Biology subjects

Montgomery, R.

Publications and source records attributed to Montgomery, R..

8 recordsLinked to original sources

bioRxiv2025

Inhibition of NLRP3 by a CNS-penetrating indazole scaffold

Low-grade inflammation is a hallmark of ageing and a key cause of age-related impairments and diseases1. The NOD-like receptor NLRP3 senses a variety of danger signals and environmental insults, resulting in pro-inflammatory response, inflammasome formation and pyroptosis2,3. Its aberrant activation has been linked to many acute and chronic diseases ranging from atherosclerosis to Alzheimers disease and cancer, making NLRP3 an attractive therapeutic target4,5. Here we report the discovery, characterization, and structure of an indazole-based NLRP3 antagonist, BAL-1516, which potently inhibits inflammasome formation in monocytes and microglia. The cryo-electron microscopy structure of BAL-1516 bound to NLRP3 reveals a previously undescribed compound binding site at a surface groove of the nucleotide-binding domain with contacts to the FISNA and WHD subdomains. The characteristic feature of BAL compound binding is the formation of three hydrogen bonds to the peripheral {beta}-strand of the triple-ATPase; two from the indazoles nitrogen atoms and a third from the compounds linker region. Additional phenyl and thiazole moieties render the compound hydrophobic, allowing excellent blood-brain barrier penetration. The compound binding site is highly specific for NOD-like receptors, and the optimized compound BAL-1516 is able to directly bind mouse NLRP3 despite two conservative residue changes in the binding interface. The BAL compounds represent a first-in-class family of NLRP3 inhibitors, providing a broad design space, including covalent and degradative properties, for the development of NLRP3-directed therapeutics. The innate immune system contains cytosolic proteins that sense cellular stress caused by bacterial, viral and fungal infections or sterile inflammation, to control cellular integrity2. NLRP3 is a well-studied member of the nucleotide-binding oligomerization domain (NOD)-like receptors (NLRs) that is involved in the activation of the inflammasome, a multiprotein complex that mediates inflammation6. Upon detection of stress or pathogen-associated signals, NLRP3 triggers the activation of caspase-1, which leads to the production of pro-inflammatory cytokines such as IL-1{beta} and IL-18, driving inflammatory responses and ultimately pyroptotic cell death. In the context of neuroinflammation, NLRP3 plays a significant role in the pathogenesis of various neurodegenerative diseases, including Alzheimers disease, Parkinsons disease, and multiple sclerosis7. Research into targeting NLRP3 signalling with CNS-penetrating molecules holds potential for developing therapeutic strategies to alleviate neuroinflammatory conditions and to slow the progression of neurodegenerative diseases.

immunology↗

bioRxiv2024

Discovery of a Potent and Selective Inhibitor of Human NLRP3 with a Novel Binding Modality and Mechanism of Action

The NLRP3 inflammasome is an intracellular protein complex that causes inflammation via the release of IL-1{beta} and pyroptosis. NLRP3 activation is associated with many age-related inflammatory diseases, and NLRP3 inhibition is a promising therapeutic strategy. We previously performed a DNA encoded library screen to identify novel NLRP3 binding molecules. Herein we describe the characterization of BAL-0028 as a potent and specific inhibitor of NLRP3 signaling. Notably, BAL-0028 is a poor inhibitor of mouse NLRP3 but inhibits human and primate NLRP3 with nanomolar potency. Using cellular and biochemical analyses we demonstrate that BAL-0028 binds to the NLRP3 NACHT domain at a site that is distinct from the MCC950 binding pocket. Using humanized NLRP3 mice we show that a derivative of BAL-0028 inhibits NLRP3 activation in vivo in a peritonitis model. Finally, we demonstrate that BAL-0028 inhibits select hyperactive NLRP3 mutations associated with autoinflammatory diseases more potently than does MCC950. BAL-0028 thus represents a new modality for NLRP3 inhibition in inflammatory diseases. SUMMARYNLRP3 is a target for anti-inflammatory therapies and can be inhibited by the tool compound MCC950. We describe the characterization of a new small molecule inhibitor of NLRP3 BAL-0028 that has a distinct mechanism of action and binding site.

immunology↗

bioRxiv2024

Molecular consequences of acute versus chronic CDK12 loss in prostate carcinoma nominates distinct therapeutic strategies

Genomic loss of the transcriptional kinase CDK12 occurs in [~]6% of metastatic castration-resistant prostate cancers (mCRPC) and correlates with poor patient outcomes. Prior studies demonstrate that acute CDK12 loss confers a homologous recombination (HR) deficiency (HRd) phenotype via premature intronic polyadenylation (IPA) of key HR pathway genes, including ATM. However, mCRPC patients have not demonstrated benefit from therapies that exploit HRd such as inhibitors of polyADP ribose polymerase (PARP). Based on this discordance, we sought to test the hypothesis that an HRd phenotype is primarily a consequence of acute CDK12 loss and the effect is greatly diminished in prostate cancers adapted to CDK12 loss. Analyses of whole genome sequences (WGS) and RNA sequences (RNAseq) of human mCRPCs determined that tumors with biallelic CDK12 alterations (CDK12BAL) lack genomic scar signatures indicative of HRd, despite carrying bi-allelic loss and the appearance of the hallmark tandem-duplicator phenotype (TDP). Experiments confirmed that acute CDK12 inhibition resulted in aberrant polyadenylation and downregulation of long genes (including BRCA1 and BRCA2) but such effects were modest or absent in tumors adapted to chronic CDK12BAL. One key exception was ATM, which did retain transcript shortening and reduced protein expression in the adapted CDK12BAL models. However, CDK12BALcells demonstrated intact HR as measured by RAD51 foci formation following irradiation. CDK12BAL cells showed a vulnerability to targeting of CDK13 by sgRNA or CDK12/13 inhibitors and in vivo treatment of prostate cancer xenograft lines showed that tumors with CDK12BALresponded to the CDK12/13 inhibitor SR4835, while CDK12-intact lines did not. Collectively, these studies show that aberrant polyadenylation and long HR gene downregulation is primarily a consequence of acute CDK12 deficiency, which is largely compensated for in cells that have adapted to CDK12 loss. These results provide an explanation for why PARPi monotherapy has thus far failed to consistently benefit patients with CDK12 alterations, though alternate therapies that target CDK13 or transcription are candidates for future research and testing.

cancer biology↗

bioRxiv2024

Forest and Biodiversity 2: a tree diversity experiment to understand the consequences of multiple dimensions of diversity and composition for long-term ecosystem function and resilience

O_LIWe introduce a new "low-density" tree diversity experiment at the Cedar Creek Ecosystem Science Reserve in central Minnesota, USA aimed at testing long-term ecosystem consequences of tree diversity and composition. The experiment was designed to provide guidance on forest restoration efforts that will simultaneously advance carbon sequestration goals and contribute to biodiversity conservation and sustainability. C_LIO_LIThe new Forest and Biodiversity (FAB2) experiment uses native tree species in varying levels of species richness, phylogenetic diversity, and functional diversity to test the mechanisms and processes that contribute to forest stability and ecosystem productivity in the face of global change. FAB2 was designed and established in conjunction with a prior experiment (FAB1) in which the same set of twelve species was planted in 16 m2 plots at high density (0.5 m spacing). In addition to lower density plantings (1 m spacing), FAB2 also has larger plots (100 m2 and 400 m2) appropriate for testing long-term ecosystem consequences of species composition and diversity. C_LIO_LIWithin the first six years, mortality in the 400 m2 monoculture plots was significantly higher than in the 100 m2 plots. The highest mortality among any treatments occurred in Tilia americana and Acer negundo monocultures, but mortality for both species decreased with increasing plot diversity. These results highlight the importance of forest diversity in reducing mortality in some species and point to potential mechanisms, including light and drought stress, that cause tree mortality in vulnerable monocultures. The experiment highlights challenges to maintaining monoculture and low-diversity treatments in tree mixture experiments of large extent. C_LIO_LIThe FAB2 experiment provides a long-term platform for discerning the importance of species and lineage effects and of multiple dimensions of diversity in restoring ecosystem functions and services provided by forests. It also provides a platform for improving remote sensing approaches, including Uncrewed Aerial Vehicles (UAVs) equipped with LiDAR, multispectral, and hyperspectral sensors, to complement ground-based monitoring of forest function and diversity. We aim for the experiment to contribute to international efforts to monitor and manage forests in the face of global change. C_LI

ecology↗

bioRxiv2021

Canopy spectral reflectance detects oak wilt at the landscape scale using phylogenetic discrimination

The oak wilt disease caused by the invasive fungal pathogen Bretziella fagacearum is one of the greatest threats to oak-dominated forests across the Eastern United States. Accurate detection and monitoring over large areas are necessary for management activities to effectively mitigate and prevent the spread of oak wilt. Canopy spectral reflectance contains both phylogenetic and physiological information across the visible near-infrared (VNIR) and short-wave infrared (SWIR) ranges that can be used to identify diseased red oaks. We develop partial least square discriminant analysis (PLS-DA) models using airborne hyperspectral reflectance to detect diseased canopies and assess the importance of VNIR, SWIR, phylogeny, and physiology for oak wilt detection. We achieve high accuracy through a three-step phylogenetic process in which we first distinguish oaks from other species (90% accuracy), then red oaks from white oaks (Quercus macrocarpa) (93% accuracy), and, lastly, infected from non-infected trees (80% accuracy). Including SWIR wavelengths increased model accuracy by ca. 20% relative to models based on VIS-NIR wavelengths alone; using a phylogenetic approach also increased model accuracy by ca. 20% over a single-step classification. SWIR wavelengths include spectral information important in differentiating red oaks from other species and in distinguishing diseased red oaks from healthy red oaks. We determined the most important wavelengths to identify oak species, red oaks, and diseased red oaks. We also demonstrated that several multispectral indices associated with physiological decline can detect differences between healthy and diseased trees. The wavelengths in these indices also tended to be among the most important wavelengths for disease detection within PLS-DA models, indicating a convergence of the methods. Indices were most significant for detecting oak wilt during late August, especially those associated with canopy photosynthetic activity and water status. Our study suggests that coupling phylogenetics, physiology, and canopy spectral reflectance provides an interdisciplinary and comprehensive approach that enables detection of forest diseases at large scales. These results have potential for direct application by forest managers for detection to initiate actions to mitigate the disease and prevent pathogen spread.

ecology↗

bioRxiv2020

Proteomics on longitudinal serum samples differentiates localized and disseminated Lyme disease

Lyme disease (LD) is the most prevalent vector-borne disease in North America, with ~300,000 new cases annually in the USA alone. LD is most often recognized by the appearance of the skin lesion erythema migrans (EM) at the tick bite site but also can present with signs of disseminated infection manifesting as multiple EM lesions and/or involvement of the heart, nervous system or joints. In this study, we examined the serum proteome of study participants presenting with either a single EM (localized LD) or early disseminated infection (disseminated LD). Samples collected at the time of diagnosis and at convalescent time points were assessed using our in-house developed MStern blotting-based serum proteomics platform. After technical validation of our platform, the temporal analysis from diagnosis to clinical resolution of the infection demonstrates LD stage-associated pathways activation such as a temporary upregulation of acute phase response specific to the participants with disseminated LD. In addition, we identified the members of the serum amyloid A protein family as potentially promising candidate biomarkers to identify those with disseminated LD. The results of this pilot study demonstrate the feasibility of using our time- and cost-effective sample sparing MStern blotting-based serum proteomics platform to efficiently interrogate proteome changes over time in those suffering infections such as LD. These observations establish a new approach to human serum proteomics, provide fresh insight into the host immune responses associated with disease severity (localized versus disseminated infection) and suggest novel biomarker candidate panels for LD stages. ImportanceWe investigated the proteome changes of Borrelia burgdorferi-infected participants with either a single erythema migrans or early disseminated Lyme disease infection. Using our in-house time-and cost-effective proteomics platform, the temporal analysis from diagnosis to clinical resolution of the infection shows a temporary upregulation of the acute phase response specific to the participants with disseminated infection. Finally, specific protein panels were identified as possible biomarker candidates to categorize those having an initial diagnosis of disseminated manifestation using a reference cohort of acute localized infection and a clinically resolved convalescent phase disease samples from the same Lyme disease participants.

immunology↗

bioRxiv2019

A Modified Injector and Sample Acquisition Protocol Can Improve Data Quality and Reduce Inter-Instrument Variability of the Helios Mass Cytometer

Mass cytometry is a powerful tool for high dimensional single cell characterization. Since the introduction of the first commercial CyTOF mass cytometer by DVS Sciences in 2009, mass cytometry technology has matured and become more widely utilized, with sequential platform upgrades designed to address specific limitations and to expand the capabilities of the platform. Fluidigms 3rd-generation Helios mass cytometer introduced a number of upgrades over the previous CyTOF2. One of these new features is a modified narrow bore sample injector that generates smaller ion clouds, which is expected to improve sensitivity and throughput. However, following rigorous testing we find that the narrow-bore sample injector may have unintended negative consequences on data quality and result in lower median signal intensities and higher coefficients of variation in antibody expression. We describe an alternative Helios acquisition protocol using a wider bore injector, which largely mitigates these data quality issues. We directly compare these two protocols in a multi-site study of 10 Helios instruments across 7 institutions and show that the modified protocol improves data quality and reduces inter-instrument variability. These findings highlight and address an important source of technical variability in mass cytometry experiments that is of particular relevance in the setting of multi-center studies.

immunology↗

bioRxiv2017

Exploring Single-Cell Data with Multitasking Deep Neural Networks

Biomedical researchers are generating high-throughput, high-dimensional single-cell data at a staggering rate. As costs of data generation decrease, experimental design is moving towards measurement of many different single-cell samples in the same dataset. These samples can correspond to different patients, conditions, or treatments. While scalability of methods to datasets of these sizes is a challenge on its own, dealing with large-scale experimental design presents a whole new set of problems, including batch effects and sample comparison issues. Currently, there are no computational tools that can both handle large amounts of data in a scalable manner (many cells) and at the same time deal with many samples (many patients or conditions). Moreover, data analysis currently involves the use of different tools that each operate on their own data representation, not guaranteeing a synchronized analysis pipeline. For instance, data visualization methods can be disjoint and mismatched with the clustering method. For this purpose, we present SAUCIE, a deep neural network that leverages the high degree of parallelization and scalability offered by neural networks, as well as the deep representation of data that can be learned by them to perform many single-cell data analysis tasks, all on a unified representation.\n\nA well-known limitation of neural networks is their interpretability. Our key contribution here are newly formulated regularizations (penalties) that render features learned in hidden layers of the neural network interpretable. When large multi-patient datasets are fed into SAUCIE, the various hidden layers contain denoised and batch-corrected data, a low dimensional visualization, unsupervised clustering, as well as other information that can be used to explore the data. We show this capability by analyzing a newly generated 180-sample dataset consisting of T cells from dengue patients in India, measured with mass cytometry. We show that SAUCIE, for the first time, can batch correct and process this 11-million cell data to identify cluster-based signatures of acute dengue infection and create a patient manifold, stratifying immune response to dengue on the basis of single-cell measurements.

bioinformatics↗