RPI-GGCN: Prediction of RNA-Protein Interaction Based on Interpretability Gated Graph Convolution Neural Network and Co-Regularized Variational Autoencoders.

RNA-protein interactions (RPIs) play an important role in several fundamental cellular physiological processes, including cell motility, chromosome replication, transcription and translation, and signaling. Predicting RPI can guide the exploration of cellular biological functions, intervening in diseases, and designing drugs. Given this, this study proposes the RPI-gated graph convolutional network (RPI-GGCN) method for predicting RPI based on the gated graph convolutional neural network (GGCN) and co-regularized variational autoencoder (Co-VAE). First, different types of feature information were extracted from RNA and protein sequences by nine feature extraction methods. Second, Co-VAEs are used to eliminate the redundancy of fused features and generate optimal features. Finally, this study introduces gated cyclic units into graph convolutional networks (GCNs) to construct a model for RPI prediction, which efficiently extracts topological information and improves the model's interpretable feature learning and expression capabilities. In the fivefold cross-validation test, the RPI-GGCN method achieved prediction accuracies of 97.27%, 97.32%, 96.54%, 95.76%, and 94.98% on the RPI369, RPI488, RPI1446, RPI1807, and RPI2241 datasets. To test the generalization performance of the model, we used the model trained on RPI369 to predict the independent NPInter v3.0 dataset and achieved excellent performance in all six independent validation sets. By visualizing the RPI network graph based on the prediction results, we aim to provide a new perspective and reference for studying RPI mechanisms and exploring new RPIs. Extensive experimental results demonstrate that RPI-GGCN can provide an efficient, accurate, and stable RPI prediction method.

The role of SRPK1-mediated phosphorylation of SR proteins in the chromatin configuration transition of mouse germinal vesicle oocytes.

Meiotic resumption in mammalian oocytes involves nucleus and organelle structural changes, notably chromatin configuration transitioning from non-surrounding nucleolus (NSN) to surrounding nucleolus (SN) in germinal vesicle (GV) oocytes. Our study found that nuclear speckles, a subnuclear structure mainly composed of serine-arginine (SR) proteins, changed from a diffuse spotted distribution in mouse NSN oocytes to an aggregation pattern in SN oocytes. We further discovered that SRPK1, an enzyme phosphorylating SR proteins, co-localized with NS at SN stage and NSN oocytes failed to convert into SN oocytes after inhibiting the activity of SRPK1. Furthermore, the typical structure of chromatin ring around the nucleolus in SN oocytes collapsed after inhibitor treatment. To explore the underlying mechanism, phosphorylated SR proteins were confirmed to be associated with chromatin by salt extraction experiment, and in situ DNase I assay showed that the accessibility of chromatin enhanced in SN oocytes with SRPK1 inhibited, accompanied by decreased repressive modification on histone and abnormal recurrence of transcriptional signal. In conclusion, our results indicated that SRPK1-regulated phosphorylation on SR proteins was involved in the NSN to SN transition and played an important role in maintaining the condensation nucleus of SN oocytes via interacting with chromatin.

ML-FGAT: Identification of multi-label protein subcellular localization by interpretable graph attention networks and feature-generative adversarial networks.

The prediction of multi-label protein subcellular localization (SCL) is a pivotal area in bioinformatics research. Recent advancements in protein structure research have facilitated the application of graph neural networks. This paper introduces a novel approach termed ML-FGAT. The approach begins by extracting node information of proteins from sequence data, physical-chemical properties, evolutionary insights, and structural details. Subsequently, various evolutionary techniques are integrated to consolidate multi-view information. A linear discriminant analysis framework, grounded on entropy weight, is then employed to reduce the dimensionality of the merged features. To enhance the robustness of the model, the training dataset is augmented using feature-generative adversarial networks. For the primary prediction step, graph attention networks are employed to determine multi-label protein SCL, leveraging both node and neighboring information. The interpretability is enhanced by analyzing the attention weight parameters. The training is based on the Gram-positive bacteria dataset, while validation employs newly constructed datasets: human, virus, Gram-negative bacteria, plant, and SARS-CoV-2. Following a leave-one-out cross-validation procedure, ML-FGAT demonstrates noteworthy superiority in this domain.

Mutations in CCNB3 affect its location thus causing a multiplicity of phenotypes in human oocytes maturation by aberrant CDK1 activity and APC/C activity at different stages.

BACKGROUND: Oocyte maturation arrest results in female infertility and the genetic etiology of this phenotype remains largely unknown. Previous studies have proven that cyclins play a significant role in the cell cycle both in meiosis and mitosis. Cyclin B3 (CCNB3) is one of the members of the cyclin family and its function in human oocyte maturation is poorly understood. METHODS: 118 infertile patients were recruited and WES was performed for 68 independent females that experienced oocyte maturation arrest. Four mutations in CCNB3 were found and effects of these mutations were validated by Sanger sequencing and in vitro functional analyses. RESULTS: We found these mutations altered the location of cyclin B3 which affected the function of cyclin dependent kinase 1 (CDK1) and led to mouse oocyte arrested at germinal vesicle (GV) stage. And then, low CDK1 activity influenced the degradation of cadherin 1 (CDH1) and the accumulation of cell division cycle 20 (CDC20) which are two types of anaphase-promoting complex/cyclosome (APC/C) activators and act in different stages of the cell cycle. Finally, APC/C activity was downregulated due to insufficient CDC20 level and resulted in oocyte metaphase I (MI) arrest. Moreover, we also found that the addition of PP1 inhibitor Okadic acid and CDK1 inhibitor Roscovitine at corresponding stages during oocyte in vitro maturation (IVM) significantly improved the maturation rates in CCNB3 mutant cRNAs injected oocytes. The above experiments were performed in mouse oocytes. CONCLUSION: Here, we report five independent patients in which mutations in CCNB3 may be the cause of oocyte maturation arrest. Our findings shed lights on the critical role of CCNB3 in human oocyte maturation.

NLRP7 participates in the human subcortical maternal complex and its variants cause female infertility characterized by early embryo arrest.

Successful human reproduction requires normal oocyte maturation, fertilization, and early embryo development. Early embryo arrest is a common phenomenon leading to female infertility, but the genetic basis is largely unknown. NLR family pyrin domain-containing 7 (NLRP7) is a member of the NLRP subfamily. Previous studies have shown that variants of NLRP7 are one of the crucial causes of female recurrent hydatidiform mole, but whether NLRP7 variants can directly affect early embryo development is unclear. We performed whole-exome sequencing in patients who experienced early embryo arrest, and five heterozygous variants (c.251G > A, c.1258G > A, c.1441G > A, c. 2227G > A, c.2323C > T) of NLRP7 were identified in affected individuals. Plasmids of NLRP7 and subcortical maternal complex components were overexpressed in 293 T cells, and Co-IP experiments showed that NLRP7 interacted with NLRP5, TLE6, PADI6, NLRP2, KHDC3L, OOEP, and ZBED3. Injecting complementary RNAs in mouse oocytes and early embryos showed that NLRP7 variants influenced the oocyte quality and some of the variants significantly affected early embryo development. These findings contribute to our understanding of the role of NLRP7 in human early embryo development and provide a new genetic marker for clinical early embryo arrest patients. KEY MESSAGES: Five heterozygous variants of NLRP7 (c.1441G > A; 2227G > A; c.251G > A; c.1258G > A; c.2323C > T) were identified in five infertile patients who experienced early embryo arrest. NLRP7 is a component of human subcortical maternal complex. NLRP7 variants lead to poor quality of oocytes and early embryo development arrest. This study provides a new genetic marker for clinical early embryo arrest patients.

Predicting the multi-label protein subcellular localization through multi-information fusion and MLSI dimensionality reduction based on MLFE classifier.

MOTIVATION: Multi-label (ML) protein subcellular localization (SCL) is an indispensable way to study protein function. It can locate a certain protein (such as the human transmembrane protein that promotes the invasion of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)) or expression product at a specific location in a cell, which can provide a reference for clinical treatment of diseases such as coronavirus disease 2019 (COVID-19). RESULTS: The article proposes a novel method named ML-locMLFE. First of all, six feature extraction methods are adopted to obtain protein effective information. These methods include pseudo amino acid composition, encoding based on grouped weight, gene ontology, multi-scale continuous and discontinuous, residue probing transformation and evolutionary distance transformation. In the next part, we utilize the ML information latent semantic index method to avoid the interference of redundant information. In the end, ML learning with feature-induced labeling information enrichment is adopted to predict the ML protein SCL. The Gram-positive bacteria dataset is chosen as a training set, while the Gram-negative bacteria dataset, virus dataset, newPlant dataset and SARS-CoV-2 dataset as the test sets. The overall actual accuracy of the first four datasets are 99.23%, 93.82%, 93.24% and 96.72% by the leave-one-out cross validation. It is worth mentioning that the overall actual accuracy prediction result of our predictor on the SARS-CoV-2 dataset is 72.73%. The results indicate that the ML-locMLFE method has obvious advantages in predicting the SCL of ML protein, which provides new ideas for further research on the SCL of ML protein. AVAILABILITY AND IMPLEMENTATION: The source codes and datasets are publicly available at https://github.com/QUST-AIBBDRC/ML-locMLFE/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Expanding the Genetic and Phenotypic Spectrum of Female Infertility Caused by TUBB8 Mutations.

Tubulin beta eight class VIII (TUBB8) is a subtype of ß-tubulin that only exists in primates. TUBB8 mutations have been reported to cause arrest of oocyte maturation and embryonic development. We aim to further investigate the mutational spectrum of TUBB8 and its relevance with female infertility. In our study, infertile patients were recruited, and their basal and clinical characteristics were analyzed. Genomic DNA was extracted from peripheral blood donated by patients. Candidate variants were identified by whole-exome sequencing, selected by relevant criteria, and validated by Sanger sequencing. We found five heterozygous variants: c.C208A(p.P70T), c.T907C(p.C303R), c.G173A(p.R58K), c.G326T(p.G109V), and c.C916T(p.R306C) in TUBB8 among six infertile patients characterized by abnormal phenotypes in oocyte maturation, fertilization, or embryo development. Most of oocytes retrieved from affected individuals were arrested at GV (germinal vesicle) stage and early embryos were arrested at variable stages. In vitro experiments were performed, and the relationship between variant c.G173A(p.R58K), c.C208A(p.P70T), and infertility phenotype was confirmed. We also discussed the possibility about patient II-1 from family 4 is affected by germinal/germline mosaicism. These results expand the kinds of variants and phenotypic spectrum of TUBB8 variants with regard to female infertility.

Integrative proteome analysis implicates aberrant RNA splicing in impaired developmental potential of aged mouse oocytes.

Aging has many effects on the female reproductive system, among which decreased oocyte quality and impaired embryo developmental potential are the most important factors affecting female fertility. However, the mechanisms underlying oocyte aging are not yet fully understood. Here, we selected normal reproductively aging female mice and constructed a protein expression profile of metaphase II (MII) oocytes from three age groups. A total of 187 differentially expressed (DE) proteins were identified, and bioinformatics analyses showed that these DE proteins were highly enriched in RNA splicing. Next, RNA-seq was performed on 2-cell embryos from these three age groups, and splicing analysis showed that a large number of splicing events and genes were discovered at this stage. Differentially spliced genes (DSGs) in the two reproductively aging groups versus the younger group were enriched in biological processes related to DNA damage repair/response. Binding motif analysis suggested that PUF60 might be one of the core splicing factors causing a decline in DNA repair capacity in the subsequent development of oocytes from reproductively aging mice, and changing the splicing pattern of its potential downstream DSG Cdk9 could partially mimic phenotypes in the reproductively aging groups. Taken together, our study suggested that the abnormal expression of splicing regulation proteins in aged MII oocytes would affect the splicing of nascent RNA after zygotic genome activation in 2-cell embryos, leading to the production of abnormally spliced transcripts of some key genes associated with DNA damage repair/response, thus affecting the developmental potential of aged oocytes.

Maternal RNF114-mediated target substrate degradation regulates zygotic genome activation in mouse embryos.

Zygotic genomic activation (ZGA) is a landmark event in the maternal-to-zygotic transition (MZT), and the regulation of ZGA by maternal factors remains to be elucidated. In this study, the depletion of maternal ring finger protein 114 (RNF114), a ubiquitin E3 ligase, led to developmental arrest of two-cell mouse embryos. Using immunofluorescence and transcriptome analysis, RNF114 was proven to play a crucial role in major ZGA. To study the underlying mechanism, we performed protein profiling in mature oocytes and found a potential substrate for RNF114, chromobox 5 (CBX5), ubiquitylation and degradation of which was regulated by RNF114. The overexpression of CBX5 prevented embryonic development and impeded major ZGA. Furthermore, TAB1 was abnormally accumulated in mutant two-cell embryos, which was consistent with the result of in vitro knockdown of Rnf114. Knockdown of Cbx5 or Tab1 in maternal RNF114-depleted embryos partially rescued developmental arrest and the defect of major ZGA. In summary, our study reveals that maternal RNF114 plays a precise role in degrading some important substrates during the MZT, the misregulation of which may impede the appropriate activation of major ZGA in mouse embryos.

The Recurrent Mutation in PATL2 Inhibits Its Degradation Thus Causing Female Infertility Characterized by Oocyte Maturation Defect Through Regulation of the Mos-MAPK Pathway.

PAT1 homolog 2 (PATL2), encoding an RNA-binding protein, is a repressor involved in the translational regulation of maternal mRNAs during oocyte maturation. Previous studies have reported mutations in PATL2 those led to female infertility with oocyte maturation arrest; however, the mechanisms by which mutations affected meiotic maturation remained unclear. Here, we identified several novel and recurrent mutations of PATL2 in patients with similar phenotype, and chose the missense mutation c.649 T>A p.Tyr217Asn in PATL2 (PATL2Y217N) as a typical to investigate the underlying mechanisms. We confirmed that this mutation disturbed oocyte maturation and observed morphological defects of large polar body, symmetrical division and abnormal spindle after microinjection of corresponding mutated mRNA. We further evaluated the effect of the PATL2Y217N mutation in 293T cells, and found this mutation decreased the ubiquitination level and degradation of PATL2. Then, abnormally increased PATL2 bound mRNAs of Mos, an upstream activator of mitogen activated protein kinase (MAPK), to regulate its translational activity and subsequently impaired MAPK signaling pathway and oocyte meiosis. These results dissented from the previous view that PATL2 mutations reduced their expression and highlight the role of PATL2 in translational regulation of Mos and its association with MAPK signaling pathway during oocyte meiotic maturation.

Heterozygous mutations in ZP1 and ZP3 cause formation disorder of ZP and female infertility in human.

The human zona pellucida (ZP) is a highly organized glycoprotein matrix that encircles oocytes and plays an essential role in successful reproduction. Previous studies have reported that mutations in human ZP1, ZP2 and ZP3 influence their functions and result in a lack of ZP or in an abnormal oocytes and empty follicle syndrome, which leads to female infertility. Here, we performed whole-exome sequencing in two probands with primary infertility whose oocytes lacked a ZP, and we identified a heterozygous mutation in ZP1 (NM_207341:c.326G>A p.Arg109His), which is situated in the N-terminus, and a heterozygous mutation in ZP3 (NM_001110354:c.400G>A p.Ala134Thr), which is situated in the ZP domain. The effects of the mutations were investigated through structure prediction and in vitro studies in HeLa cells. The results, which were in line with the phenotype, suggested that these mutations might impede the function of cross-linking and secretion of ZP proteins. Our study showed that the two mutations in ZP1 and ZP3 influenced the formation of the ZP, causing female infertility. Meanwhile, these data highlight the importance of the ZP1 N-terminus in addition to the conserved domains for ZP1 function and ZP formation. Additionally, the patient with the ZP1 mutation delivered a baby following intracytoplasmic sperm injection (ICSI); thus, we suggest the targeted genetic diagnosis of ZP genes to choose appropriate fertilization methods and improve the success rate of assisted reproductive technology (ART) treatments.