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arXiv 2023年

作者： Ma, Jun Xie, Ronald Ayyadhury, Shamini Ge, Cheng Gupta, Anubha Gupta, Ritu Gu, Song Zhang, Yao Lee, Gihun Kim, Joonkee Lou, Wei Li, Haofeng Upschulte, Eric Dickscheid, Timo de Almeida, José Guilherme Wang, Yixin Han, Lin Yang, Xin Labagnara, Marco Gligorovski, Vojislav Scheder, Maxime Rahi, Sahand Jamal Kempster, Carly Pollitt, Alice Espinosa, Leon Mignot, Tâm Middeke, Jan Moritz Eckardt, Jan-Niklas Li, Wangkai Li, Zhaoyang Cai, Xiaochen Bai, Bizhe Greenwald, Noah F. Van Valen, David Weisbart, Erin Cimini, Beth A. Cheung, Trevor Brück, Oscar Bader, Gary D. Wang, Bo Peter Munk Cardiac Centre University Health Network TorontoON Canada Department of Laboratory Medicine and Pathobiology University of Toronto TorontoON Canada Vector Institute TorontoON Canada Department of Molecular Genetics University of Toronto TorontoON Canada Donnelly Centre University of Toronto TorontoON Canada Princess Margaret Cancer Centre University Health Network TorontoON Canada School of Medicine and Pharmacy Ocean University of China Qingdao China New Delhi India Laboratory Oncology Dr. BRA-IRCH All India Institute of Medical Sciences New Delhi India Department of Image Reconstruction Nanjing Anke Medical Technology Co. Ltd. Nanjing China Shanghai Artificial Intelligence Laboratory Shanghai China Graduate School of AI KAIST Seoul Korea Republic of Shenzhen Research Institute of Big Data Shenzhen China Shenzhen China Helmholtz AI Research Center Jülich Jülich Germany Faculty of Mathematics and Natural Sciences Institute of Computer Science Heinrich Heine University Düsseldorf Düsseldorf Germany Hinxton United Kingdom Champalimaud Foundation - Centre for the Unknown Lisbon Portugal Department of Bioengineering Stanford University Palo AltoCA United States Tandon School of Engineering New York University New YorkNY United States School of Biomedical Engineering Health Science Center Shenzhen University Shenzhen China Lausanne Switzerland School of Biological Sciences University of Reading Reading United Kingdom Laboratoire de Chimie Bactérienne CNRS Université Aix Marseille UMR Institut de Microbiologie de la Méditerranée Marseille France Department of Internal Medicine I University Hospital Dresden Technical University Dresden Dresden Germany Else Kroener Fresenius Center for Digital Health Technical University Dresden Dresden Germany Department of Automation University of Science and Technology of China Hefei China Institute of Advanced Technology University of Science and Technology of China Hefei Chi

Cell segmentation is a critical step for quantitative single-cell analysis in microscopy images. Existing cell segmentation methods are often tailored to specific modalities or require manual interventions to specify hyper-parameters in different experimental settings. Here, we present a multi-modality cell segmentation benchmark, comprising over 1500 labeled images derived from more than 50 diverse biological experiments. The top participants developed a Transformer-based deep-learning algorithm that not only exceeds existing methods but can also be applied to diverse microscopy images across imaging platforms and tissue types without manual parameter adjustments. This benchmark and the improved algorithm offer promising avenues for more accurate and versatile cell analysis in microscopy imaging. © 2023, CC BY-NC-ND.

关键词： Deep learning

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Loop Catalog: a comprehensive HiChIP database of human and mouse samples

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Genome biology 2025年第1期26卷 175页

作者： Joaquin Reyna Kyra Fetter Romeo Ignacio Cemil Can Ali Marandi Astoria Ma Nikhil Rao Zichen Jiang Daniela Salgado Figueroa Sourya Bhattacharyya Ferhat Ay Centers for Cancer Immunotherapy and Autoimmunity La Jolla Institute for Immunology La Jolla CA 92037 USA. Bioinformatics and Systems Biology Graduate Program University of California San Diego La Jolla CA 92093 USA. Shu Chien-Gene Lay Department of Bioengineering University of California San Diego La Jolla CA 92093 USA. Department of Mathematics University of California San Diego La Jolla CA 92093 USA. Department of Computer Science and Engineering University of California San Diego La Jolla CA 92093 USA. School of Biological Sciences University of California San Diego La Jolla CA 92093 USA. Centers for Cancer Immunotherapy and Autoimmunity La Jolla Institute for Immunology La Jolla CA 92037 USA. ferhatay@***. Bioinformatics and Systems Biology Graduate Program University of California San Diego La Jolla CA 92093 USA. ferhatay@***. Department of Pediatrics University of California San Diego La Jolla CA 92093 USA. ferhatay@***.

HiChIP enables cost-effective and high-resolution profiling of chromatin loops. To leverage the increasing number of HiChIP datasets, we develop Loop Catalog ( https://*** ), a web-based database featuring loop calls from over 1000 distinct human and mouse HiChIP samples from 152 studies plus 44 high-resolution Hi-C samples. We demonstrate its utility for interpreting GWAS and eQTL variants through SNP-to-gene linking, identifying enriched sequence motifs and motif pairs, and generating regulatory networks and 2D representations of chromatin structure. Our catalog spans more than 4.19M unique loops, and with embedded analysis modules, constitutes an important resource for the field.

关键词： Chromatin loops Database GWAS HiChIP SNP-to-gene linking

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The Role of Synthetic Biology in Atmospheric Greenhouse Gas Reduction: Prospects and Challenges

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BioDesign Research 2020年第1期2020卷 1-8页

作者： Charles DeLisi Aristides Patrinos Michael MacCracken Dan Drell George Annas Adam Arkin George Church Robert Cook-Deegan Henry Jacoby Mary Lidstrom Jerry Melillo Ron Milo Keith Paustian John Reilly Richard J.Roberts Daniel Segrè Susan Solomon Dominic Woolf Stan D.Wullschleger Xiaohan Yang Department of Biomedical Engineering and Program in Bioinformatics College of EngineeringBoston UniversityBoston MA 02215USA The NOVIM Group Kohn HallUC Santa BarbaraCA 93106USA Climate Institute WashingtonDCUSA Department of Energy WashingtonDCUSA Center for Health Law Ethics&Human Rights at the Boston University School of Public HealthSchool of MedicineBoston UniversityUSA Department of Bioengineering University of CaliforniaBerkeley CAUSA Department of Genetics Harvard Medical SchoolCambridge MAUSA School for the Future of Innovation in Society Arizona State UniversityBarrett&O’Connor Washington Center1800 I StreetNWWashingtonDC 20006USA Sloan School of Management MITCambridge MAUSA Department of Chemical Engineering University of WashingtonSeattle WashingtonUSA The Ecosystems Center of the Marine Biological Laboratory in Woods Hole MAUSA Department of Plant and Environmental Sciences Weizmann Institute of ScienceRehovotIsrael Department of Soil and Crop Sciences Colorado State UniversityFort Collins CO 80523USA MIT Joint Program on the Science and Policy of Global Change MITCambridge MAUSA New England Biolabs Beverly MAUSA Department of Biology and Program in Bioinformatics Boston UniversityBoston MA 02215USA Department of Earth Atmospheric and Planetary SciencesMITCambridge MAUSA Soil and Crop Sciences Section School of Integrated Plant SciencesCornell UniversityIthaca NYUSA Environmental Sciences Division Oak Ridge National LaboratoryOak Ridge TNUSA Biosciences Division Oak Ridge National LaboratoryOak RidgeTNUSA

The long atmospheric residence time of CO2 creates an urgent need to add atmospheric carbon drawdown to CO2 regulatory *** and systems biology(SSB),which enables manipulation of cellular phenotypes,offers a powerful approach to amplifying and adding new possibilities to current land management practices aimed at reducing atmospheric *** participants(in attendance:Christina Agapakis,George Annas,Adam Arkin,George Church,Robert Cook-Deegan,Charles DeLisi,Dan Drell,Sheldon Glashow,Steve Hamburg,Henry Jacoby,Henry Kelly,Mark Kon,Todd Kuiken,Mary Lidstrom,Mike MacCracken,June Medford,Jerry Melillo,Ron Milo,Pilar Ossorio,Ari Patrinos,Keith Paustian,Kristala Jones Prather,Kent Redford,David Resnik,John Reilly,Richard ***,Daniel Segre,Susan Solomon,Elizabeth Strychalski,Chris Voigt,Dominic Woolf,Stan Wullschleger,and Xiaohan Yang)identified a range of possibilities by which SSB might help reduce greenhouse gas concentrations and which might also contribute to environmental sustainability and *** include,among other possibilities,engineering plants to convert CO2 produced by respiration into a stable carbonate,designing plants with an increased root-to-shoot ratio,and creating plants with the ability to self-fertilize.A number of serious ecological and societal challenges must,however,be confronted and resolved before any such application can be fully assessed,realized,and deployed.

关键词： Synthetic Roberts enable

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Remembering the work of Phillip L. Geissler: A coda to his scientific trajectory

arXiv

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arXiv 2023年

作者： Bowman, Gregory R. Cox, Stephen J. Dellago, Christoph DuBay, Kateri H. Eaves, Joel D. Fletcher, Daniel A. Frechette, Layne B. Grünwald, Michael Klymko, Katherine Ku, JiYeon Omar, Ahmad K. Rabani, Eran Reichman, David R. Rogers, Julia R. Rosnik, Andreana M. Rotskoff, Grant M. Schneider, Anna R. Schwierz, Nadine Sivak, David A. Vaikuntanathan, Suriyanarayanan Whitelam, Stephen Widmer-Cooper, Asaph Bioengineering Biochemistry and Biophysics University of Pennsylvania PA19104 United States Yusuf Hamied Department of Chemistry University of Cambridge Lensfield Road CambridgeCB2 1EW United Kingdom Faculty of Physics University of Vienna Vienna1090 Austria Department of Chemistry University of Virginia CharlottesvilleVA22903 United States Department of Chemistry University of Colorado Boulder BoulderCO80309 United States Department of Bioengineering & Biophysics Program University of California Berkeley Berkeley United States Division of Biological Systems & Engineering Lawrence Berkeley National Laboratory Berkeley United States Chan Zuckerberg Biohub San Francisco United States Martin A. Fisher School of Physics Brandeis University WalthamMA02454 United States Department of Chemistry University of Utah Salt Lake City84112 United States Lawrence Berkeley National Lab BerkeleyCA94720 United States Co. Ltd Suwon16229 Korea Republic of Department of Materials Science and Engineering University of California BerkeleyCA94720 United States Materials Sciences Division Lawrence Berkeley National Laboratory BerkeleyCA94720 United States Department of Chemistry University of California BerkeleyCA94720 United States Materials Sciences Division Lawrence Berkeley National Laboratory BerkeleyCA94720 United States The Raymond and Beverly Sackler Center Computational Molecular and Materials Science Tel Aviv University Tel Aviv69978 Israel Department of Chemistry Columbia University New YorkNY United States Department of Systems Biology Columbia University New YorkNY10032 United States Atomwise San FranciscoCA94103 United States Department of Chemistry Stanford University StanfordCA94305 United States Form Energy BerkeleyCA94710 United States Institute of Physics University of Augsburg Germany Department of Physics Simon Fraser University BurnabyBCV5A1S6 Canada Department of Chemistry University of Chicago ChicagoIL6063

Phillip L. Geissler made important contributions to the statistical mechanics of biological polymers, heterogeneous materials, and chemical dynamics in aqueous environments. He devised analytical and computational methods that revealed the underlying organization of complex systems at the frontiers of biology, chemistry, and materials science. In this retrospective, we celebrate his work at these frontiers. Copyright © 2023, The Authors. All rights reserved.

关键词： Statistical mechanics

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Towards decoding the coupled decision-making of metabolism and epithelial-mesenchymal transition in cancer

arXiv

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arXiv 2020年

作者： Jia, Dongya Park, Jun Hyoung Kaur, Harsimran Jung, Kwang Hwa Yang, Sukjin Tripathi, Shubham Galbraith, Madeline Deng, Youyuan Jolly, Mohit Kumar Kaipparettu, Benny Abraham Onuchic, José N. Levine, Herbert Center for Theoretical Biological Physics Rice University HoustonTX77005 United States Department of Molecular and Human Genetics Baylor College of Medicine HoustonTX77030 United States Centre for BioSystems Science and Engineering Indian Institute of Science BangaloreKarnataka560012 India PhD Program in Systems Synthetic and Physical Biology Rice University HoustonTX77005 United States Department of Physics Northeastern University BostonMA02115 United States Department of Physics and Astronomy Rice University HoustonTX77005 United States Applied Physics Graduate Program Rice University HoustonTX77005 United States Dan L. Duncan Comprehensive Cancer Center Baylor College of Medicine HoustonTX77030 United States Department of Chemistry Rice University HoustonTX77005 United States Department of Biosciences Rice University HoustonTX77005 United States Department of Bioengineering Northeastern University BostonMA02115 United States

Cancer cells have the plasticity to adjust their metabolic phenotypes for survival and metastasis. During metastasis, a developmental program known as the epithelial-mesenchymal transition (EMT) plays a critical role. There is extensive cross-talk between metabolism and EMT, but how this leads to coordinated physiological changes is still uncertain. The elusive connection between metabolism and EMT compromises the efficacy of metabolic therapies targeting metastasis. In this review, we aim for clarifying causation between metabolism and EMT based on recent experimental studies and propose integrated theoretical-experimental efforts to better understand the coupled decision-making of metabolism and EMT. © 2020, CC-BY-NC-ND.

关键词： Metabolism

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Comparative cellular analysis of motor cortex in human, marmoset and mouse (vol 598, pg 111, 2021)

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NATURE 2022年第7904期604卷 E8-E8页

作者： Bakken, Trygve E. Jorstad, Nikolas L. Hu, Qiwen Lake, Blue B. Tian, Wei Kalmbach, Brian E. Crow, Megan Hodge, Rebecca D. Krienen, Fenna M. Sorensen, Staci A. Eggermont, Jeroen Yao, Zizhen Aevermann, Brian D. Aldridge, Andrew I. Bartlett, Anna Bertagnolli, Darren Casper, Tamara Castanon, Rosa G. Crichton, Kirsten Daigle, Tanya L. Dalley, Rachel Dee, Nick Dembrow, Nikolai Diep, Dinh Ding, Song-Lin Dong, Weixiu Fang, Rongxin Fischer, Stephan Goldman, Melissa Goldy, Jeff Graybuck, Lucas T. Herb, Brian R. Hou, Xiaomeng Kancherla, Jayaram Kroll, Matthew Lathia, Kanan van Lew, Baldur Li, Yang Eric Liu, Christine S. Liu, Hanqing Lucero, Jacinta D. Mahurkar, Anup McMillen, Delissa Miller, Jeremy A. Moussa, Marmar Nery, Joseph R. Nicovich, Philip R. Niu, Sheng-Yong Orvis, Joshua Osteen, Julia K. Owen, Scott Palmer, Carter R. Pham, Thanh Plongthongkum, Nongluk Poirion, Olivier Reed, Nora M. Rimorin, Christine Rivkin, Angeline Romanow, William J. Sedeno-Cortes, Adriana E. Siletti, Kimberly Somasundaram, Saroja Sulc, Josef Tieu, Michael Torkelson, Amy Tung, Herman Wang, Xinxin Xie, Fangming Yanny, Anna Marie Zhang, Renee Ament, Seth A. Behrens, M. Margarita Bravo, Hector Corrada Chun, Jerold Dobin, Alexander Gillis, Jesse Hertzano, Ronna Hof, Patrick R. Hollt, Thomas Horwitz, Gregory D. Keene, C. Dirk Kharchenko, Peter V. Ko, Andrew L. Lelieveldt, Boudewijn P. Luo, Chongyuan Mukamel, Eran A. Pinto-Duarte, Antonio Preiss, Sebastian Regev, Aviv Ren, Bing Scheuermann, Richard H. Smith, Kimberly Spain, William J. White, Owen R. Koch, Christof Hawrylycz, Michael Tasic, Bosiljka Macosko, Evan Z. McCarroll, Steven A. Ting, Jonathan T. Zeng, Hongkui Zhang, Kun Feng, Guoping Ecker, Joseph R. Linnarsson, Sten Lein, Ed S. Allen Institute for Brain Science Seattle WA USA Department of Physiology and Biophysics University of Washington Seattle WA USA Department of Biomedical Informatics Harvard Medical School Boston MA USA Department of Bioengineering University of California San Diego La Jolla CA USA The Salk Institute for Biological Studies La Jolla CA USA Epilepsy Center of Excellence Department of Veterans Affairs Medical Center Seattle WA USA Stanley Institute for Cognitive Genomics Cold Spring Harbor Laboratory Cold Spring Harbor NY USA Department of Genetics Harvard Medical School Boston MA USA Broad Institute of MIT and Harvard Cambridge MA USA LKEB Department of Radiology Leiden University Medical Center Leiden The Netherlands Pattern Recognition and Bioinformatics group Delft University of Technology Delft The Netherlands J. Craig Venter Institute La Jolla CA USA Department of Pathology University of California San Diego CA USA Division of Vaccine Discovery La Jolla Institute for Immunology La Jolla CA USA Genomic Analysis Laboratory The Salk Institute for Biological Studies La Jolla CA USA Computer Science and Engineering Program University of California San Diego La Jolla CA USA Howard Hughes Medical Institute The Salk Institute for Biological Studies La Jolla CA USA Bioinformatics and Systems Biology Graduate Program University of California San Diego La Jolla CA USA Institute for Genomes Sciences University of Maryland School of Medicine Baltimore MD USA Center for Epigenomics Department of Cellular and Molecular Medicine University of California San Diego La Jolla CA USA Ludwig Institute for Cancer Research La Jolla CA USA Department of Computer Science University of Maryland College Park College Park MD USA Sanford Burnham Prebys Medical Discovery Institute La Jolla CA USA Biomedical Sciences Program School of Medicine University of California San Diego La Jolla CA USA University of Connecticut Storrs CT USA Department

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Mathematical Modeling of Plasticity and Heterogeneity in EMT

arXiv

引用

arXiv 2019年

作者： Tripathi, Shubham Xing, Jianhua Levine, Herbert Jolly, Mohit Kumar Program in Systems Synthetic and Physical Biology Rice University HoustonTX77005 United States Department of Computational and Systems Biology University of Pittsburgh PittsburghPA15261 United States Department of Physics Department of Bioengineering Northeastern University BostonMA02115 United States Center for Theoretical Biological Physics Rice University HoustonTX77005 United States Centre for BioSystems Science and Engineering Indian Institute of Science Bangalore Karnataka560012 India

Epithelial-mesenchymal transition (EMT) and the corresponding reverse process, mesenchymal-epithelial transition (MET), are dynamic and reversible cellular programs orchestrated by many changes at biochemical and morphological levels. A recent surge in identifying the molecular mechanisms underlying EMT / MET has led to the development of various mathematical models that have contributed to our improved understanding of dynamics at single-cell and population levels: a) multistability (how many phenotypes can cells attain en route EMT / MET?), b) reversibility / irreversibility (what time and / or concentration of an EMT inducer marks the 'tipping point' when cells induced to undergo EMT cannot revert?), c) symmetry in EMT / MET (do cells take the same path when reverting as they took during the induction of EMT?), d) non-cell autonomous mechanisms (how does a cell undergoing EMT alter the tendency of its neighbors to undergo EMT)? These dynamical traits may facilitate a heterogenous response within a cell population undergoing EMT / MET. Here, we present a few examples of designing different mathematical models that can contribute to decoding EMT / MET dynamics. Copyright © 2019, The Authors. All rights reserved.

关键词： Cell proliferation

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AIRR community curation and standardised representation for immunoglobulin and T cell receptor germline sets

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Immunoinformatics (Amsterdam, Netherlands) 2023年 10卷 100025页

作者： William D Lees Scott Christley Ayelet Peres Justin T Kos Brian Corrie Duncan Ralph Felix Breden Lindsay G Cowell Gur Yaari Martin Corcoran Gunilla B Karlsson Hedestam Mats Ohlin Andrew M Collins Corey T Watson Christian E Busse Institute of Structural and Molecular Biology Birkbeck College London England. Human-Centered Computing and Information Science Institute for Systems and Computer Engineering Technology and Science Porto Portugal. Peter O'Donnell Jr. School of Public Health UT Southwestern Medical Center Dallas TX USA. Bioengineering Program Faculty of Engineering Bar-Ilan University Ramat Gan Israel. Department of Biochemistry and Molecular Genetics School of Medicine University of Louisville KY USA. Department of Biological Sciences Simon Fraser University Burnaby BC Canada. Fred Hutchinson Cancer Research Center Seattle WA USA. Peter O'Donnell Jr. School of Public Health Department of Immunology School of Biomedical Sciences UT Southwestern Medical Center Dallas TX USA. Department of Microbiology Tumor and Cell Biology Karolinska Institutet Stockholm Swede. Department of Immunotechnology and SciLifeLab Lund University Lund Sweden. School of Biotechnology and Biomolecular Sciences University of New South Wales Sydney NSW Australia. Division of B Cell Immunology German Cancer Research Center Heidelberg Germany.

Analysis of an individual's immunoglobulin or T cell receptor gene repertoire can provide important insights into immune function. High-quality analysis of adaptive immune receptor repertoire sequencing data depends upon accurate and relatively complete germline sets, but current sets are known to be incomplete. Established processes for the review and systematic naming of receptor germline genes and alleles require specific evidence and data types, but the discovery landscape is rapidly changing. To exploit the potential of emerging data, and to provide the field with improved state-of-the-art germline sets, an intermediate approach is needed that will allow the rapid publication of consolidated sets derived from these emerging sources. These sets must use a consistent naming scheme and allow refinement and consolidation into genes as new information emerges. Name changes should be minimised, but, where changes occur, the naming history of a sequence must be traceable. Here we outline the current issues and opportunities for the curation of germline IG/TR genes and present a forward-looking data model for building out more robust germline sets that can dovetail with current established processes. We describe interoperability standards for germline sets, and an approach to transparency based on principles of findability, accessibility, interoperability, and reusability.

关键词： AIRR-seq Immune receptor Immune receptor germline Immune receptor repertoire Rep-seq

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Rapid 3D bioprinting of in vitro cardiac tissue models using human embryonic stem cell-derived cardiomyocytes

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Bioprinting 2019年 13卷 e00040页

作者： Liu, Justin He, Jingjin Liu, Jingfeng Ma, Xuanyi Chen, Qu Lawrence, Natalie Zhu, Wei Xu, Yang Chen, Shaochen Materials Science and Engineering Program University of California San Diego La Jolla 92093 CA United States Division of Biological Sciences University of California San Diego La Jolla 92093 CA United States Department of Bioengineering University of California San Diego La Jolla 92093 CA United States Department of NanoEngineering University of California San Diego La Jolla 92093 CA United States

There is a great need for physiologically relevant 3D human cardiac scaffolds for both short-term, the development of drug testing platforms to screen new drugs across different genetic backgrounds, and longer term, the replacement of damaged or non-functional cardiac tissue after injury or infarction. In this study, we have designed and printed a variety of scaffolds for in vitro diagnostics using light based Micro-Continuous Optical Printing (µCOP). Human embryonic stem cell-derived cardiomyocyte (hESC-CMs) were directly printed into gelatin hydrogel on glass to determine their viability and ability to align. The incorporation of Green Fluorescent Protein/Calmodulin/M13 Peptide (GCaMP3)-hESC-CMs allowed the ability to continuously monitor calcium transients over time. Normalized fluorescence of GCaMP3-hESC-CMs increased by 18 ± 6% and 40 ± 5% when treated with 500 nM and 1 µM of isoproterenol, respectively. Finally, GCaMP3-hESC-CMs were printed across a customizable 3D printed cantilever-based force system. Along with force tracking by visualizing the displacement of the cantilever, calcium transients could be observed in a non-destructive manner, allowing the samples to be examined over several days. Our µCOP-printed cardiac models presented here can be used as a powerful tool for drug screening and to analyze cardiac tissue maturation. © 2019 Elsevier B.V.

关键词： 3D bioprinting Calcium transients Cardiac tissue Embryonic stem cell-derived cardiomyocytes in vitro model

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Metatranscriptomics uncovers diurnal functional shifts in bacterial transgenes with profound metabolic effects

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Cell Host & Microbe 2025年

作者： Stephany Flores Ramos Nicole Siguenza Wuling Zhong Ipsita Mohanty Amulya Lingaraju R. Alexander Richter Smruthi Karthikeyan April L. Lukowski Qiyun Zhu Wilhan D.G. Nunes Jasmine Zemlin Zhenjiang Zech Xu Jeff Hasty Pieter C. Dorrestein Satchidananda Panda Rob Knight Amir Zarrinpar Division of Gastroenterology University of California San Diego La Jolla CA USA Biomedical Sciences Graduate Program University of California San Diego La Jolla CA USA Department of Pediatrics University of California San Diego La Jolla CA USA Skaggs School of Pharmacy and Pharmaceutical Sciences University of California San Diego La Jolla CA USA Division of Engineering and Applied Science California Institute of Technology Pasadena CA USA Scripps Institution of Oceanography University of California San Diego La Jolla CA USA School of Life Sciences Arizona State University Tempe AZ USA Biodesign Center for Fundamental and Applied Microbiomics Arizona State University Tempe AZ USA Collaborative Mass Spectrometry Innovation Center Skaggs School of Pharmacy and Pharmaceutical Sciences University of California San Diego La Jolla CA USA Key Laboratory of Food Science and Technology Nanchang University Nanchang China Shu Chien-Gene Lay Department of Bioengineering University of California San Diego La Jolla CA USA Center for Microbiome Innovation University of California San Diego La Jolla CA USA Synthetic Biology Institute University of California San Diego La Jolla CA USA Salk Institute for Biological Studies La Jolla CA USA Department of Computer Science and Engineering University of California San Diego La Jolla CA USA Halıcıoğlu Data Science Institute University of California San Diego La Jolla CA USA Moores Cancer Center University of California San Diego La Jolla CA USA Division of Gastroenterology Jennifer Moreno Department of Veterans Affairs Medical Center La Jolla CA USA Institute of Diabetes and Metabolic Health University of California San Diego La Jolla CA USA

Diurnal rhythmicity in the gut maintains gut integrity, circadian rhythms, and metabolic homeostasis. However, existing studies focus on microbial composition rather than transcriptional activity. To understand microbial functional dynamics, we characterize diurnal fluctuations in the mouse cecal metatranscriptome and metagenome under high-fat diet and time-restricted feeding (TRF). We show that metatranscriptomics uncovers TRF-induced time-dependent microbial functional shifts that are undetectable with metagenomics alone. We also found bile salt hydrolase ( bsh ) from Dubosiella newyorkensis exhibits diurnal expression in the TRF group. Engineering this bsh , along with other candidates, into a native E. coli chassis reveals distinct differences in deconjugation and amidation activities, underscoring functional specificity. In vivo , a D. newyorkensis bsh improves insulin sensitivity, glucose tolerance, and body composition, suggesting a direct role in TRF metabolic benefits. This study highlights how coupling metatranscriptomics with engineered bacterial systems is a powerful approach for uncovering time-dependent bacterial functions related to health and disease.

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