bioRxiv Science⌕ Search

Biology subjects

McLean, C.

Publications and source records attributed to McLean, C..

26 records · Page 2Linked to original sources

Multiple Low Dose therapy: an effective strategy to treat EGFR inhibitor-resistant NSCLC tumours

Targeted cancer drugs often elicit powerful initial responses, but generally fail to deliver long-term benefit due to the emergence of resistant cells1,2. This is thought to be the consequence of strong selective pressure exerted on the cancer drug target by a Maximum Tolerated Dose (MTD) of a drug3-5. We hypothesized that partial inhibition of multiple components in the same oncogenic signalling pathway might add up to complete pathway inhibition, while at the same time decreasing the selective pressure on each individual component to acquire a resistance mutation. We report here testing of this Multiple Low Dose (MLD) model of drug administration in Epidermal Growth Factor Receptor (EGFR) mutant non-small cell lung cancer (NSCLC). We show that as little as 20% of the individual drug doses required for full inhibition of cell viability is sufficient to completely block MAPK signalling and proliferation when used in 3D (RAF+MEK+ERK inhibitors) or 4D (EGFR+RAF+MEK+ERK inhibitors) combinations. Importantly, EGFR mutant NSCLC cells treated with EGFR inhibitors at a high dose rapidly developed resistance in vitro, but the cells treated with 3D or 4D MLD therapy did not. Moreover, NSCLC cells that had gained resistance to high dose anti-EGFR therapies were still sensitive to MLD therapy. Using several animal models, including patient derived xenografts of NSCLC tumours that are resistant to EGFR inhibitors erlotinib and osimertinib6,7, we found durable responses to MLD therapy without associated toxicity. These data support the notion that partial inhibition of multiple components of cancer-activated signalling pathways is difficult to circumvent and suggest that MLD therapy could deliver clinical benefit. We propose that MLD strategy could be an effective treatment option for EGFR mutant NSCLC patients, especially those having acquired resistance to even third generation EGFR inhibitor therapy.

cancer biology↗

AutoTuner: High fidelity, robust, and rapid parameter selection for metabolomics data processing

Untargeted metabolomics experiments provide a snapshot of cellular metabolism, but remain challenging to interpret due to the computational complexity involved in data processing and analysis. Prior to any interpretation, raw data must be processed to remove noise and to align mass-spectral peaks across samples. This step requires selection of dataset-specific parameters, as erroneous parameters can result in noise inflation. While several algorithms exist to automate parameter selection, each depends on gradient descent optimization functions. In contrast, our new parameter optimization algorithm, AutoTuner, obtains parameter estimates from raw data in a single step as opposed to many iterations. Here, we tested the accuracy and the run time of AutoTuner in comparison to isotopologue parameter optimization (IPO), the most commonly-used parameter selection tool, and compared the resulting parameters influence on the quality of feature tables after processing. We performed a Monte Carlo experiment to test the robustness of AutoTuner parameter selection, and found that AutoTuner generated similar parameter estimates from random subsets of samples. We conclude that AutoTuner is a desirable alternative to existing tools, because it is scalable, highly robust, and very fast ([~]100-1000X speed improvement from other algorithms going from days to minutes). AutoTuner is freely available as an R package through BioConductor.

bioinformatics↗

Carbon Assimilation Strategies in Ultrabasic Groundwater: Clues from the Integrated Study of a Serpentinization-Influenced Aquifer

Serpentinization is a low-temperature metamorphic process by which ultramafic rock chemically reacts with water. These reactions provide energy and materials that may be harnessed by chemosynthetic microbial communities at hydrothermal springs and in the subsurface. However, the biogeochemistry of microbial populations that inhabit these environments are understudied and are complicated by overlapping biotic and abiotic processes. We applied metagenomics, metatranscriptomics, and untargeted metabolomics techniques to environmental samples taken from the Coast Range Ophiolite Microbial Observatory (CROMO), a subsurface observatory consisting of twelve wells drilled into the ultramafic and serpentinite melange of the Coast Range Ophiolite in California. Using a combination of DNA and RNA sequence data and mass spectrometry data, we determined that several carbon assimilation strategies, including the Calvin-Benson-Bassham cycle, the reverse tricarboxylic acid cycle, the reductive acetyl-CoA pathway, and methylotrophy are used by the microbial communities inhabiting the serpentinite-hosted aquifer. Our data also suggests that the microbial inhabitants of CROMO use products of the serpentinization process, including methane and formate, as carbon sources in a hyperalkaline environment where dissolved inorganic carbon is unavailable.\n\nImportanceThis study describes the metabolic pathways by which microbial communities in a serpentinite-influenced aquifer may produce biomass from the products of serpentinization. Serpentinization is a widespread geochemical process, taking place over large regions of the seafloor, particularly in slow-spreading mid ocean ridge and subduction zone environments. The serpentinization process is implicated in the origin of life on Earth and as a possible environment for the discovery of life on other worlds in our solar system. Because of the difficulty in delineating abiotic and biotic processes in these environments, major questions remain related to microbial contributions to the carbon cycle and physiological adaptation to serpentinite habitats. This research explores multiple mechanisms of carbon assimilation in serpentinite-hosted microbial communities.

microbiology↗

Mouse and human microglial phenotypes in Alzheimer’s disease are controlled by amyloid plaque phagocytosis through Hif1α

The important role of microglia, the brains resident immune cells, in Alzheimers disease (AD) is now well recognized, however their molecular and functional diversity and underlying mechanisms still remain controversial. To transcriptionally and functionally characterize the diversity of microglia in AD and aging, we isolated the amyloid plaque-containing (XO4+) and non-containing (XO4-) microglia from an AD mouse model. Transcriptomics analysis unveiled independent transcriptional trajectories in ageing and AD. XO4+ microglial transcriptomes linked plaque phagocytosis to altered [Formula] expression of bona fide late onset AD genetic risk factors. We further revealed that the XO4+ transcriptional program is present in a subset of human microglia from AD patients and is a direct and reversible consequence of A{beta} plaque phagocytosis. Conversely, XO4- microglia in AD displayed an accelerated ageing signature and contained more intracellular post synaptic material than plaque-containing microglia, despite reduced active synaptosome phagocytosis. Mechanistically, we predicted HIF1 as a core regulator of the XO4-/XO4+ axis, and further validated the mechanism in vitro using human stem cell-derived microglia like cells and primary human microglia. Together these findings unveiled the molecular mechanism underpinning the functional diversity of microglia in AD, providing opportunities to develop treatments targeted at subset specific manipulation of the microglial niche.

neuroscience↗

A single cell brain atlas in human Alzheimer’s disease

Alzheimers disease (AD) is a heterogeneous disease that is largely dependent on the complex cellular microenvironment in the brain. This complexity impedes our understanding of how individual cell types contribute to disease progression and outcome. To characterize the molecular and functional cell diversity in the human AD brain we utilized single nuclei RNA- seq in AD and control patient brains in order to map the landscape of cellular heterogeneity in AD. We detail gene expression changes at the level of cells and cell subclusters, highlighting specific cellular contributions to global gene expression patterns between control and Alzheimers patient brains. We observed distinct cellular regulation of APOE which was repressed in oligodendrocyte progenitor cells (OPCs) and astrocyte AD subclusters, and highly enriched in a microglial AD subcluster. In addition, oligodendrocyte and microglia AD subclusters show discordant expression of APOE. Integration of transcription factor regulatory modules with downstream GWAS gene targets revealed subcluster-specific control of AD cell fate transitions. For example, this analysis uncovered that astrocyte diversity in AD was under the control of transcription factor EB (TFEB), a master regulator of lysosomal function and which initiated a regulatory cascade containing multiple AD GWAS genes. These results establish functional links between specific cellular sub-populations in AD, and provide new insights into the coordinated control of AD GWAS genes and their cell-type specific contribution to disease susceptibility. Finally, we created an interactive reference web resource which will facilitate brain and AD researchers to explore the molecular architecture of subtype and AD-specific cell identity, molecular and functional diversity at the single cell level.\n\nHighlightsO_LIWe generated the first human single cell transcriptome in AD patient brains\nC_LIO_LIOur study unveiled 9 clusters of cell-type specific and common gene expression patterns between control and AD brains, including clusters of genes that present properties of different cell types (i.e. astrocytes and oligodendrocytes)\nC_LIO_LIOur analyses also uncovered functionally specialized sub-cellular clusters: 5 microglial clusters, 8 astrocyte clusters, 6 neuronal clusters, 6 oligodendrocyte clusters, 4 OPC and 2 endothelial clusters, each enriched for specific ontological gene categories\nC_LIO_LIOur analyses found manifold AD GWAS genes specifically associated with one cell-type, and sets of AD GWAS genes co-ordinately and differentially regulated between different brain cell-types in AD sub-cellular clusters\nC_LIO_LIWe mapped the regulatory landscape driving transcriptional changes in AD brain, and identified transcription factor networks which we predict to control cell fate transitions between control and AD sub-cellular clusters\nC_LIO_LIFinally, we provide an interactive web-resource that allows the user to further visualise and interrogate our dataset.\nC_LI\n\nData resource web interface:http://adsn.ddnetbio.com

neuroscience↗

Evolutionarily-conserved chromatin crosstalk generates a DOT1L-dose dependency in thymic lymphoma caused by loss of HDAC1

DOT1L methylates histone H3K79 and is aberrantly regulated in MLL-rearranged leukemia. Inhibitors have been developed to target DOT1L activity in leukemia but the cellular mechanisms that regulate DOT1L are still poorly understood. Here we identify the budding yeast histone deacetylase Rpd3 as a negative regulator of Dot1. At its target genes, the transcriptional repressor Rpd3 restricts H3K79 methylation, explaining the absence of H3K79me3 at a subset of genes in the yeast genome. Similar to the crosstalk in yeast, inactivation of the murine Rpd3 homolog HDAC1 in thymocytes led to an increase in H3K79 methylation. Thymic lymphomas that arise upon genetic deletion of Hdac1 retained the increased H3K79 methylation and were sensitive to reduced DOT1L dosage. Furthermore, cell lines derived from Hdac1{Delta}/{Delta} thymic lymphomas were sensitive to DOT1L inhibitor, which induced apoptosis. In summary, we identified an evolutionarily-conserved crosstalk between HDAC1 and DOT1L with impact in murine thymic lymphoma development.

cell biology↗

Regional diversity in the postsynaptic proteome of the mouse brain

The proteome of the postsynaptic terminal of excitatory synapses comprises over one thousand proteins in vertebrate species and plays a central role in behavior and brain disease. The brain is organized into anatomically distinct regions and whether the synapse proteome differs across these regions is poorly understood. Postsynaptic proteomes were isolated from seven forebrain and hindbrain regions in mice and their composition determined using proteomic mass spectrometry. Seventy-four percent of proteins showed differential expression and each region displayed a unique compositional signature. These signatures correlated with the anatomical divisions of the brain and their embryological origins. Biochemical pathways controlling plasticity and disease, protein interaction networks and individual proteins involved with cognition all showed differential regional expression. Combining proteomic and connectomic data shows that interconnected regions have specific proteome signatures. Diversity in synapse proteome composition is key feature of mouse and human brain structure.

neuroscience↗

Improving Phenotypic Measurements in High-Content Imaging Screens

Image-based screening is a powerful technique to reveal how chemical, genetic, and environmental perturbations affect cellular state. Its potential is restricted by the current analysis algorithms that target a small number of cellular phenotypes and rely on expert-engineered image features. Newer algorithms that learn how to represent an image are limited by the small amount of labeled data for ground-truth, a common problem for scientific projects. We demonstrate a sensitive and robust method for distinguishing cellular phenotypes that requires no additional ground-truth data or training. It achieves state-of-the-art performance classifying drugs by similar molecular mechanism, using a Deep Metric Network that has been pre-trained on consumer images and a transformation that improves sensitivity to biological variation. However, our method is not limited to classification into predefined categories. It provides a continuous measure of the similarity between cellular phenotypes that can also detect subtle differences such as from increasing dose. The rich, biologically-meaningful image representation that our method provides can help therapy development by supporting high-throughput investigations, even exploratory ones, with more sophisticated and disease-relevant models.

cell biology↗