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Landscape of global urban environmental resistome and its association with local socioeconomic and medical status

Science China(Life Sciences) 2024年第6期67卷 1292-1301页

作者： Jun Wu Yige Hu Michael H Perlin David Danko Jun Lu Manuela Oliveira Johannes Werner Maria M Zambrano Maria A Sierra Olayinka O Osuolale Paweł Łabaj Nicolás Rascovan Nur Hazlin Hazrin-Chong Soojin Jang Haruo Suzuki Marina Nieto-Caballero Bharath Prithiviraj Patrick K H Lee Agnieszka Chmielarczyk Anna Różańska Yongxiang Zhao Lan Wang Christopher E Mason Tieliu Shi Center for Bioinformatics and Computational Biology and the Institute of Biomedical SciencesSchool of Life SciencesEast China Normal UniversityShanghai 200241China Department of Biology Program on Disease EvolutionUniversity of LouisvilleLouisville 40292USA Weill Cornell Medicine New York 10065USA The Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine New York 10065USA Department of Pulmonary Medicine Shanghai Chest HospitalShanghai Jiao Tong UniversityShanghai 200025China i3S-Instituto de Investiga玢o e Inova玢o em Saúde Universidade do PortoPorto 4050-290Portugal Ipatimup-Instituto de Patologia e Imunologia Molecular da Universidade do Porto Porto 4200-465Portugal Departamento de Biologia Faculdade de CiênciasUniversidade do PortoPorto 4050-290Portugal High Performance and Cloud Computing Group Zentrum für Datenverarbeitung(ZDV)Eberhard Karls University of TübingenW鋍hterstra遝7672074TübingenGermany Corporación Corpogen Research Center Bogotá110311Colombia Applied Environmental Metagenomics and Infectious Diseases Research(AEMIDR) Department of Biological SciencesElizade UniversityIlara-Mokin 340271Nigeria Maopolska Centre of Biotechnology Jagiellonian UniversityKraków 30-005Poland Aix-Marseille Université Mediterranean Institute of OceanologyUniversitéde ToulonCNRSIRDUM 110Marseille 83041France Department of Biological Sciences and Biotechnology Faculty of Science and TechnologyUniversiti Kebangsaan Malaysia43600 UKM BangiSelangor Institut Pasteur Korea Seoul 13488Republic of Korea Faculty of Environment and Information Studies Keio UniversityFujisawaKanagawa 252-0882Japan University of Colorado at Boulder CivilEnvironmental and Architectural DepartmentBoulder 80303USA Brooklyn College of the City University of New York Brooklyn 11210USA School of Energy and Environment City University of Hong KongHong Kong 999077China Department of Microbiology Faculty of MedicineJagiellonian UniversityKraków 30-005Poland Biological Targeting Diagnosis and The

Antimicrobial resistance(AMR)poses a critical threat to global health and development,with environmental factors—particularly in urban areas—contributing significantly to the spread of antibiotic resistance genes(ARGs).However,most research to date has been conducted at a local level,leaving significant gaps in our understanding of the global status of antibiotic resistance in urban *** address this issue,we thoroughly analyzed a total of 86,213 ARGs detected within 4,728 metagenome samples,which were collected by the Meta SUB International Consortium involving diverse urban environments in 60 cities of 27 countries,utilizing a deep-learning based *** findings demonstrated the strong geographical specificity of urban environmental resistome,and their correlation with various local socioeconomic and medical *** also identified distinctive evolutionary patterns of ARG-related biosynthetic gene clusters(BGCs)across different countries,and discovered that the urban environment represents a rich source of novel *** study provides a comprehensive overview of the global urban environmental resistome,and fills a significant gap in our knowledge of large-scale urban antibiotic resistome analysis.

关键词： urban environment metagenome antibiotic resistance resistance diversity biosynthetic gene clusters

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Local and global measures of the shear moduli of jammed disk packings

arXiv

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arXiv 2023年

作者： Zhang, Shiyun Jin, Weiwei Wang, Dong Xu, Ding Zhang, Jerry Shattuck, Mark D. O’Hern, Corey S. Department of Physics University of Science and Technology of China Anhui Hefei230026 China Department of Mechanical Engineering and Materials Science Yale University New HavenCT06520 United States Benjamin Levich Institute and Physics Department The City College of New York New YorkNY10031 United States Department of Physics Yale University New HavenCT06520 United States Department of Applied Physics Yale University New HavenCT06520 United States Graduate Program in Computational Biology and Bioinformatics Yale University New HavenCT06520 United States

Strain-controlled isotropic compression gives rise to jammed packings of repulsive, frictionless disks with either positive or negative global shear moduli. We carry out computational studies to understand the contributions of the negative shear moduli to the mechanical response of jammed disk packings. We first decompose the ensemble-averaged, global shear modulus as hGi = (1 − F−)hG+i + F−hG−i, where F− is the fraction of jammed packings with negative shear moduli and hG+i and hG−i are the average values from packings with positive and negative moduli, respectively. We show that hG+i and h|G−|i obey different power-law scaling relations above and below pN2 ∼ 1. For pN2 > 1, both hG+iN and h|G−|iN ∼ (pN2)β, where β ∼ 0.5 for repulsive linear spring interactions. Despite this, hGiN ∼ (pN2)β0 with β0 & 0.5 due to the contributions from packings with negative shear moduli. We show further that the probability distribution of global shear moduli P(G) collapses at fixed pN2 and different values of p and N. We calculate analytically that P(G) is a Gamma distribution in the pN2 1 limit. As pN2 increases, the skewness of P(G) decreases and P(G) becomes a skew-normal distribution with negative skewness in the pN2 1 limit. We also partition jammed disk packings into subsystems using Delanunay triangulation of the disk centers to calculate local shear moduli. We show that the local shear moduli defined from groups of adjacent triangles can be negative even when G > 0. The spatial correlation function of local shear moduli C(~r) displays weak correlations for pn2sub −2, where nsub is the number of particles within each subsystem. However, C(~r) begins to develop long-ranged spatial correlations with four-fold angular symmetry for pn2sub & 10−2 © 2023, CC BY-NC-ND.

关键词： Elastic moduli

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Simultaneous biomonitoring of volatile organic compounds’ metabolites in human urine samples using a novel in-syringe based fast urinary metabolites extraction (FaUMEx) technique coupled with UHPLC-MS/MS analysis

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Chemosphere 2023年第1期329卷 138667页

作者： Gurrani, Swapnil Prakasham, Karthikeyan Huang, Po-Chin Wu, Ming-Tsang Wu, Chia-Fang Lin, Yu-Chia Tsai, Bongee Krishnan, Anbarasu Tsai, Pei-Chien Ponnusamy, Vinoth Kumar Kaohsiung City807 Taiwan Miaoli County 35053 Taiwan Department of Medical Research China Medical University Hospital China Medical University Taichung City Taiwan Kaohsiung City807 Taiwan Department of Public Health Kaohsiung Medical University Kaohsiung City Taiwan International Master Program of Translational Medicine College of Engineering and Science National United University Miaoli Taiwan Corporation No.392 Yucheng Rd. Zuoying District. Kaohsiung City813 Taiwan Department of Computational Biology Institute of Bioinformatics Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai602105 India Kaohsiung City807 Taiwan Kaohsiung City807 Taiwan

Assessing the impact of human exposure to environmental toxicants is often crucial to biomonitoring the exposed dose. In this work, we report a novel fast urinary metabolites extraction (FaUMEx) technique coupled with UHPLC-MS/MS analysis for the highly sensitive and simultaneous biomonitoring of the five major urinary metabolites (thiodiglycolic acid, s-phenylmercapturic acid, t,t-muconic acid, mandelic acid, and phenyl glyoxylic acid) of common volatile organic compounds' (VOCs) exposure (vinyl chloride, benzene, styrene, and ethylbenzene) in human. FaUMEx technique comprises of two-steps, liquid-liquid microextraction was performed first in an extraction syringe using 1 mL of methanol (pH 3) as an extraction solvent and then, the extractant was passed through a clean-up syringe (pre-packed-with various sorbents including 500 mg anhydrous MgSO4, 50 mg C18, and 50 mg SiO2) to obtain the high order of matrice clean-up and preconcentration efficiency. The developed method displayed excellent linearity, and the correlation coefficients were >0.998 for all the target metabolites with detection and quantification limits of 0.02–0.24 ng mL−1 and 0.05–0.72 ng mL−1, respectively. Furthermore, the matrix effects were © 2023 Elsevier Ltd

关键词： Metabolites

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Local two-sample testing over graphs and point-clouds by random-walk distributions

arXiv

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arXiv 2020年

作者： Landa, Boris Qu, Rihao Chang, Joseph Kluger, Yuval Program in Applied Mathematics Yale University Department of Pathology Yale University School of Medicine Department of Statistics and Data Science Yale University Interdepartmental Program in Computational Biology and Bioinformatics Yale University Department of Immunology Yale School of Medicine

Rejecting the null hypothesis in two-sample testing is a fundamental tool for scientific discovery. Yet, aside from concluding that two samples do not come from the same probability distribution, it is often of interest to characterize how the two distributions differ. Given samples from two densities f1and f0, we consider the task of localizing occurrences of the inequality f1> f0. To avoid the challenges associated with high-dimensional space, we propose a general hypothesis testing framework where hypotheses are formulated adaptively to the data by conditioning on the combined sample from the two densities. We then investigate a special case of this framework where the notion of locality is captured by a random walk on a weighted graph constructed over this combined sample. We derive a tractable testing procedure for this case employing a type of scan statistic, and provide non-asymptotic lower bounds on the power and accuracy of our test to detect whether f1> f0in a local sense. Furthermore, we characterize the test's consistency according to a certain problem-hardness parameter, and show that our test achieves the minimax detection rate for this parameter. We conduct numerical experiments to validate our method, and demonstrate our approach on two real-world applications: detecting and localizing arsenic well contamination across the United States, and analyzing two-sample single-cell RNA sequencing data from melanoma *** Codes 62G10 Copyright © 2020, The Authors. All rights reserved.

关键词： Random processes

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Uncertainty abounds, what now?

引用

Science 2025年第6740期387卷 1261页

作者： Dov Greenbaum Mark Gerstein The reviewer is at the Zvi Meitar Institute for Legal Implications of Emerging Technologies The reviewer is at the Harry Radzyner Law School The reviewer is at the Dina Recanati School of Medicine Reichman University Herzliya Israel The reviewer is at the Department of Biomedical Informatics and Data Science The reviewer is at the Program in Computational Biology and Bioinformatics The reviewer is at the Department of Computer Science Yale University New Haven CT USA.

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Predictable clinical benefits without synergy in trials of combination therapies with immune checkpoint inhibitors

Research Square

引用

Research Square 2021年

作者： Palmer, Adam C. Izar, Benjamin Hwangbo, Haeun Sorger, Peter K. Department of Pharmacology Computational Medicine Program Lineberger Comprehensive Cancer Center University of North Carolina at Chapel Hill Chapel HillNC United States Laboratory of Systems Pharmacology Harvard Program in Therapeutic Science Harvard Medical School BostonMA United States Department of Medicine Division of Hematology and Oncology Columbia University Medical Center Columbia Center for Translational Tumor Immunology New YorkNY United States Curriculum in Bioinformatics and Computational Biology University of North Carolina at Chapel Hill Chapel HillNC United States

Hundreds of clinical trials are currently underway testing combinations of Immune Checkpoint Inhibitors (ICIs) with other cancer therapies in the hope that combination therapy will be more effective than monotherapy. Enhanced efficacy is often equated with drug additivity or synergy arising from mechanisms such as immune priming. In this paper we re-analyze progression free survival data from thirteen recent Phase III trials of ICI combinations and conclude that observed benefits are accurately accounted for by an increased chance that each patient will respond to a single agent. This is consistent with the predictions of drug independence not additivity or synergy. Using independence calculations, the efficacy of new ICI combinations can be predicted from monotherapy data (Pearson r=0.98, P -9, n = 4173 patients and 8 types of cancer), although predicting adverse effects is not yet possible. The benefits from true pharmacological additivity or synergy exceed those of drug independence, but achieving them is likely to require methods that identify patients in whom multiple constituents of a drug combination are active. © 2021, CC BY.

关键词： Oncology

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SCA-AD, a Novel Method to Uniformly Identify Cells across Single-Cell RNA Sequencing Datasets, Applied to Adult and Pediatric Self-Renewing AML Cells

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Blood 2024年 144卷 2218-2218页

作者： Yoonkyu Lee Wen Wang Timothy K Starr Klara E Noble-Orcutt Chad L Myers Zohar Sachs Masonic Cancer Center University of Minnesota Minneapolis MN Bioinformatics and Computational Biology Program University of Minnesota Minneapolis MN Division of Hematology Oncology and Transplantation Department of Medicine University of Minnesota Minneapolis MN Department of Computer Science and Engineering University of Minnesota Minneapolis MN Department of Obstetrics Gynecology and Women's Health University of Minnesota Minneapolis MN

Introduction Single cell RNA sequencing (scRNAseq) is commonly used to determine cell identity. Several scRNAseq analysis methods are available. Most methods use arbitrary scores to represent the similarity of the query cell to a reference profile and do not assess the statistical significance of those scores. We previously presented a method to identify cells that express a profile of interest (the reference profile) within a scRNAseq dataset. Our method, called Single Cell Correlation Analysis (SCA), identifies cells in a query dataset that are similar to a reference profile. SCA represents a novel advance in the field because it calculates the statistical significance of the correlation coefficient using a permutation-based false discovery rate (FDR) estimation. Here, we advanced SCA to uniformly identify cells across multiple scRNAseq datasets. The new method is called SCA-Across Datasets (SCA-AD). We tested the performance of SCA-AD in validated scRNAseq datasets of normal murine and human bone marrow, benchmarked SCA-AD to other methods, and used SCA-AD to identify and compare self-renewing cells in human AML samples from adult and pediatric patients. Methods and Results SCA-AD uses a universal scoring system to assign cell identity across datasets. Spearman's correlation is used to score the similarity of query cells to a reference profile. SCA-AD integrates a common background dataset into each query dataset which ensures heterogeneity in the data and allows SCA-AD to establish a threshold value for cell identity across the datasets. FDR calculations are used to establish the threshold value. We tested SCA-AD in validated scRNAseq datasets of normal murine and human bone marrow. In both cases, the self-renewing compartment was experimentally-validated using gold-standard, in vivo self-renewal assays. We extracted a reference normal bone marrow self-renewal profile from the in vivo- validated murine scRNAseq dataset (Rodriguez-Fraticelli et al. Nature 2020).

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Spectral Top-Down Recovery of Latent Tree Models

arXiv

引用

arXiv 2021年

作者： Aizenbud, Yariv Jaffe, Ariel Wang, Meng Hu, Amber Amsel, Noah Nadler, Boaz Chang, Joseph T. Kluger, Yuval Program in Applied Mathematics Yale University New HavenCT06511 United States Department of Computer Science Weizmann Institute of Science Rehovot76100 Israel Department of Statistics Yale University New HavenCT06520 United States Interdepartmental Program in Computational Biology and Bioinformatics Yale University New HavenCT06511 United States Department of Pathology Yale University New HavenCT06511 United States

Modeling the distribution of high dimensional data by a latent tree graphical model is a prevalent approach in multiple scientific domains. A common task is to infer the underlying tree structure, given only observations of its terminal nodes. Many algorithms for tree recovery are computationally intensive, which limits their applicability to trees of moderate size. For large trees, a common approach, termed divide-and-conquer, is to recover the tree structure in two steps. First, recover the structure separately of multiple, possibly random subsets of the terminal nodes. Second, merge the resulting subtrees to form a full tree. Here, we develop Spectral Top-Down Recovery (STDR), a deterministic divide-and-conquer approach to infer large latent tree models. Unlike previous methods, STDR partitions the terminal nodes in a non random way, based on the Fiedler vector of a suitable Laplacian matrix related to the observed nodes. We prove that under certain conditions, this partitioning is consistent with the tree structure. This, in turn, leads to a significantly simpler merging procedure of the small subtrees. We prove that STDR is statistically consistent and bound the number of samples required to accurately recover the tree with high probability. Using simulated data from several common tree models in phylogenetics, we demonstrate that STDR has a significant advantage in terms of runtime, with improved or similar accuracy. Copyright © 2021, The Authors. All rights reserved.

关键词： Recovery

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Homoharringtonine as a PHGDH inhibitor: Unraveling metabolic dependencies and developing a potent therapeutic strategy for high-risk neuroblastoma

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Biomedicine and Pharmacotherapy 2023年第1期166卷 115429-115429页

作者： Hsieh, Chiao-Hui Huang, Chen-Tsung Cheng, Yi-Sheng Hsu, Chun-Hua Hsu, Wen-Ming Chung, Yun-Hsien Liu, Yen-Lin Yang, Tsai-Shan Chien, Chia-Yu Lee, Yu-Hsuan Huang, Hsuan-Cheng Juan, Hsueh-Fen Department of Life Science National Taiwan University Taipei Taiwan Center for Computational and Systems Biology National Taiwan University Taipei Taiwan Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei Taiwan Institute of Plant Biology National Taiwan University Taipei Taiwan Genome and Systems Biology Degree Program National Taiwan University and Academia Sinica Taipei Taiwan Department of Agricultural Chemistry National Taiwan University Taipei Taiwan Department of Surgery National Taiwan University Hospital and National Taiwan University College of Medicine Taipei Taiwan Department of Pediatrics School of Medicine College of Medicine Taipei Medical University Taipei Taiwan Institute of Biomedical Informatics National Yang Ming Chiao Tung University Taipei Taiwan Center for Advanced Computing and Imaging in Biomedicine Taipei Taiwan

Neuroblastoma, a childhood cancer affecting the sympathetic nervous system, continues to challenge the development of potent treatments due to the limited availability of druggable targets for this aggressive illness. Recent investigations have uncovered that phosphoglycerate dehydrogenase (PHGDH), an essential enzyme for de novo serine synthesis, serves as a non-oncogene dependency in high-risk neuroblastoma. In this study, we show that homoharringtonine (HHT) acts as a PHGDH inhibitor, inducing intricate alterations in cellular metabolism, and thus providing an efficient treatment for neuroblastoma. We have experimentally verified the reliance of neuroblastoma on PHGDH and employed molecular docking, thermodynamic evaluations, and X-ray crystallography techniques to determine the bond interactions between HHT and PHGDH. Administering HHT to treat neuroblastoma resulted in effective cell elimination in vitro and tumor reduction in vivo. Metabolite and functional assessments additionally disclosed that HHT treatment suppressed de novo serine synthesis, initiating intricate metabolic reconfiguration and oxidative stress in neuroblastoma. Collectively, these discoveries highlight the potential of targeting PHGDH using HHT as a potent approach for managing high-risk neuroblastoma. © 2023 The Authors

关键词： computational molecular docking Drug discovery High-risk neuroblastoma Metabolic reprogramming Molecular target therapy Phosphoglycerate dehydrogenase

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Buparlisib and ponatinib inhibit aggressiveness of cholangiocarcinoma cells via suppression of IRS1-related pathway by targeting oxidative stress resistance

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Biomedicine and Pharmacotherapy 2024年 180卷 117569-117569页

作者： Kaewlert, Waleeporn Sakonsinsiri, Chadamas Lert-itthiporn, Worachart Mahalapbutr, Panupong Ali, Saba Rungrotmongkol, Thanyada Jusakul, Apinya Armartmuntree, Napat Pairojkul, Chawalit Feng, Guofei Ma, Ning Pinlaor, Somchai Murata, Mariko Thanan, Raynoo Department of Biochemistry Faculty of Medicine Khon Kaen University Khon Kaen 40002 Thailand Cholangiocarcinoma Research Institute Khon Kaen University Khon Kaen 40002 Thailand Center of Excellence in Structural and Computational Biology Department of Biochemistry Faculty of Science Chulalongkorn University Bangkok 10330 Thailand Program in Bioinformatics and Computational Biology Graduated School Chulalongkorn University Bangkok 10330 Thailand The Center for Research and Development of Medical Diagnostic Laboratories Faculty of Associated Medical Sciences Khon Kaen University Khon Kaen 40002 Thailand Department of Medical Science Amnatcharoen Campus Mahidol University Amnat Charoen 37000 Thailand Department of Pathology Faculty of Medicine Khon Kaen University Khon Kaen 40002 Thailand Department of Environmental and Molecular Medicine Mie University Graduate School of Medicine Mie 514-8507 Japan Graduate School of Health Science Suzuka University of Medical Science Suzuka Mie 510-0226 Japan Department of Parasitology Faculty of Medicine Khon Kaen University Khon Kaen 40002 Thailand

Cholangiocarcinoma (CCA) is an oxidative stress-driven liver cancer with bile duct epithelial cell phenotypes and currently lacks effective treatments, making targeted drug therapy urgently needed. Oxidative stress plays a critical role in CCA carcinogenesis, involving cells with oxidative stress resistance via upregulation of the PI3K and MEKK3 signaling pathways. In this study, we investigated the antineoplastic efficacy of a PI3K inhibitor (buparlisib) and a multi-tyrosine kinase inhibitor (ponatinib) on CCA. The cytotoxicity of the drug combination was studied in vitro using CCA cell lines and in vivo using CCA xenograft models. It was found that the drug combination suppressed growth, colony formation, and migration abilities of CCA cells and induced oxidative damage, cell cycle arrest, and autophagy by suppressing MEKK3 and YAP1 through inhibition of insulin receptor substrate 1 (IRS1) signaling. Moreover, the drugs would potentially bind to the IRS1 protein, significanly decreasing IRS1 phosphorylation. Additionally, the drug combination significantly diminished the expression of YAP1, the cell proliferation marker and an antioxidant regulator, and increased oxidative stress-responsive markers in the xenograft model. In conclusion, targeting oxidative stress resistance with combined buparlisib and ponatinib suppressed tumor growth and migration by repressing IRS1-related pathways and ultimately inducing oxidative damage, suggesting the potential for targeted therapy and clinical trials in CCA patients over the use of a single drug. © 2024 The Authors

关键词： Anti-cancer Bile duct cancer Buparlisib Insulin receptor substrate 1 Ponatinib Targeted therapy

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