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Author Correction: ML-enhanced peroxisome capacity enables compartmentalization of multienzyme pathway

Nature chemical biology 2024年 2024 Nov 8页

作者： Jordan J Baker Jie Shi Shangying Wang Elena M Mujica Simone Bianco Sara Capponi John E Dueber Department of Bioengineering University of California Berkeley CA USA. UC Berkeley and UCSF Joint Graduate Program in Bioengineering University of California Berkeley CA USA. NSF Center for Cellular Construction University of California San Francisco CA USA. Department of Functional Genomics and Cellular Engineering IBM Almaden Research Center San Jose CA USA. Bay Area Institute of Science Altos Labs Redwood City CA USA. NSF Center for Cellular Construction University of California San Francisco CA USA. sara.capponi@***. Department of Functional Genomics and Cellular Engineering IBM Almaden Research Center San Jose CA USA. sara.capponi@***. Department of Bioengineering University of California Berkeley CA USA. jdueber@berkeley.edu. NSF Center for Cellular Construction University of California San Francisco CA USA. jdueber@berkeley.edu. Biological Systems and Engineering Division Lawrence Berkeley National Laboratory Berkeley CA USA. jdueber@berkeley.edu.

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Deep learning-guided design of dynamic proteins

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Science (New York, N.Y.) 2025年第6749期388卷 eadr7094页

作者： Amy B Guo Deniz Akpinaroglu Christina A Stephens Michael Grabe Colin A Smith Mark J S Kelly Tanja Kortemme The UC Berkeley-UCSF Graduate Program in Bioengineering University of California San Francisco San Francisco CA USA. Department of Bioengineering and Therapeutic Sciences University of California San Francisco San Francisco CA USA. Department of Pharmaceutical Chemistry University of California San Francisco San Francisco CA USA. Cardiovascular Research Institute University of California San Francisco San Francisco CA USA. Department of Chemistry Wesleyan University Middletown CT USA. Quantitative Biosciences Institute University of California San Francisco San Francisco CA USA. Chan Zuckerberg Biohub San Francisco CA USA.

Deep learning has advanced the design of static protein structures, but the controlled conformational changes that are hallmarks of natural signaling proteins have remained inaccessible to de novo design. Here, we describe a general deep learning-guided approach for de novo design of dynamic changes between intradomain geometries of proteins, similar to switch mechanisms prevalent in nature, with atomic-level precision. We solve four structures that validate the designed conformations, demonstrate modulation of the conformational landscape by orthosteric ligands and allosteric mutations, and show that physics-based simulations are in agreement with deep-learning predictions and experimental data. Our approach demonstrates that new modes of motion can now be realized through de novo design and provides a framework for constructing biology-inspired, tunable, and controllable protein signaling behavior de novo.

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Attenuation coefficient estimation for PET/MRI with Bayesian deep learning pseudo-CT and maximum likelihood estimation of activity and attenuation

arXiv

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arXiv 2020年

作者： Leynes, Andrew Palmera Ahn, Sangtae P. Wangerin, Kristen A. Kaushik, Sandeep S. Wiesinger, Florian Hope, Thomas A. Larson, Peder E.Z. The Department of Radiology and Biomedical Imaging University of California San Francisco San FranciscoCA94158 United States The UC Berkeley Joint Graduate Program in Bioengineering BerkeleyCA United States UC San Francisco Joint Graduate Program in Bioengineering San FranciscoCA United States GE Research NiskayunaNY United States GE Healthcare WaukeshaWI United States GE Healthcare Munich Germany The Department of Computer Science Technical University of Munich Munich Germany The Department of Radiology San Francisco VA Medical Center San FranciscoCA United States

A major remaining challenge for magnetic resonance-based attenuation correction methods (MRAC) is their susceptibility to sources of MRI artifacts (e.g. implants, motion) and uncertainties due to the limitations of MRI contrast (e.g. accurate bone delineation and density, and separation of air/bone). We propose using a Bayesian deep convolutional neural network that, in addition to generating an initial pseudo-CT from MR data, also produces uncertainty estimates of the pseudo-CT to quantify the limitations of the MR data. These outputs are combined with MLAA reconstruction that uses the PET emission data to improve the attenuation maps. With the proposed approach (UpCT-MLAA), we demonstrate accurate estimation of PET uptake in pelvic lesions and show recovery of metal implants. In patients without implants, UpCT-MLAA had acceptable but slightly higher RMSE than Zero-echo-time and Dixon Deep pseudo-CT when compared to CTAC. In patients with metal implants, MLAA recovered the metal implant;however, anatomy outside the implant region was obscured by noise and crosstalk artifacts. Attenuation coefficients from the pseudo-CT from Dixon MRI were accurate in normal anatomy;however, the metal implant region was estimated to have attenuation coefficients of air. UpCT-MLAA estimated attenuation coefficients of metal implants alongside accurate anatomic depiction outside of implant regions. © 2020, CC BY.

关键词： Magnetic resonance

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Subcellular western blotting of single cells

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Microsystems & Nanoengineering 2017年第1期3卷 405-413页

作者： Kevin A.Yamauchi Amy E.Herr Department of Bioengineering University of CaliforniaBerkeleyCA 94720USA The UC Berkeley—UCSF Graduate Program in Bioengineering University of CaliforniaBerkeleyCA 94720USA

Although immunoassays are the de facto standard for determining subcellular protein localization in individual cells,antibody probe cross-reactivity and fixation artifacts remain confounding *** enhance selectivity while providing single-cell resolution,we introduce a subcellular western blotting technique capable of separately assaying proteins in the 14 pL cytoplasm and 2 pL nucleus of individual *** confer precision fluidic control,we describe a passive multilayer microdevice that leverages the rapid transport times afforded by *** isolating single cells in microwells,we apply single-cell differential detergent fractionation to lyse and western blot the cytoplasmic lysate,whereas the nucleus remains intact in the ***,we lyse the intact nucleus and western blot the nuclear *** index each protein analysis to the originating subcellular compartment,we utilize bi-directional electrophoresis,a multidimensional separation that assays the lysate from each compartment in a distinct region of the separation ***-cell bi-directional electrophoresis eliminates the need for semi-subjective image segmentation algorithms required in *** subcellular,single-cell western blot is demonstrated for six targets per cell,and successfully localizes spliceosome-associated proteins solubilized from large protein and RNA complexes,even for closely sized proteins(a 7 kDa difference).Measurement of NF-κB translocation dynamics in unfixed cells at 15-min intervals demonstrates reduced technical variance compared with *** chemical cytometry assay directly measures the nucleocytoplasmic protein distribution in individual unfixed cells,thus providing insight into protein signaling in heterogeneous cell populations.

关键词： cytometry microfluidic design proteomics single-cell analysis

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Mitigation of Chromosome Loss in Clinical CRISPR-Cas9-Engineered T Cells

SSRN

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SSRN 2023年

作者： Tsuchida, Connor A. Brandes, Nadav Bueno, Raymund Trinidad, Marena Mazumder, Thomas Yu, Bingfei Hwang, Byungjin Chang, Christopher Liu, Jamin Sun, Yang Hopkins, Caitlin R. Parker, Kevin R. Qi, Yanyan Satpathy, Ansuman T. Stadtmauer, Edward A. Cate, Jamie H.D. Eyquem, Justin Fraietta, Joseph A. June, Carl H. Chang, Howard Y. Ye, Chun Jimmie Doudna, Jennifer A. University of California Berkeley - University of California San Francisco Graduate Program in Bioengineering University of California Berkeley BerkeleyCA United States Innovative Genomics Institute University of California Berkeley BerkeleyCA United States Division of Rheumatology Department of Medicine University of California San Francisco San FranciscoCA United States Center for Personal Dynamic Regulomes Stanford University StanfordCA United States Parker Institute for Cancer Immunotherapy Stanford University School of Medicine StanfordCA United States Biomedical Sciences Graduate Program University of California San Francisco San FranciscoCA United States Medical Scientist Training Program University of California San Francisco San FranciscoCA United States Department of Medicine University of California San Francisco San FranciscoCA United States Parker Institute for Cancer Immunotherapy San FranciscoCA United States Gladstone-UCSF Institute of Genomic Immunology San FranciscoCA United States Department of Biochemistry and Biophysics University of California San Francisco San FranciscoCA United States Abramson Cancer Center Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Parker Institute for Cancer Immunotherapy Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Center for Cellular Immunotherapies Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Microbiology Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Pathology Stanford University School of Medicine StanfordCA United States Division of Hematology-Oncology Department of Medicine Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department o

CRISPR-Cas9 genome editing has enabled advanced T cell therapies, but occasional loss of the targeted chromosome could be a safety concern. To investigate whether Cas9-induced chromosome loss is a universal phenomenon and evaluate its clinical significance, we conducted a systematic analysis in primary human T cells. Arrayed and pooled CRISPR screens revealed that partial or entire chromosome loss after Cas9-induced DNA cutting is a rare but generalized phenomenon, occurring also in pre-clinical chimeric antigen receptor T cells. T cells with chromosome loss persist for weeks in culture, implying potential interference with clinical use. A modified cell manufacturing process, employed in our first-in-human clinical trial of Cas9-engineered T cells, dramatically reduced chromosome loss while largely preserving genome editing efficacy. Expression of p53 correlated with the protection from chromosome loss observed with this protocol, suggesting both a mechanism and a strategy for T cell engineering that mitigates genotoxicity in the clinic. © 2023, The Authors. All rights reserved.

关键词： T-cells

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Glucocorticoids cause mandibular bone fragility and suppress osteocyte perilacunar-canalicular remodeling

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Bone Reports 2018年 9卷 145-153页

作者： Alemi, A. Sean Mazur, Courtney M. Fowler, Tristan W. Woo, Jonathon J. Knott, P. Daniel Alliston, Tamara Department of Otorhinolaryngology Head and Neck Surgery University of California San Francisco United States Department of Orthopaedic Surgery University of California San Francisco United States UC Berkeley-UCSF Graduate Program in Bioengineering United States

Osteocytes support dynamic, cell-intrinsic resorption and deposition of bone matrix through a process called perilacunar/canalicular remodeling (PLR). In long bones, PLR depends on MMP13 and is tightly regulated by PTH, sclerostin, TGFβ, and glucocorticoids. However, PLR is regulated differently in the cochlea, suggesting a mechanism that is anatomically distinct. Unlike long bones, the mandible derives from neural crest and exhibits unique susceptibility to medication and radiation induced osteonecrosis. Therefore, we sought to determine if PLR in the mandible is suppressed by glucocorticoids, as it is in long bone. Hemimandibles were collected from mice subcutaneously implanted with prednisolone or vehicle containing pellets for 7, 21, or 55 days (n = 8/group) for radiographic and histological analyses. Within 21 days, micro-computed tomography revealed a glucocorticoid-dependent reduction in bone volume/total volume and trabecular thickness and a significant decrease in bone mineral density after 55 days. Within 7 days, glucocorticoids strongly and persistently repressed osteocytic expression of the key PLR enzyme MMP13 in both trabecular and cortical bone of the mandible. Cathepsin K expression was significantly reduced only after 55 days of glucocorticoid treatment, at which point histological analysis revealed a glucocorticoid-dependent reduction in the lacunocanalicular surface area. In addition to reducing bone mass and suppressing PLR, glucocorticoids also reduced the stiffness of mandibular bone in flexural tests. Thus, osteocyte PLR in the neural crest-derived mandible is susceptible to glucocorticoids, just as it is in the mesodermally-derived femur, highlighting the need to further study PLR as a target of drugs, and radiation in mandibular osteonecrosis. © 2018

关键词： Glucocorticoids Mandible Osteocyte Perilacunar/canalicular remodeling

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QSMGAN: Improved quantitative susceptibility mapping using 3d generative adversarial networks with increased receptive field

arXiv

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arXiv 2019年

作者： Chen, Yicheng Jakary, Angela Hess, Christopher P. Lupo, Janine UC Berkeley-UCSF Graduate Program in Bioengineering University of California Berkeley University of California San Francisco California San FranciscoCA94158 Department of Radiology and Biomedical Imaging University of California San Francisco San FranciscoCA94158 United States

Quantitative susceptibility mapping (QSM) is a powerful MRI technique that has shown great potential in quantifying tissue susceptibility in numerous neurological disorders. However, the intrinsic ill-posed dipole inversion problem greatly affects the accuracy of the susceptibility map. We proposed QSMGAN: A 3D deep convolutional neural network approach based on improved U-Net with increased phase receptive field and further refined the network using the WGAN-GP training strategy. Our method could generate accurate and realistic QSM from single orientation phase maps efficiently and performed significantly better than traditional non-learning-based dipole inversion algorithms. Copyright © 2019, The Authors. All rights reserved.

关键词： Magnetic resonance imaging

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Extreme MRI: Large-scale volumetric dynamic imaging from continuous non-gated acquisitions

arXiv

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arXiv 2019年

作者： Ong, Frank Zhu, Xucheng Cheng, Joseph Y. Johnson, Kevin M. Larson, Peder E.Z. Vasanawala, Shreyas S. Lustig, Michael Stanford University CA United States UC Berkeley-UCSF Graduate Program in Bioengineering University of California San Francisco University of California BerkeleyCA United States University of Wisconsin MadisonWI United States University of California San FranciscoCA United States

Purpose: To develop a framework to reconstruct large-scale volumetric dynamic MRI from rapid continuous and non-gated acquisitions, with applications to pulmonary and dynamic contrast enhanced (DCE) imaging. Theory and Methods: The problem considered here is a reconstruction of hundred-gigabytes of dynamic volumetric image data from a few gigabytes of k-space data, acquired continuously over several minutes. This is a vastly under-determined optimization, with problem sizes heavily stressing compute resources as well as memory management and storage. To overcome these challenges, we leverage intrinsic three dimensional (3D) trajectories, such as 3D radial and 3D cones, with ordering that incoherently cover time and k-space over the entire acquisition. We then propose two innovations: (1) A compressed representation using multi-scale low rank matrix factorization that both constrains the reconstruction problem and reduces its memory footprint. (2) Stochastic optimization to reduce computation, improve memory locality and minimize communications between threads and processors. We demonstrate the feasibility of the proposed method on DCE imaging acquired with a golden-angle ordered 3D cones trajectory and pulmonary imaging acquired with a bit-reversed ordered 3D radial trajectory. We compare it with "soft-gated" dynamic reconstruction for DCE and respiratory resolved reconstruction for pulmonary imaging. Results: The proposed technique shows transient dynamics that are not seen in gating based methods. When applied to datasets with irregular, or non-repetitive motions, the proposed method also displays sharper image features. Conclusion: We demonstrated a method that can reconstruct massive 3D dynamic image series in the extreme undersampling and extreme computation setting. Copyright © 2019, The Authors. All rights reserved.

关键词： Magnetic resonance imaging

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Iterative Motion Compensation reconstruction ultra-short TE(iMoCo UTE) for high resolution free breathing pulmonary MRI

arXiv

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arXiv 2020年

作者： Zhu, Xucheng Chan, Marilynn Lustig, Michael Johnson, Kevin Larson, Peder E.Z. UCSF/UC Berkeley Graduate Program in Bioengineering University of California San Francisco San FranciscoCA United States Department of Radiology and Biomedical Imaging University of California San Francisco San FranciscoCA United States Department of Pediatrics Division of Pediatric Pulmonology University of California San Francisco San FranciscoCA United States Department of Electrical Engineering and Computer Sciences University of California Berkeley BerkeleyCA United States Department of Medical Physics University of Wisconsin Madison MadisonWI United States Department of Radiology University of Wisconsin Madison MadisonWI United States

Purpose: To develop a high scanning efficiency, motion corrected imaging strategy for free-breathing pulmonary MRI by combining a motion compensation reconstruction with a UTE acquisition, called iMoCo UTE. Methods: An optimized golden angle ordering radial UTE sequence was used to continuously acquire data for 5 minutes. All readouts were grouped to different respiratory motion states based on self-navigator signals, then motion resolved data was reconstructed by XD Golden-angle RAdial Sparse Parallel reconstruction (XD-GRASP). One state from the motion resolved images was selected as a reference, and motion fields from the other states to the reference were derived via non-rigid registration. Finally, all motion resolved data and motion fields were reconstructed by using an iterative motion compensation reconstruction with a total generalized variation sparse constraint. Results: The iMoCo UTE strategy was evaluated in volunteers and non-sedated pediatric patient(4-6 y/o) studies. Images reconstructed with iMoCo UTE provided sharper anatomical lung structures, and higher apparent SNR and CNR, compared to using other motion correction strategies, such as soft-gating, motion resolved reconstruction, and non-rigid motion compensation(MoCo). iMoCo UTE also showed promising results in an infant study. Conclusions: The proposed iMoCo UTE combines self-navigation, motion modeling, and a compressed sensing reconstruction to increase scan efficiency, SNR, and reduce respiratory motion in lung MRI. This proposed strategy shows improvements in free breathing lung MRI scans, especially in very challenging application situations, such as pediatric MRI studies. Copyright © 2020, The Authors. All rights reserved.

关键词： Magnetic resonance imaging

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Synthetic CT Generation Using MRI with Deep Learning: How Does the Selection of Input Images Affect the Resulting Synthetic CT?

Synthetic CT Generation Using MRI with Deep Learning: How Do...

引用

IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Andrew P. Leynes Peder E. Z. Larson UC Berkeley - UC San Francisco Joint Graduate Program in Bioengineering

ISBN: (纸本)9781538646595

Synthetic x-ray computed tomography (CT) images derived from magnetic resonance imaging (MRI) is a recent area of focus for medical imaging researchers for applications in attenuation correction in simultaneous PET/MRI systems and MRI-guided radiotherapy planning. Several research groups have demonstrated the potential of deep learning to generate the synthetic CT images, however, there are several major open questions that remain with this approach. We investigated how the selection of MRI inputs affect the resulting output using a fixed network. We found that Dixon MRI may be sufficient for quantitatively accurate synthetic CT images and ZTE MRI may provide additional information to capture bowel air distributions.

关键词： synthetic ct deep learning mri Dixon mri zero echo-time mri

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