Ripples at edges of blooming lilies and torn plastic sheets.

Ripples arise at edges of petals of blooming Lilium casablanca flowers and at edges of torn plastic sheets. In both systems, ripples are a consequence of excess length along the edge of a sheet. Through the use of time-lapse videos of blooming lilies and published images of torn plastic sheets, we find that ripples in both systems are well described by the scaling relationship a∝w(L-w), where a is amplitude, w is wavelength, and L is arc length. A phenomenological relationship previously reported for self-similar ripple patterns, namely ⟨a⟩∝⟨w⟩, can be recovered by assuming that buckling stress is constant. Excess length along petal edges can also influence their overall Gaussian curvature, such that petals invert from a cup shape to a saddle shape upon blooming. Previous simulations of these shape changes have assumed that petal thickness decreases at least quadratically. Here, we evaluate tomograms of several varieties of lily buds and find that this assumption is valid along the short axis of the buds, but not the long axis. A challenge of employing traditional tomography methods to measure petal thickness is that the sample is destroyed; a single bud cannot be followed through the entire blooming process. To address this challenge, we provide proof of principle that the nondestructive, label-free method of x-ray tomography produces high-contrast three-dimensional scans on time scales short enough to follow lily blooming.

Several common methods of making vesicles (except an emulsion method) capture intended lipid ratios.

Researchers choose different methods of making giant unilamellar vesicles in order to satisfy different constraints of their experimental designs. A challenge of using a variety of methods is that each may produce vesicles of different lipid compositions, even if all vesicles are made from a common stock mixture. Here, we use mass spectrometry to investigate ratios of lipids in vesicles made by five common methods: electroformation on indium tin oxide slides, electroformation on platinum wires, gentle hydration, emulsion transfer, and extrusion. We made vesicles from either 5-component or binary mixtures of lipids chosen to span a wide range of physical properties: di(18:1)PC, di(16:0)PC, di(18:1)PG, di(12:0)PE, and cholesterol. For a mixture of all five of these lipids, ITO electroformation, Pt electroformation, gentle hydration, and extrusion methods result in only minor shifts (≤ 5 mol%) in lipid ratios of vesicles relative to a common stock solution. In contrast, emulsion transfer results in ∼80% less cholesterol than expected from the stock solution, which is counterbalanced by a surprising overabundance of saturated PC-lipid relative to all other phospholipids. Experiments using binary mixtures of some of the lipids largely support results from the 5-component mixture. Exact values of lipid ratios variations likely depend on the details of each method, so a broader conclusion is that experiments that increment lipid ratios in small steps will be highly sensitive to the method of lipid formation and to sample-to-sample variations, which are low (roughly ±2 mol% in the 5-component mixture and either scale proportionally with increasing mole fraction or remain low). Experiments that increment lipid ratios in larger steps or that seek to explain general trends or new phenomena will be less sensitive to the method used. SIGNIFICANCE STATEMENT: Small changes to the amounts and types of lipids in membranes can drastically affect the membrane's behavior. Unfortunately, it is unknown whether (or to what extent) different methods of making vesicles alter the ratios of lipids in membranes, even when identical stock solutions are used. This presents challenges for researchers when comparing data with colleagues who use different methods. Here, we measure ratios of lipid types in vesicle membranes produced by five methods. We assess each method's reproducibility and compare resulting vesicle compositions across methods. In doing so, we provide a quantitative basis that the scientific community can use to estimate whether differences between their results can be simply attributed to differences between methods or to sample-to-sample variations.