scholarly journals A platform for post-translational spatiotemporal control of cellular proteins

2021 ◽  
Author(s):  
Brianna Jayanthi ◽  
Bhagyashree Bachhav ◽  
Zengyi Wan ◽  
Santiago Martinez Legaspi ◽  
Laura Segatori
Keyword(s):  
Subcellular Localization ◽  
Protein Function ◽  
Mammalian Cells ◽  
Protein Localization ◽  
Genetic Circuits ◽  
Bifunctional Molecules ◽  
Protein Levels ◽  
Synthetic Gene Circuits ◽  
Spatiotemporal Regulation ◽  
Innovative Tool

Abstract Mammalian cells process information through coordinated spatiotemporal regulation of proteins. Engineering cellular networks thus relies on efficient tools for regulating protein levels in specific subcellular compartments. To address the need to manipulate the extent and dynamics of protein localization, we developed a platform technology for target-specific control of protein destination. This platform is based on bifunctional molecules comprising a target-specific nanobody and universal sequences determining target subcellular localization or degradation rate. We demonstrate that nanobody-mediated localization depends on the expression level of the target and the nanobody, and the extent of target subcellular localization can be regulated by combining multiple target-specific nanobodies with distinct localization or degradation sequences. We also show that this platform for nanobody-mediated target localization and degradation can be regulated transcriptionally and integrated within orthogonal genetic circuits to achieve the desired temporal control over spatial regulation of target proteins. The platform reported in this study provides an innovative tool to control protein subcellular localization which will be useful to investigate protein function and regulate large synthetic gene circuits.

scholarly journals Organellar Maps Through Proteomic Profiling – A Conceptual Guide

2020 ◽  
Vol 19 (7) ◽  
pp. 1076-1087 ◽  
Author(s):  
Georg H. H. Borner
Keyword(s):  
Mass Spectrometry ◽  
High Resolution ◽  
Subcellular Localization ◽  
Protein Function ◽  
Protein Localization ◽  
Proteomic Profiling ◽  
Protein Subcellular Localization ◽  
Single Experiment ◽  
Flexible Approach ◽  
Resolution Cell

Protein subcellular localization is an essential and highly regulated determinant of protein function. Major advances in mass spectrometry and imaging have allowed the development of powerful spatial proteomics approaches for determining protein localization at the whole cell scale. Here, a brief overview of current methods is presented, followed by a detailed discussion of organellar mapping through proteomic profiling. This relatively simple yet flexible approach is rapidly gaining popularity, because of its ability to capture the localizations of thousands of proteins in a single experiment. It can be used to generate high-resolution cell maps, and as a tool for monitoring protein localization dynamics. This review highlights the strengths and limitations of the approach and provides guidance to designing and interpreting profiling experiments.

scholarly journals Global, quantitative and dynamic mapping of protein subcellular localization

eLife ◽  
2016 ◽  
Vol 5 ◽  
Author(s):  
Daniel N Itzhak ◽  
Stefka Tyanova ◽  
Jürgen Cox ◽  
Georg HH Borner
Keyword(s):  
Subcellular Localization ◽  
Protein Function ◽  
Cell Biology ◽  
Dynamic Capabilities ◽  
Protein Translocation ◽  
Protein Localization ◽  
Quantitative Model ◽  
Dynamic Mapping ◽  
Global Mapping ◽  
Control Protein

Subcellular localization critically influences protein function, and cells control protein localization to regulate biological processes. We have developed and applied Dynamic Organellar Maps, a proteomic method that allows global mapping of protein translocation events. We initially used maps statically to generate a database with localization and absolute copy number information for over 8700 proteins from HeLa cells, approaching comprehensive coverage. All major organelles were resolved, with exceptional prediction accuracy (estimated at >92%). Combining spatial and abundance information yielded an unprecedented quantitative view of HeLa cell anatomy and organellar composition, at the protein level. We subsequently demonstrated the dynamic capabilities of the approach by capturing translocation events following EGF stimulation, which we integrated into a quantitative model. Dynamic Organellar Maps enable the proteome-wide analysis of physiological protein movements, without requiring any reagents specific to the investigated process, and will thus be widely applicable in cell biology.

scholarly journals GP4: an integrated Gram-Positive Protein Prediction Pipeline for subcellular localization mimicking bacterial sorting

2020 ◽  
Author(s):  
Stefano Grasso ◽  
Tjeerd van Rij ◽  
Jan Maarten van Dijl
Keyword(s):  
Subcellular Localization ◽  
Protein Function ◽  
Drug Targets ◽  
Protein Localization ◽  
Homologous Proteins ◽  
Gram Positive ◽  
Cell Factories ◽  
Sorting Signals ◽  
Protein Prediction ◽  
Improved Performance

Abstract Subcellular localization is a critical aspect of protein function and the potential application of proteins either as drugs or drug targets, or in industrial and domestic applications. However, the experimental determination of protein localization is time consuming and expensive. Therefore, various localization predictors have been developed for particular groups of species. Intriguingly, despite their major representation amongst biotechnological cell factories and pathogens, a meta-predictor based on sorting signals and specific for Gram-positive bacteria was still lacking. Here we present GP4, a protein subcellular localization meta-predictor mainly for Firmicutes, but also Actinobacteria, based on the combination of multiple tools, each specific for different sorting signals and compartments. Novelty elements include improved cell-wall protein prediction, including differentiation of the type of interaction, prediction of non-canonical secretion pathway target proteins, separate prediction of lipoproteins and better user experience in terms of parsability and interpretability of the results. GP4 aims at mimicking protein sorting as it would happen in a bacterial cell. As GP4 is not homology based, it has a broad applicability and does not depend on annotated databases with homologous proteins. Non-canonical usage may include little studied or novel species, synthetic and engineered organisms, and even re-use of the prediction data to develop custom prediction algorithms. Our benchmark analysis highlights the improved performance of GP4 compared to other widely used subcellular protein localization predictors. A webserver running GP4 is available at http://gp4.hpc.rug.nl/

scholarly journals Precision Tools in Immuno-Oncology: Synthetic Gene Circuits for Cancer Immunotherapy

Vaccines ◽  
2020 ◽  
Vol 8 (4) ◽  
pp. 732
Author(s):  
Giuliano Bonfá ◽  
Juan Blazquez-Roman ◽  
Rita Tarnai ◽  
Velia Siciliano
Keyword(s):  
T Cells ◽  
Synthetic Biology ◽  
Cancer Immunotherapy ◽  
Mammalian Cells ◽  
Special Focus ◽  
Genetic Circuits ◽  
Cell Therapies ◽  
Car T Cells ◽  
Synthetic Gene Circuits ◽  
Car T

Engineered mammalian cells for medical purposes are becoming a clinically relevant reality thanks to advances in synthetic biology that allow enhanced reliability and safety of cell-based therapies. However, their application is still hampered by challenges including time-consuming design-and-test cycle iterations and costs. For example, in the field of cancer immunotherapy, CAR-T cells targeting CD19 have already been clinically approved to treat several types of leukemia, but their use in the context of solid tumors is still quite inefficient, with additional issues related to the adequate quality control for clinical use. These limitations can be overtaken by innovative bioengineering approaches currently in development. Here we present an overview of recent synthetic biology strategies for mammalian cell therapies, with a special focus on the genetic engineering improvements on CAR-T cells, discussing scenarios for the next generation of genetic circuits for cancer immunotherapy.

Single-Molecule Imaging of Active Mitochondrial Nitroreductases using a Photo-Crosslinking Fluorescent Sensor

2019 ◽  
Author(s):  
Zacharias Thiel ◽  
Pablo Rivera-Fuentes
Keyword(s):  
Subcellular Localization ◽  
Fluorescent Probe ◽  
Single Molecule ◽  
Mammalian Cells ◽  
Fluorescent Sensor ◽  
Biological Functions ◽  
Localization Microscopy ◽  
Drug Activation ◽  
Nitroreductase Activity ◽  
Single Molecule Localization Microscopy

Many biomacromolecules are known to cluster in microdomains with specific subcellular localization. In the case of enzymes, this clustering greatly defines their biological functions. Nitroreductases are enzymes capable of reducing nitro groups to amines and play a role in detoxification and pro-drug activation. Although nitroreductase activity has been detected in mammalian cells, the subcellular localization of this activity remains incompletely characterized. Here, we report a fluorescent probe that enables super-resolved imaging of pools of nitroreductase activity within mitochondria. This probe is activated sequentially by nitroreductases and light to give a photo-crosslinked adduct of active enzymes. In combination with a general photoactivatable marker of mitochondria, we performed two-color, threedimensional, single-molecule localization microscopy. These experiments allowed us to image the sub-mitochondrial organization of microdomains of nitroreductase activity.<br>

Single-Molecule Imaging of Active Mitochondrial Nitroreductases using a Photo-Crosslinking Fluorescent Sensor

2019 ◽  
Author(s):  
Zacharias Thiel ◽  
Pablo Rivera-Fuentes
Keyword(s):  
Subcellular Localization ◽  
Fluorescent Probe ◽  
Single Molecule ◽  
Mammalian Cells ◽  
Fluorescent Sensor ◽  
Biological Functions ◽  
Localization Microscopy ◽  
Drug Activation ◽  
Nitroreductase Activity ◽  
Single Molecule Localization Microscopy

Many biomacromolecules are known to cluster in microdomains with specific subcellular localization. In the case of enzymes, this clustering greatly defines their biological functions. Nitroreductases are enzymes capable of reducing nitro groups to amines and play a role in detoxification and pro-drug activation. Although nitroreductase activity has been detected in mammalian cells, the subcellular localization of this activity remains incompletely characterized. Here, we report a fluorescent probe that enables super-resolved imaging of pools of nitroreductase activity within mitochondria. This probe is activated sequentially by nitroreductases and light to give a photo-crosslinked adduct of active enzymes. In combination with a general photoactivatable marker of mitochondria, we performed two-color, threedimensional, single-molecule localization microscopy. These experiments allowed us to image the sub-mitochondrial organization of microdomains of nitroreductase activity.<br>

PHOTACs Enable Optical Control of Protein Degradation

2019 ◽  
Author(s):  
Martin Reynders ◽  
Bryan Matsuura ◽  
Marleen Bérouti ◽  
Daniele Simoneschi ◽  
Antonio Marzio ◽  
...  
Keyword(s):  
Protein Degradation ◽  
E3 Ligase ◽  
Optical Control ◽  
Cellular Proteins ◽  
Bifunctional Molecules ◽  
Protein Levels ◽  
Lead Compounds ◽  
Subsequent Degradation ◽  
Temporal And Spatial ◽  
Precision Therapeutics

<p><i>PROTACs (proteolysis targeting chimeras) are bifunctional molecules that tag proteins for ubiquitylation by an E3 ligase complex and subsequent degradation by the proteasome. They have emerged as powerful tools to control the levels of specific cellular proteins and are on the verge of being clinically used. We now introduce photoswitchable PROTACs that can be activated with the temporal and spatial precision that light provides. These trifunctional molecules, which we named PHOTACs, consist of a ligand for an E3 ligase, a photoswitch, and a ligand for a protein of interest. We demonstrate this concept by using PHOTACs that target either BET family proteins (BRD2,3,4) or FKBP12. Our lead compounds display little or no activity in the dark but can be reversibly activated to varying degrees with different wavelengths of light. Our modular and generalizable approach provides a method for the optical control of protein levels with photopharmacology and could lead to new types of precision therapeutics that avoid undesired systemic toxicity.</i><b></b></p>

scholarly journals Model-guided design of mammalian genetic programs

2021 ◽  
Vol 7 (8) ◽  
pp. eabe9375
Author(s):  
J. J. Muldoon ◽  
V. Kandula ◽  
M. Hong ◽  
P. S. Donahue ◽  
J. D. Boucher ◽  
...  
Keyword(s):  
Mammalian Cells ◽  
Computational Models ◽  
Biological Complexity ◽  
Genetic Circuits ◽  
Cellular Functions ◽  
High Performing ◽  
Design Objective ◽  
Complex Functions ◽  
Mammalian Genetic ◽  
Analog Processing

Genetically engineering cells to perform customizable functions is an emerging frontier with numerous technological and translational applications. However, it remains challenging to systematically engineer mammalian cells to execute complex functions. To address this need, we developed a method enabling accurate genetic program design using high-performing genetic parts and predictive computational models. We built multifunctional proteins integrating both transcriptional and posttranslational control, validated models for describing these mechanisms, implemented digital and analog processing, and effectively linked genetic circuits with sensors for multi-input evaluations. The functional modularity and compositional versatility of these parts enable one to satisfy a given design objective via multiple synonymous programs. Our approach empowers bioengineers to predictively design mammalian cellular functions that perform as expected even at high levels of biological complexity.

Phospholipase D1b and D2a generate structurally identical phosphatidic acid species in mammalian cells

2001 ◽  
Vol 360 (3) ◽  
pp. 707-715 ◽  
Author(s):  
Trevor R. PETTITT ◽  
Mark McDERMOTT ◽  
Khalid M. SAQIB ◽  
Neil SHIMWELL ◽  
Michael J. O. WAKELAM
Keyword(s):  
Liquid Chromatography ◽  
Phosphatidic Acid ◽  
Phospholipase D ◽  
Mammalian Cells ◽  
Inducible Promoter ◽  
In Vitro Assays ◽  
Protein Levels ◽  
Intracellular Messenger

Mammalian cells contain different phospholipase D enzymes (PLDs) whose distinct physiological roles are poorly understood and whose products have not been characterized. The development of porcine aortic endothelial (PAE) cell lines able to overexpress PLD-1b or −2a under the control of an inducible promoter has enabled us to characterize both the substrate specificity and the phosphatidic acid (PtdOH) product of these enzymes under controlled conditions. Liquid chromatography–MS analysis showed that PLD1b- and PLD2a-transfected PAE cells, as well as COS7 and Rat1 cells, generate similar PtdOH and, in the presence of butan-1-ol, phosphatidylbutanol (PtdBut) profiles, enriched in mono- and di-unsaturated species, in particular 16:0/18:1. Although PtdBut mass increased, the species profile did not change in cells stimulated with ATP or PMA. Overexpression of PLD made little difference to basal or stimulated PtdBut formation, indicating that activity is tightly regulated in vivo and that factors other than just PLD protein levels limit hydrolytic function. In vitro assays using PLD-enriched lysates showed that the enzyme could utilize both phosphatidylcholine and, much less efficiently, phosphatidylethanolamine, with slight selectivity towards mono- and di-unsaturated species. Phosphatidylinositol was not a substrate. Thus PLD1b and PLD2a hydrolyse a structurally similar substrate pool to generate an identical PtdOH product enriched in mono- and di-unsaturated species that we propose to function as the intracellular messenger forms of this lipid.

scholarly journals Convolutional Neural Network-Based Artificial Intelligence for Classification of Protein Localization Patterns

Biomolecules ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 264
Author(s):  
Kaisa Liimatainen ◽  
Riku Huttunen ◽  
Leena Latonen ◽  
Pekka Ruusuvuori
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Convolutional Neural Network ◽  
High Throughput ◽  
Protein Function ◽  
Protein Localization ◽  
Convolutional Network ◽  
High Throughput Analysis ◽  
Fully Convolutional Network

Identifying localization of proteins and their specific subpopulations associated with certain cellular compartments is crucial for understanding protein function and interactions with other macromolecules. Fluorescence microscopy is a powerful method to assess protein localizations, with increasing demand of automated high throughput analysis methods to supplement the technical advancements in high throughput imaging. Here, we study the applicability of deep neural network-based artificial intelligence in classification of protein localization in 13 cellular subcompartments. We use deep learning-based on convolutional neural network and fully convolutional network with similar architectures for the classification task, aiming at achieving accurate classification, but importantly, also comparison of the networks. Our results show that both types of convolutional neural networks perform well in protein localization classification tasks for major cellular organelles. Yet, in this study, the fully convolutional network outperforms the convolutional neural network in classification of images with multiple simultaneous protein localizations. We find that the fully convolutional network, using output visualizing the identified localizations, is a very useful tool for systematic protein localization assessment.

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