Drug-regulated CD33-targeted CAR T cells control AML using clinically optimized rapamycin dosing.

Chimeric antigen receptor (CAR) designs that incorporate pharmacologic control are desirable; however, designs suitable for clinical translation are needed. We designed a fully human, rapamycin-regulated drug product for targeting CD33+ tumors called dimerizaing agent-regulated immunoreceptor complex (DARIC33). T cell products demonstrated target-specific and rapamycin-dependent cytokine release, transcriptional responses, cytotoxicity, and in vivo antileukemic activity in the presence of as little as 1 nM rapamycin. Rapamycin withdrawal paused DARIC33-stimulated T cell effector functions, which were restored following reexposure to rapamycin, demonstrating reversible effector function control. While rapamycin-regulated DARIC33 T cells were highly sensitive to target antigen, CD34+ stem cell colony-forming capacity was not impacted. We benchmarked DARIC33 potency relative to CD19 CAR T cells to estimate a T cell dose for clinical testing. In addition, we integrated in vitro and preclinical in vivo drug concentration thresholds for off-on state transitions, as well as murine and human rapamycin pharmacokinetics, to estimate a clinically applicable rapamycin dosing schedule. A phase I DARIC33 trial has been initiated (PLAT-08, NCT05105152), with initial evidence of rapamycin-regulated T cell activation and antitumor impact. Our findings provide evidence that the DARIC platform exhibits sensitive regulation and potency needed for clinical application to other important immunotherapy targets.

People with obesity exhibit losses in muscle proteostasis that are partly improved by exercise training.

This pilot experiment examines if a loss in muscle proteostasis occurs in people with obesity and whether endurance exercise positively influences either the abundance profile or turnover rate of proteins in this population. Men with (n = 3) or without (n = 4) obesity were recruited and underwent a 14-d measurement protocol of daily deuterium oxide (D2 O) consumption and serial biopsies of vastus lateralis muscle. Men with obesity then completed 10-weeks of high-intensity interval training (HIIT), encompassing 3 sessions per week of cycle ergometer exercise with 1 min intervals at 100% maximum aerobic power interspersed by 1 min recovery periods. The number of intervals per session progressed from 4 to 8, and during weeks 8-10 the 14-d measurement protocol was repeated. Proteomic analysis detected 352 differences (p < 0.05, false discovery rate < 5%) in protein abundance and 19 (p < 0.05) differences in protein turnover, including components of the ubiquitin-proteasome system. HIIT altered the abundance of 53 proteins and increased the turnover rate of 22 proteins (p < 0.05) and tended to benefit proteostasis by increasing muscle protein turnover rates. Obesity and insulin resistance are associated with compromised muscle proteostasis, which may be partially restored by endurance exercise.

Biomechanical loading during running: can a two mass-spring-damper model be used to evaluate ground reaction forces for high-intensity tasks?

Running impact forces expose the body to biomechanical loads leading to beneficial adaptations, but also risk of injury. High-intensity running tasks, especially, are deemed highly demanding for the musculoskeletal system, but loads experienced during these actions are not well understood. To eventually predict GRF and understand the biomechanical loads experienced during such activities in greater detail, this study aimed to (1) examine the feasibility of using a simple two mass-spring-damper model, based on eight model parameters, to reproduce ground reaction forces (GRFs) for high-intensity running tasks and (2) verify whether the required model parameters were physically meaningful. This model was used to reproduce GRFs for rapid accelerations and decelerations, constant speed running and maximal sprints. GRF profiles and impulses could be reproduced with low to very low errors across tasks, but subtler loading characteristics (impact peaks, loading rate) were modelled less accurately. Moreover, required model parameters varied strongly between trials and had minimal physical meaning. These results show that although a two mass-spring-damper model can be used to reproduce overall GRFs for high-intensity running tasks, the application of this simple model for predicting GRFs in the field and/or understanding the biomechanical demands of training in greater detail is likely limited.

A neural network method to predict task- and step-specific ground reaction force magnitudes from trunk accelerations during running activities.

Prediction of ground reaction force (GRF) magnitudes during running-based sports has several important applications, including optimal load prescription and injury prevention in athletes. Existing methods typically require information from multiple body-worn sensors, limiting their ecological validity, or aim to estimate discrete force parameters, limiting their ability to assess overall biomechanical load. This paper presents a neural network method to predict GRF time series from a single, commonly used, trunk-mounted accelerometer. The presented method uses a principal component analysis and multilayer perceptron (MLP) to obtain predictions. Time-series r2 coefficients with test data averaged around 0.9 for each impact, comparing favourably with alternative approaches which require additional sensors. For the impact peak, r2 was 0.74 across activities, comparing favourably with correlation analysis approaches. Several modifications, such as subject-specific training of the MLP, may help to improve results further, but the presented method can accurately predict GRF from trunk accelerometry data without requiring additional information. Results demonstrate the scope of machine learning to exploit common wearable technologies to estimate GRF in sport-specific environments.

Dynamic proteome profiling of individual proteins in human skeletal muscle after a high-fat diet and resistance exercise.

It is generally accepted that muscle adaptation to resistance exercise (REX) training is underpinned by contraction-induced, increased rates of protein synthesis and dietary protein availability. By using dynamic proteome profiling (DPP), we investigated the contribution of both synthesis and breakdown to changes in abundance on a protein-by-protein basis in human skeletal muscle. Age-matched, overweight males consumed 9 d of a high-fat, low-carbohydrate diet during which time they either undertook 3 sessions of REX or performed no exercise. Precursor enrichment and the rate of incorporation of deuterium oxide into newly synthesized muscle proteins were determined by mass spectrometry. Ninety proteins were included in the DPP, with 28 proteins exhibiting significant responses to REX. The most common pattern of response was an increase in turnover, followed by an increase in abundance with no detectable increase in protein synthesis. Here, we provide novel evidence that demonstrates that the contribution of synthesis and breakdown to changes in protein abundance induced by REX differ on a protein-by-protein basis. We also highlight the importance of the degradation of individual muscle proteins after exercise in human skeletal muscle.-Camera, D. M., Burniston, J. G., Pogson, M. A., Smiles, W. J., Hawley, J. A. Dynamic proteome profiling of individual proteins in human skeletal muscle after a high-fat diet and resistance exercise.

Crystallographic analyses illustrate significant plasticity and efficient recoding of meganuclease target specificity.

The retargeting of protein-DNA specificity, outside of extremely modular DNA binding proteins such as TAL effectors, has generally proved to be quite challenging. Here, we describe structural analyses of five different extensively retargeted variants of a single homing endonuclease, that have been shown to function efficiently in ex vivo and in vivo applications. The redesigned proteins harbor mutations at up to 53 residues (18%) of their amino acid sequence, primarily distributed across the DNA binding surface, making them among the most significantly reengineered ligand-binding proteins to date. Specificity is derived from the combined contributions of DNA-contacting residues and of neighboring residues that influence local structural organization. Changes in specificity are facilitated by the ability of all those residues to readily exchange both form and function. The fidelity of recognition is not precisely correlated with the fraction or total number of residues in the protein-DNA interface that are actually involved in DNA contacts, including directional hydrogen bonds. The plasticity of the DNA-recognition surface of this protein, which allows substantial retargeting of recognition specificity without requiring significant alteration of the surrounding protein architecture, reflects the ability of the corresponding genetic elements to maintain mobility and persistence in the face of genetic drift within potential host target sites.

Reprogramming MHC specificity by CRISPR-Cas9-assisted cassette exchange.

The development of programmable nucleases has enabled the application of new genome engineering strategies for cellular immunotherapy. While targeted nucleases have mostly been used to knock-out or knock-in genes in immune cells, the scarless exchange of entire immunogenomic alleles would be of great interest. In particular, reprogramming the polymorphic MHC locus could enable the creation of matched donors for allogeneic cellular transplantation. Here we show a proof-of-concept for reprogramming MHC-specificity by performing CRISPR-Cas9-assisted cassette exchange. Using murine antigen presenting cell lines (RAW264.7 macrophages), we demonstrate that the generation of Cas9-induced double-stranded breaks flanking the native MHC-I H2-Kd locus led to exchange of an orthogonal H2-Kb allele. MHC surface expression allowed for easy selection of reprogrammed cells by flow cytometry, thus obviating the need for additional selection markers. MHC-reprogrammed cells were fully functional as they could present H2-Kd-restricted peptide and activate cognate T cells. Finally, we investigated the role of various donor template formats on exchange efficiency, discovering that templates that underwent in situ linearization resulted in the highest MHC-reprogramming efficiency. These findings highlight a potential new approach for the correcting of MHC mismatches in cellular transplantation.

Simulation of Invertebrate Aggregation Shows the Importance of Stable Personality over Diversity in Consensus Decision-Making.

Aggregation of many species of invertebrate is an example of a consensus decision, the success of which is central to survival. Personality is a stable form of behavioural diversity which has been observed in the aggregation process, but neither the reasons for its stability nor its effects on consensus decisions are well understood. By using an agent-based model of invertebrate aggregation, it is found that diverse personalities have only limited benefits to the experimental consensus decision-making process, but may have a more valuable role in natural settings. Importantly, although certain personalities may ostensibly have potential drawbacks at the individual level, such as choosing to rest in unfavourable places, all individuals are likely to benefit from maintaining a constant personality, which promotes group stability. These findings help to improve understanding of consensus decision-making and the prevalence of stable personality.

Immunogenomic engineering of a plug-and-(dis)play hybridoma platform.

Hybridomas, fusions of primary mouse B cells and myelomas, are stable, rapidly-proliferating cell lines widely utilized for antibody screening and production. Antibody specificity of a hybridoma clone is determined by the immunoglobulin sequence of the primary B cell. Here we report a platform for rapid reprogramming of hybridoma antibody specificity by immunogenomic engineering. Here we use CRISPR-Cas9 to generate double-stranded breaks in immunoglobulin loci, enabling deletion of the native variable light chain and replacement of the endogenous variable heavy chain with a fluorescent reporter protein (mRuby). New antibody genes are introduced by Cas9-targeting of mRuby for replacement with a donor construct encoding a light chain and a variable heavy chain, resulting in full-length antibody expression. Since hybridomas surface express and secrete antibodies, reprogrammed cells are isolated using flow cytometry and cell culture supernatant is used for antibody production. Plug-and-(dis)play hybridomas can be reprogrammed with only a single transfection and screening step.

Quantitative assessment of the robustness of next-generation sequencing of antibody variable gene repertoires from immunized mice.

BACKGROUND: Next-generation sequencing (NGS) of antibody variable regions has emerged as a powerful tool in systems immunology by providing quantitative molecular information on polyclonal humoral immune responses. Reproducible and robust information on antibody repertoires is valuable for basic and applied immunology studies: thus, it is essential to establish the reliability of antibody NGS data. RESULTS: We isolated RNA from antibody-secreting cells (ASCs) from either 1 mouse or a pool of 9 immunized mice in order to simulate both normal and high diversity populations. Next, we prepared three technical replicates of antibody libraries by RT-PCR from each diversity scenario, which were sequenced using the Illumina MiSeq platform resulting in >106 250 bp paired-end reads per replicate. We then assessed the robustness of antibody repertoire data based on clonal identification defined by amino acid sequence of either full-length VDJ region or the complementarity determining region 3 (CDR3). Leveraging modeling approaches adapted from mathematical ecology, we found that in either diversity scenario both CDR3 and VDJ detection nears completeness indicating deep coverage of ASC repertoires. Additionally, we defined reliability thresholds for accurate quantification and ranking of CDR3s and VDJs. Importantly, we show that both factors-(i) replicate sequencing and (ii) sequencing depth-are crucial for robust CDR3 and VDJ detection and ranking. CONCLUSIONS: In summary, we established widely applicable experimental and computational guidelines for robust antibody NGS and analysis, which will help advance systems immunology studies related to the quantitative profiling of antibody responses following infection and vaccination.

Comprehensive evaluation and optimization of amplicon library preparation methods for high-throughput antibody sequencing.

High-throughput sequencing (HTS) of antibody repertoire libraries has become a powerful tool in the field of systems immunology. However, numerous sources of bias in HTS workflows may affect the obtained antibody repertoire data. A crucial step in antibody library preparation is the addition of short platform-specific nucleotide adapter sequences. As of yet, the impact of the method of adapter addition on experimental library preparation and the resulting antibody repertoire HTS datasets has not been thoroughly investigated. Therefore, we compared three standard library preparation methods by performing Illumina HTS on antibody variable heavy genes from murine antibody-secreting cells. Clonal overlap and rank statistics demonstrated that the investigated methods produced equivalent HTS datasets. PCR-based methods were experimentally superior to ligation with respect to speed, efficiency, and practicality. Finally, using a two-step PCR based method we established a protocol for antibody repertoire library generation, beginning from inputs as low as 1 ng of total RNA. In summary, this study represents a major advance towards a standardized experimental framework for antibody HTS, thus opening up the potential for systems-based, cross-experiment meta-analyses of antibody repertoires.

Multi-copy genes that enhance the yield of mammalian G protein-coupled receptors in Escherichia coli.

Low yields of recombinant expression represent a major barrier to the physical characterization of membrane proteins. Here, we have identified genes that globally enhance the production of properly folded G protein-coupled receptors (GPCRs) in Escherichia coli. Libraries of bacterial chromosomal fragments were screened using two separate systems that monitor: (i) elevated fluorescence conferred by enhanced expression of GPCR-GFP fusions and (ii) increased binding of fluorescent ligand in cells producing more active receptor. Three multi-copy hits were isolated by both methods: nagD, encoding the ribonucleotide phosphatase NagD; a fragment of nlpD, encoding a truncation of the predicted lipoprotein NlpD, and the three-gene cluster ptsN-yhbJ-npr, encoding three proteins of the nitrogen phosphotransferase system. Expression of these genes resulted in a 3- to 10-fold increase in the yields of different mammalian GPCRs. Our data is consistent with the hypothesis that the expression of these genes may serve to maintain the integrity of the bacterial periplasm and to provide a favorable environment for proper membrane protein folding, possibly by inducing a fine-tuned stress response and/or via modifying the composition of the bacterial cell envelope.

Systems approaches in global change and biogeochemistry research.

Systems approaches have great potential for application in predictive ecology. In this paper, we present a range of examples, where systems approaches are being developed and applied at a range of scales in the field of global change and biogeochemical cycling. Systems approaches range from Bayesian calibration techniques at plot scale, through data assimilation methods at regional to continental scales, to multi-disciplinary numerical model applications at country to global scales. We provide examples from a range of studies and show how these approaches are being used to address current topics in global change and biogeochemical research, such as the interaction between carbon and nitrogen cycles, terrestrial carbon feedbacks to climate change and the attribution of observed global changes to various drivers of change. We examine how transferable the methods and techniques might be to other areas of ecosystem science and ecology.

Modelling complex biological systems using an agent-based approach.

Many of the complex systems found in biology are comprised of numerous components, where interactions between individual agents result in the emergence of structures and function, typically in a highly dynamic manner. Often these entities have limited lifetimes but their interactions both with each other and their environment can have profound biological consequences. We will demonstrate how modelling these entities, and their interactions, can lead to a new approach to experimental biology bringing new insights and a deeper understanding of biological systems.

Volumetric diffusers: pseudorandom cylinder arrays on a periodic lattice.

Most conventional diffusers take the form of a surface based treatment, and as a result can only operate in hemispherical space. Placing a diffuser in the volume of a room might provide greater efficiency by allowing scattering into the whole space. A periodic cylinder array (or sonic crystal) produces periodicity lobes and uneven scattering. Introducing defects into an array, by removing or varying the size of some of the cylinders, can enhance their diffusing abilities. This paper applies number theoretic concepts to create cylinder arrays that have more even scattering. Predictions using a boundary element method are compared to measurements to verify the model, and suitable metrics are adopted to evaluate performance. Arrangements with good aperiodic autocorrelation properties tend to produce the best results. At low frequency power is controlled by object size and at high frequency diffusion is dominated by lattice spacing and structural similarity. Consequently the operational bandwidth is rather small. By using sparse arrays and varying cylinder sizes, a wider bandwidth can be achieved.

Proteases that can distinguish among different post-translational forms of tyrosine engineered using multicolor flow cytometry.

We report the isolation of a highly active (k(cat)/K(M) approximately 10(5) M(-1)s(-1)) variant of the E. coli endopeptidase OmpT that selectively hydrolyzes peptides after 3-nitrotyrosine while effectively discriminating against similar peptides containing unmodified tyrosine (160-fold), sulfotyrosine (3600-fold), phosphotyrosine (>8000-fold), and phosphoserine (>8000-fold). The isolation of endopeptidase variants that can discriminate between substrates based on the post-translational modification of Tyr was made possible by implementing a multicolor flow cytometric assay for the screening of large mutant libraries. For the multicolor assay, a desired selection substrate was used simultaneously with multiple counterselection fluorescent substrates to isolate rare enzyme variants that displayed finely tuned substrate specificity. This work demonstrates that enzymes with exquisite selectivity can be isolated from large libraries using appropriate high throughput screening approaches and constitutes a critical step toward the production of a 3-nitrotyrosine-specific protease useful for proteomic applications.

Engineering next generation proteases.

The engineering of novel and precise sequence specificity into proteases will provide an important route to the development of exciting new tools for analytical, biotechnological, and therapeutic applications. Significant progress has been made in reprogramming protease specificity, largely because of the development of high-throughput assay technologies allowing the isolation of protease variants from large libraries. For example, using directed evolution as well as other approaches, proteases have been reprogrammed to cleave substrates containing a variety of amino acids in the P1 and P1' positions including a post-translationally modified tyrosine, a specificity not yet identified in any naturally occurring protease. Together, these recent advances represent substantial progress that could soon enable the widespread application of engineered proteases.

Introducing spatial information into predictive NF-kappaB modelling--an agent-based approach.

Nature is governed by local interactions among lower-level sub-units, whether at the cell, organ, organism, or colony level. Adaptive system behaviour emerges via these interactions, which integrate the activity of the sub-units. To understand the system level it is necessary to understand the underlying local interactions. Successful models of local interactions at different levels of biological organisation, including epithelial tissue and ant colonies, have demonstrated the benefits of such 'agent-based' modelling. Here we present an agent-based approach to modelling a crucial biological system--the intracellular NF-kappaB signalling pathway. The pathway is vital to immune response regulation, and is fundamental to basic survival in a range of species. Alterations in pathway regulation underlie a variety of diseases, including atherosclerosis and arthritis. Our modelling of individual molecules, receptors and genes provides a more comprehensive outline of regulatory network mechanisms than previously possible with equation-based approaches. The method also permits consideration of structural parameters in pathway regulation; here we predict that inhibition of NF-kappaB is directly affected by actin filaments of the cytoskeleton sequestering excess inhibitors, therefore regulating steady-state and feedback behaviour.

Synthetic antibody libraries focused towards peptide ligands.

Synthetic antibody libraries have proven immensely useful for the de novo isolation of antibodies without the need for animal immunization. Recently, focused libraries designed to recognize particular classes of ligands, such as haptens or proteins, have been employed to facilitate the selection of high-affinity antibodies. Focused libraries are built using V regions encoding combinations of canonical structures that resemble the structural features of antibodies that bind the desired class of ligands and sequence diversity is introduced at residues typically involved in recognition. Here we describe the generation and experimental validation of two different single-chain antibody variable fragment libraries that efficiently generate binders to peptides, a class of molecules that has proven to be a difficult target for antibody generation. First, a human anti-peptide library was constructed by diversifying a scaffold: the human variable heavy chain (V(H)) germ line gene 3-23, which was fused to a variant of the human variable light chain (V(L)) germ line gene A27, in which L1 was modified to encode the canonical structure found in anti-peptide antibodies. The sequence diversity was introduced into 3-23 (V(H)) only, targeting for diversification residues commonly found in contact with protein and peptide antigens. Second, a murine library was generated using the antibody 26-10, which was initially isolated based on its affinity to the hapten digoxin, but also binds peptides and exhibits a canonical structure pattern typical of anti-peptide antibodies. Diversity was introduced in the V(H) only using the profile of amino acids found at positions that frequently contact peptide antigens. Both libraries yielded binders to two model peptides, angiotensin and neuropeptide Y, following screening by solution phage panning. The mouse library yielded antibodies with affinities below 20 nM to both targets, although only the V(H) had been subjected to diversification.