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Polygalacturonase-inhibiting proteins as an exogenously applied natural solution for prevention of postharvest fungal infections

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Synthetic and Systems Biotechnology 2024年第3期9卷 481-493页

作者： Tiffany Chiu Yanran Li Graduate Program in Genetics Genomicsand Bioinformatics1140 Batchelor HallUniversity of California RiversideCalifornia92521USA Program of Chemical Engineering Department of NanoengineeringUniversity of CaliforniaSan DiegoCA92521USA

Polygalacturonase inhibiting proteins(PGIPs)are plant proteins involved in the inhibition of polygalacturonases(PGs),cell-wall degrading enzymes often secreted by phytopathogenic ***,we confirmed that PGIP2 from Phaseolus vulgaris(PvPGIP2)can inhibit the growth of Aspergillus niger and Botrytis cinerea on agar *** this study,we further validated the feasibility of using PGIP as an environmental and ecological friendly agent to prevent fungal infection *** found that application of either purified PGIP(full length PvPGIP2 or truncated tPvPGIP2_5-8),or PGIP-secreting Saccharomyces cerevisiae strains can effectively inhibit fungal growth and necrotic lesions on tobacco *** also examined the effective amount and thermostability of PGIP when applied on plants.A concentration of 0.75 mg/mL or higher can significantly reduce the area of *** *** activity of full-length PvPGIPs is not affected after incubation at various temperatures ranging from􀀀20 to 42◦C for 24 h,while truncated tPvPGIP2_5-8 lost some efficacy after incubation at 42◦***,we have also examined the efficacy of PGIP on tomato *** the purified PvPGIP2 proteins were applied to tomato fruit inoculated with *** at a concentration of roughly 1.0 mg/mL,disease inci-dence and area of disease had reduced by more than half compared to the controls without PGIP *** study explores the potential of PGIPs as exogenously applied,eco-friendly fungal control agents on fruit and vegetables post-harvest.

关键词： PGIP Antifungal agent Pest control Postharvest treatment

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Brassinosteroid biosynthesis and signaling:Conserved and diversified functions of core genes across multiple plant species

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Plant Communications 2024年第9期5卷 72-100页

作者： Brian Zebosi Erik Vollbrecht Norman B.Best Department of Genetics Development and Cell BiologyIowa State UniversityAmesIA 50011USA Interdepartmental Genetics and Genomics Graduate Program Iowa State UniversityAmesIA 50011USA USDA-ARS Plant Genetics Research UnitColumbiaMO 65201USA

Brassinosteroids(BRs)are important regulators that control myriad aspects of plant growth and development,including biotic and abiotic stress responses,such that modulating BR homeostasis and signaling presents abundant opportunities for plant breeding and crop *** and other proteins involved in the biosynthesis and signaling of BRs are well understood from molecular genetics and phenotypic analysis in Arabidopsis thaliana;however,knowledge of the molecular functions of these genes in other plant species,especially cereal crop plants,is *** this manuscript,we comprehensively review functional studies of BR genes in Arabidopsis,maize,rice,Setaria,Brachypodium,and soybean to identify conserved and diversified functions across plant species and to highlight cases for which additional research is in *** performed phylogenetic analysis of gene families involved in the biosynthesis and signaling of BRs and re-analyzed publicly available transcriptomic *** trees coupled with expression data provide a valuable guide to supplement future research on BRs in these important crop species,enabling researchers to identify gene-editing targets for BR-related functional studies.

关键词： brassinosteroids maize rice Setaria soybean Brachypodium Arabidopsis

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The potential of plant proteins as antifungal agents for agricultural applications

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Synthetic and Systems Biotechnology 2022年第4期7卷 1075-1083页

作者： Tiffany Chiu Theo Poucet Yanran Li Graduate Program in Genetics GenomicsAnd Bioinformatics1140 Batchelor HallUniversity of California RiversideCalifornia92521USA Department of Chemical and Environmental Engineering University of CaliforniaRiversideCA92521USA

Fungal pathogens induce a variety of diseases in both plants and post-harvest food crops,resulting in significant crop losses for the agricultural *** the usage of chemical-based fungicides is the most common way to control these diseases,they damage the environment,have the potential to harm human and animal life,and may lead to resistant fungal ***,there is an urgent need for diverse and effective agricultural fungicides that are environmentally-and *** have evolved various mechanisms in their innate immune system to defend against fungal pathogens,including soluble proteins secreted from plants with antifungal *** proteins can inhibit fungal growth and infection through a variety of mechanisms while exhibiting diverse functionality in addition to antifungal *** this mini review,we summarize and discuss the potential of using plant antifungal proteins for future agricultural applications from the perspective of bioengineering and biotechnology.

关键词： antifungal potential crops

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High temporal resolution unoccupied aerial systems phenotyping provides unique information between flight dates

Plant Phenome Journal

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Plant Phenome Journal 2024年第1期7卷

作者： Washburn, Jacob D. Adak, Alper DeSalvio, Aaron J. Arik, Mustafa A. Murray, Seth C. USDA-ARS Plant Genetics Research Unit Department of Soil and Crop Sciences Texas A&M University Interdisciplinary Graduate Program in Genetics and Genomics Department of Biochemistry and Biophysics Texas A&M University

Unoccupied aerial systems (UAS, unoccupied aerial vehicle, and drone) are high-throughput phenotyping tools that can provide transformational insights into biological and agricultural research, but practical and scientific questions remain. The utility of dense versus sparse temporal collections (e.g., daily, weekly, and monthly flights) has important implications for experimental design, resource allocation, and the scope of scientific questions investigated through UAS. UAS-derived image data were collected on over 1500 maize hybrid yield trial plots with a temporal (longitudinal, 4D) sampling density of 2.8 days on average between 43 flights throughout the growing season. Correlations of vegetation index (VI) phenomic features between flight dates were generally high between flights separated by only 1 or 2 days but dropped when 3, 4, or more days separated the flights. These varied depending on specific dates and the VI used. Correlations between flights were lower around flowering time than during other parts of the season indicating the phenotypic uniqueness of this developmental period. The cross-validation accuracy of end of season yields prediction models on untested genotypes from the UAS data (0.59 and 0.62) far exceeded genomic prediction accuracy (0.24) for the same test set hybrids regardless of whether all flight dates were used for prediction or only dates before flowering. Phenomic prediction accuracy marginally increased as additional flight dates were added throughout the season. © 2024 The Author(s). The Plant Phenome Journal published by Wiley Periodicals LLC on behalf of American Society of Agronomy and Crop Science Society of America. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

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A novel framework for human leukocyte antigen (HLA) genotyping using probe capture-based targeted next-generation sequencing and computational analysis

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Computational and Structural Biotechnology Journal 2024年 23卷 1562-1571页

作者： Lai, Sheng-Kai Luo, Allen Chilun Chiu, I-Hsuan Chuang, Hui-Wen Chou, Ting-Hsuan Hung, Tsung-Kai Hsu, Jacob Shujui Chen, Chien-Yu Yang, Wei-Shiung Yang, Ya-Chien Chen, Pei-Lung Genome and Systems Biology Degree Program Academia Sinica and National Taiwan University Taipei Taiwan Department of Medical Genetics National Taiwan University Hospital Taipei Taiwan Graduate Institute of Medical Genomics and Proteomics College of Medicine National Taiwan University Taipei Taiwan Department of Biomechatronics Engineering National Taiwan University Taipei Taiwan Graduate Institute of Clinical Medicine College of Medicine National Taiwan University Taipei Taiwan Division of Endocrinology and Metabolism Department of Internal Medicine National Taiwan University Hospital Taipei Taiwan Department of Clinical Laboratory Sciences and Medical Biotechnology College of Medicine National Taiwan University Taipei Taiwan Department of Laboratory Medicine National Taiwan University Hospital Taipei Taiwan

Human leukocyte antigen (HLA) genes play pivotal roles in numerous immunological applications. Given the immense number of polymorphisms, achieving accurate high-throughput HLA typing remains challenging. This study aimed to harness the human pan-genome reference consortium (HPRC) resources as a potential benchmark for HLA reference materials. We meticulously annotated specific four field-resolution alleles for 11 HLA genes (HLA-A, -B, -C, -DPA1, -DPB1, -DQA1, -DQB1, -DRB1, -DRB3, -DRB4 and -DRB5) from 44 high-quality HPRC personal genome assemblies. For sequencing, we crafted HLA-specific probes and conducted capture-based targeted sequencing of the genomic DNA of the HPRC cohort, ensuring focused and comprehensive coverage of the HLA region of interest. We used publicly available short-read whole-genome sequencing (WGS) data from identical samples to offer a comparative perspective. To decipher the vast amount of sequencing data, we employed seven distinct software tools: OptiType, HLA-VBseq, HISAT genotype, SpecHLA, T1K, QzType, and DRAGEN. Each tool offers unique capabilities and algorithms for HLA genotyping, allowing comprehensive analysis and validation of the results. We then compared these results with benchmarks derived from personal genome assemblies. Our findings present a comprehensive four-field-resolution HLA allele annotation for 44 HPRC samples. Significantly, our innovative targeted next-generation sequencing (NGS) approach for HLA genes showed superior accuracy compared with conventional short-read WGS. An integrated analysis involving QzType, T1K, and DRAGEN was developed, achieving 100% accuracy for all 11 HLA genes. In conclusion, our study highlighted the combination of targeted short-read sequencing and astute computational analysis as a robust approach for HLA genotyping. Furthermore, the HPRC cohort has emerged as a valuable assembly-based reference in this realm. © 2024 The Authors

关键词： Probes

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Targeted tumor coating with antigenic, CTL-recognizable peptides via Annexin A5 chimeric constructs following chemotherapy redirects adaptive CD8+ T cell immunity for tumor clearance

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Cellular & Molecular Immunology 2021年第6期18卷 1578-1580页

作者： Tae Heung Kang Andrew Yang Yachea Tsai Louise Ferrall Chien-Fu Hung Institute of Biomedical Science and Technology Konkuk UniversitySeoulSouth Korea Genetics and Genomics Graduate Program Baylor College of MedicineHoustonTXUSA Medical Scientist Training Program Baylor College of MedicineHoustonTXUSA Department of Pathology Johns Hopkins UniversityBaltimoreMDUSA Department of Oncology Johns Hopkins UniversityBaltimoreMDUSA

A common drawback of many cancer immunotherapies,including immune checkpoint blockade,is their reliance on the expression of immunogenic tumor antigens by cancer cells for immune recognition and clearance,which limits their efficacy against cancers with weak antigenicity.1 To overcome this obstacle,we and others have explored strategies to harness the immune responses against nontumor antigens and redirect those immune responses to target tumor cells.2,3,4,5 In particular,we have pioneered a therapeutic strategy fusing tumor-targeting proteins with known antigenic peptide epitopes not naturally expressed by tumor cells,which are flanked by peptide sequences that can be recognized and cleaved by proteases overexpressed in most cancers.2,3 This strategy facilitates the targeted delivery of immunogenic peptides into tumor foci,the release of immunogenic peptides into the tumor microenvironment(TME)via tumor protease cleavage,and subsequent loading of these peptides onto major histocompatibility complex class 1(MHC-I)on the tumor cell surface,allowing the recognition of coated tumor cells by the respective peptide-specific cytotoxic CD8+T lymphocytes(CTLs)for elimination.

关键词： immunity overcome coating

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RANKL-responsive epigenetic mechanism reprograms macrophages into bone-resorbing osteoclasts

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Cellular & Molecular Immunology 2023年第1期20卷 94-109页

作者： Seyeon Bae Kibyeong Kim Keunsoo Kang Haemin Kim Minjoon Lee Brian Oh Kaichi Kaneko Sungkook Ma Jae Hoon Choi Hojoong Kwak Eun Young Lee Sung Ho Park Kyung-Hyun Park-Min Arthritis and Tissue Degeneration Program David Z.Rosensweig Genomics Research CenterHospital for Special SurgeryNew YorkNY10021USA Department of Medicine Weill Cornell Medical CollegeNew YorkNY10065USA Department of Biological Science Ulsan National Institute of Science&Technology(UNIST)Ulsan44919Republic of Korea Department of Life Science College of Natural SciencesResearch Institute for Natural SciencesHanyang UniversitySeoulKorea Department of Microbiology Dankook UniversityCheonan3116Republic of Korea Department of Molecular Biology and Genetics Cornell UniversityIthacaUSA Division of Rheumatology Department of Internal MedicineSeoul National University College of MedicineSeoulKorea BCMB Allied Program Weill Cornell Graduate School of Medical SciencesNew YorkNY10021USA

Monocyte/macrophage lineage cells are highly plastic and can differentiate into various cells under different environmental stimuli. Bone-resorbing osteoclasts are derived from the monocyte/macrophage lineage in response to receptor activator of NF-κB ligand (RANKL). However, the epigenetic signature contributing to the fate commitment of monocyte/macrophage lineage differentiation into human osteoclasts is largely unknown. In this study, we identified RANKL-responsive human osteoclast-specific superenhancers (SEs) and SE-associated enhancer RNAs (SE-eRNAs) by integrating data obtained from ChIP-seq, ATAC-seq, nuclear RNA-seq and PRO-seq analyses. RANKL induced the formation of 200 SEs, which are large clusters of enhancers, while suppressing 148 SEs in macrophages. RANKL-responsive SEs were strongly correlated with genes in the osteoclastogenic program and were selectively increased in human osteoclasts but marginally presented in osteoblasts, CD4+ T cells, and CD34+ cells. In addition to the major transcription factors identified in osteoclasts, we found that BATF binding motifs were highly enriched in RANKL-responsive SEs. The depletion of BATF1/3 inhibited RANKL-induced osteoclast differentiation. Furthermore, we found increased chromatin accessibility in SE regions, where RNA polymerase II was significantly recruited to induce the extragenic transcription of SE-eRNAs, in human osteoclasts. Knocking down SE-eRNAs in the vicinity of the NFATc1 gene diminished the expression of NFATc1, a major regulator of osteoclasts, and osteoclast differentiation. Inhibiting BET proteins suppressed the formation of some RANKL-responsive SEs and NFATc1-associated SEs, and the expression of SE-eRNA:NFATc1. Moreover, SE-eRNA:NFATc1 was highly expressed in the synovial macrophages of rheumatoid arthritis patients exhibiting high-osteoclastogenic potential. Our genome-wide analysis revealed RANKL-inducible SEs and SE-eRNAs as osteoclast-specific signatures, which may contribute to t

关键词： Osteoclasts super-enhancers enhancer RNAs Rheumatoid arthritis

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NF-κB-inducing kinase maintains mitochondrial efficiency and systemic metabolic homeostasis

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Biochimica et Biophysica Acta - Molecular Basis of Disease 2023年第5期1869卷 166682页

作者： Pflug, Kathryn M. Lee, Dong W. Keeney, Justin N. Sitcheran, Raquel Department of Cell Biology and Genetics Texas A&M University Health Science Center College Station TX 77845 United States Interdisciplinary Graduate Program in Genetics and Genomics Texas A&M University College Station TX 77845 United States

NF-κB-inducing kinase (NIK) is an essential upstream inducer of noncanonical NF-κB signaling and a critical regulator of immunity and inflammation. Our recent work has demonstrated that NIK regulates mitochondrial respiration and adaptive metabolic responses in cancer and innate immune cells. However, it is not clear whether NIK also has roles in regulating systemic metabolism. In this study, we demonstrate that NIK has local and systemic effects on developmental and metabolic processes. Our findings show that NIK-deficient mice exhibit reduced adiposity, as well as elevated energy expenditure both basally, and under the stress of a high-fat diet. Moreover, we identify NF-κB-independent and -dependent functions for NIK in white adipose tissue metabolism and development. Specifically, we found that in an NF-κB-independent manner NIK is required for maintaining mitochondrial fitness, as NIK-deficient adipocytes have impaired mitochondrial membrane potential and spare respiratory capacity. In addition to mitochondrial exhaustion, NIK-deficient adipocytes and ex vivo adipose tissue exhibit a compensatory upregulation of glycolysis to meet bioenergetic demands. Finally, while NIK regulation of mitochondrial metabolism in preadipocytes is NF-κB-independent, we demonstrate that NIK has a complementary role in adipocyte differentiation that requires activation of RelB and the noncanonical NF-κB pathway. Collectively, these data demonstrate that NIK has critical roles in local and systemic development and metabolism. Our findings establish NIK as an important regulator of organelle, cell, and systemic metabolic homeostasis, suggesting that metabolic dysfunction may be an important and unappreciated component of immune disorders and inflammatory diseases arising from NIK deficiency. © 2023

关键词： Glycolysis High-fat diet NF-κB-inducing kinase Oxidative phosphorylation (OXPHOS) Proton leak Spare respiratory capacity

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Genomic data processing with GenomeFlow

arXiv

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arXiv 2025年

作者： Park, Junseok Maury, Eduardo A. Oh, Changhoon Shin, Donghoon Denisko, Danielle Lee, Eunjung Alice Division of Genetics and Genomics Boston Children’s Hospital 3 Blackfan Circle BostonMA United States Department of Pediatrics Harvard Medical School 25 Shattuck St BostonMA United States Bioinformatics Integrative Genomics Program Harvard/MIT MD-PHD Program Harvard Medical School BostonMA United States Program in Medical and Population Genetics Broad Institute of MIT and Harvard CambridgeMA United States Graduate School of Information Yonsei University 50 Yonsei-ro Seodaemun-gu Seoul Korea Republic of Department of Human Centered Design and Engineering University of Washington SeattleWA United States Department of Biomedical Informatics Harvard Medical School BostonMA United States

Advances in genome sequencing technologies generate massive amounts of sequence data that are increasingly analyzed and shared through public repositories. On-demand infrastructure services on cloud computing platforms enable the processing of such large-scale genomic sequence data in distributed processing environments with a significant reduction in analysis time. However, parallel processing on cloud computing platforms presents many challenges to researchers, even skillful bioinformaticians. In particular, it is difficult to design a computing architecture optimized to reduce the cost of computing and disk storage as genomic data analysis pipelines often employ many heterogeneous tools with different resource requirements. To address these issues, we developed GenomeFlow, a tool for automated development of computing architecture and resource optimization on Google Cloud Platform, which allows users to process a large number of samples at minimal cost. We outline multiple use cases of GenomeFlow demonstrating its utility to significantly reduce computing time and cost associated with analyzing genomic and transcriptomic data from hundreds to tens of thousands of samples from several consortia. Here, we describe a step-by-step protocol on how to use GenomeFlow for a common genomic data processing task. We introduce this example protocol geared toward a bioinformatician with little experience in cloud computing. © 2025, CC BY.

关键词： Cloud platforms

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Survey and Improvement Strategies for Gene Prioritization with Large Language Models

arXiv

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arXiv 2025年

作者： Neeley, Matthew B. Qi, Guantong Wang, Guanchu Tang, Ruixiang Mao, Dongxue Liu, Chaozhong Pasupuleti, Sasidhar Yuan, Bo Xia, Fan Liu, Pengfei Liu, Zhandong Hu, Xia Jan and Dan Duncan Neurological Research Institute Texas Children’s Hospital Houston United States Graduate School of Biomedical Sciences Program in Quantitative and Computational Biosciences Baylor College of Medicine Houston United States Graduate School of Biomedical Sciences Program in Genetics and Genomics Baylor College of Medicine Houston United States Department of Computer Science Rice University Houston United States Department of Computer Science Rutgers University NJ United States Department of Pediatrics Baylor College of Medicine Houston United States Department of Molecular and Human Genetics Baylor College of Medicine Houston United States Human Genome Sequencing Center Baylor College of Medicine Houston United States Baylor Genetics Houston United States

Background Rare diseases can be difficult to diagnose due to limited patient data and broad genetic diversity. Despite the advances in variant prioritization tools, many rare disease cases remain undiagnosed. While large language models (LLMs) have performed well in medical exams, their accuracy in diagnosing rare genetic diseases has not yet been evaluated. Methods To identify causal genes for genetic diseases, we benchmarked various LLMs for gene prioritization. We employed multi-agent and Human Phenotype Ontology (HPO) classification approaches to identify patient case groups based on phenotypes categorizing them into different levels of solvability. To address LLM limitations in ranking large gene sets, we used a divide-and-conquer strategy to break down the ranking task into smaller subsets. Mini-batching inputs and limiting the number of generated tokens improved efficiency. Results In its vanilla form, GPT-4 consistently outperformed the other LLMs with an accuracy around 30%. Multi-agent and HPO classification approaches aided us in distinguishing between confidently-solved and challenging cases. In addition, we observed bias towards well-studied genes and input order sensitivity which are drawbacks of LLMs in disease-causal gene prioritization. Our divide-and-conquer strategy enhanced accuracy by overcoming positional and gene frequency biases in literature. This framework, based on benchmarking insights and novel techniques, significantly optimizes the overall process when identifying disease-causal genes for genetic diseases when compared to our baseline evaluation, and thereby better enables the development of targeted diagnostic and therapeutic interventions. Conclusions Using HPO classification and our novel multi-agent techniques, and our LLM divide-and-conquer strategy (1) highlighted the importance of accounting for differences in patient case solvability and (2) yielded improved performance in identifying causal genes for rare diseases when compare

关键词： Gene Ontology

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