Exploring therapy transport from implantable medical devices using experimentally informed computational methods.

Implantable medical devices that can facilitate therapy transport to localized sites are being developed for a number of diverse applications, including the treatment of diseases such as diabetes and cancer, and tissue regeneration after myocardial infraction. These implants can take the form of an encapsulation device which encases therapy in the form of drugs, proteins, cells, and bioactive agents, in semi-permeable membranes. Such implants have shown some success but the nature of these devices pose a barrier to the diffusion of vital factors, which is further exacerbated upon implantation due to the foreign body response (FBR). The FBR results in the formation of a dense hypo-permeable fibrous capsule around devices and is a leading cause of failure in many implantable technologies. One potential method for overcoming this diffusion barrier and enhancing therapy transport from the device is to incorporate local fluid flow. In this work, we used experimentally informed inputs to characterize the change in the fibrous capsule over time and quantified how this impacts therapy release from a device using computational methods. Insulin was used as a representative therapy as encapsulation devices for Type 1 diabetes are among the most-well characterised. We then explored how local fluid flow may be used to counteract these diffusion barriers, as well as how a more practical pulsatile flow regimen could be implemented to achieve similar results to continuous fluid flow. The generated model is a versatile tool toward informing future device design through its ability to capture the expected decrease in insulin release over time resulting from the FBR and investigate potential methods to overcome these effects.

Integrating multiplexed imaging and multiscale modeling identifies tumor phenotype conversion as a critical component of therapeutic T cell efficacy.

Cancer progression is a complex process involving interactions that unfold across molecular, cellular, and tissue scales. These multiscale interactions have been difficult to measure and to simulate. Here, we integrated CODEX multiplexed tissue imaging with multiscale modeling software to model key action points that influence the outcome of T cell therapies with cancer. The initial phenotype of therapeutic T cells influences the ability of T cells to convert tumor cells to an inflammatory, anti-proliferative phenotype. This T cell phenotype could be preserved by structural reprogramming to facilitate continual tumor phenotype conversion and killing. One takeaway is that controlling the rate of cancer phenotype conversion is critical for control of tumor growth. The results suggest new design criteria and patient selection metrics for T cell therapies, call for a rethinking of T cell therapeutic implementation, and provide a foundation for synergistically integrating multiplexed imaging data with multiscale modeling of the cancer-immune interface. A record of this paper's transparent peer review process is included in the supplemental information.

Diversity of sugar-diphospholipid-utilizing glycosyltransferase families.

Peptidoglycan polymerases, enterobacterial common antigen polymerases, O-antigen ligases, and other bacterial polysaccharide polymerases (BP-Pols) are glycosyltransferases (GTs) that build bacterial surface polysaccharides. These integral membrane enzymes share the particularity of using diphospholipid-activated sugars and were previously missing in the carbohydrate-active enzymes database (CAZy; www.cazy.org ). While the first three classes formed well-defined families of similar proteins, the sequences of BP-Pols were so diverse that a single family could not be built. To address this, we developed a new clustering method using a combination of a sequence similarity network and hidden Markov model comparisons. Overall, we have defined 17 new GT families including 14 of BP-Pols. We find that the reaction stereochemistry appears to be conserved in each of the defined BP-Pol families, and that the BP-Pols within the families transfer similar sugars even across Gram-negative and Gram-positive bacteria. Comparison of the new GT families reveals three clans of distantly related families, which also conserve the reaction stereochemistry.

Subcortical-cortical white matter connectivity in adults with autism spectrum disorder and schizophrenia patients.

Autism spectrum disorder (ASD) and schizophrenia (SZ) are neuropsychiatric disorders that overlap in symptoms associated with social-cognitive impairment. Alterations of the cingulate cortex, subcortical, medial-temporal, and orbitofrontal structures are frequently reported in both disorders. In this study, we examined white-matter connectivity between these structures in adults with ASD and SZ patients compared with their respective neurotypical controls and indirectly with each other, using probabilistic and local DTI tractography. This exploratory study utilized publicly available neuroimaging databases, of adults with ASD (ABIDE II; n = 28) and SZ (COBRE; n = 38), age-gender matched neurotypicals (NT) and associated phenotypic data. Tractography was performed using Freesurfer and MRtrix software, and diffusion metrics of white-matter tracts between cingulate-, orbitofrontal- cortices, subcortical structures, parahippocampal, entorhinal cortex were assessed. In ASD, atypical diffusivity parameters were found in the isthmus cingulate and parahippocampal connectivity to subcortical and rostral-anterior cingulate, which were also associated with IQ and social skills (SRS). In contrast, atypical diffusivity parameters were observed between the medial-orbitofrontal cortex and subcortical structures in SZ, and were associated with executive function (i.e., IQ, processing speed) and emotional regulation. Overall, the results suggest that defects in the isthmus cingulate, medial-orbitofrontal, and striato-limbic white matter connectivity may help unravel the neural underpinnings of executive and social-emotional dysfunction at the core of neuropsychiatric disorders.

A Spatial Multi-Modal Dissection of Host-Microbiome Interactions within the Colitis Tissue Microenvironment.

The intricate and dynamic interactions between the host immune system and its microbiome constituents undergo dynamic shifts in response to perturbations to the intestinal tissue environment. Our ability to study these events on the systems level is significantly limited by in situ approaches capable of generating simultaneous insights from both host and microbial communities. Here, we introduce Microbiome Cartography (MicroCart), a framework for simultaneous in situ probing of host features and its microbiome across multiple spatial modalities. We demonstrate MicroCart by comprehensively investigating the alterations in both gut host and microbiome components in a murine model of colitis by coupling MicroCart with spatial proteomics, transcriptomics, and glycomics platforms. Our findings reveal a global but systematic transformation in tissue immune responses, encompassing tissue-level remodeling in response to host immune and epithelial cell state perturbations, and bacterial population shifts, localized inflammatory responses, and metabolic process alterations during colitis. MicroCart enables a deep investigation of the intricate interplay between the host tissue and its microbiome with spatial multiomics.

Epstein-Barr Virus Orchestrates Spatial Reorganization and Immunomodulation within the Classic Hodgkin Lymphoma Tumor Microenvironment.

Classic Hodgkin Lymphoma (cHL) is a tumor composed of rare malignant Hodgkin and Reed-Sternberg (HRS) cells nested within a T-cell rich inflammatory immune infiltrate. cHL is associated with Epstein-Barr Virus (EBV) in 25% of cases. The specific contributions of EBV to the pathogenesis of cHL remain largely unknown, in part due to technical barriers in dissecting the tumor microenvironment (TME) in high detail. Herein, we applied multiplexed ion beam imaging (MIBI) spatial pro-teomics on 6 EBV-positive and 14 EBV-negative cHL samples. We identify key TME features that distinguish between EBV-positive and EBV-negative cHL, including the relative predominance of memory CD8 T cells and increased T-cell dysfunction as a function of spatial proximity to HRS cells. Building upon a larger multi-institutional cohort of 22 EBV-positive and 24 EBV-negative cHL samples, we orthogonally validated our findings through a spatial multi-omics approach, coupling whole transcriptome capture with antibody-defined cell types for tu-mor and T-cell populations within the cHL TME. We delineate contrasting transcriptomic immunological signatures between EBV-positive and EBV-negative cases that differently impact HRS cell proliferation, tumor-immune interactions, and mecha-nisms of T-cell dysregulation and dysfunction. Our multi-modal framework enabled a comprehensive dissection of EBV-linked reorganization and immune evasion within the cHL TME, and highlighted the need to elucidate the cellular and molecular fac-tors of virus-associated tumors, with potential for targeted therapeutic strategies.

Spatially Segregated Macrophage Populations Predict Distinct Outcomes In Colon Cancer.

Tumor-associated macrophages are transcriptionally heterogeneous, but the spatial distribution and cell interactions that shape macrophage tissue roles remain poorly characterized. Here, we spatially resolve five distinct human macrophage populations in normal and malignant human breast and colon tissue and reveal their cellular associations. This spatial map reveals that distinct macrophage populations reside in spatially segregated micro-environmental niches with conserved cellular compositions that are repeated across healthy and diseased tissue. We show that IL4I1+ macrophages phagocytose dying cells in areas with high cell turnover and predict good outcome in colon cancer. In contrast, SPP1+ macrophages are enriched in hypoxic and necrotic tumor regions and portend worse outcome in colon cancer. A subset of FOLR2+ macrophages is embedded in plasma cell niches. NLRP3+ macrophages co-localize with neutrophils and activate an inflammasome in tumors. Our findings indicate that a limited number of unique human macrophage niches function as fundamental building blocks in tissue.

Multimodal and spatially resolved profiling identifies distinct patterns of T cell infiltration in nodal B cell lymphoma entities.

The redirection of T cells has emerged as an attractive therapeutic principle in B cell non-Hodgkin lymphoma (B-NHL). However, a detailed characterization of lymphoma-infiltrating T cells across B-NHL entities is missing. Here we present an in-depth T cell reference map of nodal B-NHL, based on cellular indexing of transcriptomes and epitopes, T cell receptor sequencing, flow cytometry and multiplexed immunofluorescence applied to 101 lymph nodes from patients with diffuse large B cell, mantle cell, follicular or marginal zone lymphoma, and from healthy controls. This multimodal resource revealed quantitative and spatial aberrations of the T cell microenvironment across and within B-NHL entities. Quantitative differences in PD1+ TCF7- cytotoxic T cells, T follicular helper cells or IKZF3+ regulatory T cells were linked to their clonal expansion. The abundance of PD1+ TCF7- cytotoxic T cells was associated with poor survival. Our study portrays lymphoma-infiltrating T cells with unprecedented comprehensiveness and provides a unique resource for the investigation of lymphoma biology and prognosis.

MAPS: pathologist-level cell type annotation from tissue images through machine learning.

Highly multiplexed protein imaging is emerging as a potent technique for analyzing protein distribution within cells and tissues in their native context. However, existing cell annotation methods utilizing high-plex spatial proteomics data are resource intensive and necessitate iterative expert input, thereby constraining their scalability and practicality for extensive datasets. We introduce MAPS (Machine learning for Analysis of Proteomics in Spatial biology), a machine learning approach facilitating rapid and precise cell type identification with human-level accuracy from spatial proteomics data. Validated on multiple in-house and publicly available MIBI and CODEX datasets, MAPS outperforms current annotation techniques in terms of speed and accuracy, achieving pathologist-level precision even for typically challenging cell types, including tumor cells of immune origin. By democratizing rapidly deployable and scalable machine learning annotation, MAPS holds significant potential to expedite advances in tissue biology and disease comprehension.

Retention of Virus Versus Surrogate, by Ultrafiltration in Seawater: Case Study of Norovirus Versus Tulane.

In the field of chemical engineering and water treatment, the study of viruses, included surrogates, is well documented. Often, surrogates are used to study viruses and their behavior because they can be produced in larger quantities in safer conditions and are easier to handle. In fact, surrogates allow studying microorganisms which are non-infectious to humans but share some properties similar to pathogenic viruses: structure, composition, morphology, and size. Human noroviruses, recognized as the leading cause of epidemics and sporadic cases of gastroenteritis across all age groups, may be mimicked by the Tulane virus. The objectives of this work were to study (i) the ultrafiltration of Tulane virus and norovirus to validate that Tulane virus can be used as a surrogate for norovirus in water treatment process and (ii) the retention of norovirus and the surrogate as a function of water quality to better understand the use of the latter pathogenic viruses. Ultrafiltration tests showed significant logarithmic reduction values (LRV) in viral RNA: around 2.5 for global LRV (i.e., based on the initial and permeate average concentrations) and between 2 and 6 for average LRV (i.e., retention rate considering the increase of viral concentration in the retentate), both for norovirus and the surrogate Tulane virus. Higher reduction rates (from 2 to 6 log genome copies) are obtained for higher initial concentrations (from 101 to 107 genome copies per mL) due to virus aggregation in membrane lumen. Tulane virus appears to be a good surrogate for norovirus retention by membrane processes.

Intermittent actuation attenuates fibrotic behaviour of myofibroblasts.

The foreign body response (FBR) to implanted materials culminates in the deposition of a hypo-permeable, collagen rich fibrotic capsule by myofibroblast cells at the implant site. The fibrotic capsule can be deleterious to the function of some medical implants as it can isolate the implant from the host environment. Modulation of fibrotic capsule formation has been achieved using intermittent actuation of drug delivery implants, however the mechanisms underlying this response are not well understood. Here, we use analytical, computational, and in vitro models to understand the response of human myofibroblasts (WPMY-1 stromal cell line) to intermittent actuation using soft robotics and investigate how actuation can alter the secretion of collagen and pro/anti-inflammatory cytokines by these cells. Our findings suggest that there is a mechanical loading threshold that can modulate the fibrotic behaviour of myofibroblasts, by reducing the secretion of soluble collagen, transforming growth factor beta-1 and interleukin 1-beta, and upregulating the anti-inflammatory interleukin-10. By improving our understanding of how cells involved in the FBR respond to mechanical actuation, we can harness this technology to improve functional outcomes for a wide range of implanted medical device applications including drug delivery and cell encapsulation platforms. STATEMENT OF SIGNIFICANCE: A major barrier to the successful clinical translation of many implantable medical devices is the foreign body response (FBR) and resultant deposition of a hypo-permeable fibrotic capsule (FC) around the implant. Perturbation of the implant site using intermittent actuation (IA) of soft-robotic implants has previously been shown to modulate the FBR and reduce FC thickness. However, the mechanisms of action underlying this response were largely unknown. Here, we investigate how IA can alter the activity of myofibroblast cells, and ultimately suggest that there is a mechanical loading threshold within which their fibrotic behaviour can be modulated. These findings can be harnessed to improve functional outcomes for a wide range of medical implants, particularly drug delivery and cell encapsulation devices.

BCG vaccination stimulates integrated organ immunity by feedback of the adaptive immune response to imprint prolonged innate antiviral resistance.

Bacille Calmette-Guérin (BCG) vaccination can confer nonspecific protection against heterologous pathogens. However, the underlying mechanisms remain mysterious. We show that mice vaccinated intravenously with BCG exhibited reduced weight loss and/or improved viral clearance when challenged with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 B.1.351) or PR8 influenza. Protection was first evident between 14 and 21 d post-vaccination and lasted ∼3 months. Notably, BCG induced a biphasic innate response and robust antigen-specific type 1 helper T cell (TH1 cell) responses in the lungs. MyD88 signaling was essential for innate and TH1 cell responses, and protection against SARS-CoV-2. Depletion of CD4+ T cells or interferon (IFN)-γ activity before infection obliterated innate activation and protection. Single-cell and spatial transcriptomics revealed CD4-dependent expression of IFN-stimulated genes in lung myeloid and epithelial cells. Notably, BCG also induced protection against weight loss after mouse-adapted SARS-CoV-2 BA.5, SARS-CoV and SHC014 coronavirus infections. Thus, BCG elicits integrated organ immunity, where CD4+ T cells feed back on tissue myeloid and epithelial cells to imprint prolonged and broad innate antiviral resistance.

Characterization and structural study of a novel ß-N-acetylgalactosaminidase from Niabella aurantiaca.

We report here the identification, characterization and three-dimensional (3D) structure determination of NaNga, a newly identified ß-N-acetylgalactosaminidase from the Gram-negative soil bacterium Niabella aurantiaca DSM 17617. When recombinantly expressed in Escherichia coli, the enzyme selectively cleaved 4-nitrophenyl-N-acetyl-ß-d-galactosamine (pNP-ß-d-GalpNAc). The X-ray crystal structure of the protein was refined to 2.5 Å and consists of an N-terminal ß-sandwich domain and a (ß/α)8 barrel catalytic domain. Despite a mere 22% sequence identity, the 3D structure of NaNga is similar to those previously determined for family GH123 members, suggesting it also employs the same substrate-assisted catalytic mechanism. Inhibition by N-acetyl-galactosamine thiazoline (GalNAc-thiazoline) supports the suggested mechanism. A phylogenetic analysis of its proximal sequence space shows significant clustering of unknown sequences around NaNga with sufficient divergence with previously identified GH123 members to subdivide this family into distinct subfamilies. Although the actual biological substrate of our enzyme remains unknown, examination of the active site pocket suggests that it may be a ß-N-acetylgalactosaminide substituted by a monosaccharide at O-3. Analysis of the genomic context suggests, in turn, that this substituted ß-N-acetylgalactosaminide may be appended to a d-arabinan from an environmental Actinomycete.

T cell-mediated curation and restructuring of tumor tissue coordinates an effective immune response.

Antigen-specific T cells traffic to, are influenced by, and create unique cellular microenvironments. Here we characterize these microenvironments over time with multiplexed imaging in a melanoma model of adoptive T cell therapy and human patients with melanoma treated with checkpoint inhibitor therapy. Multicellular neighborhood analysis reveals dynamic immune cell infiltration and inflamed tumor cell neighborhoods associated with CD8+ T cells. T cell-focused analysis indicates T cells are found along a continuum of neighborhoods that reflect the progressive steps coordinating the anti-tumor immune response. More effective anti-tumor immune responses are characterized by inflamed tumor-T cell neighborhoods, flanked by dense immune infiltration neighborhoods. Conversely, ineffective T cell therapies express anti-inflammatory cytokines, resulting in regulatory neighborhoods, spatially disrupting productive T cell-immune and -tumor interactions. Our study provides in situ mechanistic insights into temporal tumor microenvironment changes, cell interactions critical for response, and spatial correlates of immunotherapy outcomes, informing cellular therapy evaluation and engineering.

Integrating Multiplexed Imaging and Multiscale Modeling Identifies Tumor Phenotype Transformation as a Critical Component of Therapeutic T Cell Efficacy.

Cancer progression is a complex process involving interactions that unfold across molecular, cellular, and tissue scales. These multiscale interactions have been difficult to measure and to simulate. Here we integrated CODEX multiplexed tissue imaging with multiscale modeling software, to model key action points that influence the outcome of T cell therapies with cancer. The initial phenotype of therapeutic T cells influences the ability of T cells to convert tumor cells to an inflammatory, anti-proliferative phenotype. This T cell phenotype could be preserved by structural reprogramming to facilitate continual tumor phenotype conversion and killing. One takeaway is that controlling the rate of cancer phenotype conversion is critical for control of tumor growth. The results suggest new design criteria and patient selection metrics for T cell therapies, call for a rethinking of T cell therapeutic implementation, and provide a foundation for synergistically integrating multiplexed imaging data with multiscale modeling of the cancer-immune interface.

Dual scaffold delivery of miR-210 mimic and miR-16 inhibitor enhances angiogenesis and osteogenesis to accelerate bone healing.

Angiogenesis is critical for successful bone repair, and interestingly, miR-210 and miR-16 possess counter-active targets involved in both angiogenesis and osteogenesis: miR-210 acts as an activator by silencing EFNA3 & AcvR1b, while miR-16 inhibits both pathways by silencing VEGF & Smad5. It was thus hypothesized that dual delivery of both a miR-210 mimic and a miR-16 inhibitor from a collagen-nanohydroxyapatite scaffold system may hold significant potential for bone repair. Therefore, this systems potential to rapidly accelerate bone repair by directing enhanced angiogenic-osteogenic coupling in host cells in a rat calvarial defect model at a very early 4 week timepoint was assessed. In vitro, the treatment significantly enhanced angiogenic-osteogenic coupling of human mesenchymal stem cells, with enhanced calcium deposition after just 10 days in 2D and 14 days on scaffolds. In vivo, these dual-miRNA loaded scaffolds showed more than double bone volume and vessel recruitment increased 2.3 fold over the miRNA-free scaffolds. Overall, this study demonstrates the successful development of a dual-miRNA mimic/inhibitor scaffold for enhanced in vivo bone repair for the first time, and the possibility of extending this 'off-the-shelf' platform system to applications beyond bone offers immense potential to impact a myriad of other tissue engineering areas. STATEMENT OF SIGNIFICANCE: miRNAs have potential as a new class of bone healing therapeutics as they can enhance the regenerative capacity of bone-forming cells. However, angiogenic-osteogenic coupling is critical for successful bone repair. Therefore, this study harnesses the delivery of miR-210, known to be an activator of both angiogenesis and osteogenesis, and miR-16 inhibitor, as miR-16 is known to inhibit both pathways, from a collagen-nanohydroxyapatite scaffold system to rapidly enhance osteogenesis in vitro and bone repair in vivo in a rat calvarial defect model. Overall, it describes the successful development of the first dual-miRNA mimic/inhibitor scaffold for enhanced in vivo bone repair. This 'off-the-shelf' platform system offers immense potential to extend beyond bone applications and impact a myriad of other tissue engineering areas.

Integration of spatial and single-cell data across modalities with weakly linked features.

Although single-cell and spatial sequencing methods enable simultaneous measurement of more than one biological modality, no technology can capture all modalities within the same cell. For current data integration methods, the feasibility of cross-modal integration relies on the existence of highly correlated, a priori 'linked' features. We describe matching X-modality via fuzzy smoothed embedding (MaxFuse), a cross-modal data integration method that, through iterative coembedding, data smoothing and cell matching, uses all information in each modality to obtain high-quality integration even when features are weakly linked. MaxFuse is modality-agnostic and demonstrates high robustness and accuracy in the weak linkage scenario, achieving 20~70% relative improvement over existing methods under key evaluation metrics on benchmarking datasets. A prototypical example of weak linkage is the integration of spatial proteomic data with single-cell sequencing data. On two example analyses of this type, MaxFuse enabled the spatial consolidation of proteomic, transcriptomic and epigenomic information at single-cell resolution on the same tissue section.

Soft robot-mediated autonomous adaptation to fibrotic capsule formation for improved drug delivery.

The foreign body response impedes the function and longevity of implantable drug delivery devices. As a dense fibrotic capsule forms, integration of the device with the host tissue becomes compromised, ultimately resulting in device seclusion and treatment failure. We present FibroSensing Dynamic Soft Reservoir (FSDSR), an implantable drug delivery device capable of monitoring fibrotic capsule formation and overcoming its effects via soft robotic actuations. Occlusion of the FSDSR porous membrane was monitored over 7 days in a rodent model using electrochemical impedance spectroscopy. The electrical resistance of the fibrotic capsule correlated to its increase in thickness and volume. Our FibroSensing membrane showed great sensitivity in detecting changes at the abiotic/biotic interface, such as collagen deposition and myofibroblast proliferation. The potential of the FSDSR to overcome fibrotic capsule formation and maintain constant drug dosing over time was demonstrated in silico and in vitro. Controlled closed loop release of methylene blue into agarose gels (with a comparable fold change in permeability relating to 7 and 28 days in vivo) was achieved by adjusting the magnitude and frequency of pneumatic actuations after impedance measurements by the FibroSensing membrane. By sensing fibrotic capsule formation in vivo, the FSDSR will be capable of probing and adapting to the foreign body response through dynamic actuation changes. Informed by real-time sensor signals, this device offers the potential for long-term efficacy and sustained drug dosing, even in the setting of fibrotic capsule formation.

Soft robotic platform for controlled, progressive and reversible aortic constriction in a small animal model.

Our understanding of cardiac remodeling processes due to left ventricular pressure overload derives largely from animal models of aortic banding. However, these studies fail to simultaneously enable control over disease progression and reversal, hindering their clinical relevance. Here, we describe a method for controlled, progressive, and reversible aortic banding based on an implantable expandable actuator that can be finely controlled to modulate aortic banding and debanding in a rat model. Through catheterization, imaging, and histologic studies, we demonstrate that our model can recapitulate the hemodynamic and structural changes associated with pressure overload in a controllable manner. We leverage the ability of our model to enable non-invasive aortic debanding to show that these changes can be partly reversed due to cessation of the biomechanical stimulus. By recapitulating longitudinal disease progression and reversibility, this model could elucidate fundamental mechanisms of cardiac remodeling and optimize timing of intervention for pressure overload.

MAPS: Pathologist-level cell type annotation from tissue images through machine learning.

Highly multiplexed protein imaging is emerging as a potent technique for analyzing protein distribution within cells and tissues in their native context. However, existing cell annotation methods utilizing high-plex spatial proteomics data are resource intensive and necessitate iterative expert input, thereby constraining their scalability and practicality for extensive datasets. We introduce MAPS (Machine learning for Analysis of Proteomics in Spatial biology), a machine learning approach facilitating rapid and precise cell type identification with human-level accuracy from spatial proteomics data. Validated on multiple in-house and publicly available MIBI and CODEX datasets, MAPS outperforms current annotation techniques in terms of speed and accuracy, achieving pathologist-level precision even for challenging cell types, including tumor cells of immune origin. By democratizing rapidly deployable and scalable machine learning annotation, MAPS holds significant potential to expedite advances in tissue biology and disease comprehension.