| RESEARCH HIGHLIGHTS |


contrast of photoacoustic images, which allows imaging of tissue in vivo. “Nanomaterials have been recognized as


promising platforms for the battle against many urgent health concerns including cancer, cardiovascular and neurodegenerative diseases,” say lead researchers Malini Olivo from A*STAR and Xing Bengang from NTU. “However, a critical challenge remains in


designing targeted nanoplatforms that are capable of selectively localizing at the specific diseases; in particular, tumor sites for early-stage diagnosis and effective treatment,” explains Olivo, who says their new work addresses this challenge. “These developments have the potential to


improve diagnostics and allow for the develop- ment of therapies that can be delivered at the cell level, leading to fewer side-effects,” says Olivo.


Previously direct targeting of diseased


cells had used ligands (or molecules) to bind nanoparticles to a cell with the complementary receptor. However, Olivo says the inability of the


ligand to differentiate between normal and tumor cells was a flaw in the strategy. A key to the latest innovation is that the nanophotonics platform is adapted to respond to a tumor-spe- cific enzyme and then accumulate at that site. The accumulation of the nanophotonics


platform improves the effectiveness of light treatments that kill cancer cells, such as photodynamic therapy and laser irradiation, and opens the possibility of inhibiting tumor growth through injection of nanoscale smart drugs. Olivo says nanostructures offer great potential in biomedical applications due to


properties such as tunable chemical composi- tion, flexible morphology, high surface area, and multivalent binding ability. Nanostructures also have the potential


to penetrate pores in the lining of blood and lymphatic vessel walls allowing the nanostructures to more effectively target and accumulate into the diseased region. Olivo says their approach could


be expanded into other areas of nanomedicine, opening “new doors for selective and precise theranostics in future clinical applications”.


1. Ai, X. Ho, C., Aw, J., Attia, A. B. E., Mu, J. et al. In vivo covalent cross-linking of photon-converted rare-earth nanostructures for tumour localization and theranostics. Nature Communications 7, 10432 (2016).


Bioinformatics:


THE PATH TO CELL FATE


ALGORITHM CAN TRACE LINEAGE TRAJECTORIES THROUGH SINGLE-CELL GENE EXPRESSION DATA


A new algorithm created at A*STAR could reveal new insights into disease state and offer a way to see how drugs are working. The tool, dubbed Mpath allows scientists to track the trajectories of different cell lineages on the basis of their gene activity at the individual cell level. “For the academic research community,


Mpath can be used to infer pathways and key regulators of cellular development and differentiation,” says Jinmiao Chen, a computational biologist at the A*STAR Singa- pore Immunology Network who led the algo- rithm’s development. “And for pharmaceutical


28 A*STAR RESEARCH


Mpath can be used to trace lineages of any cell type, including dendritic cells such as the one pictured above.


companies, when a drug is tested with different dosages or at different time points, Mpath can be used to map the kinetics of drug response.” The latest RNA-sequencing technologies


allows researchers to analyze gene expression profiles with unprecedented single-cell resolu- tion. But it was still a challenge to connect the dots between which individual cells gave rise to one another. Enter Mpath. Mpath takes in gene expression


information to infer the progression of cells from their progenitor state. It does not require data on huge numbers of cells or at


different time points, rather it works with single-cell data from a variety of different sequencing technologies, and can construct both linear and branching differentiation pathways. To demonstrate the algorithm’s usefulness,


Chen and her colleagues used Mpath to trace the development of mouse dendritic cells, a type of white blood cell involved in mounting immune responses against pathogens. By analyzing single-cell RNA, the tool exposed the timing of the branching event from precursor cells into the two functionally distinct lineages of dendritic cell and uncovered


ISSUE 5 | OCTOBER – DECEMBER 2016


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