Biology subjects

Walker, S. J.

Publications and source records attributed to Walker, S. J..

5 recordsLinked to original sources

bioRxiv2026

Impact of single-cell RNA reference selection for the deconvolution of breast cancer spatial transcriptomics datasets

BackgroundSpot-based Spatial transcriptomics (ST) allows for unbiased gene expression analysis within tissue architecture, overcoming the limitations of single-cell RNA sequencing (scRNA-seq) by preserving spatial context. However, the high spatial resolution in ST leads to cellular heterogeneity within spots, requiring computational deconvolution to infer cellular compositions. While scRNA-seq serves as a key reference for deconvolution, the impact of reference composition on its accuracy is still unclear. In this study, we systematically evaluate the impact of reference selection for cellular deconvolution and give helpful guide-lines to researchers to address this task. MethodsWe systematically evaluate the impact of single-cell reference selection for global and cell type-specific deconvolution performances in primary and metastatic breast cancer ST datasets. Focusing on state-of-the-art deconvolution tools Cell2location and Robust Cell Type Decomposition (RCTD), we assess the influence of varying reference sizes, cell-type distributions, reference-ST pairings, as well as the usage of large breast cancer and cross-cancer atlases. ResultsOur findings demonstrate that even small reference datasets can yield accurate deconvolution results, with RCTD and Cell2location exhibiting similar performances across cell-types. Heterogeneous entities, such as myeloids, presented greater challenges for accurate deconvolution compared to more distinct ones, such as epithelial cells. Spatial domains associated with prominent cell types like cancer and stromal cells were detected, although their contributions were systematically under- or over-estimated Additionally, we found that perfect reference-ST matching enhances deconvolution accuracy compared to the usage of cross-patient references. Finally, large breast cancer single-cell atlases com-posed of a diverse set of patients were also able to provide reliable deconvolution results. ConclusionThis study provides important insights into optimizing reference selection for ST deconvolution, highlighting the strengths and limitations of current computational tools in addressing cellular heterogeneity within spatial transcriptomics datasets.

bioinformatics↗

bioRxiv2025

On-target mutations confer resistance to WRN helicase inhibitors in Microsatellite Unstable Cancer Cells.

Werner helicase inhibitors (WRNi) are in clinical development for microsatellite-unstable (MSI) tumors with defective DNA mismatch repair. Here, we investigate how cancer cell evolution shapes response to WRN inhibition and informs potential resistance mechanisms. Genome-wide CRISPR screens combined with WRN knockout did not identify bypass mechanisms, underscoring WRNs essential, non-redundant function in MSI cells. Pharmacogenomic screens identified modulators of WRNi sensitivity, including SMARCAL1, which links it to WRN-MSI synthetic lethality. Semi-saturation mutagenesis of WRN and prolonged drug treatment identified on-target WRN mutations driving acquired resistance to multiple WRNi in vitro and in vivo, which was mitigated by combination with standard chemotherapies. Some resistance mutations conferred broad cross-resistance, whereas others preserved sensitivity to alternative clinical-grade WRNi with distinct mechanism of action. Our findings could inform clinical trial design by suggesting the feasibility of real-time tracking of emerging resistance and enabling early therapeutic adaptations. SignificanceWe present the first exploration of how MSI cancer cells evolve under the selective pressure of WRN helicase inhibition, providing a framework for understanding adaptive responses to this newly identified synthetic-lethal dependency. This study identifies on-target WRN mutations as key drivers of resistance in MSI cancers, supporting the use of combination strategies with other standard-of-care treatments to prevent resistance. It highlights how mutation tracking can guide therapeutic switching to clinically available WRN inhibitors with distinct mechanisms of action, thereby refining clinical development and potentially improving biomarker-informed patient outcomes.

cancer biology↗

bioRxiv2025

A hypothalamic circuit for anticipating future changes in energy balance.

AgRP neurons cause hunger, the drive to seek and consume food. Their activation by fasting is key for survival and is thought to be triggered by feedback when energy stores are low. However, we know that environmental cues can also regulate AgRP neurons, since cues that predict future food intake rapidly inhibit AgRP neurons. But is the converse true: can the prediction of future fasting rapidly activate AgRP neurons? Here we show that such rapid fasting activation of AgRP neurons does occur. This fasting response is driven by excitatory input from paraventricular hypothalamic neurons expressing Sim2, which are bidirectionally sensitive to predictions of future energy state. In this way, cognitively-processed contextual information conveyed by PVHSim2 neurons strongly activates AgRP neurons. Lastly, chronic silencing of PVHSim2 neurons causes persistent hypophagia. This PVHSim2 to AgRP neuron circuit, by anticipating and preventing negative energy balance, provides an important new dimension of hunger regulation.

neuroscience↗

bioRxiv2018

optoPAD: a closed-loop optogenetics system to study the circuit basis of feeding behaviors

The regulation of feeding plays a key role in determining the fitness of animals through its impact on nutrition. Elucidating the circuit basis of feeding and related behaviors is an important goal in neuroscience. We recently used a system for closed-loop optogenetic manipulation of neurons contingent on the flys feeding behavior to dissect the impact of a specific subset of taste neurons on yeast feeding (Steck et al., 2018). Here we describe the development and validation of this system, which we term the optoPAD. We use the optoPAD to induce appetitive and aversive effects on feeding by activating or inhibiting gustatory neurons in closed loop - effectively creating virtual taste realities. The use of optogenetics allowed us to vary the dynamics and probability of stimulation in single flies and assess the impact on feeding behavior quantitatively and with high throughput. These data demonstrate that the optoPAD is a powerful tool to dissect the circuit basis of feeding behavior, allowing the efficient implementation of sophisticated behavioral paradigms to study the mechanistic basis of animals adaptation to dynamic environments.

neuroscience↗

bioRxiv2017

Internal amino acid state modulates yeast taste neurons to support protein homeostasis in Drosophila

To optimize fitness, animals must dynamically match food choices to their current needs. For drosophilids, yeast fulfils most dietary protein and micronutrient requirements. While several yeast metabolites activate known gustatory receptor neurons (GRNs) in Drosophila melanogaster, the chemosensory channels mediating yeast feeding remain unknown. Here we identify a class of proboscis GRNs required for yeast intake, and show that these GRNs act redundantly to mediate yeast feeding. While nutritional and reproductive states synergistically increase yeast appetite, we find a separation of these state signals at the level of GRN responses to yeast: amino acid but not mating state enhances yeast GRN gain. The sensitivity of sweet GRNs to sugar is not increased by protein deprivation, providing a potential basis for protein-specific appetite. The emerging picture is that different internal states act at distinct levels of a dedicated gustatory circuit to elicit nutrient-specific appetites towards a complex, ecologically relevant protein source.

neuroscience↗