bioRxiv Science⌕ Search

bioRxiv · 10.1101/2022.06.21.497082

Reprogramming brain immunosurveillance with engineered cytokines

Abstract

Immune surveillance of the brain is regulated by resident non-neuronal cells and the blood-brain barrier.1 Dys-regulation of immunosurveillance is a hallmark feature of several diseases2-5 including brain tumors6 that interact with and rely heavily on immune cells,7 suggesting that disrupting the neuroimmunology of tumors could slow their progression. Yet few tools are available to control brain immunology in vivo with local precision, and fewer yet are used for therapeutic intervention. 2 Here, we propose engineered cytokines as a neuroimmune-modulation platform. We demonstrate that the residence time of cytokines in the brain can be tuned by binding them to the extracellular matrix or synthetic scaffolds. We then show that the aluminum hydroxide adjuvant (alum) is retained in the brain >2 weeks. Tethering of inflammatory cytokines such as interleukins (IL) 2 and 12 to alum yields extended neuroinflammation and brain immunosurveillance after intracranial administration, while avoiding systemic toxicity. In mouse models of both immunologically hot and cold brain tumors, the intracranial deposition of alum-tethered cytokines causes significant delay in tumor progression. RNA profiling reveals that engineered cytokines engage both innate and adaptive immunity in the brain. These findings suggest that engineered cytokines can reprogram brain immunosurveillance, informing the development of future therapies for neuroimmune diseases.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Tabet, A., Agarwal, Y., Stinson, J., Apra, C., Will, V., Manthey, M., Momin, N., Sheen, A., Murdock, M., Santollani, L., Tsai, L.-H., Chiu, I., Lawler, S. E., Irvine, D. J., Wittrup, K. D., Anikeeva, P.. 2022-06-24. Reprogramming brain immunosurveillance with engineered cytokines. https://doi.org/10.1101/2022.06.21.497082

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Engineered microvessel networks -- Longitudinal transcriptomic profiling validates chip-grown tissues as a robust model for studying vasculature

Vascularised Organ-on-Chip (OoC) models are promising New Approach Methodologies (NAMs), but their translation requires validation for defined Contexts of Use (CoU). Here, we combine microfluidic microvessel networks (MVNs) with longitudinal bulk and single-cell RNA sequencing to determine how cell provenance influences engineered vascular phenotype. Stromal cell identity produced distinct network architectures and transcriptional trajectories, demonstrating that support cells, commonly treated as interchangeable, represent an important CoU variable. Primary human pancreatic microvascular endothelial cells failed to form stable perfusable networks, but supplementation with 10% Human Umbilical Vein Endothelial Cells (HUVECs) or Blood Outgrowth Endothelial Cells (BOECs) rescued self-assembly. Single-cell transcriptomics identified specialised endothelial populations associated with vascular morphogenesis, including tip, stalk, phalanx, endothelial to mesenchymal transition (EndMT) and pericyte-like endothelial cells. Failed networks lacked coherent endothelial specialisation, whereas rescued networks restored stabilising cell states and revealed FLRT2--UNC5B signalling within pericyte-like HUVECs, recapitulating a pathway implicated in angiogenic development in vivo. These findings establish cell provenance as a critical determinant of microvascular NAM performance and demonstrate how transcriptomic validation can define and strengthen the biological relevance of microvessel-on-chip models for specific CoUs.

bioengineering↗

Benchmarking foundation models for resting-state functional magnetic resonance imaging time series in cognitive aging research

Foundation models trained on large neuroimaging datasets could help smaller studies investigate cognition from brain recordings. However, whether the foundation model-derived representations improve assessment of current cognition, prediction of follow-up cognition, or characterization of cognitive change remains unclear. We evaluated nine configurations from five model families that process regional resting-state functional magnetic resonance imaging time series, using 3,103 scans from 1,653 participants across two observational and five intervention aging cohorts. Primary frozen representations showed no consistent superiority over conventional functional connectivity for concurrent cognitive associations or diagnostic classification. Changing the readout improved selected concurrent cognitive associations without updating model weights, indicating that performance depended partly on how representations were extracted. Additional post-training and embedding alignment yielded gains in selected settings but did not consistently improve performance across outcomes. In the primary longitudinal analyses, imaging representations did not establish added value beyond baseline clinical measures. These findings show that readout choice influences concurrent cognitive associations, while the added value of these representations for longitudinal outcomes remains unestablished.

bioengineering↗

PROST: An Open Toolbox, Harmonised Multi-Lab Dataset, and Meta-Analysis of Ankle-Foot Roll-Over Shape

The ankle-foot roll-over shape (ROS) is the sagittal-plane path of the centre of pressure (CoP) during the stance phase of walking, expressed in a shank-based coordinate system. It describes the effective rocker geometry that emerges from both the shape and the elastic deformation of the ankle-foot system during walking, and informs prosthetic and orthotic design. Previous studies characterised ROS in small samples with differing laboratory protocols, so they have not systematically assessed inter-individual variability or its relation to anthropometrics. We developed the open-source Public ROS Toolbox (PROST) for standardised ROS computation, and used it to harmonise marker trajectories, ground reaction forces and CoP data from four public gait datasets collected in independent laboratories. For each leg, we fitted a circular arc to the pooled ROS of all its stance phases. In a one-stage individual-participant data meta-analysis, linear mixed-effects models, with dataset as a fixed effect and participant as a random intercept, related the arc radius and the horizontal coordinate of the circle centre to anthropometrics, and, in the two self-selected-speed datasets, to walking speed. The harmonised dataset comprises 249 participants and 5,667 stance phases at walking speeds of 0.7-8.5 km/h. Circular arcs fitted the ROS closely (mean RMS radial residual 1.9 mm). The radius had a median of 410.3 mm (interquartile range, IQR, 237.6 mm), and the circle centre lay posterior to the ankle (median -20.6 mm, IQR 49.5 mm). Between-participant differences, quantified by the intraclass correlation coefficient (ICC), accounted for 42% of the variance in log radius (95% CI 25-57%) and 47% of the variance in the horizontal coordinate of the circle centre (95% CI 24-65%). Anthropometrics explained a negligible share of this variance (radius: pseudo-R2 -0.001, 95% CI -0.03 to 0.12), and height normalisation did not reduce radius variability (robust coefficient of variation 43% with and without normalisation). Faster self-selected walking was associated with a larger radius and a more posterior circle centre. To our knowledge, this study provides the first harmonised multi-lab ROS dataset. Together with the open-source toolbox, it is publicly available to support reproducible research in gait biomechanics, rehabilitation device design and clinical gait assessment. ROS geometry was participant-specific but was not predicted by age, sex, height or mass. A device ROS scaled from anthropometrics is therefore unlikely to match an individual's ROS, motivating studies of whether matching it, through device geometry and stiffness, improves gait mechanics.

bioengineering↗