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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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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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Shared alleles and genetic structures in different Thai domestic cat breeds: the possible influence of common racial origins

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genomics and Informatics 2024年第1期22卷 1-15页

作者： Jaito, Wattanawan Singchat, Worapong Patta, Chananya Thatukan, Chadaphon Kumnan, Nichakorn Chalermwong, Piangjai Budi, Trifan Panthum, Thitipong Wongloet, Wongsathit Wattanadilokchatkun, Pish Thong, Thanyapat Muangmai, Narongrit Han, Kyudong Duengkae, Prateep Phatcharakullawarawat, Rattanin Srikulnath, Kornsorn Animal Genomics and Bioresource Research Unit (AGB Research Unit) Faculty of Science Kasetsart University 50 Ngamwongwan Chatuchak Bangkok 10900 Thailand Sciences for Industry Faculty of Science Kasetsart University 50 Ngamwongwan Chatuchak Bangkok 10900 Thailand Mind Pets Animal Hospital 169/10 Khlongsongtonnun Latkrabang Bangkok 10520 Thailand Special Research Unit for Wildlife Genomics (SRUWG) Department of Forest Biology Faculty of Forestry Kasetsart University 50 Ngamwongwan Chatuchak Bangkok 10900 Thailand Interdisciplinary Graduate Program in Bioscience Faculty of Science Kasetsart University 50 Ngamwongwan Chatuchak Bangkok 10900 Thailand Department of Fishery Biology Faculty of Fisheries Kasetsart University Bangkok 10900 Thailand Department of Microbiology Dankook University Cheonan 31116 South Korea Bio-Medical Engineering Core Facility Research Center Dankook University Cheonan 31116 South Korea Laboratory of Animal Cytogenetics and Comparative Genomics (ACCG) Department of Genetics Faculty of Science Kasetsart University 50 Ngamwongwan Chatuchak Bangkok 10900 Thailand Center for Advanced Studies in Tropical Natural Resources National Research University-Kasetsart University Kasetsart University Bangkok 10900 Thailand

Over hundreds of years, cats have been domesticated and selectively bred, resulting in numerous pedigreed breeds expedited by recent cat shows and breeding associations. Concerns have been raised about the limited breeding options and the genetic implications of inbreeding, indicating challenges in maintaining genetic diversity and accurate identification in purebred cats. In this study, genetic variability and structure were examined in 5 Thai domestic cat breeds using 15 microsatellite markers and mitochondrial DNA (mtDNA) D-loop sequencing. In total, 184 samples representing the Wichien Maat (WCM), Suphalak (SL), Khao-Manee (KM), Korat (KR), and Konja (KJ) breeds were analyzed. High genetic diversity (H_o and H_e > 0.5) was observed in all breeds, and mtDNA analysis revealed two primary haplogroups (A and B) that were shared among all domestic cat breeds in Thailand and globally. However, minor differences were observed between Thai domestic cat breeds based on clustering analyses, in which a distinct genetic structure was observed in the WCM breed. This suggests that allele fixation for distinctive morphological traits has occurred in Thai domestic cat breeds that emerged in isolated regions with shared racial origins. Analysis of relationships among individuals within the breed revealed high identification efficiency in Thai domestic cat breeds (P_(ID)sibs < 10⁻⁴). Additionally, diverse and effective individual identification can be ensured by optimizing marker efficiency by using only nine loci. This comprehensive genetic characterization provides valuable insights into conservation strategies and breeding practices for Thai domestic cat breeds. © The Author(s) 2024.

关键词： Clustering Individual identification Microsatellite Siamese cat

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Effects of Ligand vs. Linker on Phase Behavior and Mechanical Properties of Nanoparticle Gels

arXiv

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arXiv 2024年

作者： Chen, Qizan Devarajan, Dinesh Sundaravadivelu Nikoubashman, Arash Howard, Michael P. Mittal, Jeetain Artie McFerrin Department of Chemical Engineering Texas A&M University College StationTX77843 United States Leibniz-Institut für Polymerforschung Dresden e.V. Hohe Strase 6 Dresden01069 Germany Institut für Theoretische Physik Technische Universität Dresden Dresden01069 Germany Department of Chemical Engineering Auburn University AuburnAL36849 United States Department of Chemistry Texas A&M University College StationTX77843 United States Interdisciplinary Graduate Program in Genetics and Genomics Texas A&M University College StationTX77843 United States

Nanoparticle gels have attracted considerable attention due to their highly tunable properties. One strategy for producing nanoparticle gels involves utilizing strong local attractions between polymeric molecules, such as DNA hybridization or dynamic covalent chemistry, to form percolated nanoparticle networks. These molecules can be used in two distinct roles: as "ligands" with one end grafted to a nanoparticle or as "linkers" with both ends free. Here, we explore how these roles shape the phase behavior and mechanical properties of gel-like nanoparticle assemblies using coarsegrained simulations. We systematically vary the interaction strength and bending stiffness of both ligands and linkers. We find that phase separation can be limited to low nanoparticle volume fractions by making the ligands rigid, consistent with previous studies on linked nanoparticle gels. At fixed interaction strength and volume fraction, both ligand- and linker-mediated nanoparticle assemblies show similar mechanical responses to variations in bending stiffness. However, a comparison between the two association schemes reveals that the linked nanoparticles form rigid percolated networks that are less stretchable than the ligand-grafted gels, despite exhibiting similar tensile strength. We attribute these differences between ligands and linkers to the distinct structural arrangement of nanoparticles. Our findings highlight the potential to utilize different association schemes to tune specific mechanical properties. © 2024, CC BY-NC-ND.

关键词： Tensile strength

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Mining the Metabolic Capacity ofClostridium sporogenesAided by Machine Learning

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Angewandte Chemie 2024年第12期136卷

作者： Huanrong Ouyang Zhao Xu Joshua Hong Jeshua Malroy Liangyu Qian Shuiwang Ji Xuejun Zhu Department of Chemical Engineering Texas A&M University College Station 77843 United States Department of Computer Science & Engineering Texas A&M University College Station 77843 United States Interdisciplinary Graduate Program in Genetics and Genomics Texas A&M University College Station 77843 United States

Anaerobes dominate the microbiota of the gastrointestinal (GI) tract, where a significant portion of small molecules can be degraded or modified. However, the enormous metabolic capacity of gut anaerobes remains largely elusive in contrast to aerobic bacteria, mainly due to the requirement of sophisticated laboratory settings. In this study, we employed an in silico machine learning platform, MoleculeX, to predict the metabolic capacity of a gut anaerobe, Clostridium sporogenes , against small molecules. Experiments revealed that among the top seven candidates predicted as unstable, six indeed exhibited instability in C. sporogenes culture. We further identified several metabolites resulting from the supplementation of everolimus in the bacterial culture for the first time. By utilizing bioinformatics and in vitro biochemical assays, we successfully identified an enzyme encoded in the genome of C. sporogenes responsible for everolimus transformation. Our framework thus can potentially facilitate future understanding of small molecules metabolism in the gut, further improve patient care through personalized medicine, and guide the development of new small molecule drugs and therapeutic approaches.

关键词： Anaerobes metabolic capacity small molecules machine learning enzyme identification

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How a Disordered Linker in the Polycomb Protein Polyhomeotic Tunes Phase Separation and Oligomerization

SSRN

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SSRN 2023年

作者： Gemeinhardt, Tim Marvin Regy, Roshan Mammen Mendiola, Andrea J. Ledterman, Heather J. Henrickson, Amy Phan, Tien M. Kim, Young C. Demeler, Borries Kim, Chongwoo A. Mittal, Jeetain Francis, Nicole Jane MontrealQC Canada Division of Experimental Medicine McGill University MontrealQC Canada Artie McFerrin Department of Chemical Engineering Texas A&M University College StationTX United States Department of Biochemistry and Molecular Genetics Midwestern University GlendaleAZ United States Department of Chemistry and Biochemistry The University of Lethbridge LethbridgeAB Canada Center for Materials Physics and Technology Naval Research Laboratory WashingtonDC20375 United States Department of Chemistry University of Montana MissoulaMT United States Department of Chemistry Texas A&M University College StationTX United States Interdisciplinary Graduate Program in Genetics and Genomics Texas A&M University College StationTX United States Department of Biochemistry and Molecular Medicine University of Montreal MontrealQC Canada

The Polycomb Group (PcG) complex PRC1 represses transcription, forms condensates in cells, and modifies chromatin architecture. These processes are connected through the essential, polymerizing Sterile Alpha Motif (SAM) present in the PRC1 subunit Polyhomeotic (Ph). In vitro, Ph SAM drives formation of short oligomers and phase separation with DNA or chromatin in the context of a Ph truncation ("mini-Ph"). Oligomer length is controlled by the long disordered linker (L) that connects the SAM to the rest of Ph-replacing Drosophila PhL with the evolutionarily diverged human PHC3L strongly increases oligomerization. How the linker controls SAM polymerization, and how polymerization and the linker affect condensate formation are not know. We analyzed PhL and PHC3L using biochemical assays and molecular dynamics (MD) simulations. PHC3L promotes mini-Ph phase separation and makes it relatively independent of DNA. In MD simulations, basic amino acids in PHC3L form contacts with acidic amino acids in the SAM. Engineering the SAM to make analogous charge-based contacts with PhL increased polymerization and phase separation, partially recapitulating the effects of the PHC3L. Ph to PHC3 linker swaps and SAM surface mutations alter Ph condensate formation in cells, and Ph function in Drosophila imaginal discs. Thus, SAM-driven phase separation and polymerization are conserved between flies and mammals, but the underlying mechanisms have diverged through changes to the disordered linker. © 2023, The Authors. All rights reserved.

关键词： Molecular dynamics

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Deep learning-based high-throughput detection of flowered maize (Zea mays L.) plots from UAS imagery across environments

Plant Phenome Journal

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Plant Phenome Journal 2025年第1期8卷

作者： Shepard, Nicholas R. DeSalvio, Aaron J. Arik, Mustafa Adak, Alper Murray, Seth C. Varela, Jose Ignacio Department of Molecular & Environmental Plant Science (Department of Biochemistry and Biophysics) Texas A&M University College Station TX United States Interdisciplinary Graduate Program in Genetics and Genomics (Department of Biochemistry and Biophysics) Texas A&M University College Station TX United States Department of Soil and Crop Sciences Texas A&M University College Station TX United States Department of Plant and Agroecosystem Sciences University of Wisconsin–Madison Madison WI United States

Flowering time is a critical phenological trait in maize (Zea mays L.) breeding programs. Traditional measurements for assessing flowering time involve semi-subjective and labor-intensive manual observation, limiting the scale and efficiency of genetics and breeding improvement. Leveraging unoccupied aerial system (UAS, also known as unoccupied aerial vehicles or drones) technology coupled with convolutional neural networks (CNNs) presents a promising approach for high-throughput detection of flowered plots in maize. Most CNN image analysis is overly complicated for simple tasks relevant to plant scientists. Here, a methodology for extracting tasseling from UAS red/green/blue imagery using a CNN-based approach was applied to 220 hybrids and 30 test lines grown in eight diverse environments (Wisconsin and Texas) and then validated through an unrelated set of hybrids. Overall accuracies of 0.946, 0.911, 0.985, and 0.988 were obtained for classifying maize images with or without tassels from College Station, TX, in 2020;College Station, TX, in 2021;Arlington, WI, in 2021;and Madison, WI, in 2021, respectively. By employing deep learning techniques, larger volumes of phenotypic data can be processed enabling high-throughput phenotyping in breeding programs. Although large datasets are required to train CNN models, the proposed methodology prioritizes simplicity in computational architecture while maintaining effectiveness in identifying flowered maize across diverse genotypes and environments. © 2025 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.

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Intra-condensate demixing of TDP-43 inside stress granules generates pathological aggregates

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Cell 2025年

作者： Yan, Xiao Kuster, David Mohanty, Priyesh Nijssen, Jik Pombo-García, Karina Garcia Morato, Jorge Rizuan, Azamat Franzmann, Titus M. Sergeeva, Aleksandra Ly, Anh M. Liu, Feilin Passos, Patricia M. George, Leah Wang, Szu-Huan Shenoy, Jayakrishna Danielson, Helen L. Ozguney, Busra Honigmann, Alf Ayala, Yuna M. Fawzi, Nicolas L. Dickson, Dennis W. Rossoll, Wilfried Mittal, Jeetain Alberti, Simon Hyman, Anthony A. Max Planck Institute of Molecular Cell Biology and Genetics (MPI-CBG) Saxony Dresden 01307 Germany Artie McFerrin Department of Chemical Engineering Texas A&M University College Station 77843 TX United States Department of Neuroscience Mayo Clinic Jacksonville 32224 FL United States Biotechnology Center (BIOTEC) Center for Molecular and Cellular Bioengineering Technische Universität Dresden Saxony Dresden 01307 Germany Edward Doisy Department of Biochemistry and Molecular Biology Saint Louis University St. Louis 63104 MO United States Department of Molecular Biology Cell Biology & Biochemistry Brown University Providence 02912 RI United States Center for Biomedical Engineering Brown University Providence 02912 RI United States Department of Chemistry Texas A&M University College Station 77843 TX United States Interdisciplinary Graduate Program in Genetics and Genomics Texas A&M University College Station 77843 TX United States

Cytosolic aggregation of the nuclear protein TAR DNA-binding protein 43 (TDP-43) is associated with many neurodegenerative diseases, but the triggers for TDP-43 aggregation are still debated. Here, we demonstrate that TDP-43 aggregation requires a double event. One is up-concentration in stress granules beyond a threshold, and the other is oxidative stress. These two events collectively induce intra-condensate demixing, giving rise to a dynamic TDP-43-enriched phase within stress granules, which subsequently transition into pathological aggregates. Intra-condensate demixing of TDP-43 is observed in iPS-motor neurons, a disease mouse model, and patient samples. Mechanistically, intra-condensate demixing is triggered by local unfolding of the RRM1 domain for intermolecular disulfide bond formation and by increased hydrophobic patch interactions in the C-terminal domain. By engineering TDP-43 variants resistant to intra-condensate demixing, we successfully eliminate pathological TDP-43 aggregates in cells. We suggest that up-concentration inside condensates followed by intra-condensate demixing could be a general pathway for protein aggregation. © 2025 The Author(s)

关键词： ALS biomolecular condensate FTD intra-condensate demixing neurodegenerative diseases oxidative stress phase separation protein aggregation stress granules TDP-43

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A disordered linker in the Polycomb protein Polyhomeotic tunes phase separation and oligomerization

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Molecular cell 2025年第11期85卷 2128-2146.e15页

作者： Tim M Gemeinhardt Roshan M Regy Tien M Phan Nanu Pal Jyoti Sharma Olga Senkovich Andrea J Mendiola Heather J Ledterman Amy Henrickson Daniel Lopes Utkarsh Kapoor Ashish Bihani Djamouna Sihou Young C Kim David Jeruzalmi Borries Demeler Chongwoo A Kim Jeetain Mittal Nicole J Francis Montreal Clinical Research Institute (IRCM) Montreal QC Canada Division of Experimental Medicine McGill University Montreal QC Canada. Artie McFerrin Department of Chemical Engineering Texas A&M University College Station TX USA. Department of Biochemistry and Molecular Medicine University of Montreal Montreal QC Canada. Montreal Clinical Research Institute (IRCM) Montreal QC Canada. Department of Biochemistry and Molecular Genetics Midwestern University Glendale AZ USA. Department of Chemistry and Biochemistry The University of Lethbridge Lethbridge AB Canada. Department of Chemistry and Biochemistry City College of New York New York NY USA. Department of Chemical and Biomedical Engineering University of Wyoming Laramie WY USA. Center for Materials Physics and Technology Naval Research Laboratory Washington DC USA. Department of Chemistry and Biochemistry City College of New York New York NY USA Ph.D. Program in Biochemistry The Graduate Center of the City University of New York New York NY USA Ph.D. Program in Biology The Graduate Center of the City University of New York New York NY USA Ph.D. Program in Chemistry The Graduate Center of the City University of New York New York NY USA. Department of Chemistry and Biochemistry The University of Lethbridge Lethbridge AB Canada Department of Chemistry and Biochemistry University of Montana Missoula MT USA. Artie McFerrin Department of Chemical Engineering Texas A&M University College Station TX USA Department of Chemistry Texas A&M University College Station TX USA Interdisciplinary Graduate Program in Genetics and Genomics Texas A&M University College Station TX USA. Electronic address: jeetain@tamu.edu. Division of Experimental Medicine McGill University Montreal QC Canada Department of Biochemistry and Molecular Medicine University of Montreal Montreal QC Canada. Electronic address: nicole.francis@ircm.qc.ca.

Biomolecular condensates are increasingly recognized as key regulators of chromatin organization, yet how their formation and properties arise from protein sequences remains incompletely understood. Cross-species comparisons can reveal both conserved functions and significant evolutionary differences. Here, we integrate in vitro reconstitution, molecular dynamics simulations, and cell-based assays to examine how Drosophila and human variants of Polyhomeotic (Ph)-a subunit of the PRC1 chromatin regulatory complex-drive condensate formation through their sterile alpha motif (SAM) oligomerization domains. We identify divergent interactions between SAM and the disordered linker connecting it to the rest of Ph. These interactions enhance oligomerization and modulate both the formation and properties of reconstituted condensates. Oligomerization influences condensate dynamics but minimally impacts condensate formation. Linker-SAM interactions also affect condensate formation in Drosophila and human cells and growth in Drosophila imaginal discs. Our findings show how evolutionary changes in disordered linkers can fine-tune condensate properties, providing insights into sequence-function relationships.

关键词： CRISPR Drosophila Polycomb analytical ultracentrifugation biochemistry biomolecular condensates gene regulation intrinsically disordered regions molecular dynamics simulations oligomerization phase separation sterile alpha motif

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Patterns of somatic structural variation in human cancer genomes (vol 578, pg 112, 2020)

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NATURE 2023年第7948期614卷 E38-E38页

作者： Li, Yilong Roberts, Nicola D. Wala, Jeremiah A. Shapira, Ofer Schumacher, Steven E. Kumar, Kiran Khurana, Ekta Waszak, Sebastian Korbel, Jan O. Haber, James E. Imielinski, Marcin Weischenfeldt, Joachim Beroukhim, Rameen Campbell, Peter J. Cancer Genome Project Wellcome Trust Sanger Institute Hinxton UK Totient Inc Cambridge MA USA Wellcome Sanger Institute Wellcome Genome Campus Hinxton UK Department of Haematology University of Cambridge Cambridge UK Cambridge University Hospitals NHS Foundation Trust Cambridge UK Korea Advanced Institute of Science and Technology Daejeon South Korea Department of Zoology Genetics and Physical Anthropology University of Santiago de Compostela Santiago de Compostela Spain Centre for Research in Molecular Medicine and Chronic Diseases (CIMUS) University of Santiago de Compostela Santiago de Compostela Spain The Biomedical Research Centre (CINBIO) University of Vigo Vigo Spain Centre for Research in Molecular Medicine and Chronic Diseases (CiMUS) Universidade de Santiago de Compostela Santiago de Compostela Spain Department of Zoology Genetics and Physical Anthropology (CiMUS) Universidade de Santiago de Compostela Santiago de Compostela Spain The Biomedical Research Centre (CINBIO) Universidade de Vigo Vigo Spain The Broad Institute of Harvard and MIT Cambridge MA USA Bioinformatics and Integrative Genomics Harvard University Cambridge MA USA Department of Cancer Biology Dana-Farber Cancer Institute Boston MA USA Broad Institute of MIT and Harvard Cambridge MA USA Department of Medical Oncology Dana-Farber Cancer Institute Boston MA USA Harvard Medical School Boston MA USA Massachusetts General Hospital Center for Cancer Research Charlestown MA USA Dana-Farber Cancer Institute Boston MA USA Department of Biostatistics and Computational Biology Dana-Farber Cancer Institute and Harvard Medical School Boston MA USA Weill Cornell Medical College New York NY USA Department of Physiology and Biophysics Weill Cornell Medicine New York NY USA Institute for Computational Biomedicine Weill Cornell Medicine New York NY USA Controlled Department and Institution New York NY USA Englander Institute for Precision Medicine Weill Cornell Medicine Ne

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