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Williams, K. J.

Publications and source records attributed to Williams, K. J..

27 records · Page 2Linked to original sources

IL-10 constrains sphingolipid metabolism via fatty acid desaturation to limit inflammation

Unchecked chronic inflammation is the underlying cause of many diseases, ranging from inflammatory bowel disease to obesity and neurodegeneration. Given the deleterious nature of unregulated inflammation, it is not surprising that cells have acquired a diverse arsenal of tactics to limit inflammation. IL-10 is a key anti-inflammatory cytokine that can limit immune cell activation and cytokine production in innate immune cell types; however, the exact mechanism by which IL-10 signaling subdues inflammation remains unclear. Here, we find that IL-10 signaling constrains sphingolipid metabolism. Specifically, we find increased saturated very long chain (VLC) ceramides are critical for the heightened inflammatory gene expression that is a hallmark of IL-10-deficient macrophages. Genetic deletion of CerS2, the enzyme responsible for VLC ceramide production, limited exacerbated inflammatory gene expression associated with IL-10 deficiency both in vitro and in vivo, indicating that "metabolic correction" is able to reduce inflammation in the absence of IL-10. Surprisingly, accumulation of saturated VLC ceramides was regulated by flux through the de novo mono-unsaturated fatty acid (MUFA) synthesis pathway, where addition of exogenous MUFAs could limit both saturated VLC ceramide production and inflammatory gene expression in the absence of IL-10 signaling. Together, these studies mechanistically define how IL-10 signaling manipulates fatty acid metabolism as part of its molecular anti-inflammatory strategy and could lead to novel and inexpensive approaches to regulate aberrant inflammation.

immunology↗

PARP14 inhibition restores PD-1 immune checkpoint inhibitor response following IFNγ-driven adaptive resistance

Adaptive resistance limits immune checkpoint blockade therapy (ICBT) response duration and magnitude. Interferon {gamma} (IFN{gamma}), a critical cytokine that promotes cellular immunity, also induces adaptive resistance to ICBT. Using syngeneic mouse tumour models, we confirmed that chronic IFN{gamma} exposure confers resistance to anti-Programmed cell death protein 1 (-PD-1) therapy. We identified consistent upregulation of poly-ADP ribosyl polymerase 14 (PARP14) in both chronic IFN{gamma}-treated cancer cells and patient melanoma with elevated IFNG expression. Knockdown or pharmacological inhibition of PARP14 increased effector T cell infiltration into tumours derived from cells pre-treated with IFN{gamma} and decreased the presence of regulatory T cells, leading to restoration of -PD-1 sensitivity. Finally, we determined that tumours which spontaneously relapsed following -PD-1 therapy could be re-sensitised upon receiving PARP14 inhibitor treatment, establishing PARP14 as an actionable target to reverse IFN{gamma}-driven ICBT resistance.

cancer biology↗

Alveolar macrophage lipid burden correlates with clinical improvement in patients with Pulmonary Alveolar Proteinosis

Pulmonary alveolar proteinosis (PAP) is a life-threatening rare lung syndrome characterized by the accumulation of surfactant and lipid-loaded macrophages within the alveoli for which there is no cure and no approved therapies. The clinical diagnosis of PAP, often made by invasive lung biopsies and/or cytology of bronchoalveolar lavage fluid does not identify the underlying cause of disease. In addition, no biomarkers exist to inform prognosis or therapeutic options in PAP. We now report on the use of comprehensive mass spectrometry to profile and define the lipid signature of alveolar macrophages obtained from PAP patients. In addition, we quantify how these macrophage-associated lipids change during clinical treatment. Our studies demonstrate that clinical improvement in treated PAP patients is associated with a decrease in total lipid content, indicating that levels of these macrophage-associated lipids correlate with the severity of the disease.

physiology↗

Invasion and Secondary Site Colonization as a function of In vitro Primary Tumor Matrix Stiffness

Increased breast tissue stiffness is correlated with breast cancer risk and invasive cancer progression. However, its role in promoting bone metastasis, which shares a large burden of breast cancer deaths, has not yet been understood. To better understand the cause-effect relationship of tissue stiffness on breast cancers metastatic potential, we fabricated three-dimensional (3D) models to mimic breast and bone tissue in vitro. Based on our previous work, we used alginate-based hydrogels allowing precise control over stiffness and composition of extracellular breast tissue matrix; and 3D printed poly-caprolactone (PCL)-composite scaffolds to mimic the bone. The latter were further modified by promoting bone-ECM deposition using Saos-2 cells. After a decellularization step, PCL scaffolds were assembled with alginate-gelatin hydrogels and a novel breast-to-bone in vitro model was established. It was observed that increased stiffness of hydrogel resulted in higher migration and invasion capacity of MDA-MB 231 cells. Additionally, PTHrP and IL-6 expression, both of which are implicated in bone metastasis, were higher when cells from stiff hydrogels were cultured in bone/PCL scaffolds. These breast-to-bone in vitro models pose as a novel non-animal technology to pave the way for incorporating important tissue microenvironmental factors of the disease physiology (e.g. tissue stiffness) and emerge as promising future platforms for monitoring metastatic disease phenotypes and therapeutic efficacy.

bioengineering↗

Using generalised dissimilarity modelling and targeted field surveys to gap-fill an ecosystem surveillance network

O_LIWhen considering which sites or land parcels complement existing conservation or monitoring networks, there are many strategies for optimising ecological coverage in the absence of ground observations. However, such optimisation is often implemented theoretically in conservation prioritisation frameworks and real-world implementation is rarely assessed, particularly for networks of monitoring sites. C_LIO_LIWe assessed the performance of adding new survey sites informed by predictive modelling in gap-filling the ecological coverage of the Terrestrial Ecosystem Research Networks (TERN) continental network of ecosystem surveillance plots, Ausplots. Using plant cover observations from 531 sites, we constructed a generalised dissimilarity model (GDM) in which species composition was predicted by environmental parameters. We combined predicted nearest-neighbour ecological distances for locations across Australia with practical considerations to select regions for gap-filling surveys of 181 new plots across 18 trips. We tracked the drop in mean nearest-neighbour distances in GDM space, and increases in the actual sampling of ecological space through cumulative multivariate dispersion. C_LIO_LIGDM explained 34% of deviance in species compositional turnover and retained geographic distance, soil P, aridity, actual evapotranspiration and rainfall seasonality among 17 significant predictors. C_LIO_LIKey bioregions highlighted as gaps included Cape York Peninsula, Brigalow Belt South, South Eastern Queensland, Gascoyne and Dampierland. C_LIO_LIWe targeted identified gap regions for surveys in addition to opportunistic or project-based gap-filling over two years. Approximately 20% of the land area of Australia received increased servicing of biological representation, corresponding to a drop in mean nearest-neighbour ecological distances from 0.38 to 0.33 in units of compositional dissimilarity. The gain in sampled ecological space was 172% that from the previous 181 plots. Notable gaps were filled in northern and south-east Queensland, north-east New South Wales and northern Western Australia. C_LIO_LIBiological scaling of environmental variables through GDM supports practical sampling decisions for ecosystem monitoring networks. Optimising putative survey locations via ecological distance to a nearest neighbour rather than to all existing sites is useful when the aim is to increase representation of habitats rather than sampling evenness per se. Iterations between modelled gaps and field campaigns provide a pragmatic compromise between theoretical optima and real-world decision-making. C_LI

ecology↗

Stocktaking the environmental coverage of a continental ecosystem observation network

Field-based sampling of terrestrial habitats at continental scales is required to build ecosystem observation networks. However, a key challenge for detecting change in ecosystem composition, structure and function is to obtain a representative sample of habitats. Representative sampling contributes to ecological validity when analysing large spatial surveys, but field resources are limited and representativeness may differ markedly from purely practical sampling strategies to statistically rigorous ones. Here, we report a post hoc assessment of the coverage of environmental gradients as a surrogate for ecological coverage by a continental-scale survey of the Australian Terrestrial Ecosystem Research Network (TERN). TERNs surveillance program maintains a network of ecosystem observation plots that were init ially established in the rangelands through a stratification method (clustering of bioregions by environment) and Ausplots methodology. Subsequent site selection comprised gap filling combined with opportunistic sampling. Firstly, we confirmed that environmental coverage has been a good surrogate for ecological coverage. The cumulative sampling of environments and plant species composition over time were strongly correlated (based on mean multivariate dispersion; r = 0.93). We then compared the environmental sampling of Ausplots to 100,000 background points and a set of retrospective (virtual) sampling schemes: systematic grid, simple random, stratified random, and generalised random-tessellation stratified (GRTS). Differences were assessed according to sampling densities along environmental gradients, and multivariate dispersion (environmental space represented via multi-dimensional scaling). Ausplots outperformed systematic grid, simple random and GRTS in coverage of environmental space (Tukey HSD of mean dispersion, p < .001). GRTS site selection obtained similar coverage to Ausplots when employing the same bioregional stratification. Stratification by climatic zones generated the highest environmental coverage (p < .001), but the resulting sampling densities over-represented mesic coastal habitats. The Ausplots stratification by bioregions implemented under practical constraints represented complex environments well compared to statistically oriented or spatially even samples. However, potential statistical inference and power also depend on spatial and temporal replication, unbiased site selection, and accurate field measurements relative to the magnitude of change. A key conclusion is that environmental, rather than spatial, stratification is required to maximise ecological coverage across continental ecosystem observation networks.

ecology↗

An oxide transport chain essential for balanced insulin signaling

Patients with overnutrition, obesity, the atherometabolic syndrome, and type 2 diabetes mellitus exhibit imbalanced insulin action, also called pathway-selective insulin resistance. To control glycemia, they require hyperinsulinemia that then overdrives ERK and hepatic de-novo lipogenesis. We recently reported that NADPH oxidase-4 regulates balanced insulin action. Here, we show that NADPH oxidase-4 is part of a new limb of insulin signaling that we abbreviate \"NSAPP\" after its five major proteins. The NSAPP pathway is an oxide transport chain that begins when insulin stimulates NADPH oxidase-4 to generate [Formula]. NADPH oxidase-4 hands [Formula] to superoxide dismutase-3 for conversion into H2O2. The pathway ends when aquaporin-3 channels H2O2 across the membrane to inactivate PTEN. Disruption of any component of the NSAPP chain, from NADPH oxidase-4 up to PTEN, leaves PTEN persistently active, thereby producing the same deadly pattern of imbalanced insulin action seen clinically. Unraveling the molecular basis for NSAPP dysfunction in overnutrition has now become a top priority.

cell biology↗

Supporting global biodiversity assessment through high-resolution macroecological modelling: Methodological underpinnings of the BILBI framework

AimGlobal indicators of change in the state of terrestrial biodiversity are often derived by intersecting observed or projected changes in the distribution of habitat transformation, or of protected areas, with underlying patterns in the distribution of biodiversity. However the two main sources of data used to account for biodiversity patterns in such assessments - i.e. ecoregional boundaries, and vertebrate species ranges - are typically delineated at a much coarser resolution than the spatial grain of key ecological processes shaping both land-use and biological distributions at landscape scale. Species distribution modelling provides one widely used means of refining the resolution of mapped species distributions, but is limited to a subset of species which is biased both taxonomically and geographically, with some regions of the world lacking adequate data to generate reliable models even for better-known biological groups.\n\nInnovationMacroecological modelling of collective properties of biodiversity (e.g. alpha and beta diversity) as a correlative function of environmental predictors offers an alternative, yet highly complementary, approach to refining the spatial resolution with which patterns in the distribution of biodiversity can be mapped across our planet. Here we introduce a new capability - BILBI (the Biogeographic Infrastructure for Large-scaled Biodiversity Indicators) - which has implemented this approach by integrating advances in macroecological modelling, biodiversity informatics, remote sensing and high-performance computing to assess spatial-temporal change in biodiversity at ~1km grid resolution across the entire terrestrial surface of the planet. The initial implementation of this infrastructure focuses on modelling beta-diversity patterns using a novel extension of generalised dissimilarity modelling (GDM) designed to extract maximum value from sparsely and unevenly distributed occurrence records for over 400,000 species of plants, invertebrates and vertebrates.\n\nMain conclusionsModels generated by BILBI greatly refine the mapping of beta-diversity patterns relative to more traditional biodiversity surrogates such as ecoregions. This capability is already proving of considerable value in informing global biodiversity assessment through: 1) generation of indicators of past-to-present change in biodiversity based on observed changes in habitat condition and protected-area coverage; and 2) projection of potential future change in biodiversity as a consequence of alternative scenarios of global change in drivers and policy options.

ecology↗

All-optical electrophysiology reveals brain-state dependent changes in hippocampal subthreshold dynamics and excitability

A technology to record membrane potential from multiple neurons, simultaneously, in behaving animals will have a transformative impact on neuroscience research1. Parallel recordings could reveal the subthreshold potentials and intercellular correlations that underlie network behavior2. Paired stimulation and recording can further reveal the input-output properties of individual cells or networks in the context of different brain states3. Genetically encoded voltage indicators are a promising tool for these purposes, but were so far limited to single-cell recordings with marginal signal to noise ratio (SNR) in vivo4-6. We developed improved near infrared voltage indicators, high speed microscopes and targeted gene expression schemes which enabled recordings of supra- and subthreshold voltage dynamics from multiple neurons simultaneously in mouse hippocampus, in vivo. The reporters revealed sub-cellular details of back-propagating action potentials, correlations in sub-threshold voltage between multiple cells, and changes in dynamics associated with transitions from resting to locomotion. In combination with optogenetic stimulation, the reporters revealed brain state-dependent changes in neuronal excitability, reflecting the interplay of excitatory and inhibitory synaptic inputs. These tools open the possibility for detailed explorations of network dynamics in the context of behavior.

neuroscience↗