RAB-6.1 and RAB-6.2 Promote Retrograde Transport in C. elegans

Retrograde transport is a critical mechanism for recycling certain membrane cargo. Following endocytosis from the plasma membrane, retrograde cargo is moved from early endosomes to Golgi followed by transport (recycling) back to the plasma membrane. The complete molecular and cellular mechanisms of retrograde transport remain unclear. The small GTPase RAB-6.2 mediates the retrograde recycling of the AMPA-type glutamate receptor (AMPAR) subunit GLR-1 in C. elegans neurons. Here we show that RAB-6.2 and a close paralog, RAB-6.1, together regulate retrograde transport in both neurons and non-neuronal tissue. Mutants for rab-6.1 or rab-6.2 fail to recycle GLR-1 receptors, resulting in GLR-1 turnover and behavioral defects indicative of diminished GLR-1 function. Loss of both rab-6.1 and rab-6.2 results in an additive effect on GLR-1 retrograde recycling, indicating that these two C. elegans Rab6 isoforms have overlapping functions. MIG-14 (Wntless) protein, which undergoes retrograde recycling, undergoes a similar degradation in intestinal epithelia in both rab-6.1 and rab-6.2 mutants, suggesting a broader role for these proteins in retrograde transport. Surprisingly, MIG-14 is localized to separate, spatially segregated endosomal compartments in rab-6.1 mutants compared to rab-6.2 mutants. Our results indicate that RAB-6.1 and RAB-6.2 have partially redundant functions in overall retrograde transport, but also have their own unique cellular- and subcellular functions.     

Wnt-7a in feather morphogenesis: involvement of anterior-posterior asymmetry and proximal-distal elongation demonstrated with an in vitro reconstitution model.

How do vertebrate epithelial appendages form from the flat epithelia? Following the formation of feather placodes, the previously radially symmetrical primordia become anterior-posterior (A-P) asymmetrical and develop a proximo-distal (P-D) axis. Analysis of the molecular heterogeneity revealed a surprising parallel of molecular profiles in the A-P feather buds and the ventral-dorsal (V-D) Drosophila appendage imaginal discs. The functional significance was tested with an in vitro feather reconstitution model. Wnt-7a expression initiated all over the feather tract epithelium, intensifying as it became restricted first to the primordia domain, then to an accentuated ring pattern within the primordia border, and finally to the posterior bud. In contrast, sonic hedgehog expression was induced later as a dot within the primordia. RCAS was used to overexpress Wnt-7a in reconstituted feather explants derived from stage 29 dorsal skin to further test its function in feather formation. Control skin formed normal elongated, slender buds with A-P orientation, but Wnt-7a overexpression led to plateau-like skin appendages lacking an A-P axis. Feathers in the Wnt-7a overexpressing skin also had inhibited elongation of the P-D axes. This was not due to a lack of cell proliferation, which actually was increased although randomly distributed. While morphogenesis was perturbed, differentiation proceeded as indicated by the formation of barb ridges. Wnt-7a buds have reduced expression of anterior (Tenascin) bud markers. Middle (Notch-1) and posterior bud markers including Delta-1 and Serrate-1 were diffusely expressed. The results showed that ectopic Wnt-7a expression enhanced properties characteristic of the middle and posterior feather buds and suggest that P-D elongation of vertebrate skin appendages requires balanced interactions between the anterior and posterior buds.     

Effect of precursors on biosynthesis of monensins A and B

Precursors of monensins (acetate, propionate, butyrate, isobutyrate) affect the total production and the relative proportion of monensins A and B. Addition of propionate into the fermentation medium causes a prevalence of monensin B whereas butyrate and isobutyrate stimulate the production of monensin A and suppress the production of monensin B.     

Chewing lice from high‐altitude and migrating birds in Yunnan,China, with descriptions of two new species of Guimaraesiella

In total, 366 birds representing 55 species in 24 families and eight orders, were examined for chewing lice (Phthiraptera: Amblycera, Ischnocera) in two high‐altitude localities in Yunnan Province, China. In Ailaoshan, almost all of the birds examined were resident passeriforms, of which 36% were parasitized by chewing lice. In Jinshanyakou, most birds were on migration, and included both passerine and non‐passerine birds. Of the passerine birds caught in Jinshanyakou, only one bird (0.7%) was parasitized by chewing lice. The prevalence of Myrsidea and Brueelia‐complex lice on birds caught in Ailaoshan was higher than in previous reports. Of the chewing lice identifiable to species level, three represent new records for China: Actornithophilus hoplopteri (Mjöberg, 1910), Maculinirmus ljosalfar Gustafsson & Bush, 2017 and Quadraceps sinensis Timmermann, 1954. In total, 17 new host records are included, of which we describe two as new species in the Brueelia‐complex: Guimaraesiella (Cicchinella) ailaoshanensis sp. nov. ex Schoeniparus dubius dubius (Hume, 1874) and G. (C.) montisodalis sp. nov. ex Fulvetta manipurensis tonkinensis Delacour & Jabouille, 1930. This published work has been registered in ZooBank, http://zoobank.org/urn:lsid:zoobank.org:pub:9FC3D8EE‐2CED‐4DBE‐A1DB‐471B71260D27 .     

A cross-talk between epithelium and endothelium mediates human alveolar–capillary injury during SARS-CoV-2 infection

COVID-19, caused by SARS-CoV-2, is an acute and rapidly developing pandemic, which leads to a global health crisis. SARS-CoV-2 primarily attacks human alveoli and causes severe lung infection and damage. To better understand the molecular basis of this disease, we sought to characterize the responses of alveolar epithelium and its adjacent microvascular endothelium to viral infection under a co-culture system. SARS-CoV-2 infection caused massive virus replication and dramatic organelles remodeling in alveolar epithelial cells, alone. While, viral infection affected endothelial cells in an indirect manner, which was mediated by infected alveolar epithelium. Proteomics analysis and TEM examinations showed viral infection caused global proteomic modulations and marked ultrastructural changes in both epithelial cells and endothelial cells under the co-culture system. In particular, viral infection elicited global protein changes and structural reorganizations across many sub-cellular compartments in epithelial cells. Among the affected organelles, mitochondrion seems to be a primary target organelle. Besides, according to EM and proteomic results, we identified Daurisoline, a potent autophagy inhibitor, could inhibit virus replication effectively in host cells. Collectively, our study revealed an unrecognized cross-talk between epithelium and endothelium, which contributed to alveolar–capillary injury during SARS-CoV-2 infection. These new findings will expand our understanding of COVID-19 and may also be helpful for targeted drug development.Subject terms: Mechanisms of disease, Viral infection     

A study on giant panda recognition based on images of a large proportion of captive pandas

1. As a highly endangered species, the giant panda (panda) has attracted significant attention in the past decades. Considerable efforts have been put on panda conservation and reproduction, offering the promising outcome of maintaining the population size of pandas. To evaluate the effectiveness of conservation and management strategies, recognizing individual pandas is critical. However, it remains a challenging task because the existing methods, such as traditional tracking method, discrimination method based on footprint identification, and molecular biology method, are invasive, inaccurate, expensive, or challenging to perform. The advances of imaging technologies have led to the wide applications of digital images and videos in panda conservation and management, which makes it possible for individual panda recognition in a noninvasive manner by using image‐based panda face recognition method.
2. In recent years, deep learning has achieved great success in the field of computer vision and pattern recognition. For panda face recognition, a fully automatic deep learning algorithm which consists of a sequence of deep neural networks (DNNs) used for panda face detection, segmentation, alignment, and identity prediction is developed in this study. To develop and evaluate the algorithm, the largest panda image dataset containing 6,441 images from 218 different pandas, which is 39.78% of captive pandas in the world, is established.
3. The algorithm achieved 96.27% accuracy in panda recognition and 100% accuracy in detection.
4. This study shows that panda faces can be used for panda recognition. It enables the use of the cameras installed in their habitat for monitoring their population and behavior. This noninvasive approach is much more cost‐effective than the approaches used in the previous panda surveys.