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Biology subjects

Giuliani, N.

Publications and source records attributed to Giuliani, N..

2 recordsLinked to original sources

Targeting DNA2 Overcomes Metabolic Reprogramming in Multiple Myeloma

DNA damage resistance is a major barrier to effective DNA-damaging therapy in multiple myeloma (MM). To discover novel mechanisms through which MM cells overcome DNA damage, we investigated how MM cells become resistant to antisense oligonucleotide (ASO) therapy targeting ILF2, a DNA damage regulator that is overexpressed in 70% of MM patients whose disease has progressed after standard therapies have failed. Here, we show that MM cells undergo an adaptive metabolic rewiring and rely on oxidative phosphorylation to restore energy balance and promote survival in response to DNA damage activation. Using a CRISPR/Cas9 screening strategy, we identified the mitochondrial DNA repair protein DNA2, whose loss of function suppresses MM cells ability to overcome ILF2 ASO-induced DNA damage, as being essential to counteracting oxidative DNA damage and maintaining mitochondrial respiration. Our study revealed a novel vulnerability of MM cells that have an increased demand for mitochondrial metabolism upon DNA damage activation. STATEMENT OF SIGNIFICANCEMetabolic reprogramming is a mechanism through which cancer cells maintain survival and become resistant to DNA-damaging therapy. Here, we show that targeting DNA2 is synthetically lethal in myeloma cells that undergo metabolic adaptation and rely on oxidative phosphorylation to maintain survival after DNA damage activation.

cancer biology↗

How Euglena gracilis swims: flow field reconstruction and analysis

Euglena gracilis is a unicellular organism that swims by beating a single anterior flagellum. We study the nonplanar waveforms spanned by the flagellum during a swimming stroke, and the three-dimensional flows that they generate in the surrounding fluid. Starting from a small set of time-indexed images obtained by optical microscopy on a swimming Euglena cell, we construct a numerical interpolation of the stroke. We define an optimal interpolation (which we call synthetic stroke) by minimizing the discrepancy between experimentally measured velocities (of the swimmer) and those computed by solving numerically the equations of motion of the swimmer driven by the trial interpolated stroke. The good match we obtain between experimentally measured and numerically computed trajectories provides a first validation of our synthetic stroke. We further validate the procedure by studying the flow velocities induced in the surrounding fluid. We compare the experimentally measured flow fields with the corresponding quantities computed by solving numerically the Stokes equations for the fluid flow, in which the forcing is provided by the synthetic stroke, and find good matching. Finally, we use the synthetic stroke to derive a coarse-grained model of the flow field resolved in terms of a few dominant singularities. The far field is well approximated by a time-varying Stresslet, and we show that the average behavior of Euglena during one stroke is that of an off-axis puller. The reconstruction of the flow field closer to the swimmer body requires a more complex system of singularities. A system of two Stokeslets and one Rotlet, that can be loosely associated with the force exerted by the flagellum, the drag of the body, and a torque to guarantee rotational equilibrium, provides a good approximation.

biophysics↗