Pub Date : 2024-09-07DOI: 10.1101/2024.09.03.611064
Qufei Gu, Nathan Ming, Yalikunjiang Aizezi, Xiaoyang Wei, Yizhong Yuan, Brian Esquivel, Zhi-Yong Wang
While many variations of protein delivery methods have been described, it can still be difficult or inefficient to introduce exogenous proteins into plants. A major barrier to progress is the cell wall which is primarily composed of polysaccharides and thus only permeable to small molecules. Here, we report a partial enzymatic cell wall digestion-mediated uptake method that efficiently delivers protein into the nucleus of plant cells. Such a method allowed efficient nuclear delivery of GFP proteins into Arabidopsis root cells throughout all cell layers. This study establishes that a partial enzymatic cell wall degradation could enable a myriad of plant biotechnology applications that rely on functional protein delivery into walled plant cells.
{"title":"Direct Nuclear Delivery of Proteins on Living Plant via Partial Enzymatic Cell Wall Digestion","authors":"Qufei Gu, Nathan Ming, Yalikunjiang Aizezi, Xiaoyang Wei, Yizhong Yuan, Brian Esquivel, Zhi-Yong Wang","doi":"10.1101/2024.09.03.611064","DOIUrl":"https://doi.org/10.1101/2024.09.03.611064","url":null,"abstract":"While many variations of protein delivery methods have been described, it can still be difficult or inefficient to introduce exogenous proteins into plants. A major barrier to progress is the cell wall which is primarily composed of polysaccharides and thus only permeable to small molecules. Here, we report a partial enzymatic cell wall digestion-mediated uptake method that efficiently delivers protein into the nucleus of plant cells. Such a method allowed efficient nuclear delivery of GFP proteins into Arabidopsis root cells throughout all cell layers. This study establishes that a partial enzymatic cell wall degradation could enable a myriad of plant biotechnology applications that rely on functional protein delivery into walled plant cells.","PeriodicalId":501308,"journal":{"name":"bioRxiv - Bioengineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142216642","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-06DOI: 10.1101/2024.09.03.611015
Cameron A. B. Smith, Matthieu Toulemonde, Marcelo Lerendegui, Kai Riemer, Dina Malounda, Peter D. Weinberg, Mikhail G. Shapiro, Meng-Xing Tang
Ultrasound imaging is a valuable clinical tool. It is commonly achieved using the delay and sum beamformer algorithm, which takes the signals received by an array of sensors and generates an image estimating the spatial distribution of the signal sources. This algorithm, while computationally efficient, has limited resolution and suffers from high side lobes. Nonlinear processing has proven to be an effective way to enhance the image quality produced by beamforming in a computationally efficient manner. In this work, we describe a new beamforming algorithm called Cross-Angular Delay Multiply and Sum, which takes advantage of nonlinear compounding to enhance contrast and resolution. This is then implemented with a mathematical reformulation to produce images with tighter point spread functions and enhanced contrast at a low computational cost. We tested this new algorithm over a range of in vitro and in vivo scenarios for both conventional B-Mode and amplitude modulation imaging, and for two types of ultrasound contrast agents, demonstrating its potential for clinical settings.
{"title":"Enhanced Ultrasound Image Formation with Computationally Efficient Cross-Angular Delay Multiply and Sum Beamforming","authors":"Cameron A. B. Smith, Matthieu Toulemonde, Marcelo Lerendegui, Kai Riemer, Dina Malounda, Peter D. Weinberg, Mikhail G. Shapiro, Meng-Xing Tang","doi":"10.1101/2024.09.03.611015","DOIUrl":"https://doi.org/10.1101/2024.09.03.611015","url":null,"abstract":"Ultrasound imaging is a valuable clinical tool. It is commonly achieved using the delay and sum beamformer algorithm, which takes the signals received by an array of sensors and generates an image estimating the spatial distribution of the signal sources. This algorithm, while computationally efficient, has limited resolution and suffers from high side lobes. Nonlinear processing has proven to be an effective way to enhance the image quality produced by beamforming in a computationally efficient manner. In this work, we describe a new beamforming algorithm called Cross-Angular Delay Multiply and Sum, which takes advantage of nonlinear compounding to enhance contrast and resolution. This is then implemented with a mathematical reformulation to produce images with tighter point spread functions and enhanced contrast at a low computational cost. We tested this new algorithm over a range of in vitro and in vivo scenarios for both conventional B-Mode and amplitude modulation imaging, and for two types of ultrasound contrast agents, demonstrating its potential for clinical settings.","PeriodicalId":501308,"journal":{"name":"bioRxiv - Bioengineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142216643","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-06DOI: 10.1101/2024.09.03.610922
Claudio Mueller, Thomas Vuillemin, Chethana Janardhana Gadiyar, Jonathan Souquet, Jean Marc Bielser, Alessandro Fagnani, Michae Sokolov, Moritz von Stosch, Fabian Feidl, Alessandro Butte, Mariano Nicolas Cruz Bournazou
It is essential to increase the number of autonomous agents bioprocess development for biopharma innovation to shorten time and resource utilization in the path from product to process. While robotics and machine learning have significantly accelerated drug discovery and initial screening, the later stages of development have seen improvement only in the experimental automation but lack advanced computational tools for experimental planning and execution. For instance, during development of new monoclonal antibodies, the search for optimal upstream conditions (feeding strategy, pH, temperature, media composition, etc.) is often performed in highly advanced high-throughput (HT) mini-bioreactor systems. However, the integration of machine learning tools for experiment design and operation in these systems remains underdeveloped. In this study, we introduce an integrated framework composed by a Bayesian experimental design algorithm, a cognitive digital twin of the cultivation system, and an advanced 24 parallel mini-bioreactor perfusion experimental setup. The result is an autonomous experimental machine capable of 1. embedding existing process knowledge, 2. learning during experimentation, 3. Using information from similar processes, 4. Notifying events in the near future, and 5. Autonomously operating the parallel cultivation setup to reach challenging objectives. As a proof of concept, we present experimental results of 27 days long cultivations operated by an autonomous software agent reaching challenging goals as are increasing the VCV and maximizing the viability of the cultivation up to its end.
{"title":"Self-driving development of perfusion processes for monoclonal antibody production","authors":"Claudio Mueller, Thomas Vuillemin, Chethana Janardhana Gadiyar, Jonathan Souquet, Jean Marc Bielser, Alessandro Fagnani, Michae Sokolov, Moritz von Stosch, Fabian Feidl, Alessandro Butte, Mariano Nicolas Cruz Bournazou","doi":"10.1101/2024.09.03.610922","DOIUrl":"https://doi.org/10.1101/2024.09.03.610922","url":null,"abstract":"It is essential to increase the number of autonomous agents bioprocess development for biopharma innovation to shorten time and resource utilization in the path from product to process. While robotics and machine learning have significantly accelerated drug discovery and initial screening, the later stages of development have seen improvement only in the experimental automation but lack advanced computational tools for experimental planning and execution. For instance, during development of new monoclonal antibodies, the search for optimal upstream conditions (feeding strategy, pH, temperature, media composition, etc.) is often performed in highly advanced high-throughput (HT) mini-bioreactor systems. However, the integration of machine learning tools for experiment design and operation in these systems remains underdeveloped. In this study, we introduce an integrated framework composed by a Bayesian experimental design algorithm, a cognitive digital twin of the cultivation system, and an advanced 24 parallel mini-bioreactor perfusion experimental setup. The result is an autonomous experimental machine capable of 1. embedding existing process knowledge, 2. learning during experimentation, 3. Using information from similar processes, 4. Notifying events in the near future, and 5. Autonomously operating the parallel cultivation setup to reach challenging objectives. As a proof of concept, we present experimental results of 27 days long cultivations operated by an autonomous software agent reaching challenging goals as are increasing the VCV and maximizing the viability of the cultivation up to its end.","PeriodicalId":501308,"journal":{"name":"bioRxiv - Bioengineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142216648","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-06DOI: 10.1101/2024.09.05.611463
Édouard Delaire, Thomas Vincent, Zhengchen Cai, Alexis Machado, Laurent hugueville, Denis Schwartz, Francois Tadel, Raymundo Cassani, Louis Bherer, jean-marc JM Lina, Mélanie Pélégrini-Issac, Christophe Grova
Significance: We propose NIRSTORM, a software package built within Brainstorm environment, enabling full data analysis of functional Near InfraRed Spectroscopy (fNIRS) data from experiment planning to 3D reconstruction of hemodynamic fluctuations on the cortical surface using optical tomographic approaches. NIRSTORM enables the integration of fNIRS analysis within a multimodal setup making it easy to study fNIRS in combination with other multimodal data such as electroencephalography (EEG) or magnetic resonance imaging (MRI). Aim: NIRSTORM aims to provide an easy-to-use and fully modular toolbox for fNIRS analysis from experimental planning to optical tomography 3D reconstruction extending Brainstorm capacity for multimodal analysis. Approach: NIRSTORM was developed in MATLAB ® and integrated as a plugin of the software Brainstorm. Brainstorm is a GUI-oriented, widely used software originally dedicated to statistical analysis and source imaging of EEG and magnetoencephalography (MEG) data. Results: In addition to conventional fNIRS preprocessing steps, including standard channel space and statistical analyses, NIRSTORM provides advanced methods dedicated to optimal probe placement, allowing personalized fNIRS study designs and accurate near-infrared optical tomography within the Maximum Entropy on the Mean (MEM) framework. Conclusion: NIRSTORM is an open-access, user-friendly plugin extending the capacity of Brainstorm, for fNIRS analysis, therefore narrowing the gap between EEG/MEG and hemodynamics.
{"title":"NIRSTORM: a Brainstorm extension dedicated to functional Near Infrared Spectroscopy (fNIRS) data analysis, advanced 3D reconstructions, and optimal probe design.","authors":"Édouard Delaire, Thomas Vincent, Zhengchen Cai, Alexis Machado, Laurent hugueville, Denis Schwartz, Francois Tadel, Raymundo Cassani, Louis Bherer, jean-marc JM Lina, Mélanie Pélégrini-Issac, Christophe Grova","doi":"10.1101/2024.09.05.611463","DOIUrl":"https://doi.org/10.1101/2024.09.05.611463","url":null,"abstract":"Significance: We propose NIRSTORM, a software package built within Brainstorm environment, enabling full data analysis of functional Near InfraRed Spectroscopy (fNIRS) data from experiment planning to 3D reconstruction of hemodynamic fluctuations on the cortical surface using optical tomographic approaches. NIRSTORM enables the integration of fNIRS analysis within a multimodal setup making it easy to study fNIRS in combination with other multimodal data such as electroencephalography (EEG) or magnetic resonance imaging (MRI). Aim: NIRSTORM aims to provide an easy-to-use and fully modular toolbox for fNIRS analysis from experimental planning to optical tomography 3D reconstruction extending Brainstorm capacity for multimodal analysis.\u0000Approach: NIRSTORM was developed in MATLAB ® and integrated as a plugin of the software Brainstorm. Brainstorm is a GUI-oriented, widely used software originally dedicated to statistical analysis and source imaging of EEG and magnetoencephalography (MEG) data. Results: In addition to conventional fNIRS preprocessing steps, including standard channel space and statistical analyses, NIRSTORM provides advanced methods dedicated to optimal probe placement, allowing personalized fNIRS study designs and accurate near-infrared optical tomography within the Maximum Entropy on the Mean (MEM) framework. Conclusion: NIRSTORM is an open-access, user-friendly plugin extending the capacity of Brainstorm, for fNIRS analysis, therefore narrowing the gap between EEG/MEG and hemodynamics.","PeriodicalId":501308,"journal":{"name":"bioRxiv - Bioengineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142216660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-06DOI: 10.1101/2024.09.03.611001
Katelyn Neuman, Abigail N Koppes, Ryan A Koppes
Mesenchymal stem cells (MSCs) are a promising source of stem cells for treating peripheral nerve injuries. Here, we present the first investigation of differentiation of olfactory mucosa-derived MSC (OM-MSC) towards a Schwann Cell (SC)-like phenotype. OM-MSCs are an advantageous potential source of SCs for peripheral nerve repair, as isolation can be accomplished with a minimally invasive procedure compared to autologous nerve harvest and isolation. Here, Schwann Cell Conditioned Media (SCCM) or a defined growth factor supplemented media (GF) was applied to OM-MSC for twenty-one days. The differentiation process and resulting populations were characterized by immunocytochemistry and RT-qPCR. Functionality of differentiated populations was assessed in an in vitro co-culture model to evaluate interaction with sensory neurons (dorsal root ganglia) juxtaposed to native SCs. Compared to undifferentiated MSCs, differentiation protocols resulted in significant changes in morphology, gene expression, and functionality using SCCM and GF media, representing key characteristics of SCs. Specifically, differentiated populations exhibit elongated, spindle-like morphologies, a high degree of eccentricity, increased S-100, CD44, and NGF expression, and colocalization of myelin basic proteins with neurites in the co-culture model. In conclusion, this work highlights the potential of OM-MSCs to be expanded and differentiated to SCs to improve synthetic scaffolds or for use in decellularized allografts for nerve repair.
{"title":"Olfactory Mucosa-Derived Mesenchymal Stem Cells Differentiate Towards a Schwann Cell-Like Phenotype Towards Sourcing for Peripheral Nerve Regeneration","authors":"Katelyn Neuman, Abigail N Koppes, Ryan A Koppes","doi":"10.1101/2024.09.03.611001","DOIUrl":"https://doi.org/10.1101/2024.09.03.611001","url":null,"abstract":"Mesenchymal stem cells (MSCs) are a promising source of stem cells for treating peripheral nerve injuries. Here, we present the first investigation of differentiation of olfactory mucosa-derived MSC (OM-MSC) towards a Schwann Cell (SC)-like phenotype. OM-MSCs are an advantageous potential source of SCs for peripheral nerve repair, as isolation can be accomplished with a minimally invasive procedure compared to autologous nerve harvest and isolation. Here, Schwann Cell Conditioned Media (SCCM) or a defined growth factor supplemented media (GF) was applied to OM-MSC for twenty-one days. The differentiation process and resulting populations were characterized by immunocytochemistry and RT-qPCR. Functionality of differentiated populations was assessed in an in vitro co-culture model to evaluate interaction with sensory neurons (dorsal root ganglia) juxtaposed to native SCs. Compared to undifferentiated MSCs, differentiation protocols resulted in significant changes in morphology, gene expression, and functionality using SCCM and GF media, representing key characteristics of SCs. Specifically, differentiated populations exhibit elongated, spindle-like morphologies, a high degree of eccentricity, increased S-100, CD44, and NGF expression, and colocalization of myelin basic proteins with neurites in the co-culture model. In conclusion, this work highlights the potential of OM-MSCs to be expanded and differentiated to SCs to improve synthetic scaffolds or for use in decellularized allografts for nerve repair.","PeriodicalId":501308,"journal":{"name":"bioRxiv - Bioengineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142216645","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-06DOI: 10.1101/2024.09.01.609623
A M Shahruj Rashid, Bryan Carmichael, Charlize Su, Keming Shi, Keefe Lim, Poorvika Senthil Kumar, Ngok Jeun Wan, Eshaan Govil, Dennis Yap
Despite significant advancements in deception detection, traditional methods often fall short in real-world applications. This study addresses these limitations by evaluating the effectiveness of various physiological measures Pupil Response, Electrodermal Activity (EDA), Heart Rate (HR), and facial temperature changes in predicting deception using the Comparison Question Test (CQT). It also fills a critical research gap by validating these methods within an Asian context. Employing a between-subjects design, data was collected from a diverse sample of 118 participants from Singapore, including Chinese, Indian, and Malay individuals. The research aims to identify which physiological indicators, in combination, offer the most robust predictions of deceptive behavior. Key innovations include the adaptation of the CQT with a modified directed lie paradigm and an expanded sample size to assess the relative importance of each physiological measure. The study's findings reveal that Pupil Response is the most significant predictor of deception, with EDA enhancing the model's explanatory power. HR, while relevant, adds limited value when combined with Pupil Response and EDA, and facial temperature changes were statistically non-significant. The study highlights the need for further research into the interactions among physiological measures and their application in varied contexts. This research contributes valuable insights into improving deception detection methodologies and sets the stage for future investigations that could incorporate additional physiological indicators and explore real-world applications.
{"title":"Evaluating Physiological Indicators in Detecting Deception using the Comparison Question Test (CQT)","authors":"A M Shahruj Rashid, Bryan Carmichael, Charlize Su, Keming Shi, Keefe Lim, Poorvika Senthil Kumar, Ngok Jeun Wan, Eshaan Govil, Dennis Yap","doi":"10.1101/2024.09.01.609623","DOIUrl":"https://doi.org/10.1101/2024.09.01.609623","url":null,"abstract":"Despite significant advancements in deception detection, traditional methods often fall short in real-world applications. This study addresses these limitations by evaluating the effectiveness of various physiological measures Pupil Response, Electrodermal Activity (EDA), Heart Rate (HR), and facial temperature changes in predicting deception using the Comparison Question Test (CQT). It also fills a critical research gap by validating these methods within an Asian context. Employing a between-subjects design, data was collected from a diverse sample of 118 participants from Singapore, including Chinese, Indian, and Malay individuals. The research aims to identify which physiological indicators, in combination, offer the most robust predictions of deceptive behavior. Key innovations include the adaptation of the CQT with a modified directed lie paradigm and an expanded sample size to assess the relative importance of each physiological measure. The study's findings reveal that Pupil Response is the most significant predictor of deception, with EDA enhancing the model's explanatory power. HR, while relevant, adds limited value when combined with Pupil Response and EDA, and facial temperature changes were statistically non-significant. The study highlights the need for further research into the interactions among physiological measures and their application in varied contexts. This research contributes valuable insights into improving deception detection methodologies and sets the stage for future investigations that could incorporate additional physiological indicators and explore real-world applications.","PeriodicalId":501308,"journal":{"name":"bioRxiv - Bioengineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142216647","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-06DOI: 10.1101/2024.09.03.610954
Jishizhan Chen, Alissa L Parmenter, Aikta Sharma, Elis Newham, Eral Bele, Sebastian Marussi, Andrew A Pitsillides, Nick J Terrill, Himadri S Gupta, Peter D Lee
Lower back pain is linked to vertebral biomechanics, with vertebral endplates (VEPs) playing a key role in vertebral load transfer and distribution. Synchrotron computed tomography (sCT) allows for detailed visualisation of the microstructure of intact VEPs under near-physiological loads and, when coupled with digital volume correlation (DVC), can be used to quantify three-dimensional (3D) strain fields with nanoscale resolution. Herein, we spatially couple DVC data and an image-based finite element model (FEM) to determine the material properties of murine VEPs. This model was then extended to investigate VEP biomechanics under different motions and disease conditions to reveal that VEP protrusions are important for load absorption and redistribution under different motions and predicted that abnormal intervertebral disc (IVD) stress may underpin osteoporosis- and pycnodysostosis-related IVD degeneration. Our study validates the efficacy of using DVC to increase the accuracy of FEM predictions and highlights that these methodologies may be scalable to large animals and humans.
{"title":"Synchrotron Tomography-Based Finite Element Analysis of Vertebral Endplate Loading Reveals Functional Roles for Architectural Features","authors":"Jishizhan Chen, Alissa L Parmenter, Aikta Sharma, Elis Newham, Eral Bele, Sebastian Marussi, Andrew A Pitsillides, Nick J Terrill, Himadri S Gupta, Peter D Lee","doi":"10.1101/2024.09.03.610954","DOIUrl":"https://doi.org/10.1101/2024.09.03.610954","url":null,"abstract":"Lower back pain is linked to vertebral biomechanics, with vertebral endplates (VEPs) playing a key role in vertebral load transfer and distribution. Synchrotron computed tomography (sCT) allows for detailed visualisation of the microstructure of intact VEPs under near-physiological loads and, when coupled with digital volume correlation (DVC), can be used to quantify three-dimensional (3D) strain fields with nanoscale resolution. Herein, we spatially couple DVC data and an image-based finite element model (FEM) to determine the material properties of murine VEPs. This model was then extended to investigate VEP biomechanics under different motions and disease conditions to reveal that VEP protrusions are important for load absorption and redistribution under different motions and predicted that abnormal intervertebral disc (IVD) stress may underpin osteoporosis- and pycnodysostosis-related IVD degeneration. Our study validates the efficacy of using DVC to increase the accuracy of FEM predictions and highlights that these methodologies may be scalable to large animals and humans.","PeriodicalId":501308,"journal":{"name":"bioRxiv - Bioengineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142227037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-06DOI: 10.1101/2024.09.03.610811
Katariina Mamia, Solrun Kolbeinsdottir, Zhuokun Li, Kornel Labun, Anna Komisarczuk, Salla Keskitalo, Ganna Reint, Frida Hosoien Haugen, Britt Olaug Lindestad, Thea Johanne Gjerdingen, Antti Tuhkala, Carolina Wieczorek Ervik, Pavel Kopcil, Nail Fatkhutdinov, Monika Szymanska, Eero Tolo, Virpi Glumoff, Janna Saarela, Trond Melbye Michelsen, Camilla Schalin-Jantti, Johanna Olweus, Eira Leinonen, Markku Varjosalo, Eivind Valen, Timo Hautala, Martin Enge, Timi Martelius, Shiva Dahal-Koirala, Emma Haapaniemi
CRISPR/Cas9 gene editing technology is a promising tool for correcting pathogenic variants for autologous cell therapies for Inborn Errors of Immunity (IEI). The present IEI correction strategies mainly focus on the knock-in of therapeutic cDNAs, or knockout of the disease-causing gene when feasible. These strategies address many single-gene defects but may disrupt gene expression and require significant optimization for each newly discovered IEI-causing gene, highlighting the need for complementary platforms that can precisely correct diverse pathogenic variants. Here, we present a safe and efficient T cell single nucleotide variant (SNV) correction pipeline based on homology-directed repair (HDR), suitable for diverse monogenic mutations. By using founder mutations of Deficiency of ADA2 (DADA2), Autoimmune polyendocrinopathy-candidiasis-ectodermal dystrophy (APECED) and Cartilage Hair Hypoplasia (CHH) as IEI models, we show that our pipeline can achieve up to 80% bi-allelic editing, with resultant functional correction of the disease phenotype in patient T cells. We do not find detectable pre-malignant off-target effects or karyotypic, transcriptomic or proteomic aberrations upon profiling patient T cells with GUIDE-seq, single cell RNA sequencing, PacBio based long-read whole genome sequencing, and high-throughput proteomics. This study demonstrates that HDR-based SNV editing is a safe and effective option for IEI T cell correction and that it could be developed to an autologous T cell therapy, as the presented protocol is scalable for a GMP-compatible workflow. This study is a step towards the development of gene correction platform that targets a broad number of monogenic mutations.
CRISPR/Cas9基因编辑技术是一种很有前途的工具，可用于纠正先天性免疫错误（IEI）自体细胞疗法的致病变异体。目前的先天性免疫错误（IEI）纠正策略主要集中在敲入治疗性 cDNA，或在可行的情况下敲除致病基因。这些策略可以解决许多单基因缺陷，但可能会破坏基因表达，而且需要对每个新发现的 IEI 致病基因进行大量优化，这就凸显了对能精确纠正各种致病变体的互补平台的需求。在这里，我们提出了一种基于同源定向修复（HDR）的安全高效的 T 细胞单核苷酸变异（SNV）校正管道，适用于各种单基因突变。通过使用 ADA2 缺乏症 (DADA2)、自身免疫性多内分泌病-念珠菌病-外胚层营养不良症 (APECED) 和软骨毛发发育不全症 (CHH) 的创始突变作为 IEI 模型，我们展示了我们的管道可以实现高达 80% 的双等位基因编辑，从而对患者 T 细胞中的疾病表型进行功能校正。在使用 GUIDE-seq、单细胞 RNA 测序、基于 PacBio 的长读程全基因组测序和高通量蛋白质组学分析患者 T 细胞时，我们没有发现可检测到的预恶性脱靶效应或核型、转录组或蛋白质组畸变。这项研究表明，基于 HDR 的 SNV 编辑是 IEI T 细胞校正的一种安全有效的选择，而且它可以发展成一种自体 T 细胞疗法，因为所提出的方案可以扩展到与 GMP 兼容的工作流程。这项研究为开发针对大量单基因突变的基因校正平台迈出了一步。
{"title":"T cell correction pipeline for Inborn Errors of Immunity","authors":"Katariina Mamia, Solrun Kolbeinsdottir, Zhuokun Li, Kornel Labun, Anna Komisarczuk, Salla Keskitalo, Ganna Reint, Frida Hosoien Haugen, Britt Olaug Lindestad, Thea Johanne Gjerdingen, Antti Tuhkala, Carolina Wieczorek Ervik, Pavel Kopcil, Nail Fatkhutdinov, Monika Szymanska, Eero Tolo, Virpi Glumoff, Janna Saarela, Trond Melbye Michelsen, Camilla Schalin-Jantti, Johanna Olweus, Eira Leinonen, Markku Varjosalo, Eivind Valen, Timo Hautala, Martin Enge, Timi Martelius, Shiva Dahal-Koirala, Emma Haapaniemi","doi":"10.1101/2024.09.03.610811","DOIUrl":"https://doi.org/10.1101/2024.09.03.610811","url":null,"abstract":"CRISPR/Cas9 gene editing technology is a promising tool for correcting pathogenic variants for autologous cell therapies for Inborn Errors of Immunity (IEI). The present IEI correction strategies mainly focus on the knock-in of therapeutic cDNAs, or knockout of the disease-causing gene when feasible. These strategies address many single-gene defects but may disrupt gene expression and require significant optimization for each newly discovered IEI-causing gene, highlighting the need for complementary platforms that can precisely correct diverse pathogenic variants. Here, we present a safe and efficient T cell single nucleotide variant (SNV) correction pipeline based on homology-directed repair (HDR), suitable for diverse monogenic mutations. By using founder mutations of Deficiency of ADA2 (DADA2), Autoimmune polyendocrinopathy-candidiasis-ectodermal dystrophy (APECED) and Cartilage Hair Hypoplasia (CHH) as IEI models, we show that our pipeline can achieve up to 80% bi-allelic editing, with resultant functional correction of the disease phenotype in patient T cells. We do not find detectable pre-malignant off-target effects or karyotypic, transcriptomic or proteomic aberrations upon profiling patient T cells with GUIDE-seq, single cell RNA sequencing, PacBio based long-read whole genome sequencing, and high-throughput proteomics. This study demonstrates that HDR-based SNV editing is a safe and effective option for IEI T cell correction and that it could be developed to an autologous T cell therapy, as the presented protocol is scalable for a GMP-compatible workflow. This study is a step towards the development of gene correction platform that targets a broad number of monogenic mutations.","PeriodicalId":501308,"journal":{"name":"bioRxiv - Bioengineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142216665","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-04DOI: 10.1101/2024.09.01.610710
Jose F Delgado, Ayele H Negussie, Nicole A Varble, Andrew S Mikhail, Antonio Arrichiello, Tabea Borde, Laetitia Saccenti, Ivane Bakhutashvili, Robert Morhard, Joshua W Owen, John W Karanian, William F Pritchard, Bradford J Wood
Intratumoral injections often lack visibility, leading to unpredictable outcomes such as incomplete tumor coverage, off-target drug delivery and systemic toxicities. This study investigated an ultrasound (US) and x-ray imageable thermosensitive hydrogel based on poloxamer 407 (POL) percutaneously delivered in a healthy swine model. The primary objective was to assess the 2D and 3D distribution of the hydrogel within tissue across three different needle devices and injection sites: liver, kidney, and intercostal muscle region. Secondly, pharmacokinetics of POL loaded with doxorubicin (POLDOX) were evaluated and compared to free doxorubicin injection (DOXSoln) with a Single End Hole Needle. Utilizing 2D and 3D morphometrics from US and x-ray imaging techniques such as Computed Tomography (CT) and Cone Beam CT (CBCT), we monitored the localization and leakage of POLDOX over time. Relative iodine concentrations measured with CBCT following incorporation of an iodinated contrast agent in POL indicated potential drug diffusion and advection transport. Furthermore, US imaging revealed temporal changes, suggesting variations in acoustic intensity, heterogeneity, and echotextures. Notably, 3D reconstruction of the distribution of POL and POLDOX from 2D ultrasound frames was achieved and morphometric data obtained. Pharmacokinetic analysis revealed lower systemic exposure of the drug in various organs with POLDOX formulation compared to DOXSoln formulation. This was demonstrated by a lower area under the curve (852.1 ± 409.1 ng/mL·h vs 2283.4 ± 377.2 ng/mL·h) in the plasma profile, suggesting a potential reduction in systemic toxicity. Overall, the use of POL formulation offers a promising strategy for precise and localized drug delivery, that may minimize adverse effects. Dual modality POL imaging enabled analysis of patterns of gel distribution and morphology, alongside of pharmacokinetics of local delivery. Incorporating hydrogels into drug delivery systems holds significant promise for improving the predictability of the delivered drug and enhancing spatial conformability. These advancements can potentially enhance the safety and precision of anticancer therapy.
瘤内注射往往缺乏可视性，导致无法预测的结果，如肿瘤覆盖不全、脱靶给药和全身毒性。本研究调查了在健康猪模型中经皮给药的基于聚氧乙烯酰胺 407（POL）的超声（US）和 X 射线可成像热敏水凝胶。主要目的是评估水凝胶在三种不同针头装置和注射部位（肝脏、肾脏和肋间肌区域）组织内的二维和三维分布情况。其次，评估负载多柔比星的 POL（POLDOX）的药代动力学，并与使用单端孔针注射游离多柔比星（DOXSoln）进行比较。利用 US 和 X 射线成像技术（如计算机断层扫描 (CT) 和锥形束 CT (CBCT)）的二维和三维形态计量学，我们监测了 POLDOX 随时间变化的定位和渗漏情况。在 POL 中加入碘化造影剂后，用 CBCT 测得的相对碘浓度显示了潜在的药物扩散和平流传输。此外，US 成像显示了时间上的变化，表明声强、异质性和回声纹理存在变化。值得注意的是，通过二维超声帧实现了 POL 和 POLDOX 分布的三维重建，并获得了形态计量数据。药代动力学分析表明，与 DOXSoln 制剂相比，POLDOX 制剂的药物在各器官中的全身暴露量较低。这表现在血浆曲线下的面积较低（852.1 ± 409.1 ng/mL-h vs 2283.4 ± 377.2 ng/mL-h），表明全身毒性可能会降低。总之，使用 POL 制剂为精确和局部给药提供了一种前景广阔的策略，可将不良反应降至最低。双模式 POL 成像可分析凝胶分布和形态模式，以及局部给药的药代动力学。在给药系统中加入水凝胶有望提高给药的可预测性并增强空间保形性。这些进步有可能提高抗癌治疗的安全性和精确性。
{"title":"In vivo Imaging and Pharmacokinetics of Percutaneously Injected Ultrasound and X-ray Imageable Thermosensitive Hydrogel loaded with Doxorubicin versus Free Drug in Swine","authors":"Jose F Delgado, Ayele H Negussie, Nicole A Varble, Andrew S Mikhail, Antonio Arrichiello, Tabea Borde, Laetitia Saccenti, Ivane Bakhutashvili, Robert Morhard, Joshua W Owen, John W Karanian, William F Pritchard, Bradford J Wood","doi":"10.1101/2024.09.01.610710","DOIUrl":"https://doi.org/10.1101/2024.09.01.610710","url":null,"abstract":"Intratumoral injections often lack visibility, leading to unpredictable outcomes such as incomplete tumor coverage, off-target drug delivery and systemic toxicities. This study investigated an ultrasound (US) and x-ray imageable thermosensitive hydrogel based on poloxamer 407 (POL) percutaneously delivered in a healthy swine model. The primary objective was to assess the 2D and 3D distribution of the hydrogel within tissue across three different needle devices and injection sites: liver, kidney, and intercostal muscle region. Secondly, pharmacokinetics of POL loaded with doxorubicin (POLDOX) were evaluated and compared to free doxorubicin injection (DOXSoln) with a Single End Hole Needle. Utilizing 2D and 3D morphometrics from US and x-ray imaging techniques such as Computed Tomography (CT) and Cone Beam CT (CBCT), we monitored the localization and leakage of POLDOX over time. Relative iodine concentrations measured with CBCT following incorporation of an iodinated contrast agent in POL indicated potential drug diffusion and advection transport. Furthermore, US imaging revealed temporal changes, suggesting variations in acoustic intensity, heterogeneity, and echotextures. Notably, 3D reconstruction of the distribution of POL and POLDOX from 2D ultrasound frames was achieved and morphometric data obtained. Pharmacokinetic analysis revealed lower systemic exposure of the drug in various organs with POLDOX formulation compared to DOXSoln formulation. This was demonstrated by a lower area under the curve (852.1 ± 409.1 ng/mL·h vs 2283.4 ± 377.2 ng/mL·h) in the plasma profile, suggesting a potential reduction in systemic toxicity. Overall, the use of POL formulation offers a promising strategy for precise and localized drug delivery, that may minimize adverse effects. Dual modality POL imaging enabled analysis of patterns of gel distribution and morphology, alongside of pharmacokinetics of local delivery. Incorporating hydrogels into drug delivery systems holds significant promise for improving the predictability of the delivered drug and enhancing spatial conformability. These advancements can potentially enhance the safety and precision of anticancer therapy.","PeriodicalId":501308,"journal":{"name":"bioRxiv - Bioengineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142216658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-12DOI: 10.1101/2024.08.09.605335
Antonio Garcia Guerra, Chaitra Sathyaprakash, Olivier Gerrit de Jong, Wooi Lim, Pieter Vader, Samir EL Andaloussi, Jonathan Bath, Jesus Reine, Yoshitsugu Aoki, Andrew Turberfield, Matthew Wood, Carlo Rinaldi
Nucleic acid nanostructures offer unique opportunities for biomedical applications due to their sequence-programmable structures and functions, which enable the design of complex responses to molecular cues. Control of the biological activity of therapeutic cargoes based on endogenous molecular signatures holds the potential to overcome major hurdles in translational research: cell specificity and off-target effects. Endogenous microRNAs can be used to profile cell type and cell state and are ideal inputs for RNA nanodevices. Here we present CRISPR MiRAGE (miRNA-activated genome editing), a tool comprising a dynamic single-guide RNA that senses miRNA complexed with Argonaute proteins and controls downstream CRISPR activity based on the detected miRNA signature. We study the operation of the miRNA-sensing single-guide RNA and attain muscle-specific activation of gene editing through CRISPR MiRAGE in models of Duchenne muscular dystrophy. By enabling RNA-controlled gene editing activity, this technology creates opportunities to advance tissue-specific CRISPR treatments for human diseases.
{"title":"Tissue-specific modulation of CRISPR activity by miRNA-sensing guide RNAs","authors":"Antonio Garcia Guerra, Chaitra Sathyaprakash, Olivier Gerrit de Jong, Wooi Lim, Pieter Vader, Samir EL Andaloussi, Jonathan Bath, Jesus Reine, Yoshitsugu Aoki, Andrew Turberfield, Matthew Wood, Carlo Rinaldi","doi":"10.1101/2024.08.09.605335","DOIUrl":"https://doi.org/10.1101/2024.08.09.605335","url":null,"abstract":"Nucleic acid nanostructures offer unique opportunities for biomedical applications due to their sequence-programmable structures and functions, which enable the design of complex responses to molecular cues. Control of the biological activity of therapeutic cargoes based on endogenous molecular signatures holds the potential to overcome major hurdles in translational research: cell specificity and off-target effects. Endogenous microRNAs can be used to profile cell type and cell state and are ideal inputs for RNA nanodevices. Here we present CRISPR MiRAGE (miRNA-activated genome editing), a tool comprising a dynamic single-guide RNA that senses miRNA complexed with Argonaute proteins and controls downstream CRISPR activity based on the detected miRNA signature. We study the operation of the miRNA-sensing single-guide RNA and attain muscle-specific activation of gene editing through CRISPR MiRAGE in models of Duchenne muscular dystrophy. By enabling RNA-controlled gene editing activity, this technology creates opportunities to advance tissue-specific CRISPR treatments for human diseases.","PeriodicalId":501308,"journal":{"name":"bioRxiv - Bioengineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141941666","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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