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Jones, M. G.

Publications and source records attributed to Jones, M. G..

2 recordsLinked to original sources

Super-resolved polarisation-enhanced second harmonic generation for direct imaging of nanoscale changes in collagen architecture

Super-resolution (SR) optical microscopy has allowed the investigation of many biological structures below the diffraction limit, however, most of the techniques are hampered by the need for fluorescent labels. Non-linear label-free techniques such as Second Harmonic Generation (SHG) provide structurally specific contrast without the addition of exogenous labels, allowing observation of unperturbed biological systems. Here we achieve super-resolution SHG (SR-SHG) for the first time. We use the photonic nanojet (PNJ) phenomena to achieve a resolution of ~{lambda}/6 with respect to the fundamental wavelength, a ~2.7-fold improvement over diffraction-limited SHG under the same imaging conditions. Crucially we find that the polarisation properties of excitation are maintained in a PNJ allowing the resolution to be further enhanced by detection of polarisation-resolved SHG (p-SHG) by observing anisotropy in signals. These new findings allowed us to visualise biological SHG-active structures such as collagen at an unprecedented and previously unresolvable spatial scale. Moreover, we demonstrate that the use of an array of self-assembled high-index spheres overcomes the issue of a limited field of view for such a method, allowing PNJ-assisted SR-SHG to be used over a large area. Dysregulation of collagen at the nanoscale occurs in many diseases and is an underlying cause in diseases such as lung fibrosis. Here we are able to demonstrate that pSR-SHG allows unprecedented observation of changes at the nanoscale that are invisible by conventional diffraction-limited SHG imaging. The ability to non-destructively image SHG-active biological structures without labels at the nanoscale with a relatively simple optical method heralds the promise of a new tool to understand biological phenomena and drive drug discovery.

biophysics

Inference of Single-Cell Phylogenies from Lineage Tracing Data

The pairing of CRISPR/Cas9-based gene editing with massively parallel single-cell readouts now enables large-scale lineage tracing. However, the rapid growth in complexity of data from these assays has outpaced our ability to accurately infer phylogenetic relationships. To address this, we provide three resources. First, we introduce Cassiopeia - a suite of scalable and theoretically grounded maximum parsimony approaches for tree reconstruction. Second, we provide a simulation framework for evaluating algorithms and exploring lineage tracer design principles. Finally, we generate the most complex experimental lineage tracing dataset to date - consisting of 34,557 human cells continuously traced over 15 generations, 71% of which are uniquely marked - and use it for benchmarking phylogenetic inference approaches. We show that Cassiopeia outperforms traditional methods by several metrics and under a wide variety of parameter regimes, and provide insight into the principles for the design of improved Cas9-enabled recorders. Together these should broadly enable large-scale mammalian lineage tracing efforts. Cassiopeia and its benchmarking resources are publicly available at www.github.com/YosefLab/Cassiopeia.

bioinformatics