Although rare (1 in 150,000 cases), Niemann Pick Type C (NPC) is a progressive, genetic lysosomal storage disorder where patients have a life expectancy of <20 years due to the lack of rationally designed therapies. Recent evidence demonstrates the importance of histone deacetylase (HDAC) inhibition in impeding the cholesterol storage defect in NPC, thereby playing a key role in NPC progression. HDACs, particularly Class I HDACs (HDACs 1, 2, 3), are epigenetic modulators that have shown in vivo promise against NPC cholesterol accumulation when inhibited. There are 7 Class I HDAC inhibitors (HDACi) in clinical trials. However, all Class I HDACi in the clinic are pan-inhibitors that are plagued with off-target effects, leading to toxicities. HDAC3 has been specifically shown to be significantly dysregulated in NPC, making it an attractive therapeutic target. In this study, we are exploring the concept of introducing covalent warheads to generate more efficacious compounds. This program is geared toward synthesizing, and evaluating the physico-chemical properties of HDAC3 covalent inhibitors in NPC.

Background:
Congenital disorders, such as congenital diaphragmatic hernia (CDH), pose significant challenges in maternal-fetal health. They affect approximately 2% of live births and contribute to 20% of infant mortality. Developing safe and effective gene therapies for congenital diseases requires early intervention with lipid nanoparticles (LNPs) targeted to the diseased fetal organ. LNP formulations consist of four different classes of lipids, each could be of various molecular structures or molar ratios, creating a vast design space for optimization.

Methodology:
We developed and characterized a diverse library of LNP formulations using microfluidics. Machine learning (ML) models were employed to identify key determinants of LNP size and zeta potential. A total of 41 LNP formulations were screened across different in vitro placental models, generating a dataset of hundreds of transport data points. Our dataset included 18 input features delineating 48 transport experiments. Random Forest algorithms were used to analyze the dataset and identify the top features driving the transport percentage and kinetics. We further evaluated the LNPs' safety and transfection efficiency in placental trophoblasts and fetal lung fibroblasts. The top-performing formulations are currently being assessed as a potential prenatal therapy to rescue abnormal lung development in a CDH rat model.

Results:
In our in-vitro and ex-vivo studies, LNPs showed minimal to no toxicity in fetal and placental cells. The Random Forest algorithm identified the top features driving LNPs placental transport percentage and kinetics; zeta potential and dose were the top features. Leveraging insights from the ML model results, we developed new LNPs formulations that achieved a 622% increase in placental transport. Furthermore, studying LNPs in an integrated placental and fetal lung fibroblasts model showed a strong correlation between zeta potential and fetal lung transfection. Also, it ensured the integrity of the LNPs following transplacental transport.

Conclusion:
Utilizing machine learning has advanced our understanding of LNPs placental transport and delineated key design features for optimization. Our research findings represent a significant step toward establishing the safety and efficacy of LNP-based gene delivery to fetal organs, paving the way for potential prenatal therapies.

Macrophage-derived BIGH3 drives lung fibrosis.
Authors: Altieri A1, Chung Y1, Schuster R2,3, Abdullah F1, Cooper S4, Hasan S1, Namdar A1, Hinz B2,3, Buechler MB1.
1Department of Immunology, University of Toronto.
2Faculty of Dentistry, University of Toronto.
3Keenan Research Institute for Biomedical Science, St. Michael’s Hospital.
4Phenomic AI.

Abstract: Idiopathic pulmonary fibrosis (IPF) affects 14,000 Canadians per year. IPF is an incurable long-term lung disease where scarring (fibrosis) causes difficulty breathing, decreased quality of life, and shortened lifespan. IPF is characterized by decreased lung function caused by the pathological accumulation of extracellular matrix (ECM) proteins by pro-fibrotic fibroblasts. Clinical trials targeting the potent ECM-inducer transforming growth factor B (TGF-B) have failed due to uncontrollable side effects, resulting in unmet clinical need for IPF patients. We propose targeting Transforming growth factor-B inducible growth hormone 3 (BIGH3), a TGF-B co-factor that may be required for the pro-fibrotic effects of TGF-B, as a novel therapeutic opportunity for IPF treatment. We have found that bleomycin administration elicited lung fibrosis and the upregulation of BIGH3 by fibroblasts and macrophages. Next, we generated Bigh3-/- knockout mice and observed that these mice lost less weight and exhibited diminished expression of ECM genes such as Col1a1 and Fn1 compared to WT mice that received bleomycin. In vitro, Bigh3-/- macrophages induced significantly less Col1a1 expression in lung fibroblasts compared to Bigh3+/+ macrophages. Taken together, these data suggest that fibroblast-macrophage interactions and BIGH3 may promote lung fibrosis.

Introduction
Antibody therapies provide precise and effective treatment for degenerative retinal diseases but are limited by the need for frequent intravitreal injections. This poses challenges such as patient noncompliance, increased treatment burden, and risks associated with repeated procedures. To address these limitations, sustained delivery systems have emerged as a promising strategy to reduce injection frequency while maintaining therapeutic efficacy. This work explores a hyaluronan (HA)-based hydrogel platform functionalized with peptides targeting the Fragment crystallizable (Fc) domain of antibodies. By incorporating peptides with different binding affinities, the system enables controlled and adaptable antibody release. Bevacizumab, a therapeutic monoclonal antibody, was selected as a model to demonstrate this platform's potential.

Materials and Methods
Two Fc-binding peptides with distinct binding affinities were synthesized via solid-phase peptide synthesis and characterized by biolayer interferometry (BLI) to determine equilibrium dissociation constants (KD). These peptides were immobilized onto a HA-based hydrogel using oxime and IEDDA chemistry to create a crosslinked network. Bevacizumab was loaded into the hydrogels, and its release kinetics were evaluated through enzyme-linked immunosorbent assay (ELISA).

Results
The two peptides exhibited different binding affinities to the Fc domain of bevacizumab. Their covalent conjugation to a HA-based hydrogel was successful and resulted in distinct release kinetics from the hydrogels. These results highlight the potential of affinity-controlled release via the Fc as a platform for customizable and sustained therapeutic antibody delivery.

Conclusions
This comprehensive approach enabled the synthesis of Fc-affinity peptides, the characterization of their binding affinity to bevacizumab, and the design of functional Fc-peptide-conjugated HA-based hydrogels capable of sustained bioactive bevacizumab release in vitro. By utilizing peptides with distinct binding affinities, the system achieves customizable release profiles without the need for antibody modification. This study highlights the potential of affinity-controlled release via the Fc domain as a versatile platform for antibody delivery and offers promise for reducing injection frequency and can be applied to any Fc-containing protein.

Acknowledgments
This work was supported by Ontario Graduate Scholarship (to NB), and PRiME – next generation precision medicine at the University of Toronto (to DI-B).

Background: Multiple Sclerosis (MS) is a neuroinflammatory disease characterized by immune cell infiltration and lesions in the central nervous system (CNS). Radiologically Isolated Syndrome (RIS) is a term used when lesions which fulfil strict radiological criteria for MS are present in the CNS without the associated symptoms and is believed to be the precursor to MS with variable outcome. Clear, accessible, and reproducible approaches to estimate prognosis for persons with RIS (pwRIS) remain to be developed. In an immune-driven disease such as MS, early changes in peripheral blood may allow for prediction of disease progression while contributing additional insight into early CNS trafficking of immune cells.

Objectives: We propose to study peripheral blood mononuclear cell and spinal fluid (CSF) samples of pwRIS, pwMS and healthy control (HC) individuals to determine a pattern and improve in-clinic treatment for pwRIS. Selected for this study is the lymphocyte migration receptor CXCR4, that has been implicated to be an MS-specific biomarker, and its ligand CXCL12.

Methods: Following collection of peripheral blood, the samples were phenotyped ex-vivo by Cytometry by Time of Flight, particularly focusing on T cell migration and activation markers. Following collection of CSF, an Ella assay was performed to titer levels of CXCL12 and correlated to markers of neurodegeneration from the same donors.

Results: Significant upregulation of CXCR4 was observed on multiple lymphocyte subsets in pwRIS, including MS-relevant subsets. CXCL12 levels in pwRIS and pwMS CSF were observed to have increased significantly in comparison to HC. These levels positively correlated to both GFAP and NfL levels in CSF.

Conclusions: We have shown that CXCR4 is upregulated on several lymphocyte subsets, suggesting an aberrant immune response leading to early CNS trafficking. CXCL12, a proposed ligand for early CNS chemotaxis and entry, is upregulated in the CSF of pwRIS and pwMS. We found that CXCL12 levels correlate with established markers of CNS damage (NfL, GFAP), suggesting a potential use for early prognosis. These findings will be central in the improvement in clinical care of pwRIS by providing a tool to estimate prognosis and allow for specialized treatment, while understanding the pathophysiology of early disease.

Proper control of protein synthesis is critical to cell survival and function. Metabolic incorporation of amino acid analogues is an established method for interrogating proteomic changes directly at the translation level, but existing probes have limited sensitivity and applicability in animal models. Namely, the gold standard BONCAT method (BioOrthogonal Non-Canonical Amino acid Tagging), which uses azide- and alkyne-bearing analogues of methionine, suffers from poor bio-incorporation efficiency in the presence of the canonical amino acid. We aim to address this challenge using an alternative strategy involving a phenylalanine analogue and a newly developed bioorthogonal labeling reaction.

TePhe is an analogue of phenylalanine in which the phenyl side chain is replaced by a tellurophene ring. Using only endogenous translation machinery, TePhe competes effectively against phenylalanine for incorporation into newly synthesized proteins, and can thus achieve robust incorporation in complete media for cell culture as well as in through IV injections in mice without additional special treatments.

The tellurophene side chain of TePhe is a versatile functionality compatible with multiple analytical modalities. It was originally developed as a heavy metal tag for direct detection by mass cytometry, but we have recently discovered it to also be a powerful handle for bioconjugation. Labeling is achieved through oxidative activation of the tellurophene followed by cycloaddition with a strained alkyne. The process is extremely rapid (complete within 20 min) and enables TePhe to be stably modified for fluorescence imaging as well as target enrichment purposes in an analogous manner to BONCAT probes.

This poster will showcase the robust OSTAC-based fluorescent labeling that has been achieved on purified proteins, lysates, and fixed cell samples. OSTAC is compatible with antibody staining and can be multiplexed with the copper-catalyzed alkyne-azide click reaction for multicomponent visualization. Finally, we will highlight how TePhe injection into a mouse model allows for analysis of protein synthesis in tissues by fluorescence microscopy and by mass-spectrometry-based proteomics.

Human neurological diseases are complex disorders affecting the nervous system, leading to significant cognitive, motor, and emotional impairments. Genetic defects cause many such brain diseases. While these disorders have been exceedingly difficult to treat using conventional approaches, they are ideal candidates for gene therapy, with antisense oligonucleotide (ASO) therapy offering a highly promising approach. To date, the US FDA has approved three ASO drugs targeting previously untreatable CNS diseases, with many other clinical trials underway. However, one of the most significant limitations of ASO-based therapy lies in its delivery. Existing ASO drugs require repeated high-dose injections to show clinical benefits, imposing substantial financial and treatment barriers on the patients. Therefore, we need a cost-effective, efficient, and dose-optimized one-stop delivery system for ASOs.

My project proposes DNA origami (DORI) as a novel nanocarrier for ASOs. We are working on developing a DORI-ASO therapy aimed at treating Alzheimer’s disease (AD), a neurodegenerative disorder impacting millions of adults worldwide, as well as Dravet syndrome (DS), a rare neurodevelopmental condition marked by severe drug-resistant seizures and cognitive deficits, for which no treatments currently exist. We have identified under-trial ASOs targeting human MAPT (for AD; BIIB080/IONIS-MAPTRx) and SCN1A (for DS; STK-001) genes and successfully developed DORI-ASO complexes in the Chou Lab. Preliminary results indicate that DORI-ASOMAPT effectively reduces MAPT expression in a human primary neural cell line (ReN VM) at very low dosages. Additionally, we demonstrated the ability to incorporate multiple ASOs within a single DORI molecule (>2), achieving consistent responses. While these initial findings are promising, extensive standardization experiments are ongoing to refine and develop additional DORI-ASO complexes. In the future, we also plan to track fluorescence-labeled DORI-ASO complex stability over time, intracellular localization, and evaluate dosage effects. For subsequent efficacy testing, we aim to test these DORI-ASO candidates in the preclinical human brain organoid model of AD and DS; we will identify the most promising DORI-ASOs, characterized by the reduction of protein expression and maximum stability at the lowest dosage.

Therefore, this research will significantly advance ASO-based therapy treatment and establish a novel precision medicine strategy for a wide spectrum of brain disorders.

The surface of all cells is decorated in a dense forest of carbohydrates. These structures are covalently linked to proteins or lipids on the cell surface and are critical regulators of cellular function. They regulate the folding, stability, and function of the proteins they are attached to, including signalling receptors and transporters on the cell surface, and act as ligands to enhance or block cellular communication and adhesion. In the context of immune cells called T cells, artificially manipulating carbohydrates that terminate in a monosaccharide called sialic acid (i.e., sialoglycans) directly affects their activation and effector function, and are already the target of cancer immunotherapy clinical trials. However, it is unknown whether T cells in vivo naturally present different levels of sialoglycans on their surface depending on their activation status (e.g., Naïve T cells, Effector-Memory T cells, Exhausted T cells). Herein, we use high-dimensionality flow cytometry and RNA sequencing to characterize the diversity of sialoglycan presentation on T cells from healthy humans and mice. We show that sialoglycan presentation is diverse across murine T cell populations, but largely homogenous on all human T cell populations at rest. Murine and human T cells also display divergent dynamics of sialoglycan remodelling upon activation – further suggesting fundamental species differences. Overall, our work serves as an atlas that maps the diversity and dynamics of functionally relevant carbohydrates (i.e., sialoglycans) across a wide range of human and murine T cell populations. These insights are broadly useful and critical to consider when developing and testing therapeutics that target T cell surface carbohydrates.

Viruses continue to pose a significant health burden to the human population and recent history has shown a concerning surge in viral threats. Treatment options for viral infections are limited, and viruses have proven adept at evolving resistance to many existing therapies, highlighting a significant vulnerability in our defenses. In response to this challenge, our group has explored the modulation of cellular RNA processing as an alternative paradigm to antiviral development. Many different viruses depend on the host cell’s RNA splicing machinery to maximize their coding potential. Small alterations to this host process results in catastrophic changes in viral protein production ultimately inhibiting virus replication. Previously, we identified the small molecule 5342191, as a potent inhibitor of HIV-1 replication. 5342191 induces changes in viral RNA accumulation at doses that minimally affect host gene expression, demonstrating the greater susceptibility of HIV-1 to this treatment approach. More recent experiments have identified 5342191 as a potent inhibitor of adenovirus, coronavirus, and influenza virus replication. In each case, 5342191 addition induced significant alterations in viral RNA accumulation, resulting in loss of viral structural protein expression. Interestingly, our investigations revealed that the antiviral effect of 5342191 against HIV-1, coronaviruses, and influenza is mediated through the activation of specific cell signaling networks, including GPCR and/or MEK signaling pathways. Furthermore, in parallel tests, while resistant viruses were rapidly isolated for compounds targeting either virus-encoded proteases or polymerases, to date we have not isolated 534219-resistant variants of coronavirus or influenza. Together, these studies highlight the therapeutic potential of compounds that target cellular processes essential for the replication of multiple viruses. Not only do these compounds hold promise as broad-spectrum antivirals, they also offer the potential for greater durability in combating viral infections.

Alzheimer’s disease (AD) remains the leading cause of dementia worldwide and currently lacks effective therapies. Recent studies have identified AD-associated genetic variants in several microglial-enriched genes including TREM2 and ABI3, highlighting microglia as key contributors to disease pathogenesis and as promising therapeutic targets. Current reports on the impact of ABI3 on AD pathology in mouse models are conflicted as the deletion of ABI3 reduces amyloid phenotypes in human Amyloid Precursor Protein (APP) transgenic mouse models on a C57 background but exacerbates these phenotypes in similar lines on an SJL background. We have recently identified a species-specific missense substitution at TREM2 codon 148 (S148 in C57 and E148 in SJL mice) that significantly modulates microglial responses, especially in the absence of ABI3, and explains the SJL vs C57 dichotomy.

Using hybrid mouse models expressing TREM2 S148 or E148 with or without ABI3 knockout (ABI3KO) on similar genetic backgrounds, we demonstrate that the S148 variant enhances protective microglial responses (i.e. increased TREM2 signalling, sTREM2 shedding, and Aβ clearance) whereas the E148 variant impairs these protective responses. We also discovered that these opposing features are amplified by ABI3KO. Thus, the protective effects of S148 microglia are further enhanced in S148+ABI3KO microglia and conversely, the attenuation of protective microglial effects in E148 microglia is further exacerbated in E148+ABI3KO microglia.

These in vitro findings which are quantitatively consistent with our in vivo observations in APP transgenic mice, reveal the existence of a previously unrecognized functional interaction between TREM2 and ABI3 that governs microglial activity and is impacted by the TREM2 E148S variant. Crucially, since the human wild-type allele at codon 148 is the “risky” E148, in future work, we aim to determine whether the E148 to S148 substitution in human microglia has the same protective effect observed in murine microglia. Characterizing the TREM2 E148S variant as a novel therapeutic target for AD could lead to the generation of a pipeline of precision medicine approaches that will duplicate the effects of the rare protective S148 variant to rectify the effects of the common deleterious TREM2 E148 allele, leading to potential transformative treatments for AD.

Pre-term labour is the leading cause of infant morbidity and mortality, with 1:10 births affected. Despite its prevalence, interventions to prevent preterm labour are limited, with no effective pharmacological strategy that can stop labour and prolong gestation. This limitation is in part due to lack of understanding of how labour is regulated, including the genomic mechanisms driving pre-term labour.

At labour onset, the myometrium, smooth muscle of the uterus, transitions to a contractile state, representing a functional change essential for parturition. Previously, our lab has demonstrated that changes in gene expression associated with this switch in contractility at term labour were regulated at the epigenetic level, largely due to changes in chromatin accessibility. Given the role of multi-transcription factor complexes in other contexts where cell state transition occurs, many transcription factors are likely involved in the contractile state switch in the myometrium. To identify these transcription factors in the context of pre-term labour, we examined the differential chromatin profiles of the myometrium during pre-term labour in two mouse models; intrauterine lipopolysaccharide (LPS) injection, to mimic infection-induced labour, and mifepristone (RU486) treatment, which induces labour via progesterone withdrawal. By analyzing changes in chromatin accessibility using ATAC-seq, we identified transcription factor binding sites (TFBS) that were unique to each pre-term labour model, as well as those shared. Most notably, though we have shown both inflammatory-associated factors (e.g. NFKB, RELA) and AP-1 factors as enriched in the mouse myometrium during term labour, these factors were present independently in the LPS and mifepristone models respectively. Furthermore, we found a striking overlap of TFBS that were lost in both models, suggesting a novel and potentially targetable network of transcription factors that are involved in maintaining a non-contractile myometrium.

Through the application of ATAC-seq, we have provided additional evidence for the dynamic regulation of the myometrium at labour onset. We have further identified that mechanisms common in term labour can be independently triggered in pre-term labour models. This identification of transcription factors involved in mediating pre-term labour will enable further dissection of labour-linked regulatory mechanisms and the development of novel therapeutics to prevent preterm labour.

Glioblastoma (GBM) is the most common and aggressive brain tumour in adults. Standard treatment options are ineffective, in part due to the presence of therapy-resistant glioblastoma stem cells (GSCs).  These GSCs play a critical role in GBM tumor progression, yet current therapies fail to target them effectively. Despite extensive research establishing the importance of some microRNAs (miRNA) in GSC survival and GBM progression, their underlying molecular mechanisms remain poorly understood.

To address this knowledge gap, we have designed a novel high-throughput screening strategy using a miRNA-focused CRISPR/Cas9 library. Leveraging this tool and patient-derived GSC-enriched cells, we conducted a miRNA essentiality screen which identified 23 miRNA to be essential for GSC survival. Individual validation experiments characterized 5 miRNA as essential across different GSC cell models. These results led us to hypothesize that these miRNAs support GSC viability and tumor progression, indicating their potential as therapeutic targets in GBM. Our current research focuses on unravelling the mechanisms through which miRNA regulate GSC maintenance. By integrating miRNA target prediction and pathway analysis, we have identified potential regulatory roles of these miRNAs in key cellular processes such as the cell cycle and cell survival. Further analyses aim to identify specific molecular targets and pathways that are modulated by these miRNAs, providing insights into the underlying mechanisms driving GBM pathogenesis. Experimental validation demonstrated that loss of miRNA led to increased cell death, G2/M arrest, polyploidy and multinucleation. These findings suggest a role for these miRNA in mitotic catastrophe, an oncosuppressive mechanism triggered by mitotic failure. This mechanism can result in cell death, senescence, and mitotic slippage, characterized by multinucleation due to mitotic exit without cytokinesis. We are currently conducting further experiments to fully explore these mitotic catastrophe-related effects.

Overall, we identified 5 miRNA which are essential for the survival of GSC cells by regulating cell death and cell cycle progression. These miRNA candidates hold significant promise as therapeutic strategies for GBM.

The liver plays a critical role in metabolism and immune function. These crucial functions are diminished in chronic liver diseases, leading to over two million deaths annually worldwide. The complex and heterogeneous nature of liver disease, which can vary significantly between individuals in terms of progression, treatment response, and underlying molecular mechanisms warrants a precision medicine approach to liver disease. Single-cell transcriptomics has provided insights into the cellular composition of the liver in health and disease, but is inherently biased due to cell type specific destruction during the single-cell dissociation process. Previous work has highlighted difficulties in capturing specific populations such as cholangiocytes and hepatocytes.
Spatial transcriptomics (ST) is a promising approach that does not have inherent bias for cell populations and adds important spatial context. Until recently, ST technologies have been low-resolution (i.e at a multi-cellular level) potentially mixing signals from different cell types. The latest spatial transcriptomic technology from 10X Genomics, VisiumHD, enables high-resolution spatial mapping of gene expression in tissue samples, offering a sophisticated platform for exploring the cellular composition of the liver. With a bin width of 2um, it can quantify transcripts at a sub-cellular resolution.
Here we present the first ever characterization of the human liver using the VisiumHD platform. We sequenced samples from two healthy human liver donors, and performed cell segmentation to transition from the grid-based structure of VisiumHD data to cell-level annotations. Cells were then clustered into cell types and subtypes, by integrating ST data with existing single-cell reference maps. We identified spatially distinct cell signatures through differential expression analyses and created a high-resolution map of the liver.

This resource provides unprecedented insights into the cellular and spatial heterogeneity of the liver and lays the groundwork for researchers to identify disease-specific spatial signatures and novel therapeutic targets.

The ATP-binding cassette (ABC) proteins are multi-pass transmembrane proteins that translocate various substrates across intracellular and plasma membranes. The transport of the substrate is coupled to ATP binding and hydrolysis by the nucleotide-binding domain of the transporter. ABC transporters carry out important biological processes by serving as translocators, receptors, and ion channels, among others. ABC transporters perform critical biological roles, functioning as translocators, receptors, and ion channels. Defective ABC transporter function is linked to various genetic disorders, including cystic fibrosis. Moreover, some ABC transporters are overexpressed in cancer cells that are resistant to chemotherapy. Due to their clinical and pharmaceutical relevance, understanding the regulation and function of ABC transporters is a major area of interest. In this study, we aim to expand this understanding by generating a reference map of the protein-protein interactions (PPIs) involving human ABC transporters. Investigating these PPIs, using conventional methods, has been difficult due to the large, multi-pass nature of ABC transporters. To overcome this, we will employ the Mammalian Membrane Two Hybrid High-Throughput Screening (MaMTH-HTS) system, a split ubiquitin-based method, to identify PPIs for all human ABC transporters. This approach allows for PPI screening of ABC transporters in their native cellular context without the need for harsh cell lysis. Computational analysis will then be used to refine the list of candidate interactors, which will undergo further functional validation. Perturbing the expression of these interactors will allow us to assess their effects on transporter localization, activity, and post-translational modifications. This comprehensive, annotated interactome of human ABC transporters will provide new insights into their regulation and function, potentially leading to novel therapeutic strategies.

Antibody therapy offers provides a precise approach for the treatment of neurodegenerative diseases of the retina. However, frequent intravitreal bolus injections are often needed to achieve a therapeutic benefit. While this strategy works, it carries the risk of infection and it poses challenges for patients, leading to poor compliance and adherence. Sustained release strategies aim to minimize repetitive dosing while improving therapeutic outcomes.
In this work, we developed an affinity-based hydrogel system for the controlled release of two antibody therapeutics, anti-sFRP2 and Fc-Noggin, both critical for stimulating vision repair. The interactions between these antibody-based therapeutics and the hydrogel system were tuned by incorporating specific binding ligands. We formulated a biocompatible, minimally swelling and injectable hydrogel comprising Fragment crystallizable domain (Fc) peptide ligands (FcL) to control and sustain the release of anti-sFRP2 and Fc-noggin. The hydrogel matrix is comprised of hyaluronan-ketone-tetrazine (HAKT) crosslinked with a 4-arm polyethylene glycol oxyamine (PEGOA4) via oxime chemistry (HAT-ox). Ligand immobilization was achieved via inverse electron demand Diels-Alder chemistry with the tetrazine-modified HAK.
Through biolayer interferometry, we confirmed that FcL1 interacts to both anti-sFRP2 and Fc-Noggin with dissociation constants (KD) of 70 nM and 30 nM, respectively. After successful immobilization of FcL into HAT-ox, we demonstrated single and simultaneous controlled release of both anti-sFRP2 and Fc-Noggin from HAT-ox in the presence of FcL. Moreover, we verified that both therapeutics retained their bioactivity after release. In vivo studies in adult CD1 mice revealed that a single injection of our slow-release formulation achieved equivalent cellular responses to those achieved with repeated bolus injections, thus highlighting the benefit of our hydrogel system.
We present a new approach to achieving the slow release of antibody platforms. Unlike traditional encapsulation methods that often require harsh environmental conditions, this system relies on the simple mixing of the antibody with the delivery vehicle, obviating the need for antibody modification or treatment. Controlled release is governed by the inherent affinity between the antibody and FcL. This platform holds significant potential for broader applications across various antibody-based therapeutics and presents a promising strategy for ocular drug delivery.

Here, we introduce a novel approach for miRNA profiling at the point-of-need for severe sepsis, leveraging both novel and established biomarkers. This method employs CRISPR-Cas12, traditionally utilized for DNA detection, to identify miRNAs. The motivation for this project arises from the critical need for sensitive and specific detection of miRNA biomarkers for sepsis.

At the foundation of our project is a new method that enables Cas12 to detect RNA, including short miRNA without the need for PAM sites. Historically, Cas13 was the go-to tool for such tasks, but the protein is susceptible to degradation, limiting its practical value. In contrast, Cas12 has remarkable stability and superior thermal resilience, making it well-suited for diagnostics, particularly for samples with contaminants (salts, pH changes, etc.). There is also evidence that Cas12 has better specificity in comparison with Cas13, and, additionally, Cas12 is widely available from commercial suppliers.

The global sepsis crisis, responsible for 11 million deaths each year, is worsened by delayed treatments and the lack of early detection biomarkers. Drs. Claudia dos Santos and Gilbert Walker have discovered specific miRNAs linked to sepsis, notably in COVID-19 patients at different stages of infection. Our goal is to harness our Cas12 platform to detect crucial sepsis miRNA biomarkers, facilitating timely and precise interventions. As an initial step, we have successfully demonstrated the Cas12 system's efficacy with miRNA-21, with detection in as little as 10 minutes. These promising results have prompted us to broaden our efforts to include a wider range of sepsis biomarkers.

Currently, we have integrated exponential amplification reaction (EXPAR) with our Cas12 platform to guarantee sensitive miRNA detection and profiling, with sensitivity down to the attomolar level. Following this, the comprehensive system will undergo evaluation with contrived miRNA samples prior to testing with patient samples. This includes plans for implementation at the point of care at St. Michael’s Hospital. Our vision is to provide a new tool in the toolbox of ICU physicians in the triage of patients, ensuring the early diagnosis and the appropriate treatment of infected patients.

The dynamic localization and expression of membrane proteins are critical for cellular signaling in both physiological and pathological contexts. Inspired by the success of PROTACs in inducing targeted protein degradation, we aimed to expand this concept to membrane proteins by identifying guide proteins that modulate their surface abundance in a proximity-dependent manner. Using PD-L1-GFP as a sensor, we screened 18,000 human ORFs fused with a GFP nanobody and identified over 200 proteins that reduce and 200 that enhance the sensor’s surface expression. Among these, membrane-type E3 ligases were found to effectively degrade target membrane proteins, while other proteins specifically reduced or enhanced their surface localization. These findings demonstrate the potential of proximity-based strategies to regulate receptor localization and abundance.

Stroke is the third leading cause of long-term disability worldwide, with nearly half of all survivors experiencing chronic impairments. Currently approved treatments focus solely on restoring blood flow, without clinically available options to promote tissue regeneration. Cell transplantation represents a promising therapeutic strategy; however, poor cell survival remains a major challenge due to the hostile post-stroke microenvironment and lack of structural support within the damaged tissue.
To address these limitations, we developed an injectable hyaluronan-based hydrogel (HAO-lam) that mimics the brain’s extracellular matrix, enhancing the survival and neuronal differentiation of human induced pluripotent stem cell-derived neural progenitor cells (iPSC-NPCs). Encapsulated iPSC-NPCs exhibited robust viability and neuronal differentiation for at least 14 days in vitro.
In addition, to mitigate the inhibitory effects of chondroitin sulfate proteoglycans (CSPGs), which are abundantly secreted post-injury and impede neural repair, we co-delivered an engineered thermostable mutant of the bacterial enzyme chondroitinase ABC, ChASE37. This enzyme, expressed as a fusion protein with a Src homology 3 (SH3) domain (SH3-ChASE37), was incorporated into an injectable cross-linked methylcellulose hydrogel (XMC) functionalized with SH3-binding peptides to enable affinity-controlled release. The hydrogel formulation provided sustained release of bioactive SH3-ChASE37 in vitro and in vivo, effectively degrading CSPGs.
Using the endothelin-1 stroke model in rats, iPSC-NPCs encapsulated in HAO-lam hydrogel were transplanted into the lesion cavity, while SH3-ChASE37 in XMC hydrogel was applied epicortically one-week post-stroke. This combinatorial treatment significantly improved behavioral outcomes compared to controls. Histological analysis revealed that ChASE37 successfully degraded CSPGs in and around the lesion, which led to survival of transplanted iPSC-NPCs. Furthermore, transplanted cells expressed immature neuronal markers, indicating ongoing neuronal differentiation.
In conclusion, our findings demonstrate, for the first time, the potential of co-delivering neural progenitor cells and ChASE37 as a viable therapeutic strategy to promote tissue regeneration and functional recovery following stroke.

Protein abundance within a single cell can range from just a few copies to as many as 10⁹. Identification of a biological system’s protein composition (proteomics) is essential for understanding nearly all biological processes and diseases. Currently, mass spectrometry (MS) is the dominant proteomic technique. However, existing MS instruments are limited in their ability to detect low-abundance proteins in complex mixtures, particularly when they are present at concentrations of more than 10⁵-fold lower concentrations than other proteins in the sample. To overcome these limitations, significant efforts have been made to develop single-molecule protein sequencing technologies. A promising route has emerged for sequencing proteins through nanopores in a manner analogous to DNA sequencing. A major challenge in this field is the requirement to unfold a protein and control its translocation through the pore. Various AAA+ unfoldases have been explored for this purpose, yielding promising signals, though still falling short of single amino acid resolution. Our project aims to enhance the resolution of a nanopore-based protein sequencing system by utilizing a novel enzyme. One of the most effective ways to improve resolution is by increasing the baseline ionic current through the nanopore, as this amplifies the signal when an amino acid obstructs the pore. However, most enzymes function within a narrow ionic range and lose activity at high salt concentrations. To address this, we have engineered a salt-tolerant AAA+ protein and are working to integrate it into a commercially available nanopore platform.This approach is designed to enable nanopore operation under high-ionic-strength conditions, thereby enhancing resolution. If successful, this platform could revolutionize precision medicine. It has the potential to advance fundamental biological research by facilitating the discovery of previously undetectable disease biomarkers. Such a platform could also be integrated into clinical settings, enabling proteomics-based diagnostics and real-time monitoring of a patient's response to treatment.

Exposure to chronic caloric overload leads to obesity, a major risk factor for the development of comorbidities such as type 2 diabetes, cancer, and cardiovascular disease. In obesity, caloric overload results in adipocyte lipid droplet enlargement and exhaustion of their dynamic lipid storage capacity. Therapies that modulate lipid uptake to prevent adipocyte exhaustion have the potential to mitigate obesity-associated comorbidities. However, no large-scale in vitro studies have assessed lipid droplet morphology in a 3D obesity disease model for the discovery of new therapeutic targets.
Long-term culture of obese adipocytes in traditional 2D culture systems is complicated by the adipocyte hypertrophy, sphericity and buoyancy, necessitating a three-dimensional (3D) culture platform. To address this, we have created a novel cellulose-based 3D human obese adipocyte culture model and developed robotic and automation strategies to enable large in vitro image-based morphological screens. Through stimulation with a selection of small molecules and kinase inhibitors, we set out to generate a wide range of morphological lipid droplet perturbations in the high-throughput 3D obese adipocyte model. Fluorescent lipid droplet and nuclear dyes, combined with high-content confocal microscopy, facilitated the generation of a large image dataset for the establishment of an automated, image analysis pipeline assessing approximately 1600 parameters per image. Compound treatments that significantly perturbed lipid droplet morphology were identified through an unsupervised clustering algorithm (Gaussian Mixture Model). The relevance of these lipid droplet perturbations to broader adipocyte function was validated by correlating hits with altered cellular metabolic activity (Seahorse assay).
This study highlights the utility of a novel 3D in vitro obese adipocyte model combined with high-throughput imaging and analysis to identify compounds that induce metabolically relevant changes in lipid droplet morphology. This platform provides a powerful tool for uncovering pathways that regulate lipid uptake and storage, processes that are critically dysregulated in obesity.

Globally, medical conditions including cardiovascular disease, cancer, diabetes, and osteoarthritis are leading causes of health complications. Medical technologies used to treat these conditions, such as implants and drug delivery systems, are rapidly evolving with the integration of biocompatible polymers. Polymers used in these medical interventions are usually expected to undergo degradation, absorption, and /or excretion in vivo. The detection, quantification, and characterization of biocompatible polymers and their degradants are thus essential to demonstrate product safety and efficacy. At PolyAnalytik Inc, we have patented technologies to precisely extract and analyze both polymers and small molecules from various models of medically treated animals. However, due to the complexity of organs, tissues, and excrement, the characterization of analytes from in vivo samples can be complicated by the presence of biologically derived interferences. Our extraction methods selectively eliminate interfering compounds, leading to improved detection and quantification limits thereby promoting innovation by reducing research and development costs. Herein, we present a variety of results from our lab encompassing drug- eluting stents, drug-coated balloons, drug-delivery nanoparticles, and crosslinked polymer implants, as examples to demonstrate the challenges and opportunities for analyzing polymers in vivo.

Glioblastoma multiforme (GBM) the most aggressive primary brain tumor in adults. Hypoxia in GBM causes tumor progression, invasion, immunosuppression, and resistance to conventional therapies including radiotherapy. Although various strategies have been attempted to sensitize radiation, delivery of radio-sensitizing agents to the brain is poor due to the blood-brain barrier (BBB) and aberrant tumor vasculature. As a result, higher radiation doses are required to improve efficacy, however, they often damage healthy brain tissue, causing severe side effects. To overcome this challenge, we have developed MnO₂-loaded polymer-lipid hybrid nanoparticles (TP-MDNPs) that activate in the H₂O₂-rich, acidic TME, generating oxygen to mitigate hypoxia and meantime releasing paramagnetic Mn²⁺ ions that can enhance MRI contrast. These scalable, colloidally stable nanoparticles are effectively taken up by GBM cells, providing strong radiation sensitization and MR contrast enhancement at the cellular level. Building on these findings, we are incorporating a BBB-crossing terpolymer to develop optimized hypoxia detecting theragnostic agents for imaging hypoxia region, offering a transformative approach to treating GBM and guiding radiotherapy by MRI. A single intravenous dose of TP-MDNPs in an orthotopic GBM mouse model significantly improved RT efficacy, inhibited tumor progression, and extended median survival. Our TP-MDNPs demonstrated excellent biosafety in vitro and in vivo, enhancing both MRI and RT sensitivity. These findings support the promising potential of TP-MDNP as a theragnostic agent for improving the treatment quality and outcome of MRI-guided RT against aggressive brain tumours.

Lipid nanoparticles (LNP) have proven highly successful for the delivery of RNA therapeutics as demonstrated by Onpattro, the first FDA approved siRNA-LNP drug and the Moderna and Pfizer-BioNTech COVID-19 mRNA vaccines. Among LNPs components, ionizable lipids are the most structurally diverse as they are tailored to the RNA cargo being delivered and are crucial for RNA loading and endosomal escape. LNP delivery systems, however, have not been largely explored for the delivery of small, structured RNA such as tRNA. Genetic diseases caused by premature stop codons in mRNA lead to the production of non-functional truncated proteins. tRNAs play an important role in protein synthesis as they bring amino acids to the ribosome and base pair to codons on the mRNA with high specificity, allowing incorporation of the correct amino acid to the growing protein chain. While no tRNA naturally recognizes stop codons, premature stop codons can be recognized by tRNAs through engineering the anticodon region on tRNAs to suppress the premature stop codon and restore full length protein. These ‘suppressor tRNAs’ have been shown to effectively restore full length protein production. Currently, one limitation in tRNA therapies is that delivery systems have not been designed for tRNA delivery. Additionally, as the disease phenotype of many genetic diseases are localized to specific organs, the organ specificity of tRNA delivery is of importance to avoid non-specific and off target side effects. This work therefore aims to identify ionizable lipid structures that will effectively deliver suppressor tRNAs to different organs and suppress premature stop codons. A high-throughput screening method will be utilized to rapidly screen ionizable lipid structures for those that are most effective for delivering tRNAs to specific organs.

Early diagnosis of Ovarian cancer, in stage II, is exceedingly difficult due to its asymptomatic nature, and the biomarker tests lacks the sensitivity in the detection. Mortality rates of the ovarian cancer patients, within five years after diagnosis, are approximately 40% (stage II), 61% (stage III), and 83% (stage IV). The diagnostic challenge is in the limitation of the available biomarkers, extremely low blood concentrations of the biomarkers, and the low specificity of the prime CA-125 biomarker.

We propose to use AI-driven inverse design to artificially engineer periodic subwavelength photonic resonators (Metasurfaces) to enhance sensor capabilities for detecting multiple ovarian cancer biomarkers (HE4, CA-125 and its glycoforms) concurrently that can significantly enhance diagnostics accuracy. This innovative approach optimizes metasurface properties (Q-factor/sensitivity) crucial for precise biomarker identification of varying concentrations across individuals due to genetic differences. Our research aims to revolutionize early-stage ovarian cancer detection and personalized treatment strategies through PRiME Next-Generation-Precision-Medicine.

Generative models offer significant potential for small molecule drug discovery, substantially expanding the search space compared to traditional in silico screening libraries. However, most existing machine learning methods for small molecule generation suffer from poor synthesizability of candidate compounds, complicating their transition to wet lab experiments. We will present Reaction-GFlowNet (RGFN), a generative model that operates directly in the space of chemical reactions, thereby allowing out-of-the-box synthesizability while producing high-reward candidates. We will demonstrate that the proposed set of reactions, combined with low-cost building blocks, enables efficient exploration of a chemical space that is significantly larger than existing libraries. Furthermore, our approach allows simultaneous screening of generated molecules against various biological targets, utilizing pre-trained proxy models and GPU-accelerated docking techniques. We will also discuss an extension of RGFN that can utilize large, diverse building block datasets while optimizing the synthesis cost, further expanding accessible search space. Finally, we will present the effectiveness of the proposed approach across a range of oracle models and experimentally validate the synthesizability of generated compounds.

The mRNA vaccine platform has enabled vaccine development against many challenging pathogens due to its ability to be rapidly manufactured and induce robust humoral responses. However, current nucleoside-modified mRNA vaccines elicit weak CD8+ T cell responses, limiting their use against diseases that evade antibody neutralization such as intracellular pathogens or cancer. We find that improvements to ionizable lipid chemistry can strengthen CD8+ T cell responses in an influenza model in mice. These improvements are driven by the pH-responsive ionization behaviour (pKa) of lipid nanoparticles (LNPs), which impacts the efficiency of cytosolic delivery. We identified a lipid (δO3) that generated tenfold higher antigen-specific, cytotoxic CD8+ T cell responses compared to Moderna’s SM-102 while also inducing protective humoral responses against a matched influenza strain. We investigated the mechanism of the CD8+ T cell responses and found a correlation with the LNP’s ability to deliver mRNA to muscle-infiltrating monocytes and trigger markers of activation. Prior to this work, it was unclear whether mRNA vaccines could generate strong CD8+ T cell responses. Now, our findings provide greater understanding of the adjuvant mechanisms of LNPs and contribute to development of precision next-generation mRNA vaccines.

Diffuse large B cell lymphoma (DLBCL) is the most common subtype of non-Hodgkin lymphoma, with poor outcomes in the relapsed/refractory setting. Selinexor is an orally available inhibitor of nuclear export protein Exportin-1 (XPO1) with activity in DLBCL, but knowledge gaps exist in understanding how XPO1 drives DLBCL. Here, we analyzed Selinexor’s effects on DLBCL metabolism and conducted a proteomic analysis of enriched mitochondrial fractions to delineate the proteins and pathways related to selinexor mediated changes in bioenergetics.

Treating DLBCL cell lines with selinexor compromised mitochondrial and glycolytic metabolism in all lines tested, as measured by a XFe96 bioanalyzer. Specifically, reductions in oxygen consumption rate and extracellular acidification rate indicated reduced mitochondrial and glycolytic ATP production, respectively. Selinexor also compromised mitochondrial fitness as measured by decreased spare respiratory capacity. To identify factors driving selinexor-mediated changes in cellular metabolism, mitochondria were purified from DLBCL cell lines with and without selinexor. Following digestion, the resulting peptides were identified by mass spectrometry (MS). MS analysis identified 4224 proteins, of which 92 showed a statistically significant change in mitochondrial abundance with selinexor treatment; 61 of these were downregulated, while 31 were upregulated. Proteins identified as having significant changes in abundance following selinexor treatment were interrogated with Reactome. The top pathways modified by selinexor included mitotic cell cycle control, mRNA splicing, and rRNA modification, all of which were detected at lower abundance following selinexor treatment. Several metabolic enzymes also decreased in the dataset including the short-chain acyl-CoA dehydrogenase (ACADS), which catalyzes the oxidation of short-chain fatty acids (< 4 carbons). The sequences of these proteins were analyzed using the LocNES nuclear export sequence identifier tool to probe for canonical XPO1 interacting motifs. Predicted nuclear export sequences were identified in several selinexor-modulated proteins, including ACADS. Using nuclear-cytoplasmic fractionation, ACADS was also shown to accumulate in the nucleus following selinexor treatment.

Our data demonstrate selinexor’s ability to lower ATP production in DLBCL, possibly in part by preventing the nuclear export of ACADS to inhibit fatty acid oxidation. Future work will further validate ACADS as an XPO1 cargo to better understand selinexor’s mechanism of action.

Liting Wang1, Mahya Rezaeifarimani1, Chenguang Liu1, Pei Zhi1, Chunsheng He1, Azhar Z Abbasi1, Jeffrey T. Henderson1, Laurie Ailles2, Ahmed Aman2, Xiao Yu Wu1

1 Leslie Dan Faculty of Pharmacy, University of Toronto, Toronto, Ontario, Canada
2 Ontario Institute for Cancer Research, Toronto, Ontario, Canada

Glioblastoma (GBM) is the most aggressive type of primary intracranial tumor in adults with low median survival and 5-year survival. The standard frontline treatment for GBM is surgery followed by radiation therapy and chemotherapy. Unfortunately, the standard treatment has not increased the survival of GBM patients, due to therapy resistance, tumor microenvironment (TME), and the formidable blood-brain barrier (BBB). To address these challenges, we developed a brain-penetrating, iRGD-functionalized terpolymer-lipid hybrid nanoparticle containing a synergistic combination of anticancer drug doxorubicin and oligomeric hyaluronic acid (iRGD-DOX-oHA-TPN). The nanoparticles were specifically designed to cross the BBB and effectively target GBM cells as well as cancer-associated fibroblasts (CAFs) and block their intricate cross-talks. The iRGD-DOX-oHA-TPN demonstrated higher cellular uptake and cytotoxicity in activated CAFs that overexpress integrins compared to non-activated fibroblasts. Moreover, the iRGD-DOX-oHA-TPN exhibited remarkably higher cytotoxicity in GBM cells and activated CAFs compared to free DOX+oHA solution and non-targeted DOX-oHA-TPN. We furtherly evaluated the efficacy of this nanoparticle formulation in disrupting GBM cell-CAF interactions and CD44-mediated chemoresistance pathway. Our ongoing research will explore the effect of iRGD-DOX-oHA-TPN on interaction between GBM cells and varying cells within TME, including CAFs, GBM stem cells and immune cells. We will also investigate its impact on CD44-mediated pro-tumoral and chemoresistance mechanisms.

Injury to the brain and spinal cord often results in poor functional recovery due to a lack of regenerative responses in the central nervous system. Although damage can occur through a variety of means, such as traumatic injury, stroke or neurodegenerative disease, the result is a complex cascade that ultimately permanently disrupts neuronal signaling via axons. Given that current therapies are ineffective in reversing damage, patients face drastically reduced life-expectancies, require long-term physical therapy and endure severe psychological, social and economic burdens. Thus, there is an imminent need for therapeutics that promote functional regeneration of affected neurons.
A challenge in developing regenerative therapies for the central nervous system is a lack of suitable human disease models. Stem-cell derived platforms represent a powerful tool to mimic human specific molecular signatures across various types of neurological diseases and applying these platforms towards drug screening can further provide insight into critical disease mechanisms that vary from patient to patient.
To this end, we will present the results of our preliminary efforts towards establishing human iPSC-derived platforms as models to mimic neurological disease and their use as a pre-clinical screening tool. Using human iPSC-derived neurons, we have implemented assays to model axonal damage and the inhibitory microenvironment. We have also used these assays to identify compounds that promote regeneration in damaged cortical neurons. The results of this work represent the utility of iPSC-derived platforms to investigate mechanisms and therapeutics for diseases affecting the central nervous system.

Purpose: Digital twins are an emerging concept in healthcare, whereby a patient's medical condition is replicated using a comprehensive set of functional and molecular data to create precise computer-based models. Digital twins have been widely used in engineering to accelerate technological innovation, and parallel opportunities exist in medicine to leverage them to enhance the evaluation of novel therapeutics; however, a full systems-level digital twins in medicine remains unrealized. Ex vivo lung perfusion (EVLP) sustains donor lungs before transplantation and generates real-time, multi-modal data, offering a unique opportunity to train machine learning models to forecast lung function and create digital twins of human lungs. We developed a digital twin model of ex vivo lungs and validated its clinical utility to evaluate therapeutic efficacy of donor lung treatments.

Methods: Lung physiology, biochemistry, proteomic and metabolomic biomarkers, transcriptomics, and imaging features were derived from n=1000 EVLP cases performed at our centre (2008-2024). For each parameter, a multi-modal time-series forecasting model (XGBoost, gated recurrent unit) was trained to predict future lung function using baseline EVLP data, with mean absolute percentage error as the primary model evaluation metric. Therapeutic efficacy (pulmonary arterial pressure, PAP) and safety (edema) of a thrombolytic treatment were evaluated using the digital twins of n=16 EVLP cases with suspected pulmonary emboli.

Results: The digital lung model accurately predicted donor lung function for over 75 functional parameters during EVLP, with an average accuracy of 94.5% compared to the observed values. Digital twins successfully predicted the counterfactual outcome of the treatment to provide paired analyses between the untreated digital controls and the treated lung function. The digital twin approach identified treatment-induced reductions in PAP without causing lung edema in thrombolytic-treated lungs, tailored to individual cases.

Conclusion: Digital twins enable direct comparisons between treated organs and their personalized virtual models, advancing precision medicine at the organ level. By creating digital twins of ex vivo lungs, researchers can conduct more advanced preclinical evaluations of therapies, leading to more efficient clinical trials in transplant medicine.

G protein-coupled receptors (GPCRs) are a major gateway to cellular signaling, which respond to ligands binding at extracellular sites through allosteric conformational changes that modulate their interactions with G proteins at intracellular sites. While significant evidence from recent structural and spectroscopic studies suggests GPCRs exist in a dynamic equilibrium between multiple conformational and oligomeric states, their spatial organization in the plasma membrane is also important for downstream signalling. Using single-molecule fluorescence techniques, such as single-particle tracking and fluorescence correction spectroscopy, we studied the diffusion behavior and the quaternary structure of M1 muscarinic receptor (M1R) and its cognate G protein (G11) in living cells in different activation states and cellular nano-environments. M1Rs exhibit spatiotemporal heterogenous diffusion characterized by three diffusion constants: ~0.01 μm2/s (immobile), ~0.04 μm2/s (slow), and ~0.14 μm2/s (fast), whose populations were found to be modulated by both orthosteric ligands and membrane disruptors. Mean squared displacement analysis reveals the confined nature for the apparent slow diffusion component, with the confinement radius similar to those reported for lipid raft domains (30-300nm). By incorporating an internal ribosome entry site (IRES), both M1R and G11 were simultaneously expressed at stable, controlled levels in the same cell line, and bio-orthogonally labelled using Halo or SNAP tags. Co-diffusion events of M1R and G11 in the absence of any ligand was obtained by dual-color tracking and was used to shed light into the mechanisms of basal signaling. This study is an important step towards defining “when”, “where” and “how” GPCRs and G proteins diffuse, activate and interact with each other within the cell membrane, and can lead to new in-vivo screening assays for novel therapeutic drug design.

Background and objectives:
Osteoarthritis (OA), a degenerative joint disease, is affected by systemic and local factors such as metabolites from the gut microbiome. High concentrations of lipopolysaccharide-binding protein (LBP ) and bacterial metabolites in synovial fluid (SF), including lipopolysaccharide (LPS), show a correlation with the severity of OA. This study examines the important roles of gut-derived metabolites, specifically short-chain fatty acids (SCFAs), LPS and LBP, in substantially modulating local and systemic monocyte/macrophage (MΦ) subsets and contributing to OA pathogenesis.

Methods:
LPS and LBP levels were measured using Kinetic Chromogenic LAL and ELISA assays, while SCFAs were quantified via LC-MS/MS. Immune cell populations in SF were analyzed by flow cytometry. Correlations between these markers and patient-reported outcomes (PROMs) were examined. In a murine destabilization of the medial meniscus (DMM) model, probiotics were administered to evaluate their effects on cartilage degradation and synovial inflammation.

Results:
In a cohort of 38 OA patients, SF LBP levels positively correlated with WOMAC pain scores (ρ = 0.36, P = 0.026) and negatively with intermediate and non-classical MΦ subsets. Plasma LBP levels were negatively associated with WOMAC stiffness (ρ = −0.38, P = 0.018) and KOOS pain scores (ρ = −0.33, P = 0.044). Obese patients (BMI ≥ 30) we saw a positive correlations between SF LBP and WOMAC function (ρ = 0.55, P = 0.02) and negative correlations with CD14lowCD16+/CD45+ cells (ρ = −0.51, P = 0.041).

A 5-week treatment using 1 x 10^8 CFU/mL of probiotics in the DMM mouse model demonstrably reduced cartilage degradation (P = 0.03) as well as synovial inflammation (P = 0.04) compared to control groups. After 8 weeks, we did not observe cartilage rescue; however, the probiotic group showed a significantly lower level of synovial inflammation (P < 0.0001).

Conclusion:
Specific gut-derived metabolites and LBP affect the severity of OA and modulate several immune system characteristics. Following probiotic supplementation, a reduction in synovial inflammation and early cartilage degradation was observed, suggesting that gut-joint interactions represent a potential therapeutic target for osteoarthritis.