Eukaryotic expression, Co-IP and MS identify BMPR-1B protein-protein interaction network

Effect of alfalfa supplementary change dietary non-fibrous carbohydrate (NFC) to neutral detergent fiber (NDF) ratio on rumen fermentation and microbial function in Gansu alpine fine wool sheep (Ovis aries)

Bodyweight loss and rumen microbial dysfunction of grazing sheep was a challenge for the sheep production industry during cold season, which were considered to correlated with under-roughage-feeding. Alfalfa is a good roughage supplementary for ruminants, which can improve grazing sheep bodyweight-loss and rumen microbial dysfunction during grass-withering period. This study evaluated the effects of alfalfa hay supplementary change dietary non-fibrous carbohydrate/neutral detergent fiber (NFC/NDF) ratios on rumen fermentation and microbial function of Gansu alpine fine wool sheep during extreme cold season. 120 ewes (3-4 yrs) with an average body weight of 28.71 ± 1.22 kg were allocated randomly into three treatments, and fed NFC/NDF of 1.92 (H group), 1.11 (M group), and 0.68 (L group), respectively. This study was conducted for 107 d, including 7 d of adaption to the diets. The rumen fermentation parameters and microbial characteristics were measured after the end of feeding trials. The results showed that the concentrations of sheep body weight, nitrogen components (Total-N, Soluble protein-N and Ammonia-N), blood biochemical indices (LDH, BUN and CHO) and ruminal volatile fatty acids (TVFA and propionate) significantly increased with an increase in the proportion of NFC/NDF ratios (p < .05), and the acetate and acetate/propionat ratio presented a contrary decreasing trend (p < .05). A total of 1018 OTUs were obtained with 97% consistency. Ruminococcus, Ruminococcaceae and Prevotella were observed as the predominant phyla in ruminal fluid microbiota. Higher NFC/NDF ratios with Alfalfa supplementary increased the richness and diversity of ruminal fluid microbiota, and decreased ruminal fluid microbiota beta-diversity. Using clusters of orthologous groups (COG), the ruminal fluid microbiota of alfalfa supplementary feeding showed low immune pathway and high carbohydrate metabolism pathway. In summary, the study suggested that there was an increasing tendency in dietary NFC/NDF ratio of 1.92 in body weight, ruminal fermentation, microbial community composition and fermentation characteristics through developing alfalfa supplementary system.

Key mRNAs and lncRNAs of pituitary that affect the reproduction of FecB + + small tail han sheep

BACKGROUND

The pituitary directly regulates the reproductive process through follicle-stimulating hormone (FSH) and luteinizing hormone (LH). Transcriptomic research on the pituitaries of ewes with different FecB (fecundity Booroola) genotypes has shown that some key genes and lncRNAs play an important role in pituitary function and sheep fecundity. Our previous study found that ewes with FecB + + genotypes (without FecB mutation) still had individuals with more than one offspring per birth. It is hoped to analyze this phenomenon from the perspective of the pituitary transcriptome.

RESULTS

The 12 Small Tail Han Sheep were equally divided into polytocous sheep in the follicular phase (PF), polytocous sheep in the luteal phase (PL), monotocous sheep in the follicular phase (MF), and monotocous sheep in the luteal phase (ML). Pituitary tissues were collected after estrus synchronous treatment for transcriptomic analysis. A total of 384 differentially expressed genes (DEGs) (182 in PF vs. MF and 202 in PL vs. ML) and 844 differentially expressed lncRNAs (DELs) (427 in PF vs. MF and 417 in PL vs. ML) were obtained from the polytocous-monotocous comparison groups in the two phases. Functional enrichment analysis showed that the DEGs in the two phases were enriched in signaling pathways known to play an important role in sheep fecundity, such as calcium ion binding and cAMP signaling pathways. A total of 1322 target relationship pairs (551 pairs in PF vs. MF and 771 pairs in PL vs. ML) were obtained for the target genes prediction of DELs, of which 29 DEL-DEG target relationship pairs (nine pairs in PF vs. MF and twenty pairs in PL vs. ML). In addition, the competing endogenous RNA (ceRNA) networks were constructed to explore the regulatory relationships of DEGs, and some important regulatory relationship pairs were obtained.

CONCLUSION

According to the analysis results, we hypothesized that the pituitary first receives steroid hormone signals from the ovary and uterus and that VAV3 (Vav Guanine Nucleotide Exchange Factor 3), GABRG1 (Gamma-Aminobutyric Acid A Receptor, Gamma 1), and FNDC1 (Fibronectin Type III Domain Containing 1) played an important role in this process. Subsequently, the reproductive process was regulated by gonadotropins, and IGFBP1 (Insulin-like Growth Factor Binding Protein 1) was directly involved in this process, ultimately affecting litter size. In addition, TGIF1 (Transforming Growth Factor-Beta-Induced Factor 1) and TMEFF2 (Transmembrane Protein With EGF Like And Two Follistatin Like Domains 2) compensated for the effect of the FecB mutation and function by acting on TGF-β/SMAD signaling pathway, an important pathway for sheep reproduction. These results provided a reference for understanding the mechanism of multiple births in Small Tail Han Sheep without FecB mutation.

Applications of multi-omics analysis in human diseases

Multi-omics usually refers to the crossover application of multiple high-throughput screening technologies represented by genomics, transcriptomics, single-cell transcriptomics, proteomics and metabolomics, spatial transcriptomics, and so on, which play a great role in promoting the study of human diseases. Most of the current reviews focus on describing the development of multi-omics technologies, data integration, and application to a particular disease; however, few of them provide a comprehensive and systematic introduction of multi-omics. This review outlines the existing technical categories of multi-omics, cautions for experimental design, focuses on the integrated analysis methods of multi-omics, especially the approach of machine learning and deep learning in multi-omics data integration and the corresponding tools, and the application of multi-omics in medical researches (e.g., cancer, neurodegenerative diseases, aging, and drug target discovery) as well as the corresponding open-source analysis tools and databases, and finally, discusses the challenges and future directions of multi-omics integration and application in precision medicine. With the development of high-throughput technologies and data integration algorithms, as important directions of multi-omics for future disease research, single-cell multi-omics and spatial multi-omics also provided a detailed introduction. This review will provide important guidance for researchers, especially who are just entering into multi-omics medical research.

Targeting Protein-Protein Interfaces with Peptides: The Contribution of Chemical Combinatorial Peptide Library Approaches

Protein-protein interfaces play fundamental roles in the molecular mechanisms underlying pathophysiological pathways and are important targets for the design of compounds of therapeutic interest. However, the identification of binding sites on protein surfaces and the development of modulators of protein-protein interactions still represent a major challenge due to their highly dynamic and extensive interfacial areas. Over the years, multiple strategies including structural, computational, and combinatorial approaches have been developed to characterize PPI and to date, several successful examples of small molecules, antibodies, peptides, and aptamers able to modulate these interfaces have been determined. Notably, peptides are a particularly useful tool for inhibiting PPIs due to their exquisite potency, specificity, and selectivity. Here, after an overview of PPIs and of the commonly used approaches to identify and characterize them, we describe and evaluate the impact of chemical peptide libraries in medicinal chemistry with a special focus on the results achieved through recent applications of this methodology. Finally, we also discuss the role that this methodology can have in the framework of the opportunities, and challenges that the application of new predictive approaches based on artificial intelligence is generating in structural biology.

Significance of Identifying Key Genes Involved in HBV-Related Hepatocellular Carcinoma for Primary Care Surveillance of Patients with Cirrhosis

Cirrhosis is frequently the final stage of disease preceding the development of hepatocellular carcinoma (HCC) and is one of the risk factors for HCC. Preventive surveillance for early HCC in patients with cirrhosis is advantageous for achieving early HCC prevention and diagnosis, thereby enhancing patient prognosis and reducing mortality. However, there is no highly sensitive diagnostic marker for the clinical surveillance of HCC in patients with cirrhosis, which significantly restricts its use in primary care for HCC. To increase the accuracy of illness diagnosis, the study of the effective and sensitive genetic biomarkers involved in HCC incidence is crucial. In this study, a set of 120 significantly differentially expressed genes (DEGs) was identified in the GSE121248 dataset. A protein-protein interaction (PPI) network was constructed among the DEGs, and Cytoscape was used to extract hub genes from the network. In TCGA database, the expression levels, correlation analysis, and predictive performance of hub genes were validated. In total, 15 hub genes showed increased expression, and their positive correlation ranged from 0.80 to 0.90, suggesting they may be involved in the same signaling pathway governing HBV-related HCC. The GSE10143, GSE25097, GSE54236, and GSE17548 datasets were used to investigate the expression pattern of these hub genes in the progression from cirrhosis to HCC. Using Cox regression analysis, a prediction model was then developed. The ROC curves, DCA, and calibration analysis demonstrated the superior disease prediction accuracy of this model. In addition, using proteomic analysis, we investigated whether these key hub genes interact with the HBV-encoded oncogene X protein (HBx), the oncogenic protein in HCC. We constructed stable HBx-expressing LO2-HBx and Huh-7-HBx cell lines. Co-immunoprecipitation coupled with mass spectrometry (Co-IP/MS) results demonstrated that CDK1, RRM2, ANLN, and HMMR interacted specifically with HBx in both cell models. Importantly, we investigated 15 potential key genes (CCNB1, CDK1, BUB1B, ECT2, RACGAP1, ANLN, PBK, TOP2A, ASPM, RRM2, NEK2, PRC1, SPP1, HMMR, and DTL) participating in the transformation process of HBV infection to HCC, of which 4 hub genes (CDK1, RRM2, ANLN, and HMMR) probably serve as potential oncogenic HBx downstream target molecules. All these findings of our study provided valuable research direction for the diagnostic gene detection of HBV-related HCC in primary care surveillance for HCC in patients with cirrhosis.

TRIM65 Promotes Malignant Cell Behaviors in Triple-Negative Breast Cancer by Impairing the Stability of LATS1 Protein

TNBC is a malignant tumor that easily relapses and metastasizes, with a poor prognosis in women. Ubiquitination plays a key role in promoting the tumor process. In various tumors, TRIM65 can affect malignant biological tumor behavior by ubiquitination of related proteins. We aimed to investigate TRIM65 expression in TNBC and whether it promotes malignant biological behavior in TNBC cells using Cell Counting Kit-8, colony formation, and transwell assays. Mechanically, we confirmed that TRIM65 promoted TNBC invasion and metastasis by ubiquitination of LATS1 protein through Co-IP, CHX, and endogenous ubiquitination experiments. The expression of TRIM65 was abnormally high and accelerated the proliferation, invasion, and migration of MDA-MB-231 and MDA-MB-453 cells. In vivo animal experiments also revealed that TRIM65 accelerated TNBC cell proliferation. Mechanistically, TRIM65 degraded LATS1 protein expression through ubiquitination in the Co-IP, CHX, and endogenous ubiquitination experiments. Rescue assays confirmed that TRIM65 degraded LATS1 protein expression, accelerating the proliferation, invasion, and migration ability of TNBC cells. Our results show that TRIM65 is upregulated in TNBC, and TRIM65 degrades LATS1 protein expression through ubiquitination and promotes malignant biological behavior in TNBC cells. TRIM65 may play an important role as a new oncogene in TNBC.

Are Copy Number Variations within the FecB Gene Significantly Associated with Morphometric Traits in Goats?

The Booroola fecundity (FecB) gene is a major fertility-related gene first identified in Booroola sheep. Numerous studies have investigated whether the FecB gene is a major fecundity gene in goats or whether there are other genes that play a critical role in goat fertility. Nevertheless, little attention has been paid to the role of the FecB gene in the body morphometric traits of goats, despite the positive relationship discerned between litter size and growth. We identified five copy number variations (CNVs) within the FecB gene in 641 goats, including 318 Shaanbei white cashmere (SBWC) goats, 203 Guizhou Heima (GZHM) goats, and 120 Nubian goats, which exhibited different distributions among these populations. Our results revealed that these five CNVs were significantly associated with goat morphometric traits (p < 0.05). The normal type of CNV3 was the dominant type and displayed superior phenotypes in both litter size and morphometric traits, making it an effective marker for goat breeding. Consequently, LD blocks in the region of 10 Mb upstream and downstream from FecB and potential transcription factors (TFs) that could bind with the CNVs were analyzed via bioinformatics. Although no significant LD block was detected, our results illustrated that these CNVs could bind to growth-related TFs and indirectly affect the growth development of the goats. We identified potential markers to promote litter size and growth, and we offer a theoretical foundation for further breeding work.

Protein-protein interaction networks as miners of biological discovery

Protein-protein interactions (PPIs) form the basis of a myriad of biological pathways and mechanism, such as the formation of protein-complexes or the components of signaling cascades. Here, we reviewed experimental methods for identifying PPI pairs, including yeast two-hybrid, mass spectrometry, co-localization, and co-immunoprecipitation. Furthermore, a range of computational methods leveraging biochemical properties, evolution history, protein structures and more have enabled identification of additional PPIs. Given the wealth of known PPIs, we reviewed important network methods to construct and analyze networks of PPIs. These methods aid biological discovery through identifying hub genes and dynamic changes in the network, and have been thoroughly applied in various fields of biological research. Lastly, we discussed the challenges and future direction of research utilizing the power of PPI networks. This article is protected by copyright. All rights reserved.

Thyroid Transcriptomic Profiling Reveals the Follicular Phase Differential Regulation of lncRNA and mRNA Related to Prolificacy in Small Tail Han Sheep with Two FecB Genotypes

Long non-coding RNA (lncRNA) accounts for a large proportion of RNA in animals. The thyroid gland has been established as an important gland involved in animal reproduction, however, little is known of its gene expression patterns and potential roles in the sheep. Herein, RNA-Seq was used to detect reproduction-related differentially expressed lncRNAs (DELs) and mRNAs (DEGs) in the follicular phase (FT) FecBBB (MM) and FecB++ (ww) genotypes of Small Tail Han (STH) sheep thyroids. Overall, 29 DELs and 448 DEGs in thyroid between MM and ww sheep were screened. Moreover, GO and KEGG enrichment analysis showed that targets of DELs and DEGs were annotated in biological transitions, such as cell cycle, oocyte meiosis and methylation, which in turn affect reproductive performance in sheep. In addition, we constructed co-expression and networks of lncRNAs-mRNAs. Specifically, XLOC_075176 targeted MYB, XLOC_014695 targeted VCAN, 106991527 targeted CASR, XLOC_075176 targeted KIFC1, XLOC_360232 targeted BRCA2. All these differential lncRNAs and mRNAs expression profiles in the thyroid provide a new resource for elucidating the regulatory mechanism underlying STH sheep prolificacy.

Protein–Protein Interaction (PPI) Network of Zebrafish Oestrogen Receptors: A Bioinformatics Workflow

Protein–protein interaction (PPI) is involved in every biological process that occurs within an organism. The understanding of PPI is essential for deciphering the cellular behaviours in a particular organism. The experimental data from PPI methods have been used in constructing the PPI network. PPI network has been widely applied in biomedical research to understand the pathobiology of human diseases. It has also been used to understand the plant physiology that relates to crop improvement. However, the application of the PPI network in aquaculture is limited as compared to humans and plants. This review aims to demonstrate the workflow and step-by-step instructions for constructing a PPI network using bioinformatics tools and PPI databases that can help to predict potential interaction between proteins. We used zebrafish proteins, the oestrogen receptors (ERs) to build and analyse the PPI network. Thus, serving as a guide for future steps in exploring potential mechanisms on the organismal physiology of interest that ultimately benefit aquaculture research.

Combined approaches identify known and novel genes associated with sheep litter size and non-seasonal breeding

Improvement of ewe reproduction is considerable by appropriately increasing litter size and sustaining non-seasonal breeding. However, their genetic makeups have not been entirely elucidated. Genome-wide analyses of 821 individuals were performed by combining three genomic approaches (genome-wide association study, XP-nSL, and runs of homozygosity). Consequently, 35 candidate genes including three domestication genes (TSHR, GTF2A1, and KITLG) were identified. Other than the FecB mutation at BMPR1B, we described a significant association of a missense mutation rs406686139 at seasonal lambing-associated TSHR gene with litter size. Some promising novel genes may be relevant for sheep reproduction by multitude biological processes, such as FETUB functioning in fertilization, HNRNPA1 in oogenesis, DCUN1D1 in spermatogenesis, and HRG in fertility outcome. The present study suggests that improvement of ewe reproduction is attributed to selective breeding, and casts light on the genetic basis and improvement of sheep reproduction.

Polymorphism Detection of GDF9 Gene and Its Association with Litter Size in Luzhong Mutton Sheep (Ovis aries)

Simple Summary

GDF9 and BMPR1B are two important reproduction genes. In this study, the whole coding region of GDF9 was sequenced, of which the mutations were detected in Luzhong mutton sheep. The results suggested that two single nucleotide polymorphisms (SNPs), g.41768501A > G and g.41768485 G > A in GDF9 gene were associated with litter size. The g.41768485 G > A is a missense mutation which is predicted to affect the tertiary structure of the protein. Thus, these two mutations may be potential effective genetic markers to improve the litter size in sheep.

Abstract

Litter size is one of the most important economic traits in sheep. GDF9 and BMPR1B are major genes affecting the litter size of sheep. In this study, the whole coding region of GDF9 was sequenced and all the SNPs (single nucleotide polymorphisms) were determined in Luzhong mutton ewes. The FecB mutation was genotyped using the Sequenom MassARRAY^®SNP assay technology. Then, the association analyses between polymorphic loci of GDF9 gene, FecB, and litter size were performed using a general linear model procedure. The results showed that eight SNPs were detected in GDF9 of Luzhong mutton sheep, including one novel mutation (g.41769606 T > G). The g.41768501A > G, g.41768485 G > A in GDF9 and FecB were significantly associated with litter size in Luzhong mutton ewes. The g.41768485 G > A is a missense mutation in the mature GDF9 protein region and is predicted to affect the tertiary structure of the protein. The results preliminarily demonstrated that GDF9 was a major gene affecting the fecundity of Luzhong mutton sheep and the two loci g.41768501A > G and g.41768485 G > A may be potential genetic markers for improving litter size.

Receptor binding competition: A paradigm for regulating TGF-β family action

The transforming growth factor (TGF)-β family is a group of structurally related, multifunctional growth factors, or ligands that are crucially involved in the development, regulation, and maintenance of animal tissues. In humans, the family counts over 33 members. These secreted ligands typically form multimeric complexes with two type I and two type II receptors to activate one of two distinct signal transduction branches. A striking feature of the family is its promiscuity, i.e., many ligands bind the same receptors and compete with each other for binding to these receptors. Although several explanations for this feature have been considered, its functional significance has remained puzzling. However, several recent reports have promoted the idea that ligand-receptor binding promiscuity and competition are critical features of the TGF-β family that provide an essential regulating function. Namely, they allow a cell to read and process multi-ligand inputs. This capability may be necessary for producing subtle, distinctive, or adaptive responses and, possibly, for facilitating developmental plasticity. Here, we review the molecular basis for ligand competition, with emphasis on molecular structures and binding affinities. We give an overview of methods that were used to establish experimentally ligand competition. Finally, we discuss how the concept of ligand competition may be fundamentally tied to human physiology, disease, and therapy.