead to long COVID and its attendant morbidities and costs.

Objective

To empirically derive a long COVID case definition consisting of significantly increased signs, symptoms, and diagnoses to support clinical, public health, research, and policy initiatives related to the pandemic.

Design

Case-Crossover Population-based study.

Setting

Veterans Affairs (VA) medical centers across the United States between January 1, 2020 and August 18, 2022.

Participants

367,148 individuals with positive COVID-19 tests and preexisting ICD-10-CM codes recorded in the VA electronic health record were enrolled.

Trigger

SARS-CoV-2 infection documented by positive laboratory test.

Case Window

One to seven months following positive COVID testing.

Main Outcomes and Measures

We defined signs, symptoms, and diagnoses as being associated with long COVID if they had a novel case frequency of >= 1:1000 and they were significantly increased in our entire cohort after a positive COVID test when compared to case frequencies before COVID testing. We present odds ratios with confidence intervals for long COVID signs, symptoms, and diagnoses, organized by ICD-10-CM functional groups and medical specialty. We used our definition to assess long COVID risk based upon a patient’s demographics, Elixhauser score, vaccination status, and COVID disease severity.

Results

We developed a long COVID definition consisting of 323 ICD-10-CM diagnosis codes grouped into 143 ICD-10-CM functional groups that were significantly increased in our 367,148 patient post-COVID population. We define seventeen medical-specialty long COVID subtypes such as cardiology long COVID. COVID-19 positive patients developed signs, symptoms, or diagnoses included in our long COVID definition at a proportion of at least 59.7% (based on all COVID positive patients). Patients with more severe cases of COVID-19 and multiple comorbidities were more likely to develop long COVID.

Conclusions and Relevance

An actionable, empirical definition for long COVID can help clinicians screen for and diagnose long COVID, allowing identified patients to be admitted into appropriate monitoring and treatment programs. An actionable long COVID definition can also support public health, research and policy initiatives. COVID patients with low oxygen saturation levels or multiple co-morbidities should be preferentially watched for the development of long COVID.
The impact of flavored e-cigarette bans on e-cigarette use in three US states
Authors: Yang Yong , Lindblom Eric N. , Ward Kenneth D. , Salloum Ramzi G.
Published: May 2023

Introduction

Beginning in 2019, several U.S. states implemented temporary or permanent bans on the sale of flavored e-cigarettes. This study examined the impact of flavor bans on adult e-cigarette use in Washington, New Jersey, and New York.

Methods

Adults who used e-cigarettes at least once a week before the flavor bans were recruited online. Respondents reported their e-cigarette use, primarily used flavor, and ways of obtaining ecigarettes before and after the bans. Descriptive statistics and multinomial logistic regression models were applied.

Results

After the ban, 8.1% of respondents (N=1624) quit using e-cigarettes, those primarily used banned menthol or other flavors declined from 74.4% to 50.8, those using tobacco-flavored declined from 20.1% to 15.6%, and those using non-flavored increased from 5.4% to 25.4%. More frequent e-cigarette use and smoking cigarettes were associated with being less likely to quit e-cigarettes and more likely to use banned flavors. Of those primarily using banned flavors, 45.1% obtained e-cigarettes from in-state stores, 31.2% from out-of-state stores, 32% from friends, family, or others, 25.5% from Internet/mail sellers, 5.2% from illegal sellers, 4.2% mixed flavored e-liquids themselves, and 6.9% stocked up on e-cigarettes before the ban.

Conclusions

Most respondents continued to use e-cigarettes with banned flavors post-ban. Compliance of local retailers with the ban was not high, and many respondents obtained banned-flavor e-cigarettes through legal channels. However, the significant increase in the use of non-flavored e-cigarettes post-ban suggests that these may serve as a viable alternative among those who used previously used banned or tobacco flavors.

Implications

This study examined the impact on adult e-cigarette users from the recent e-cigarette-only flavor bans in Washington State, New Jersey, and New York. We found that most respondents continued to use e-cigarettes with banned flavors post-ban and obtain banned-flavor e-cigarettes through legal channels. Our findings indicate that non-flavored e-cigarettes may serve as an acceptable alternative to both non-tobacco and tobacco-flavored e-cigarettes and state e-cigarette flavor bans are unlikely to prompt a significant number of adult e-cigarette users to replace their e-cigarette use with new or increased smoking. Enforcing compliance of retailers to the policy is crucial to control e-cigarette use.
Reciprocal polarization imaging of complex media
Authors: Xie Zhineng , Huang Guowu , Lin Weihao , Jin Xin , Qian Xiafei , Xu Min
Published: May 2023

The vectorial evolution of polarized light interaction with a medium can reveal its microstructure and anisotropy beyond what can be obtained from scalar light interaction. Anisotropic properties (diattenuation, retardance, and depolarization) of a complex medium can be quantified by polarization imaging by measuring the Mueller matrix. However, polarization imaging in the reflection geometry, ubiquitous and often preferred in diverse applications, has suffered a poor recovery of the medium’s anisotropic properties due to the lack of suitable decomposition of the Mueller matrices measured inside a backward geometry. Here, we present reciprocal polarization imaging of complex media after introducing reciprocal polar decomposition for backscattering Mueller matrices. Based on the reciprocity of the optical wave in its forward and backward scattering paths, the anisotropic diattenuation, retardance, and depolarization of a complex medium are determined by measuring the backscattering Mueller matrix. We demonstrate reciprocal polarization imaging in various applications for quantifying complex non-chiral and chiral media, uncovering their anisotropic microstructures with remarkable clarity and accuracy. Reciprocal polarization imaging will be instrumental in imaging complex media from remote sensing to biomedicine and will open up new applications of polarization optics in reflection geometry.
WebAtlas pipeline for integrated single cell and spatial transcriptomic data
Authors: Li Tong , Horsfall David , Basurto-Lozada Daniela , Roberts Kenny , Prete Martin , Lawrence John E G , He Peng , Tuck Elisabeth , Moore Josh , Ghazanfar Shila , Teichmann Sarah , Haniffa Muzlifah , Bayraktar Omer Ali
Published: May 2023

Single cell and spatial transcriptomics illuminate complementary features of tissues. However, online dissemination and exploration of integrated datasets is challenging due to the heterogeneity and scale of data. We introduce the WebAtlas pipeline for user-friendly sharing and interactive navigation of integrated datasets. WebAtlas unifies commonly used atlassing technologies into the cloud-optimised Zarr format and builds on Vitessce to enable remote data navigation. We showcase WebAtlas on the developing human lower limb to cross-query cell types and genes across single cell, sequencing- and imaging-based spatial transcriptomic data.
The spatially resolved tumor microenvironment predicts treatment outcome in relapsed/refractory Hodgkin lymphoma
Authors: Aoki Tomohiro , Jiang Aixiang , Xu Alexander , Yin Yifan , Gamboa Alicia , Milne Katy , Takata Katsuyoshi , Miyata-Takata Tomoko , Wu Shaocheng , Warren Mary , Strong Celia , Goodyear Talia , Morris Kayleigh , Chong Lauren C. , Hav Monirath , Colombo Anthony R. , Telenius Adele , Boyle Merrill , Ben-Neriah Susana , Power Maryse , Gerrie Alina S. , Weng Andrew P. , Karsan Aly , Roth Andrew , Farinha Pedro , Scott David W. , Savage Kerry J. , Nelson Brad H. , Merchant Akil , Steidl Christian
Published: May 2023

PURPOSE

About a third of relapsed or refractory classic Hodgkin lymphoma (r/r CHL) patients succumb to their disease after high-dose chemotherapy followed by autologous stem cell transplantation (HDC/ASCT). Here, we aimed to describe spatially resolved tumor microenvironment (TME) ecosystems to establish novel biomarkers associated with treatment failure in r/r CHL.

METHODS

We performed imaging mass cytometry (IMC) on 169 paired primary diagnostic and relapse biopsies using a marker panel specific for CHL biology. For each cell type in the TME, we calculated a ’spatial score’ measuring the distance of nearest neighbor cells to the malignant Hodgkin Reed Sternberg cells within close interaction range. ‘Spatial scores’ were used as features in prognostic model development for post-ASCT outcomes.

RESULTS

Highly multiplexed IMC data revealed shared TME patterns in paired diagnostic and early relapse/refractory CHL samples, whereas TME patterns were more divergent in pairs of diagnostic and late relapse samples. Integrated analysis of IMC and single cell RNA sequencing data identified unique architecture defined by CXCR5+HRS cells and their strong spatial relationship with CXCL13+ macrophages in the TME. We developed a prognostic assay (‘RHL4S’) using four spatially resolved parameters, CXCR5+ HRS cells, PD1+CD4+ T cells, tumor-associated macrophages, and CXCR5+ B cells, which effectively separated patients into high-risk vs low-risk groups with significantly different post-ASCT outcomes. The RHL4S assay was validated in an independent r/r CHL cohort using a multicolor immunofluorescence assay.

CONCLUSIONS

We identified the interaction of CXCR5+ HRS cells with ligand-expressing CXCL13+ macrophages as a prominent crosstalk axis in relapsed CHL. Harnessing this TME biology, we developed a novel prognostic model applicable to r/r CHL biopsies, RHL4S, opening new avenues for spatial biomarker development.
A Scalable High Throughput Fully Automated Pipeline for the Quantification of Amyloid Pathology in Alzheimer’s Disease using Deep Learning Algorithms
Authors: Gopal Ramaswamy Vivek , Ahirwar Monika , Ryan Genadi , Signaevsky Maxim , Haroutunian Vahram , Finkbeiner Steven
Published: May 2023

The most common approach to characterize neuropathology in Alzheimer’s disease (AD) involves a manual survey and inspection by an expert neuropathologist of postmortem tissue that has been immunolabeled to visualize the presence of amyloid β in plaques and around blood vessels and neurofibrillary tangles of the tau protein. In the case of amyloid β pathology, a semiquantitative score is given that is based on areas of densest pathology. The approach has been well-validated but the process is laborious and time consuming, and inherently susceptible to intra- and inter-observer variability. Moreover, the tremendous growth in genetic, transcriptomic and proteomic data from AD patients has created new opportunities to link clinical features of AD to molecular pathogenesis through pathology, but the lack of high throughput quantitative and comprehensive approaches to assess neuropathology limits the associations that can be discovered. To address these limitations, we designed a computational pipeline to analyze postmortem tissue from AD patients in a fully automated, unbiased and high throughput manner. We used deep learning to train algorithms with a Mask Regional-Convolutional Neural Network to detect and classify different types of amyloid pathology with human level accuracy. After training on pathology slides from a Mt Sinai cohort, our algorithms identified amyloid pathology in samples made at an independent brain bank and from an unrelated cohort of patients, indicating that the algorithms were detecting reproducible and generalizable pathology features. We designed the pipeline to retain the position of the pathology it detects, making it possible to reconstruct a map of pathology across the entire whole slide image, facilitating neuropathological analyses at multiple scales. Quantitative measurements of amyloid pathology correlated positively and significantly with the severity of AD as measured by standard approaches. We conclude that we have developed a computational pipeline to analyze digitized images of neuropathology in high throughput and algorithms to detect types of amyloid pathology with human level accuracy that should enable neuropathological analysis of large tissue collections and integration of those results with orthogonal clinical and multiomic measurements.
Genome-wide neighbor effects predict genotype pairs that reduce herbivory in mixed planting
Authors: Sato Yasuhiro , Shimizu-Inatsugi Rie , Takeda Kazuya , Schmid Bernhard , Nagano Atsushi J. , Shimizu Kentaro K.
Published: May 2023

Genetically diverse populations can increase plant resistance to natural enemies. Yet, beneficial genotype pairs remain elusive due to the occurrence of both positive and negative effects of mixed planting on plant resistance, called associational resistance and susceptibility. We used genome-wide polymorphisms of the plant speciesArabidopsis thalianato identify genotype pairs that enhance associational resistance to herbivory. By quantifying neighbor interactions among 199 genotypes grown in a randomized block design, we predicted that 823 of the 19,701 candidate pairs could reduce herbivory through associational resistance. We planted such pairs with predicted associational resistance in mixtures and monocultures and found a significant reduction in herbivore damage in the mixtures. Our study highlights the potential application to assemble genotype mixtures with positive biodiversity effects.
Kaempferide induces apoptosis in cervical cancer by attenuating the HPV oncoproteins, E6 and E7
Authors: Nath Lekshmi R , Alex Vijai V , Aiswarya Sreekumar U , Rayginia Tennyson P , Haritha Nair Hariprasad , Keerthana Chenicheri K , Thulasidasan Arun Kumar T , Swetha Mundanattu , Lankalapalli Ravi Shankar , Anto Ruby John
Published: May 2023

Despite the advancement in HPV prevention strategies, cervical cancer is a leading cause of cancer death in women worldwide. The anticancer potential of kaempferide, which was derived from Chromolaena odorata, was previously revealed in our in-vitro study. The current investigation aims to confirm the therapeutic efficacy of the molecule against cervical cancer, in-vitro and in-vivo. In NOD-SCID mice with HeLa Luc+ xenografts, kaempferide significantly increases ROS production resulting in a drastic decrease in the luc activity and growth of cervical tumours. It also exhibits down-regulation of oncoproteins E6, E7 and MDM2 and concurrent up-regulation of p53, p21 and pRb. The degradation of phospho-pRb, along with a strong expression of cleaved PARP, TUNEL positivity and a significant decrease in PCNA expression, confirms apoptotic mode of cell death in the treated tissues. Taken together, our study reveals the antioncogenic potential of kaempferide, which regulates oncoproteins and tumor suppressors accordingly. This is the first report depicting kaempferide as an inhibitor of HPV oncoproteins and hence as a candidate drug molecule against cervical cancer.
RPM: an open-source rotation platform for open- and closed-loop vestibular stimulation in head-fixed mice
Authors: Cano-Ferrer Xavier , Tran-Van-Minh Alexandra , Rancz Ede
Published: May 2023

Head fixation allows the recording and presentation of controlled stimuli and is used to study neural processes underlying spatial navigation. However, it disrupts the head direction system because of the lack of vestibular stimulation.

To overcome this limitation, we developed a novel rotation platform which can be driven by the experimenter (open-loop) or by animal movement (closed-loop). The platform is modular, affordable, easy to build and open source. Additional modules presented here include cameras for monitoring eye movements, visual virtual reality and a micro-manipulator for positioning various probes for recording or optical interference.

We demonstrate the utility of the platform by recording eye movements and showing the robust activation of head-direction cells. This novel experimental apparatus combines the advantages of head fixation and intact vestibular activity in the horizontal plane. The open-loop mode can be used to study e.g. vestibular sensory representation and processing, while the closed-loop mode allows animals to navigate in rotational space, providing a better substrate for 2-D navigation in virtual environments. Documentation is available at (https://ranczlab.github.io/RPM/).
Epigenetic age acceleration in frontotemporal lobar degeneration: a comprehensive analysis in the blood and brain
Authors: Murthy Megha , Rizzu Patrizia , Heutink Peter , Mill Jonathan , Lashley Tammaryn , Bettencourt Conceição
Published: May 2023

Frontotemporal lobar degeneration (FTLD) includes a heterogeneous group of disorders pathologically characterized by the degeneration of the frontal and temporal lobes. In addition to major genetic contributors of FTLD such as mutations inMAPT, GRN, andC9orf72, recent work has identified several epigenetic modifications including significant differential DNA methylation inDLX1, andOTUD4loci. As aging remains to be one of the major risk factors for FTLD, we investigated the presence of accelerated epigenetic aging in FTLD compared to controls. We calculated epigenetic age in both peripheral blood and brain tissues of multiple FTLD subtypes using several DNA methylation clocks, i.e., DNAmClockMulti, DNAmClockHannum, DNAmClockCortical, GrimAge and PhenoAge, and determined age acceleration and its association with different cellular proportions and clinical traits. Significant epigenetic age acceleration was observed in the peripheral blood of both frontotemporal dementia (FTD) and progressive supranuclear palsy (PSP) patients compared to controls with DNAmClockHannum, even after accounting for confounding factors. A similar trend was observed with both DNAmClockMultiand DNAmClockCorticalin post-mortem frontal cortex tissue of PSP patients and in FTLD cases harboringGRNmutations. Our findings support that increased epigenetic age acceleration in the peripheral blood could be an indicator for PSP and to a smaller extent, FTD.
Ampk activation by glycogen expenditure primes the exit of naive pluripotency
Authors: Kim Seong-Min , Kwon Eun-Ji , Oh Ji-Young , Kim Han Sun , Park Sunghyouk , Jang Goo , Do Jeong Tae , Kim Keun-Tae , Cha Hyuk-Jin
Published: May 2023

Embryonic and epiblast stem cells in pre-and post-implantation embryos are characterized by their naive and primed states, respectively, which represent distinct phases of pluripotency. Thus, the cellular transition from naive to primed pluripotency recapitulates a drastic metabolic and cellular remodeling after implantation to adapt to changes in extracellular conditions. Here, we found that inhibition of Ampk occurred during naive transition with two conventional inhibitors (2i) of the Mek1 and Gsk3b pathways. The accumulation of glycogen due to the inhibition of Gsk3b was responsible for Ampk inhibition, which accounted for high de novo fatty acid synthesis in naive embryonic stem cells (ESCs). The knockout of glycogen synthase 1 (Gys1) in naive ESCs (GKO), resulting in a drastic glycogen loss, led to a robust Ampk activation and lowered the level of fatty acids. GKO lost the cellular characteristics of naive ESCs and rapidly transitioned to a primed state, as evidenced by a decrease in pluripotency markers in teratoma from GKO. The characteristics of GKO were restored by the simultaneous knockout of Ampk. These findings suggest that glycogen in naive ESCs within the blastocyst may act as a signaling molecule for the timely activation of Ampk, thus ultimately contributing to the transition to the epiblast stage.
An RNA origami robot that traps and releases a fluorescent aptamer
Authors: Sampedro Vallina Néstor , McRae Ewan K.S. , Geary Cody , Andersen Ebbe Sloth
Published: May 2023

RNA nanotechnology aims at using RNA as a programmable material to create self-assembling nanodevices for application in medicine and synthetic biology. RNA devices have been developed by adopting mechanisms such as allosteric binding and toehold-mediated strand displacement. There are, however, no examples of RNA “robotic” devices that sense, compute, and actuate through mechanical reconfiguration as has been demonstrated in DNA nanotechnology. Here we use the RNA origami method to prototype an RNA robotic device, named the “Traptamer”, that senses two RNA key strands, acts as a Boolean AND gate, and activates the fluorescent aptamer iSpinach through release from a mechanical trap. The Traptamer depends on binding of two different RNA key strands to achieve full activation and can be reversed by addition of two complementary RNA anti-key strands. Cryo-EM of the closed Traptamer structure at 5.45 Å resolution reveals a hinge-like mechanical distortion of the iSpinach motif. Our RNA robot prototype opens the door to build more sophisticated RNA machines that use sensing, computing, and acting modules to precisely control RNA functionalities.
Quantifying dynamic pro-inflammatory gene expression and heterogeneity in single macrophage cells
Authors: Naigles Beverly , Narla Avaneesh V , Soroczynski Jan , Tsimring Lev S , Hao Nan
Published: May 2023

Macrophages must respond appropriately to pathogens and other pro-inflammatory stimuli in order to perform their roles in fighting infection. One way in which inflammatory stimuli can vary is in their dynamics – that is, the amplitude and duration of stimulus experienced by the cell. In this study, we performed long-term live cell imaging in a microfluidic device to investigate how the pro-inflammatory genes IRF1, CXCL10, and CXCL9 respond to dynamic interferon-gamma (IFNγ) stimulation. We found that IRF1 responds to low concentration or short duration IFNγ stimulation, whereas CXCL10 and CXCL9 require longer or higher-concentration stimulation to be expressed. We also investigated the heterogeneity in the expression of each gene and found that CXCL10 and CXCL9 have substantial cell-to-cell variability. In particular, the expression of CXCL10 appears to be largely stochastic with a subpopulation of non-responding cells across all the stimulation conditions tested. We developed both deterministic and stochastic models for the expression of each gene. Our modeling analysis revealed that the heterogeneity in CXCL10 can be attributed to a slow chromatin-opening step that is on a similar timescale to that of adaptation of the upstream signal. In this way, CXCL10 expression in individual cells can remain stochastic in response to each pulse of repeated simulations, as validated by experiments. Together, we conclude that pro-inflammatory genes in the same signaling pathway can respond to dynamic IFNγ stimulus with very different response features and that upstream signal adaptation can contribute to shaping the features of heterogeneous gene expression.
Frequency-dependent Distribution of Different Subtypes of Spiral Ganglion Neurons in the Cochlea and the Changes During Aging
Authors: Wang Meijian , Lin Shengyin , Xie Ruili
Published: May 2023

Sound information is transmitted from the cochlea to the brain mainly by type I spiral ganglion neurons (SGNs), which consist of different subtypes with distinct physiological properties and selective expression of molecular markers. It remains unclear how these SGN subtypes distribute along the tonotopic axis, and how the distribution pattern changes during aging that might underlie age-related hearing loss (ARHL). We investigated these questions using immunohistochemistry in three age groups of CBA/CaJ mice of either sex, including 2-5 months (young), 17-19 months (middle-age), and 28-32 months (old). Mouse cochleae were cryo-sectioned and triple-stained using antibodies against Tuj1, calretinin (CR) and calbindin (CB), which are reportedly expressed in all type I, subtype Ia, and subtype IbSGNs, respectively. Labeled SGNs were classified into four groups based on the expression pattern of stained markers, including CR+(subtype Ia), CB+(subtype Ib), CR+CB+(dual-labeled Ia/Ib), and CR-CB-(subtype Ic) neurons. The distribution of these SGN groups was analyzed in the apex, middle, and base regions of the cochleae. It showed that the prevalence of subtype Ia, Iband dual-labeled Ia/IbSGNs are high in the apex and low in the base. In contrast, the distribution pattern is reversed in IcSGNs. Such frequency-dependent distribution is largely maintained during aging except for a preferential reduction of IcSGNs, especially in the base. These findings suggest that sound processing of different frequencies involves distinct combinations of SGN subtypes, and the age-dependent loss of IcSGNs in the base may especially impact high-frequency hearing during ARHL.
Temporally variable drug profiles select for diverse adaptive pathways despite conservation of efflux-based resistance mechanism
Authors: Akanksha  , Mehra Sarika
Published: May 2023

Antibiotic resistance is a global health concern with emergence of resistance in bacteria out-competing the discovery of novel drug candidates. While Adaptive Laboratory Evolution (ALE) has been used to identify bacterial resistance determinants, most studies investigate evolution under stepwise increasing drug profiles. Thus, bacterial adaptation under long-term constant drug concentration, a physiologically relevant profile, remains underestimated. Using ALE ofMycobacterium smegmatissubjected to a range of Norfloxacin concentrations under both constant and stepwise increasing drug dosage, we investigated the impact of variation of drug profiles on resistance evolution. All the evolved mutants exhibited a drug concentration dependent increase in resistance accompanied with an increase in the number of mutations. Mutations in an efflux pump regulator, LfrR, were found in all the evolved populations suggesting conservation of an efflux-based resistance mechanism. The selection of these mutations was tightly coupled to the presence of its regulated gene in the genetic background. Further,lfrR mutations appeared early during the adaptive trajectory and imparted low-level resistance. Subsequently, sequential acquisition of other mutations, dependent on the drug profile, led to high-level resistance emergence. While divergent mutational trajectories led to comparable phenotype, populations evolved under constant drug exposure accumulated mutations in dehydrogenase genes whereas in populations under increasing drug exposure, mutations in additional regulatory genes were selected. Our data also shows that irrespective of the evolutionary trajectory, drug target mutations were not selected up to 4X drug concentration. Overall, this work demonstrates that evolutionary trajectory is strongly influenced by the drug profile.
Evolutionary analyses of gene expression divergence inPanicum hallii: exploring constitutive and plastic responses using reciprocal transplants
Authors: Bhaskara Govinal Badiger , Haque Taslima , Bonnette Jason E , Napier Joseph D , Bauer Diane , Schmutz Jeremy , Juenger Thomas E
Published: May 2023

The evolution of gene expression is thought to be an important mechanism of local adaptation and ecological speciation. Gene expression divergence occurs through the evolution of cis-polymorphisms and through more widespread effects driven by trans-regulatory factors. Lovell et al. (2018) studied expression divergence between two ecotypes ofPanicum halliiusing expression quantitative trait loci (eQTL) analyses and discovered a pre-dominance of cis and several trans-regulatory divergences. Here, we explore expression and sequence divergence in a large sample ofP. halliiaccessions encompassing the species range using a reciprocal transplantation experiment. We observed widespread genotype and transplant site drivers of expression divergence, with a limited number of genes exhibited genotype-by-site interactions. We used a modified Fst-Qstoutlier approach (QPCanalysis) to detect local adaptation. We identified 514 genes with constitutive expression divergence above and beyond the levels expected under neutral processes. However, no plastic expression responses met our multiple testing correction asQPCoutliers. ConstitutiveQPCoutlier genes were involved in a number of developmental processes and responses to abiotic environments. Leveraging the earlier eQTL results, we found a strong enrichment of expression divergence, including forQPCoutliers, in genes previously identified with cis and cis-drought interactions but found no patterns related to trans-factors. Population genetic analyses detected elevated sequence divergence (FST, DXY) of promoters and coding sequence of constitutive expression outliers, but little evidence for positive selection on these proteins. Our results are consistent with a hypothesis of cis-regulatory divergence as a primary driver of expression divergence inP. hallii.
Telomere-to-telomere genome of the model plantPhyscomitrium patens
Authors: Bi Guiqi , Zhao Shijun , Yao Jiawei , Wang Huan , Zhao Mengkai , Sun Yuanyuan , Hou Xueren , Jiao Yuling , Ma Yingxin , Yan Jianbin , Dai Junbiao
Published: May 2023

The model plantPhyscomitrium patens(P. patens) has played a pivotal role in enhancing our comprehension of plant evolution, growth, and development. However, the current genome harbors numerous intricate regions that remain unfinished and erroneous. To address these issues, we present an exemplary assembly of theP. patensnuclear genome, which incorporates telomeres and centromere regions, thereby establishing it as the telomere-to-telomere (T2T) genome in a non-seed plant. This T2T genome not only dispels the prevailing misconception regarding chromosome number inP. patensbut also provides indispensable resources for conducting in-depth studies in moss genomics and biology.
Socioeconomic status and healthcare resource disparities among children with epilepsy in the United States: Results from a nationally representative sample
Authors: Muthiah Nallammai , Rothenberger Scott , Abel Taylor J.
Published: May 2023

Rationale

Epilepsy affects 1% of the US population. Healthcare and socioeconomic disparities are relatively well-studied among adults with epilepsy, but substantially less so among children. This study examines whether children with epilepsy 1) have lower SES than or 2) utilize healthcare resources differently from their peers, and 3) if SES moderates healthcare resource utilization.

Methods

Data from the 2016-2019 National Survey of Children’s Heath (NSCH) were used to identify children with active “epilepsy or seizure disorder”. Children with versus without epilepsy were compared. SES and healthcare utilization variables were modeled with logistic and Poisson regressions. Significance was assessed at the alpha=0.05 level.

Results

This analysis included 131,326 children; 835 were diagnosed with active epilepsy. The estimated population prevalence of epilepsy was 0.6%. A higher proportion of those with epilepsy were Black, non-Hispanic. Children with epilepsy were more likely to visit an ED (aOR=5.4), have seen a healthcare professional for medical care (aOR: 2.7), have ≥1 preventative checkup (aOR: 2.3), and receive medical care from a specialist (aOR: 10.3). Children from higher-income households were less likely to have epilepsy (aOR: 0.7). SES moderated the relationship between epilepsy status and ED visits. Still, 7.7% of children with epilepsy needed healthcare but did not receive it, the most common barriers being: ineligibility for services (aOR: 3.2), problems getting an appointment (aOR: 3.9), and transportation issues (aOR: 4.7).

Conclusions

Children with epilepsy were more likely than their peers to live in lower income households, visit EDs, and see healthcare professionals. Despite increased needs, children with epilepsy had 2.6 times the odds of not receiving needed healthcare. SES moderated the relationship between epilepsy status and healthcare resource utilization. Most common barriers to healthcare were: service eligibility, appointment scheduling, and transport. Barrier-specific policy interventions may improve medical care access for children with epilepsy.