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Bruce, A. M.

Publications and source records attributed to Bruce, A. M..

4 recordsLinked to original sources

Beyond Navigation - Tissue-contacting Fluorescent Lifetime Imaging reveals a pathology-linked lung cancer phenotype at the point of biopsy

Background: Accurate sampling of suspected peripheral lung cancers depends on access to the lesion and confirmation that the biopsy tool is in contact with target tissue. Current bronchoscopic navigation and imaging techniques can guide instruments to a target but do not provide real-time biological confirmation at the point of sampling. Fluorescence lifetime imaging microscopy (FLIM) provides molecular contrast by measuring fluorescence decay - how long photons continue to be emitted from fluorescent molecules. In the Precision Lung clinical study (ISRCTN15093468), the Prothea Imaging System (Generation 1) identified a candidate tumour-associated phenotype of spatially overlapped low fluorescence lifetime and low intensity (LLLI) from in-vivo imaging. We used this observation as the basis for a reverse-translational study to determine whether the LLLI phenotype is linked to cancer pathology; reproducible with the Imaging System (Generation 2); and distinguishable from normal lung tissue. Methods: Previously reported Precision Lung findings were used as the clinical starting observation and were not re-analysed. Validation was then performed using: (i) pathology linked benchtop FLIM of early-stage non-small-cell lung tissue microarrays encompassing malignant cell clusters of approximately 300 um2, matched to the EoT imaging scale; (ii) five sequential fresh lung-cancer resections imaged at tumour and comparator regions, including visibly blood-rich contact sites, using the (Generation 2) Imaging System; and (iii) systematic mapping of two ventilated non-cancer donor lungs, one from a smoker and one from a non-smoker, across all available lobes. The LLLI phenotype was defined as spatial co-localisation of low intensity and short lifetime. Results: Using a real time fibre based FLIM system, capable of deployment through a working channel of a bronchoscope, the LLLI tumour phenotype was optically identified in freshly resected tumour tissue. The same phenotype was identified in fixed tissue samples with known pathology, and with images taken in the Precision Lung clinical study. Whole human lung controls did not show evidence of the tumour phenotype. Conclusions: This evidence forms a reverse-translational chain that supports the concept of the Prothea Imaging System - as a platform that confirms that the tool is in contact with a region of cancer in the lesion, while preserving continuous access for biopsy or intervention.

cancer biology↗

Endomicroscopic fluorescence lifetime imaging enables molecular detection and targeted sampling in the distal human lung

PurposeAccurate molecular characterisation of infection and inflammation within the distal human lung remains challenging, particularly in critically ill patients, due to limited access to the alveolar space and delayed diagnostic workflows. Molecular imaging approaches capable of real-time detection and targeted sampling could substantially improve diagnostic precision and the future translational development of molecular imaging probes and therapeutics. MethodsIn a preclinical setting, we evaluated a clinic-ready endomicroscopic fluorescence lifetime imaging microscopy (eFLIM) platform combined with molecularly targeted SmartProbes for in situ detection of bacteria and activated neutrophils in the distal human lung. A multifunctional 1.9-mm diameter imaging and sampling catheter (Eyes on Target; EoT) enabled real-time fluorescence intensity and lifetime imaging alongside directed alveolar microlavage via a 1.2-mm working channel. Fluorescence intensity and lifetime signatures of Gram-negative bacteria, Gram-positive bacteria, and activated neutrophils were characterised using three wash-free SmartProbes: NBD-PMX, Merocy-Van, and a neutrophil activation probe (NAP). Imaging and sampling performance were assessed in ventilated ex vivo human lungs. ResultsEoT reliably navigated to alveolar regions across all lung lobes in both phantom and ventilated human lung models. eFLIM distinguished alveolar microanatomy and enabled probe-specific molecular detection within the distal lung. Increased NBD-PMX signal was detected in Escherichia coli-instilled lobes, while Merocy-Van lifetime signatures selectively identified Staphylococcus aureus-instilled regions. Activated neutrophils were detected throughout lung tissue following NAP administration. Directed alveolar microlavage enabled recovery of cellular material and bacterial DNA from imaged regions for downstream analysis. ConclusioneFLIM using EoT combined with molecular SmartProbes enables real-time molecular imaging and targeted sampling within the distal human lung. This platform provides a translatable approach for evaluating infection and inflammation at the alveolar level and supports the clinical development of molecular imaging probes for pulmonary disease.

microbiology↗

Transkingdom Network Analysis (TkNA): a systems approach inferring causal factors underlying host-microbiota interactions.

Technological advances have generated tremendous amounts of high-throughput omics data. Integrating data from multiple cohorts and diverse omics types from new and previously published studies can offer a holistic view of a biological system and aid in deciphering its critical players and key mechanisms. In this protocol, we describe how to use Transkingdom Network Analysis (TkNA), a unique causal-inference analytical framework that can perform meta-analysis of cohorts and detect master regulators among measured parameters that govern pathological or physiological responses of host-microbiota (or any multi-omic data) interactions in a particular condition or disease. TkNA first reconstructs the network that represents a statistical model capturing the complex relationships between the different omics of the biological system. Here, it selects differential features and their per-group correlations by identifying robust and reproducible patterns of fold change direction and sign of correlation across several cohorts. Next, a causality-sensitive metric, statistical thresholds, and a set of topological criteria are used to select the final edges that form the transkingdom network. The second part of the analysis involves interrogating the network. Using the networks local and global topology metrics, it detects nodes that are responsible for control of given subnetwork or control of communication between kingdoms and/or subnetworks. The underlying basis of the TkNA approach involves fundamental principles including laws of causality, graph theory and information theory. Hence, TkNA can be used for causal inference via network analysis of any host and/or microbiota multi-omics data. This quick and easy-to-run protocol requires very basic familiarity with the Unix command-line environment.

systems biology↗

Reversing gut microbiome-driven adipose tissue inflammation alleviates metabolic syndrome

The gut microbiota contributes to macrophage-mediated inflammation in adipose tissue with consumption of an obesogenic diet, thus driving the development of metabolic syndrome. There is a need to identify and develop interventions that abrogate this condition. The hops-derived prenylated flavonoid xanthohumol (XN) and its semi-synthetic derivative tetrahydroxanthohumol (TXN) attenuate high-fat diet-induced obesity, hepatosteatosis and metabolic syndrome in C57Bl/6J mice. This coincides with a decrease in pro-inflammatory gene expression in the gut and adipose tissue, together with alterations in the gut microbiota and bile acid composition. In this study, we integrated and interrogated multi-omics data from different organs with fecal 16S sequences and systemic metabolic phenotypic data using a transkingdom network analysis. By incorporating cell type information from single cell RNA-seq data, we discovered TXN attenuates macrophage inflammatory processes in adipose tissue. TXN treatment also reversed levels of inflammation-inducing microbes, such as Oscillibacter valericigenes, that lead to adverse metabolic phenotypes. Furthermore, in vitro validation in macrophage cell lines and in vivo mouse supplementation showed addition of O. valericigenes supernatant induced the expression of metabolic macrophage signature genes that are downregulated by TXN in vivo. Our findings establish an important mechanism by which TXN mitigates adverse phenotypic outcomes from diet-induced obesity and metabolic syndrome. It primarily reduces the abundance of pro-inflammatory gut microbes that can otherwise promote macrophage-associated inflammation in adipose tissue.

systems biology↗