The Drosophila melanogaster septin gene Sep2 has a redundant function with the retrogene Sep5 in imaginal cell proliferation but is essential for oogenesis

Two Septin complexes mediate actin dynamics during cell wound repair

Cells have robust wound repair systems to prevent further damage or infection and to quickly restore cell cortex integrity when exposed to mechanical and chemical stress. Actomyosin ring formation and contraction at the wound edge are major events during closure of the plasma membrane and underlying cytoskeleton during cell wound repair. Here, we show that all five Drosophila Septins are required for efficient cell wound repair. Based on their different recruitment patterns and knockdown/mutant phenotypes, two distinct Septin complexes, Sep1/Sep2/Pnut and Sep4/Sep5/Pnut, are assembled to regulate actin ring assembly, contraction, and remodeling during the repair process. Intriguingly, we find that these two Septin complexes have different F-actin bending activities. In addition, we find that Anillin regulates the recruitment of only one of two Septin complexes upon wounding. Our results demonstrate that two functionally distinct Septin complexes work side by side to discretely regulate actomyosin ring dynamics during cell wound repair.

Essential genes identification model based on sequence feature map and graph convolutional neural network

BACKGROUND

Essential genes encode functions that play a vital role in the life activities of organisms, encompassing growth, development, immune system functioning, and cell structure maintenance. Conventional experimental techniques for identifying essential genes are resource-intensive and time-consuming, and the accuracy of current machine learning models needs further enhancement. Therefore, it is crucial to develop a robust computational model to accurately predict essential genes.

RESULTS

In this study, we introduce GCNN-SFM, a computational model for identifying essential genes in organisms, based on graph convolutional neural networks (GCNN). GCNN-SFM integrates a graph convolutional layer, a convolutional layer, and a fully connected layer to model and extract features from gene sequences of essential genes. Initially, the gene sequence is transformed into a feature map using coding techniques. Subsequently, a multi-layer GCN is employed to perform graph convolution operations, effectively capturing both local and global features of the gene sequence. Further feature extraction is performed, followed by integrating convolution and fully-connected layers to generate prediction results for essential genes. The gradient descent algorithm is utilized to iteratively update the cross-entropy loss function, thereby enhancing the accuracy of the prediction results. Meanwhile, model parameters are tuned to determine the optimal parameter combination that yields the best prediction performance during training.

CONCLUSIONS

Experimental evaluation demonstrates that GCNN-SFM surpasses various advanced essential gene prediction models and achieves an average accuracy of 94.53%. This study presents a novel and effective approach for identifying essential genes, which has significant implications for biology and genomics research.

Two Septin Complexes Mediate Actin Dynamics During Cell Wound Repair

Cells have robust wound repair systems to prevent further damage or infection and to quickly restore cell cortex integrity when exposed to mechanical and chemical stress. Actomyosin ring formation and contraction at the wound edge are major events during closure of the plasma membrane and underlying cytoskeleton during cell wound repair. Here, we show that all five Drosophila Septins are required for efficient cell wound repair. Based on their different recruitment patterns and knockdown/mutant phenotypes, two distinct Septin complexes, Sep1-Sep2-Pnut and Sep4-Sep5-Pnut, are assembled to regulate actin ring assembly, contraction, and remodeling during the repair process. Intriguingly, we find that these two Septin complexes have different F-actin bending activities. In addition, we find that Anillin regulates the recruitment of only one of two Septin complexes upon wounding. Our results demonstrate that two functionally distinct Septin complexes work side-by-side to discretely regulate actomyosin ring dynamics during cell wound repair.

Conservation and divergence of the G-interfaces of Drosophila melanogaster septins

Septins possess a conserved guanine nucleotide-binding (G) domain that participates in the stabilization of organized hetero-oligomeric complexes which assemble into filaments, rings and network-like structures. The fruit fly, Drosophila melanogaster, has five such septin genes encoding Sep1, Sep2, Sep4, Sep5 and Pnut. Here, we report the crystal structure of the heterodimer formed between the G-domains of Sep1 and Sep2, the first from an insect to be described to date. A G-interface stabilizes the dimer (in agreement with the expected arrangement for the Drosophila hexameric particle) and this bears significant resemblance to its human counterparts, even down to the level of individual amino acid interactions. On the other hand, a model for the G-interface formed between the two copies of Pnut which occupy the centre of the hexamer, shows important structural differences, including the loss of a highly favourable bifurcated salt-bridge network. Whereas wild-type Pnut purifies as a monomer, the reintroduction of the salt-bridge network results in stabilizing the dimeric interface in solution as shown by size exclusion chromatography and thermal stability measurements. Adaptive steered molecular dynamics reveals an unzipping mechanism for dimer dissociation which initiates at a point of electrostatic repulsion within the switch II region. Overall, the data contribute to a better understanding of the molecular interactions involved in septin assembly/disassembly.

A Computational Framework Based on Ensemble Deep Neural Networks for Essential Genes Identification

Essential genes contain key information of genomes that could be the key to a comprehensive understanding of life and evolution. Because of their importance, studies of essential genes have been considered a crucial problem in computational biology. Computational methods for identifying essential genes have become increasingly popular to reduce the cost and time-consumption of traditional experiments. A few models have addressed this problem, but performance is still not satisfactory because of high dimensional features and the use of traditional machine learning algorithms. Thus, there is a need to create a novel model to improve the predictive performance of this problem from DNA sequence features. This study took advantage of a natural language processing (NLP) model in learning biological sequences by treating them as natural language words. To learn the NLP features, a supervised learning model was consequentially employed by an ensemble deep neural network. Our proposed method could identify essential genes with sensitivity, specificity, accuracy, Matthews correlation coefficient (MCC), and area under the receiver operating characteristic curve (AUC) values of 60.2%, 84.6%, 76.3%, 0.449, and 0.814, respectively. The overall performance outperformed the single models without ensemble, as well as the state-of-the-art predictors on the same benchmark dataset. This indicated the effectiveness of the proposed method in determining essential genes, in particular, and other sequencing problems, in general.

Transfection of choanoflagellates illuminates their cell biology and the ancestry of animal septins

As the closest living relatives of animals, choanoflagellates offer unique insights into animal origins and core mechanisms underlying animal cell biology. However, unlike traditional model organisms, such as yeast, flies, and worms, choanoflagellates have been refractory to DNA delivery methods for expressing foreign genes. Here we report a robust method for expressing transgenes in the choanoflagellate Salpingoeca rosetta, overcoming barriers that have previously hampered DNA delivery and expression. To demonstrate how this method accelerates the study of S. rosetta cell biology, we engineered a panel of fluorescent protein markers that illuminate key features of choanoflagellate cells. We then investigated the localization of choanoflagellate septins, a family of GTP-binding cytoskeletal proteins that are hypothesized to regulate multicellular rosette development in S. rosetta. Fluorescently tagged septins localized to the basal poles of S. rosetta single cells and rosettes in a pattern resembling septin localization in animal epithelia. The establishment of transfection in S. rosetta and its application to the study of septins represent critical advances in the use of S. rosetta as an experimental model for investigating choanoflagellate cell biology, core mechanisms underlying animal cell biology, and the origin of animals.

SEPT7-mediated regulation of Ca2+ entry through Orai channels requires other septin subunits

Orai channels are plasma membrane resident Ca²⁺ channels that allow extracellular Ca²⁺ uptake after depletion of ER-Ca²⁺ stores by a process called store-operated Ca²⁺ entry (SOCE). Septins of the SEPT2 subgroup act as positive regulators of SOCE in human nonexcitable cells. SEPT2 subgroup septins form the central core of hetero-hexameric or hetero-octameric complexes with SEPT6, SEPT7 and SEPT9 subgroup septins. The presence of fewer septin encoding genes coupled with ease of genetic manipulation allows for better understanding of septin subgroup function in Drosophila. Our earlier findings show that although dSEPT7 reduction does not alter Orai-mediated Ca²⁺ entry during SOCE, it results in constitutive activation of Orai channels in resting neurons. Here, we have investigated the role of other septin subgroup members in regulating Orai channel activation in Drosophila neurons by both cellular and functional assays. We show that dSEPT1, a SEPT2 subgroup septin can exist in a complex with dSEPT2 and dSEPT7 in the central nervous system (CNS) of Drosophila. Our findings suggest that the nature of septin filaments and heteromers obtained after reducing septins of different subgroups alters their ability to regulate Orai channel opening. The molecular mechanisms underlying this complex regulation of Orai function by septins require further cellular investigations.

Prediction and analysis of essential genes using the enrichments of gene ontology and KEGG pathways

Identifying essential genes in a given organism is important for research on their fundamental roles in organism survival. Furthermore, if possible, uncovering the links between core functions or pathways with these essential genes will further help us obtain deep insight into the key roles of these genes. In this study, we investigated the essential and non-essential genes reported in a previous study and extracted gene ontology (GO) terms and biological pathways that are important for the determination of essential genes. Through the enrichment theory of GO and KEGG pathways, we encoded each essential/non-essential gene into a vector in which each component represented the relationship between the gene and one GO term or KEGG pathway. To analyze these relationships, the maximum relevance minimum redundancy (mRMR) was adopted. Then, the incremental feature selection (IFS) and support vector machine (SVM) were employed to extract important GO terms and KEGG pathways. A prediction model was built simultaneously using the extracted GO terms and KEGG pathways, which yielded nearly perfect performance, with a Matthews correlation coefficient of 0.951, for distinguishing essential and non-essential genes. To fully investigate the key factors influencing the fundamental roles of essential genes, the 21 most important GO terms and three KEGG pathways were analyzed in detail. In addition, several genes was provided in this study, which were predicted to be essential genes by our prediction model. We suggest that this study provides more functional and pathway information on the essential genes and provides a new way to investigate related problems.

Partial Functional Diversification of Drosophila melanogaster Septin Genes Sep2 and Sep5

The septin family of hetero-oligomeric complex-forming proteins can be divided into subgroups, and subgroup members are interchangeable at specific positions in the septin complex. Drosophila melanogaster has five septin genes, including the two SEPT6 subgroup members Sep2 and Sep5. We previously found that Sep2 has a unique function in oogenesis, which is not performed by Sep5. Here, we find that Sep2 is uniquely required for follicle cell encapsulation of female germline cysts, and that Sep2 and Sep5 are redundant for follicle cell proliferation. The five D. melanogaster septins localize similarly in oogenesis, including as rings flanking the germline ring canals. Pnut fails to localize in Sep5; Sep2 double mutant follicle cells, indicating that septin complexes fail to form in the absence of both Sep2 and Sep5. We also find that mutations in septins enhance the mutant phenotype of bazooka, a key component in the establishment of cell polarity, suggesting a link between septin function and cell polarity. Overall, this work suggests that Sep5 has undergone partial loss of ancestral protein function, and demonstrates redundant and unique functions of septins.