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STAT5 and STAT3 balance shapes dendritic cell function and tumour immunity

Nature 2025年 1-10页

作者： Zhou, Jiajia Tison, Kole Zhou, Haibin Bai, Longchuan Acharyya, Ranjan Kumar McEachern, Donna Metwally, Hoda Wang, Yu Pitter, Michael Choi, Jae Eun Vatan, Linda Liao, Peng Yu, Jiali Lin, Heng Jiang, Long Wei, Shuang Gao, Xue Grove, Sara Parolia, Abhijit Cieslik, Marcin Kryczek, Ilona Green, Michael D. Lin, Jian-Xin Chinnaiyan, Arul M. Leonard, Warren J. Wang, Shaomeng Zou, Weiping Department of Surgery University of Michigan Medical School Ann Arbor MI United States Center of Excellence for Cancer Immunology and Immunotherapy University of Michigan Rogel Cancer Center Ann Arbor MI United States Graduate Program in Immunology University of Michigan Ann Arbor MI United States Department of Computational Medicine and Bioinformatics University of Michigan Medical School Ann Arbor MI United States Division of Hematology and Oncology Department of Internal Medicine University of Michigan Medical School Ann Arbor MI United States Department of Pathology University of Michigan Medical School Ann Arbor MI United States Michigan Center for Translational Pathology University of Michigan Medical School Ann Arbor MI United States Department of Radiation Oncology University of Michigan Medical School Ann Arbor MI United States Laboratory of Molecular Immunology and the Immunology Center National Heart Lung and Blood Institute National Institutes of Health Bethesda MD United States Howard Hughes Medical Institute University of Michigan Medical School Ann Arbor MI United States University of Michigan Rogel Cancer Center University of Michigan Ann Arbor MI United States Graduate Program in Cancer Biology University of Michigan Ann Arbor MI United States Department of Pharmacology University of Michigan Medical School Ann Arbor MI United States Department of Medicinal Chemistry College of Pharmacy University of Michigan Ann Arbor MI United States

Immune checkpoint blockade (ICB) has transformed cancer therapy1,2. The efficacy of immunotherapy depends on dendritic cell-mediated tumour antigen presentation, T cell priming and activation3,4. However, the relation...

Immune checkpoint blockade (ICB) has transformed cancer therapy^1,2. The efficacy of immunotherapy depends on dendritic cell-mediated tumour antigen presentation, T cell priming and activation^3,4. However, the relationship between the key transcription factors in dendritic cells and ICB efficacy remains unknown. Here we found that ICB reprograms the interplay between the STAT3 and STAT5 transcriptional pathways in dendritic cells, thereby activating T cell immunity and enabling ICB efficacy. Mechanistically, STAT3 restrained the JAK2 and STAT5 transcriptional pathway, determining the fate of dendritic cell function. As STAT3 is often activated in the tumour microenvironment⁵, we developed two distinct PROTAC (proteolysis-targeting chimera) degraders of STAT3, SD-36 and SD-2301. STAT3 degraders effectively degraded STAT3 in dendritic cells and reprogrammed the dendritic cell–transcriptional network towards immunogenicity. Furthermore, STAT3 degrader monotherapy was efficacious in treatment of advanced tumours and ICB-resistant tumours without toxicity in mice. Thus, the crosstalk between STAT3 and STAT5 transcriptional pathways determines the dendritic cell phenotype in the tumour microenvironment and STAT3 degraders hold promise for cancer immunotherapy. © The Author(s) 2025.

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Exploring transposable element-based markers to identify allelic variations underlying agronomic traits in rice

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Plant Communications 2022年第3期3卷 59-71页

作者： Haidong Yan David C.Haak Song Li Linkai Huang Aureliano Bombarely School of Plant and Environmental Sciences Virginia TechBlacksburgVA 24061USA Graduate Program in Genetics Bioinformatics and Computational Biology(GBCB)Virginia TechBlacksburgVA 24061USA Department of Grassland Science Animal Science and Technology CollegeSichuan Agricultural UniversityChengdu 611130China Department of Bioscience Universita degli Studi di Milano(UNIMI)20133 MilanoItaly Instituto de Biologıa Molecular y Celular de Plantas(IBMCP) UPV-CSIC46022 ValenciaSpain

Transposable elements(TEs)are a major force in the production of new alleles during domestication;nevertheless,their use in association studies has been limited because of their *** have developed a TE genotyping pipeline(TEmarker)and applied it to whole-genome genome-wide association study(GWAS)data from 176 Oryza sativa *** accessions to identify genetic elements associated with specific agronomic *** markers recovered a large proportion(69%)of single-nucleotide polymorphism(SNP)-based GWAS peaks,and these TE peaks retained ca.25%of the *** use of TEs in GWASs may reduce false positives associated with linkage disequilibrium(LD)among SNP markers.A genome scan revealed positive selection on TEs associated with agronomic *** found several cases of insertion and deletion variants that potentially resulted from the direct action of TEs,including an allele of LOC_Os11g08410 associated with plant height and panicle length ***,these findings reveal the utility of TE markers for connecting genotype to phenotype and suggest a potential role for TEs in influencing phenotypic variations in rice that impact agronomic traits.

关键词： transposable element marker agronomic trait rice GWAS

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Simultaneous identification for synergistic transcription factors and their transcription factor binding sites

Simultaneous identification for synergistic transcription fa...

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5th International Conference on Complex, Intelligent and Software Intensive Systems, CISIS 2011

作者： Tsai, Zing Tsung-Yeh Huang, Grace Tzu-Wei Tsai, Huai-Kuang Institute of Information Science Academia Sinica Taipei 115 Taiwan Bioinformatics Program Taiwan International Graduate Program Taiwan Institute of Biomedical Informatics National Yang-Ming University Taiwan Joint CMU-Pitt PhD Program in Computational Biology University of Pittsburgh Carnegie Mellon University Pittsburgh PA United States Research Center for Information Technology Innovation Taipei 115 Taiwan Computer Science and Engineering National Taiwan Ocean University Keelung 202 Taiwan

ISBN: (纸本)9780769543734

Identifying transcription factor binding sites (TFBSs) is crucial for understanding the mechanism of transcriptional regulation. It is known that transcription factors (TFs) often cooperate to regulate genes. While traditional approaches can be used to discover binding motifs of a group of co-regulated genes, they often fail to accurately assign motifs to the corresponding TFs. Here, we consider two TFs together to infer their TFBSs and their synergistic relationship simultaneously. The basic idea is that if two TFs interact, their TFBSs, if distinct, would be conserved across species and coincided in the promoter regions of the genes they co-regulated. Applying our method to Saccharomyces cerevisiae chromatin immunoprecipitation data, we predicted 110 TF pairs with statistically significant motif assignments. A majority of these TF pairs have literature support to be synergistic, and the designated motifs to TFs match well with their known consensus. We further examined the synergism of predicted TF pairs in seven experimental conditions using ANOVA, and identified significant interactions. © 2011 IEEE.

关键词： Yeast

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Flor Revisited(Again):eQTL and Mutational Analysis of NB-LRR Mediated Immunity to Powdery Mildew in Barley

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Journal of Integrative Agriculture 2014年第2期13卷 237-243页

作者： Roger Wise Priyanka Surana Greg Fuerst Ruo Xu Divya Mistry Julie Dickerson Dan Nettleton Corn Insects and Crop Genetics Research Unit U.S.Department of Agriculture-Agricultural Research ServiceIowa State UniversityAmesIowa 50011USA Department of Plant Pathology & Microbiology Center for Plant Responses to Environmental StressesIowa State UniversityAmesIowa 50011USA Bioinformatics and Computational Biology Graduate Program Iowa State UniversityAmesIowa 50011USA Department of Statistics Iowa State UniversityAmesIowa 50011USA Department of Electrical and Computer Engineering Iowa State UniversityAmesIowa 50011USA

Genes encoding early signaling events in pathogen defense often are identified only by their phenotype. Such genes involved in barley-powdery mildew interactions include Mla, specifying race-specific resistance; Rarl （Required for Mla12-specified resistance1）, and Roml （Restoration of Mla-specified resistancel）. The HSP90-SGT1-RAR1 complex appears to function as chaperone in MLA-specified resistance, however, much remains to be discovered regarding the precise signaling underlying plant immunity. Genetic analyses of fast-neutron mutants derived from CI 16151 （Mla6） uncovered a novel locus, designated Rar3 （R_equired for Mla6-specified resitance3）. Rar3 segregates independent of Mla6 and Rarl, and rar3 mutants are susceptible to Blumeria graminis f. sp. hordei （Bgh） isolate 5874 （A VRar）, whereas, wild-type progenitor plants are resistant. Comparative expression analyses of the rar3 mutant vs. its wild-type progenitor were conducted via Barleyl GeneChip and GAIIx paired-end RNA-Seq. Whereas Rarl affects transcription of relatively few genes; Rar3 appears to influence thousands, notably in genes controlling ATP binding, catalytic activity, transcription, and phosphorylation; possibly membrane bound or in the nucleus, eQTL analysis of a segregating doubled haploid population identified over two-thousand genes as being regulated by Mla （q value/FDR=0.00001）, a subset of which are significant in Rar3 interactions. The intersection of datasets derived from mla-loss-of-function mutants, Mla-associated eQTL, and rar3-mediated transcriptome reprogramming are narrowing the focus on essential genes required for Mla-specified immunity.

关键词： eQTL transcript profiling immunity resistance signaling barley Blumeria graminis

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Identifying interaction sites in "Recalcitrant" proteins: Predicted protein and RNA binding sites in REV proteins of HIV-1 and EIAV agree with experimental data

Identifying interaction sites in "Recalcitrant" proteins: Pr...

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11th Pacific Symposium on Biocomputing 2006, PSB 2006

作者： Terribllini, Michael Lee, Jae-Hyung Yan, Changhui Jernigan, Robert L. Carpenter, Susan Honavar, Vasant Dobbs, Drena Bioinformatics and Computational Biology Graduate Program LH. Baker Center for Bioinformatics and Biological Statistics Iowa State University Ames IA 50010 United States Department of Computer Science Iowa State University Ames IA 50010 United States Department of Biochemistry Biophysics and Molecular Biology Iowa State University Ames IA 50010 United States Department of Genetics Development and Cell Biology Iowa State University Ames IA 50010 United States Artificial Intelligence Research Laboratory Center for Computational Intelligence Learning and Discovery Iowa State University Ames IA 50010 United States Department of Veterinary Microbiology and Pathology Washington State University Pullman WA. 99164 United States

ISBN: (纸本)9812564632

Protein-protein and protein nucleic acid interactions are vitally important for a wide range of biological processes, including regulation or gene expression, protein synthesis, and replication and assembly of many viruses. We have developed machine learning approaches for predicting which amino acids of a protein participate in its interactions with other proteins and/or nucleic acids, using only the proiein sequence as input. In this paper, we describe an application of classifiers trained on datasets of well-characterized protein-protein and protein-RNA complexes for which experimental structures are available. We apply these classifiers to the problem of predicting protein and RNA binding sites in the sequence of a clinically important protein for which the structure is not known: the regulatory protein Rev, essential for the replication of HIV-I and other lentiviruses. We compare our predictions with published biochemical, genetic and partial structural information for HIV-1 and EIAV Rev and with our own published experimental mapping of RNA binding sites in EIAV Rev. The predicted and experimentally determined binding sites are in very good agreement. The ability to predict reliably the residues of a protein that directly contribute to specific binding events - without the requirement for structural information regarding either the protein or complexes in which it participates - can potentially generate new disease intervention strategies.

关键词： Binding sites

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SRAMM: Short read alignment mapping metrics

arXiv

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arXiv 2021年

作者： Chon, Alvin Huang, Xiaoqiu Bioinformatics and Computational Biology Graduate Program Iowa State University AmesIA50010 United States Department of Computer Science Iowa State University AmesIA50010 United States

Short Read Alignment Mapping Metrics (SRAMM): is an efficient and versatile command line tool providing additional short read mapping metrics, filtering, and graphs. Short read aligners report MAPing Quality (MAPQ), but these methods generally are neither standardized nor well described in literature or software manuals. Additionally, third party mapping quality programs are typically computationally intensive or designed for specific applications. SRAMM efficiently generates multiple different concept-based mapping scores to provide for an informative post alignment examination and filtering process of aligned short reads for various downstream applications. SRAMM is compatible with Python 2.6+ and Python 3.6+ on all operating systems. It works with any short read aligner that generates SAM/BAM/CRAM file outputs and reports 'AS' tags. It is freely available under the MIT license at http://***/achon/sramm. © 2021, CC BY.

关键词： Mapping

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Diversity and Evolution of RNA Recognition Motifs: A Case Study on the Utility of RdRp in the phylum Duplornaviricota

Diversity and Evolution of RNA Recognition Motifs: A Case St...

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IEEE International Conference on bioinformatics and Biomedicine (BIBM)

作者： Mikyung Je Myeongji Cho Hyeon S. Son Interdisciplinary Graduate Program in Bioinformatics College of Natural Science Seoul National University Seoul Republic of Korea Lab. of Computational Biology & Bioinformatics Graduate School of Public Health Seoul National University Seoul Republic of Korea Institute of Health and Environment Seoul National University Seoul Republic of Korea

Viruses possess specific conserved regions known as RNA recognition motifs, which are shared within taxonomic groups. Applying these to the Baltimore virus classification system, there are genes/proteins that serve as biomarkers for each of the seven groups. Mutations in conserved sequence regions can have a significant impact on the function of a virus, especially if these conserved regions are part of a major protein. In this study, we analyzed the RdRp gene, known to be a representative RRM of RNA viruses, from viruses of five families (Alternaviridae, Chrysoviridae, Totiviridae, Sedoreoviridae, and Spinareoviridae) within the phylum Duplornaviricota. Data were retrieved from the NCBI non-redundant (nr) database (https://***/protein) applying a cut-off of 300 amino acids in length. RdRp protein sequences were aligned using PROMALS3D, and PhyML (v3.0) was used for phylogenetic analysis. In the next step, we utilized the officially provided ICTV taxonomy and bioinformatics tools to assign the phylogenetic position of RdRp. Although this analysis focused solely on RdRp, it can be concluded that using this gene as a marker may be sufficient for taxonomic assignment. Subsequent analyses will target DNA viruses and RT viruses to perform a more comprehensive assessment. This extensive analysis aims to validate the usefulness of marker genes in the overall viral taxonomy.

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Multiomics Reveals Induction of Neuroblastoma SK-N-BE(2)C Cell Death by Mitochondrial Division Inhibitor 1 through Multiple Effects

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Journal of Proteome Research 2024年第1期23卷 301-315页

作者： Wang, Wei-Hsuan Kao, Yi-Chun Hsieh, Chiao-Hui Tsai, Shin-Yu Cheung, Chantal Hoi Yin Huang, Hsuan-Cheng Juan, Hsueh-Fen Genome and Systems Biology Degree Program Academia Sinica and National Taiwan University Taipei 106 Taiwan Department of Life Science National Taiwan University Taipei 106 Taiwan Center for Computational and Systems Biology National Taiwan University Taipei 106 Taiwan Institute of Biomedical Informatics National Yang Ming Chiao Tung University Taipei 112 Taiwan Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei 106 Taiwan Center for Advanced Computing and Imaging in Biomedicine National Taiwan University Taipei 106 Taiwan

Mitochondrial division inhibitor 1 (Mdivi-1) is a well-known synthetic compound aimed at inhibiting dynamin-related protein 1 (Drp1) to suppress mitochondrial fission, making it a valuable tool for studying mitochondrial dynamics. However, its specific effects beyond Drp1 inhibition remain to be confirmed. In this study, we employed integrative proteomics and phosphoproteomics to delve into the molecular responses induced by Mdivi-1 in SK-N-BE(2)C cells. A total of 3070 proteins and 1945 phosphorylation sites were identified, with 880 of them represented as phosphoproteins. Among these, 266 proteins and 97 phosphorylation sites were found to be sensitive to the Mdivi-1 treatment. Functional enrichment analysis unveiled their involvement in serine biosynthesis and extrinsic apoptotic signaling pathways. Through targeted metabolomics, we observed that Mdivi-1 enhanced intracellular serine biosynthesis while reducing the production of C24:1-ceramide. Within these regulated phosphoproteins, dynamic dephosphorylation of proteasome subunit alpha type 3 serine 250 (PSMA3-S250) occurred after Mdivi-1 treatment. Further site-directed mutagenesis experiments revealed that the dephosphorylation-deficient mutant PSMA3-S250A exhibited a decreased cell survival. This research confirms that Mdivi-1’s inhibition of mitochondrial division leads to various side effects, ultimately influencing cell survival, rather than solely targeting Drp1 inhibition. © 2023 American Chemical Society.

关键词： Mdivi-1 multiomics neuroblastoma phosphoproteome proteome targeted metabolome

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Classification of Multiple Time-Series via Boosting

Classification of Multiple Time-Series via Boosting

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IEEE Digital Signal Processing Workshop

作者： Patrick L. Harrington Arvind Rao Alfred O., Hero Bioinformatics Graduate Program University of Michigan Ann Arbor MI USA Lane Center of Computational Biology Carnegie Mellon University Pittsburgh PA USA Department of Statistics University of Michigan Ann Arbor MI USA

Much of modern machine learning and statistics research consists of extracting information from high-dimensional patterns. Often times, the large number of features that comprise this high-dimensional pattern are themselves vector valued, corresponding to sampled values in a time-series. Here, we present a classification methodology to accommodate multiple time-series using boosting. This method constructs an additive model by adaptively selecting basis functions consisting of a discriminating feature's full time-series. We present the necessary modifications to fisher linear discriminant analysis and least-squares, as base learners, to accommodate the weighted data in the proposed boosting procedure. We conclude by presenting the performance of our proposed method against a synthetic stochastic differential equation data set and a real world data set involving prediction of cancer patient susceptibility for a particular chemoradiotherapy.

关键词： Boosting Statistics Vectors Linear discriminant analysis Gene expression bioinformatics computational biology Machine learning Data mining Stochastic processes

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A Path Analysis Model for Explaining Factors That Influence the Use of Masker among Commuting Workers Using KRL Commuter Line Bogor Jakarta

Research Square

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Research Square 2021年

作者： Kusmawan, David Andari, Shofi Indri Hapsari, S. Faculty Medicine and Health Science Universitas Jambi Indonesia Bioinformatics and Computational Biology Graduate Program Iowa State University United States Occupational Health and Safety Department Faculty of Public Health Universitas Indonesia Indonesia

Jakarta is one of the most air polluted cities in the world, it can increase the risk of healthy of commuting worker. As one of the most air polluted cities in the world, Jakarta is at high risk of its commuting worker’s health. They are at risk of being exposed to pollutant. This study aims to determine the factors influencing directly and indirectly to healthy behavior (using masker) for commuting workers who use the KRL Commuterline Bogor - Jakarta. A total of 155 respondents participated in the study and the collected data were then analyzed using descriptive and path analysis. Commuters are aware of the hazard potential related to air pollution during commuting were 137 people (88.4%). Commuters with good perception of pollution were 104 people (67.1%). Commuters used masker during commuting was 125 people (80.6%). Healthy behavior (using masker) in commuting worker using KRL Commuter Line were affected by some factors both directly and indirectly. Knowledge and commuting experience toward healthy behavior using masker were two variables with a significant direct influence on healthy behavior using masker, and knowledge was also the only mediated variable with a significant indirect effect of education to healthy behavior (using masker). © 2021, CC BY.

关键词： Pollution

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