Arp2/3 complex interactions and actin network turnover in lamellipodia

Cell migration is initiated by lamellipodia—membrane-enclosed sheets of cytoplasm containing densely packed actin filament networks. Although the molecular details of network turnover remain obscure, recent work points towards key roles in filament nucleation for Arp2/3 complex and its activator WAVE complex. Here, we combine fluorescence recovery after photobleaching (FRAP) of different lamellipodial components with a new method of data analysis to shed light on the dynamics of actin assembly/disassembly. We show that Arp2/3 complex is incorporated into the network exclusively at the lamellipodium tip, like actin, at sites coincident with WAVE complex accumulation. Capping protein likewise showed a turnover similar to actin and Arp2/3 complex, but was confined to the tip. In contrast, cortactin—another prominent Arp2/3 complex regulator—and ADF/cofilin—previously implicated in driving both filament nucleation and disassembly—were rapidly exchanged throughout the lamellipodium. These results suggest that Arp2/3- and WAVE complex-driven actin filament nucleation at the lamellipodium tip is uncoupled from the activities of both cortactin and cofilin. Network turnover is additionally regulated by the spatially segregated activities of capping protein at the tip and cofilin throughout the mesh

Microtubules as Platforms for Assaying Actin Polymerization In Vivo

The actin cytoskeleton is continuously remodeled through cycles of actin filament assembly and disassembly. Filaments are born through nucleation and shaped into supramolecular structures with various essential functions. These range from contractile and protrusive assemblies in muscle and non-muscle cells to actin filament comets propelling vesicles or pathogens through the cytosol. Although nucleation has been extensively studied using purified proteins in vitro, dissection of the process in cells is complicated by the abundance and molecular complexity of actin filament arrays. We here describe the ectopic nucleation of actin filaments on the surface of microtubules, free of endogenous actin and interfering membrane or lipid. All major mechanisms of actin filament nucleation were recapitulated, including filament assembly induced by Arp2/3 complex, formin and Spir. This novel approach allows systematic dissection of actin nucleation in the cytosol of live cells, its genetic re-engineering as well as screening for new modifiers of the process

Variability of cloud optical depth and cloud droplet effective radius in layer clouds : satellite based analysis

Measurements made by the AVHRR (Advanced Very High Resolution Radiometer) on board of five NOAA polar orbiting satellites were used to retrieve cloud optical depth (τ) and cloud droplet effective radius (r[sub eff]) for marine boundary layer clouds over the Pacific Ocean west of California and over the Southern Ocean near Tasmania. Retrievals were obtained for 21 days of data acquired between 1987 and 1995 from which over 300 subscenes ~ 256 km x 256 km in size were extracted. On this spatial scale cloud fields were found to have mean τ between 8 and 32 and mean r[sub eff] between 6 and 17 μm. The frequency distribution of τ is well approximated by a two parameter gamma distribution. The gamma distribution also provides a good fit to the observed r[sub eff] distribution if the distribution is symmetric or positively skewed but fails for negatively skewed or bi-modal distributions of r[sub eff] which were also observed. The retrievals show a relationship between τ and r[sub eff] which is consistent with a simple "reference" cloud model with reff ~ r[sup 1 / 5]. The proportionality constant depends on cloud droplet number concentration N and cloud subadiabaticity β through the parameter N[sub sat] = N/ [sq rt. Β]. Departures from the reference behaviour occur in scenes with spatially coherent N[sub sat] regimes, separated by a sharp boundary. AVHRR imagery is able to separate two N[sub sat] regimes if they differ by at least 30% in most cases. Satellite retrievals of τ and r[sub eff] were compared with in situ aircraft measurement near Tasmania. The retrievals overestimated r[sub eff] by 0.7 to 3.6 μm on different flights, in agreement with results from earlier comparison studies. The r[sub eff] overestimation was found to be an offset independent of τ. The reference cloud model and the N[sub sat] retrieval were tested on aircraft data and yield results consistent with direct in situ measurements of N and 8. Spectral and multifractal analyses of the spatial structure of cloud visible radiance, τ and r[sub eff] fields in 34 satellite scenes revealed scale breaks at 3 to 2 km in all analysed scenes in agreement with some earlier observations (Davis et al. (1996a)) but in contrast with other work (Lovejoy et al. (1993)). The nonstationarity H(1) and intermittency C(1) parameters were computed for the 34 scenes, stratified using the reference cloud model and according to mean τ and r[sub eff]. Similar values of H(1) and C(1) were found in all these categories. These measurements of the frequency distribution and spatial variability of τ, r[sub eff], liquid water path (Iwp), and N[sub sat] can be used to place constraints on mesoscale models of layer clouds.Arts, Faculty ofGeography, Department ofGraduat

Relative Merits of Optimal Estimation and Non-Linear Retrievals of Sea-Surface Temperature from MODIS

We compared the results of an Optimal Estimation (OE) based approach for the retrieval of the skin sea surface temperature (SSTskin) with those of the traditional non-linear sea surface temperature (NLSST) algorithm. The retrievals were from radiance measurements in two infrared channels of the Moderate Resolution Imaging Spectroradiometer (MODIS) on the NASA satellite Aqua. The OE used a reduced state vector of SST and total column water vapor (TCWV). The SST and atmospheric profiles of temperature and humidity from ERA5 provided prior knowledge, and we made reasonable assumptions about the variance of these fields. An atmospheric radiative transfer model was used as the forward model to simulate the MODIS measurements. The performances of the retrieval approaches were assessed by comparison with in situ measurements. We found that the OESST reduces the satellite–in situ bias, but mostly for retrievals with an already small bias between in situ and the prior SST. The OE approach generally fails to improve the SST retrieval when that difference is large. In such cases, the NLSST often provides a better estimate of the SST than the OE. The OESST also underperforms NLSST in areas that include large horizontal SST gradients

High latitude sea surface skin temperature from the Saildrone uncrewed surface vehicles deployed in 2019

Saildrone, as one of the most capable uncrewed surface vehicles, carries a suite of meteorological and oceanographic instruments for long-duration cruises. From 15th May to 11th October 2019, two NASA-funded Saildrones, SD-1036 and SD-1037, made a 150-day round-trip cruise from Dutch Harbor, Alaska, into the Arctic Ocean. Both were equipped with a pair of IR pyrometers on the deck at 0.8 m height for the sea surface skin temperature (SSTskin) retrieval, viewing the sea surface and the sky at the same nadir angle and zenith angle. The pyrometers were manufactured by Heitronics Inc., the sea-viewing sensor was a CT15.10 while the sky-viewing sensor was a CT09.10. After the deployments, the CT15 calibration was tested in the University of Miami Rosenstiel School laboratory using SI-traceable blackbody calibrator, and also by Wintronics, the US agent of Heitronics Inc. The performance of CT15 was much better than the stated accuracy in the manufacturer's specifications. The uncertainty of Saildrone-derived SSTskin is ~0.12 K and the systematic error is insignificant. Therefore, the SSTskin data from SD-1036 and SD-1037 are sufficiently accurate to be used in the validation of satellite SSTskin retrievals and other studies of sea surface and air-sea interaction at high latitudes

Ship-based high resolution sea surface skin temperature from the Marine-Atmospheric Emitted Radiance Interferometer (M-AERI) deployed between 2013 and 2020

This dataset is a part of that taken with sea-going instruments described by “Minnett, P.J., Knuteson, R.O., Best, F.A., Osborne, B.J., Hanafin, J.A., & Brown, O.B. (2001). The Marine-Atmospheric Emitted Radiance Interferometer (M-AERI), a high-accuracy, sea-going infrared spectroradiometer. Journal of Atmospheric and Oceanic Technology, 18, 994-1013". Specifically, this dataset comprises measurements of M-AERIs, ship-based Fourier Transform Infrared (FTIR) interferometric spectroradiometers mounted on ships a few meters (research ships) or a few tens of meters (cruise ships) above the sea surface. M-AERI spectra can be used to derive several geophysical variables, including accurate Skin Sea Surface Temperature (SSTskin) and near-surface air temperature (Minnett et al., 2005). M-AERI includes two infrared detectors and two internal blackbody cavities with SI-traceable calibration to perform real-time instrument calibration and achieve high-resolution spectra of the sea surface and atmospheric emitted infrared radiation. The scan mirror directs the field of view to include two internal blackbody calibration cavities to the sea surface and atmosphere. Before and after each deployment, the M-AERI calibration is tested using an external validation procedure in the University of Miami RSMAS laboratory using SI-traceable blackbody calibrator thus providing a calibration chain to standards at the National Institute of Standards and Technology (NIST) in the USA (Rice et al., 2004) and the National Physical Laboratory (NPL) in the UK (Theocharous et al., 2019). The absolute accuracy of the infrared spectra produced by the M-AERI is determined by the effectiveness of the black-body cavities as calibration targets. The absolute accuracy of the spectral measurements of the M-AERI is better than 0.03K, which is sufficiently small to give confidence in the use of such data in the validation of satellite SSTskin retrievals. The detailed technical description is given by Minnett et al. (2001), who describe the first generation of M-AERIs which have been replaced by newer models, but for which the measurement process and calibration remain the same.</p