PLASMODESMATA-LOCATED PROTEIN 6 regulates plasmodesmal function in Arabidopsis vasculature.

Plasmodesmata connect adjoining plant cells, allowing molecules to move between the connected cells for communication and sharing resources. It has been well established that the plant polysaccharide callose is deposited at plasmodesmata, regulating their aperture and function. Among proteins involved in maintaining callose homeostasis, PLASMODESMATA-LOCATED PROTEINSs (PDLPs) promote callose deposition at plasmodesmata. This study explored the function of PDLP5 and PDLP6 in different cell types. We discovered that PDLP5 and PDLP6 are expressed in non-overlapping cell types in Arabidopsis (Arabidopsis thaliana). The overexpression of PDLP5 and PDLP6 results in the overaccumulation of plasmodesmal callose at different cell interfaces, indicating that PDLP5 and PDLP6 are active in different cell types. We also observed two distinct patterns of starch accumulation in mature leaves of PDLP5 and PDLP6 overexpressors. An enzyme-catalyzed proximity labeling approach was used to identify putative functional partners of the PDLPs. We identified SUCROSE SYNTHASE6 (SUS6) as a functional partner of PDLP6 in the vasculature. We further demonstrated that PDLP6 physically and genetically interacts with SUS6. In addition, CALLOSE SYNTHASE7 (CALS7) physically interacts with SUS6 and PDLP6. Genetic interaction studies showed that CALS7 is required for PDLP6 function. We propose that PDLP6 functions with SUS6 and CALS7 in the vasculature to regulate plasmodesmal function.

Both Las17-binding sites on Arp2/3 complex are important for branching nucleation and assembly of functional endocytic actin networks in S. cerevisiae.

Arp2/3 complex nucleates branched actin filaments that drive membrane invagination during endocytosis and leading-edge protrusion in lamellipodia. Arp2/3 complex is maximally activated in vitro by binding of a WASP family protein to two sites-one on the Arp3 subunit and one spanning Arp2 and ARPC1-but the importance of each site in the regulation of force-producing actin networks is unclear. Here, we identify mutations in budding yeast Arp2/3 complex that decrease or block engagement of Las17, the budding yeast WASP, at each site. As in the mammalian system, both sites are required for maximal activation in vitro. Dimerization of Las17 partially restores activity of mutations at both CA-binding sites. Arp2/3 complexes defective at either site assemble force-producing actin networks in a bead motility assay, but their reduced activity hinders motility by decreasing actin assembly near the bead surface and by failing to suppress actin filament bundling within the networks. While even the most defective Las17-binding site mutants assembled actin filaments at endocytic sites, they showed significant internalization defects, potentially because they lack the proper architecture to drive plasma membrane remodeling. Together, our data indicate that both Las17-binding sites are important to assemble functional endocytic actin networks in budding yeast, but Arp2/3 complex retains some activity in vitro and in vivo even with a severe defect at either Las17-binding site.

Rapid discrimination of four Salmonella enterica serovars: A performance comparison between benchtop and handheld Raman spectrometers.

Foodborne illnesses, particularly those caused by Salmonella enterica with its extensive array of over 2600 serovars, present a significant public health challenge. Therefore, prompt and precise identification of S. enterica serovars is essential for clinical relevance, which facilitates the understanding of S. enterica transmission routes and the determination of outbreak sources. Classical serotyping methods via molecular subtyping and genomic markers currently suffer from various limitations, such as labour intensiveness, time consumption, etc. Therefore, there is a pressing need to develop new diagnostic techniques. Surface-enhanced Raman spectroscopy (SERS) is a non-invasive diagnostic technique that can generate Raman spectra, based on which rapid and accurate discrimination of bacterial pathogens could be achieved. To generate SERS spectra, a Raman spectrometer is needed to detect and collect signals, which are divided into two types: the expensive benchtop spectrometer and the inexpensive handheld spectrometer. In this study, we compared the performance of two Raman spectrometers to discriminate four closely associated S. enterica serovars, that is, S. enterica subsp. enterica serovar dublin, enteritidis, typhi and typhimurium. Six machine learning algorithms were applied to analyse these SERS spectra. The support vector machine (SVM) model showed the highest accuracy for both handheld (99.97%) and benchtop (99.38%) Raman spectrometers. This study demonstrated that handheld Raman spectrometers achieved similar prediction accuracy as benchtop spectrometers when combined with machine learning models, providing an effective solution for rapid, accurate and cost-effective identification of closely associated S. enterica serovars.

Differentiation of closely-related species within Acinetobacter baumannii-calcoaceticus complex via Raman spectroscopy: a comparative machine learning analysis.

Bacterial species within the Acinetobacter baumannii-calcoaceticus (Acb) complex are very similar and are difficult to discriminate. Misidentification of these species in human infection may lead to severe consequences in clinical settings. Therefore, it is important to accurately discriminate these pathogens within the Acb complex. Raman spectroscopy is a simple method that has been widely studied for bacterial identification with high similarities. In this study, we combined surfaced-enhanced Raman spectroscopy (SERS) with a set of machine learning algorithms for identifying species within the Acb complex. According to the results, the support vector machine (SVM) model achieved the best prediction accuracy at 98.33% with a fivefold cross-validation rate of 96.73%. Taken together, this study confirms that the SERS-SVM method provides a convenient way to discriminate between A. baumannii, Acinetobacter pittii, and Acinetobacter nosocomialis in the Acb complex, which shows an application potential for species identification of Acinetobacter baumannii-calcoaceticus complex in clinical settings in near future.