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Biology subjects

Martin, A. G.

Publications and source records attributed to Martin, A. G..

2 recordsLinked to original sources

Nanometer condensate organization in live cells derived from partitioning measurements

Biomolecules self-organize into membrane-less organelles known as condensates that compartmentalize essential biochemical processes, such as ribosome biogenesis in the nucleolus1-3. Molecular dynamics within condensates are governed by chemical preferences and interaction networks that can imbue nanoscale structure4-7. Such organization is typically inferred from ensemble-averaged measurements, such as scattering and electron microscopy, which reveal molecular arrangements8-14. However, the complexity of cells obscures the interpretability of these techniques, limiting insight into condensate internal structure and roles in macromolecular assembly and transport. Here, we develop an approach to quantify the average microenvironment surrounding specific proteins within condensates in live cells, using thermodynamic principles to interpret the partitioning of designed protein probes. Using this approach, we find that condensates in cells, including the nucleolus, stress granule, and nuclear pore, exhibit spatial inhomogeneity, aligning with emerging views of condensates as networked fluids5,6,15-18. Within the nucleolus, we link spatial inhomogeneity to ribosome biogenesis, which progressively loosens the average local meshwork, facilitating transport of assembled ribosomal subunits. Within the nuclear pore, we find that transporters experience a weaker local meshwork than nucleoporins, consistent with the selective phase model19,20. Together, our approach uncovers a distinct mode of biomolecular control arising from nanoscale structure, which we term microenvironment coupling, whereby internal interaction landscapes shape transport to enable regulation and proofreading.

biophysics↗

Modelling drug responses and evolutionary dynamics using triple negative breast cancer patient-derived xenografts

Triple negative breast cancers (TNBC) exhibit inter- and intra-tumour heterogeneity, which is reflected in diverse drug responses and interplays with tumour evolution. Here, we use TNBC patient-derived tumour xenografts (PDTX) as a platform for co-clinical trials to test their predictive value and explore the molecular features of drug response and resistance. Patients and their matched PDTX exhibited mirrored drug responses to neoadjuvant therapy in a clinical trial. In parallel, additional clinically-relevant treatments were tested in PDTXs in vivo to identify alternative effective therapies for each PDTX model. This framework establishes the foundation for anticipatory personalised therapies for those patients with resistant or relapsed tumours. The PDTXs were further explored to model PDTX- and treatment-specific behaviours. The dynamics of drug response were characterised at single-cell resolution revealing a novel mechanism of response to olaparib. Upon olaparib treatment PDTXs showed phenotypic plasticity, including transient activation of the immediate-early response and irreversible sequential phenotypic switches: from epithelial to epithelial-mesenchymal-hybrid states, and then to mesenchymal states. This molecular mechanism was exploited ex vivo by combining olaparib and salinomycin (an inhibitor of mesenchymal-transduced cells) to reveal synergistic effects. In summary, TNBC PDTXs have the potential to help design individualised treatment strategies derived from model-specific evolutionary insights.

cancer biology↗