Due to a range of promising results from T cell therapy clinical trials, methods and technologies of cell selection are being explored to increase safety, reproducible high potency as well as lean ...operation. Although conventional methods such as (density gradient or counterflow) centrifugation, directed cell culture and magnetic field-based cell selection methods have long been applied successfully in cGMP-compliant manufacturing of therapeutic cells, the increasing need for manufacturing large numbers of specific subpopulations of T cells demands a new approach.
In academic research settings, accurate selection of specific subpopulations of T cells such as Regulatory T cells or CD4 Cytotoxic T cells, is performed by means of flow cytometry-based cell sorting involving identification of multiple phenotypic characteristics of a single cell type. While conventional, high-speed cell sorting has been applied to clinical-grade manufacturing in the past, it is not a sustainable method for current and future demands in clinical manufacturing.
During the last decade, significant progress has been made on flow cytometry-based, microfluidic chip cell sorting that has led to the availability of at least 3 different brands of cell sorters with acceptable features and performances for selecting specific subpopulations of T cells in cGMP-compliant manufacturing of therapeutic cells.
We report on having worked with a number of these new cell sorters to select highly purified Regulatory T cells as well as CD4 Cytotoxic T cells as a component of clinical manufacturing processes for clinical trials with specific subpopulations of T cells to treat GVHD and CLL, respectively. Most of our T cell manufacturing processes begin with PBMCs – Regulatory T cells represent 2.5 – 5 % and CD4 Cytotoxic T cells 20 – 30% of PBMCs. Cell selection strategies may involve debulking, enrichment and/or high purification steps. Manufacturing criteria such as processing time, purity, yield and complexity of the workflow, determine which strategy to use. Our report provides detailed insight into best practices to apply in clinical manufacturing procedures in order to efficiently obtain high potency therapeutic cells. We conclude that this new technology narrows the methods gap between academic research and clinical trials, clearing the path to quickly establish reproducibility at large-scale.
Sorting a set of items is a task that can be useful by itself or as a building block for more complex operations. That is why a lot of effort has been put into finding sorting algorithms that sort ...large sets as efficiently as possible. But the more sophisticated and complex the algorithms become, the less efficient they are for small sets of items due to large constant factors. A relatively simple sorting algorithm that is often used as a base case sorter is insertion sort, because it has small code size and small constant factors influencing its execution time. We aim to determine if there is a faster way to sort small sets of items to provide an efficient base case sorter. We looked at sorting networks, at how they can improve the speed of sorting few elements, and how to implement them in an efficient manner using conditional moves. Since sorting networks need to be implemented explicitly for each set size, providing networks for larger sizes becomes less efficient due to increased code sizes. To also enable the sorting of slightly larger base cases, we adapted sample sort to Register Sample Sort, to break down those larger sets into sizes that can in turn be sorted by sorting networks. From our experiments we found that when sorting only small sets of integers, the sorting networks outperform insertion sort by a factor of at least 1.76 for any array size between six and 16, and by a factor of 2.72 on average across all machines and array sizes. When integrating sorting networks as a base case sorter into Quicksort, we achieved far less performance improvements over using insertion sort, which is probably due to the networks having a larger code size and cluttering the L1 instruction cache. The same effect occurs when including Register Sample Sort as a base case sorter for IPS4o. But for x86 machines that have a larger L1 instruction cache of 64 KiB or more, we obtained speedups of 12.7% when using sorting networks as a base case sorter in std::sort, and of 5%–6% when integrating Register Sample Sort as a base case sorter into IPS4o, each in comparison to using insertion sort as the base case sorter. In conclusion, the desired improvement in speed could only be achieved under special circumstances, but the results clearly show the potential of using conditional moves in the field of sorting algorithms.
Eukaryotic cells traffic proteins and lipids between different compartments using protein-coated vesicles and tubules. The retromer complex is required to generate cargo-selective tubulovesicular ...carriers from endosomal membranes
. Conserved in eukaryotes, retromer controls the cellular localization and homeostasis of hundreds of transmembrane proteins, and its disruption is associated with major neurodegenerative disorders
. How retromer is assembled and how it is recruited to form coated tubules is not known. Here we describe the structure of the retromer complex (Vps26-Vps29-Vps35) assembled on membrane tubules with the bin/amphiphysin/rvs-domain-containing sorting nexin protein Vps5, using cryo-electron tomography and subtomogram averaging. This reveals a membrane-associated Vps5 array, from which arches of retromer extend away from the membrane surface. Vps35 forms the 'legs' of these arches, and Vps29 resides at the apex where it is free to interact with regulatory factors. The bases of the arches connect to each other and to Vps5 through Vps26, and the presence of the same arches on coated tubules within cells confirms their functional importance. Vps5 binds to Vps26 at a position analogous to the previously described cargo- and Snx3-binding site, which suggests the existence of distinct retromer-sorting nexin assemblies. The structure provides insight into the architecture of the coat and its mechanism of assembly, and suggests that retromer promotes tubule formation by directing the distribution of sorting nexin proteins on the membrane surface while providing a scaffold for regulatory-protein interactions.
The sorting nexin 27 (SNX27)-retromer complex is a major regulator of endosome-to-plasma membrane recycling of transmembrane cargos that contain a PSD95, Dlg1, zo-1 (PDZ)-binding motif. Here we ...describe the core interaction in SNX27-retromer assembly and its functional relevance for cargo sorting. Crystal structures and NMR experiments reveal that an exposed β-hairpin in the SNX27 PDZ domain engages a groove in the arrestin-like structure of the vacuolar protein sorting 26A (VPS26A) retromer subunit. The structure establishes how the SNX27 PDZ domain simultaneously binds PDZ-binding motifs and retromer-associated VPS26. Importantly, VPS26A binding increases the affinity of the SNX27 PDZ domain for PDZ- binding motifs by an order of magnitude, revealing cooperativity in cargo selection. With disruption of SNX27 and retromer function linked to synaptic dysfunction and neurodegenerative disease, our work provides the first step, to our knowledge, in the molecular description of this important sorting complex, and more broadly describes a unique interaction between a PDZ domain and an arrestin-like fold.
•Multi- physical properties-based label-free particle sorting.•Tunable acoustofluidic system integrated with elasto-inertial particle focusing.•Particle separation at submicron size ...difference.•Separation of particles with the same size but different material properties.
Acoustophoretic manipulation has been drawing great attention in the area of microfluidics-based cell/particle isolation and sorting due to its advantages of high biocompatibility, contactless manipulation and fabrication simplicity. Most label-free microfluidic particle sorting methodologies are solely based on a single physical property for example particle size, density or material composition, which hinder their broad usage in various applications. In this work, we demonstrate a tunable acoustofluidic device for continuous particle separation based on multi-physical properties such as size, density, compressibility and speed of sound. The tunable acoustofluidic system utilizes an elasto-inertial particle focusing technique to align particles into a single line and integrates a slanted interdigitated transducer (SFIT) that generates a tunable travelling surface acoustic wave to separate the particles with improved sorting accuracy and efficiency. The presented acoustofluidic sorting device allows the generation of a variable frequency from 99 MHz to 247 MHz corresponding to the wavelength 40 μm and 16 μm using the SFIT. We have successfully sorted 5.26 μm from 5 μm polystyrene particles at 90 % accuracy with a relative size difference of 5.2 %. Furthermore, a theoretical analysis of acoustic radiation force (ARF) exerted on rigid particles of different materials (i.e., polystyrene, PLGA, PMMA) is presented. Based on the optimal frequencies identified in the theoretical analysis, we have also experimentally demonstrated effective sorting of the three above-mentioned materials of particles with the same particle size.
Recognising the signals for endosomal trafficking Weeratunga, Saroja; Paul, Blessy; Collins, Brett M.
Current opinion in cell biology,
August 2020, 2020-08-00, 20200801, Volume:
65
Journal Article
Peer reviewed
The endosomal compartment is a major sorting station controlling the balance between endocytic recycling and lysosomal degradation, and its homeostasis is emerging as a central factor in various ...neurodegenerative diseases such as Alzheimer's and Parkinson's. Membrane trafficking is generally coordinated by the recognition of specific signals in transmembrane protein cargos by different transport machineries. A number of different protein trafficking complexes are essential for sequence-specific recognition and retrieval of endosomal cargos, recycling them to other compartments and acting to counter-balance the default endosomal sorting complex required for transport–mediated degradation pathway. In this review, we provide a summary of the key endosomal transport machineries, and the molecular mechanisms by which different cargo sequences are specifically recognised.
Intralumenal vesicle formation of the multivesicular body is a critical step in the delivery of endocytic cargoes to the lysosome for degradation. Endosomal sorting complex required for transport III ...(ESCRT-III) subunits polymerize on endosomal membranes to facilitate membrane budding away from the cytoplasm to generate these intralumenal vesicles. The ATPase Vps4 remodels and disassembles ESCRT-III, but the manner in which Vps4 activity is coordinated with ESCRT-III function remains unclear. Ist1 is structurally homologous to ESCRT-III subunits and has been reported to inhibit Vps4 function despite the presence of a microtubule-interacting and trafficking domain-interacting motif (MIM) capable of stimulating Vps4 in the context of other ESCRT-III subunits. Here we report that Ist1 inhibition of Vps4 ATPase activity involves two elements in Ist1: the MIM itself and a surface containing a conserved ELYC sequence. In contrast, the MIM interaction, in concert with a more open conformation of the Ist1 core, resulted in stimulation of Vps4. Addition of the ESCRT-III subunit binding partner of Ist1, Did2, also converted Ist1 from an inhibitor to a stimulator of Vps4 ATPase activity. Finally, distinct regulation of Vps4 by Ist1 corresponded with altered ESCRT-III disassembly in vitro. Together, these data support a model in which Ist1-Did2 interactions during ESCRT-III polymerization coordinate Vps4 activity with the timing of ESCRT-III disassembly.
Microparticles (MPs) are cell-cell communication vesicles derived from the cell surface plasma membrane, although they are not known to originate from cardiac ventricular muscle. In ventricular ...cardiomyocytes, the membrane deformation protein cardiac bridging integrator 1 (cBIN1 or BIN1+13+17) creates transverse-tubule (t-tubule) membrane microfolds, which facilitate ion channel trafficking and modulate local ionic concentrations. The microfold-generated microdomains continuously reorganize, adapting in response to stress to modulate the calcium signaling apparatus. We explored the possibility that cBIN1-microfolds are externally released from cardiomyocytes. Using electron microscopy imaging with immunogold labeling, we found in mouse plasma that cBIN1 exists in membrane vesicles about 200 nm in size, which is consistent with the size of MPs. In mice with cardiac-specific heterozygous Bin1 deletion, flow cytometry identified 47% less cBIN1-MPs in plasma, supporting cardiac origin. Cardiac release was also evidenced by the detection of cBIN1-MPs in medium bathing a pure population of isolated adult mouse cardiomyocytes. In human plasma, osmotic shock increased cBIN1 detection by enzyme-linked immunosorbent assay (ELISA), and cBIN1 level decreased in humans with heart failure, a condition with reduced cardiac muscle cBIN1, both of which support cBIN1 release in MPs from human hearts. Exploring putative mechanisms of MP release, we found that the membrane fission complex endosomal sorting complexes required for transport (ESCRT)-III subunit charged multivesicular body protein 4B (CHMP4B) colocalizes and coimmunoprecipitates with cBIN1, an interaction enhanced by actin stabilization. In HeLa cells with cBIN1 overexpression, knockdown of CHMP4B reduced the release of cBIN1-MPs. Using truncation mutants, we identified that the N-terminal BAR (N-BAR) domain in cBIN1 is required for CHMP4B binding and MP release. This study links the BAR protein superfamily to the ESCRT pathway for MP biogenesis in mammalian cardiac ventricular cells, identifying elements of a pathway by which cytoplasmic cBIN1 is released into blood.
The endosomal sorting complex required for transport (ESCRT) machinery is an ancient system that deforms membrane and severs membrane necks from the inside. Extensive evidence has accumulated to ...demonstrate the conserved functions of plant ESCRTs in multivesicular body (MVB) biogenesis and MVB-mediated membrane protein sorting. In addition, recent exciting findings have uncovered unique plant ESCRT components and point to emerging roles for plant ESCRTs in non-endosomal sorting events such as autophagy, cytokinesis, and viral replication. Plant-specific processes, such as abscisic acid (ABA) signaling and chloroplast turnover, provide further evidence for divergences in the functions of plant ESCRTs during evolution. We summarize the multiple roles and current working models for plant ESCRT machinery and speculate on future ESCRT studies in the plant field.
ESCRT is an evolutionarily conserved machinery for membrane deformation and scission from the inner face of a membrane away from the cytoplasm.
Plants encode most ESCRT isoforms in their genome, including ESCRT-I, -II, -III, and VPS4/SKD1, with the exception of the canonical ESCRT-0. TOL (TOM1-like) proteins were identified as upstream ESCRT factors that partially fulfill ESCRT-0 function in plants.
Extensive evidence has accumulated to demonstrate the essential and conserved functions of ESCRTs in endosomal sorting in plants.
Plant-specific ESCRT components have been identified. In addition, ESCRTs in plants are also involved in a variety of non-endosomal sorting events such as autophagosome maturation, chloroplast turnover, cytokinesis, and viral replication.
Plant ESCRTs are also actively involved in hormone signaling and plant responses to biotic and abiotic stresses.
Sorting machines use computer vision (CV) to separate food items based on various attributes. For instance, sorting based on size and colour are commonly used in commercial machines. However, ...detecting external defects using CV remains an open problem. This paper presents an experimental contribution to external defect detection using deep learning. An uncensored dataset with 43,843 images including external defects was built during this study. The dataset is heavily imbalanced towards the healthy class, and it is available online. Deep residual neural network (ResNet) classifiers were trained that are capable of detecting external defects using feature extraction and fine-tuning. The results show that fine-tuning outperformed feature extraction, revealing the benefit of training additional layers when sufficient data samples are available. The best model was a ResNet50 with all its layers fine-tuned. This model achieved an average precision of 94.6% on the test set. The optimal classifier had a recall of 86.6% while maintaining a precision of 91.7%. The posterior class-conditional distributions of the classifier scores showed that the key to classifier success lies in its almost ideal healthy class distribution. The results also explain why the model does not confuse stems/calyxes with external defects. The best model constitutes a milestone for detecting external defects using CV. Because deep learning does not require feature engineering or prior knowledge about the dataset content, the methodology may also work well with other foods.
•Deep learning detects different types of external defects without feature engineering.•Fine tuning outperformed feature extraction in external defect detection.•The best model has Average Precision = 94.6 %.•The best model has 86.6 % Recall and 91.7 % Precision at the optimal threshold.•The best model does not confuse external defects with stems/calyxes.
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