BMC Biology最新文献

Background: Accurately identifying drug-target affinity (DTA) plays a pivotal role in drug screening, design, and repurposing in pharmaceutical industry. It not only reduces the time, labor, and economic costs associated with biological experiments but also expedites drug development process. However, achieving the desired level of computational accuracy for DTA identification methods remains a significant challenge.

Results: We proposed a novel multi-view-based graph deep model known as MvGraphDTA for DTA prediction. MvGraphDTA employed a graph convolutional network (GCN) to extract the structural features from original graphs of drugs and targets, respectively. It went a step further by constructing line graphs with edges as vertices based on original graphs of drugs and targets. GCN was also used to extract the relationship features within their line graphs. To enhance the complementarity between the extracted features from original graphs and line graphs, MvGraphDTA fused the extracted multi-view features of drugs and targets, respectively. Finally, these fused features were concatenated and passed through a fully connected (FC) network to predict DTA.

Conclusions: During the experiments, we performed data augmentation on all the training sets used. Experimental results showed that MvGraphDTA outperformed the competitive state-of-the-art methods on benchmark datasets for DTA prediction. Additionally, we evaluated the universality and generalization performance of MvGraphDTA on additional datasets. Experimental outcomes revealed that MvGraphDTA exhibited good universality and generalization capability, making it a reliable tool for drug-target interaction prediction.

Background: The previously underestimated effects of commensal gut microbiota on the human body are increasingly being investigated using omics. The discovery of active molecules of interaction between the microbiota and the host may be an important step towards elucidating the mechanisms of symbiosis.

Results: Here, we show that in the bloodstream of healthy people, there are over 900 peptides that are fragments of proteins from microorganisms which naturally inhabit human biotopes, including the intestinal microbiota. Absolute quantitation by multiple reaction monitoring has confirmed the presence of bacterial peptides in the blood plasma and serum in the range of approximately 0.1 nM to 1 μM. The abundance of microbiota peptides reaches its maximum about 5 h after a meal. Most of the peptides correlate with the bacterial composition of the small intestine and are likely obtained by hydrolysis of membrane proteins with trypsin, chymotrypsin and pepsin - the main proteases of the gastrointestinal tract. The peptides have physicochemical properties that likely allow them to selectively pass the intestinal mucosal barrier and resist fibrinolysis.

Conclusions: The proposed approach to the identification of microbiota peptides in the blood, after additional validation, may be useful for determining the microbiota composition of hard-to-reach intestinal areas and monitoring the permeability of the intestinal mucosal barrier.

Background: The ability to learn from humans via observation was considered to be equally present across properly socialized dogs. We showed recently that cooperative working breeds learned from a human demonstrator more effectively. We hypothesized that functional breed selection could affect sensitivity to human attention-eliciting behavior. Accordingly, we ran the first ever study on dogs that compared the effect of ostensive and neutral verbal communication in a social learning scenario. We used the detour paradigm around a transparent V-shaped fence with either ostensive (addressing the receiver both with words and specific, attention-eliciting prosody) or neutral speech (monotonous reciting of a short poem) demonstration. The other features (gestures, movement) of the demonstration sequence were kept identical between the two conditions. We tested (N = 70) companion dogs from 17 cooperative and 16 independent breeds in three 1-min trials. Subjects had to obtain the reward by detouring around the fence.

Results: Detour latencies of the cooperative dogs improved after both ostensive and neutral speech demonstrations. The independent dogs did not improve their detour latency in either of the conditions. Remarkably, ostensive verbal utterances elicited longer relative looking time towards the demonstrator, cooperative dogs looked longer at the demonstrator, and longer looking time resulted in more successful detours.

Conclusions: Our study provides the first indication that functional breed selection had a significant impact on dogs' sensitivity to ostensive human communication, which, apart from being crucially important for social learning from humans, until now was considered as a uniformly present heritage of domestication in dogs.

Background: Cell wall integrity (CWI) is crucial for fungal growth, pathogenesis, and adaptation to extracellular environments. Calcofluor white (CFW) is a cell wall perturbant that inhibits fungal growth, yet little is known about how phytopathogenic fungi respond to the CFW-induced stress.

Results: In this study, we unveiled a significant discovery that CFW triggered the translocation of the transcription factor CgCrzA from the cytoplasm to the nucleus in Colletotrichum gloeosporioides. This translocation was regulated by an interacting protein, CgMkk1, a mitogen-activated protein kinase involved in the CWI pathway. Further analysis revealed that CgMkk1 facilitated nuclear translocation by phosphorylating CgCrzA at the Ser280 residue. Using chromatin immunoprecipitation sequencing, we identified two downstream targets of CgCrzA, namely CgCHS5 and CgCHS6, which are critical for growth, cell wall integrity, and pathogenicity as chitin synthase genes.

Conclusions: These findings provide a novel insight into the regulatory mechanism of CgMkk1-CgCrzA-CgChs5/6, which enables response of the cell wall inhibitor CFW and facilitates infectious growth for C. gloeosporioides.

Background: Casein kinase 1α (CK1α), expressed in both ovarian germ and somatic cells, is involved in the initial meiosis and primordial follicle formation of mouse oocytes. Using in vitro and in vivo experiments in this study, we explored the function and mechanism of CK1α in estrogen synthesis in mice ovarian granulosa cells.

Methods: A CK1α knockout (cKO) mouse model, targeted specifically to ovarian granulosa cells (GCs), was employed to establish the influence of CK1α on in vivo estrogen synthesis. The influence of CK1α deficiency on GCs was determined in vivo and in vitro by immunofluorescence analysis and Western blot assay. Transcriptome profiling, differentially expressed genes and gene functional enrichment analyses, and computation protein-protein docking, were further employed to assess the CK1α pathway. Furthermore, wild-type female mice were treated with the CK1α antagonist D4476 to elucidate the CK1α's role in estrogen regulation.

Results: Ovarian GCs CK1α deficiency impaired fertility and superovulation of female mice; also, the average litter size and the estradiol (E₂) level in the serum of cKO female mice were decreased by 57.3% and 87.4% vs. control mice, respectively. This deficiency disrupted the estrous cycle and enhanced the apoptosis in the GCs. We observed that CK1α mediated the secretion of estradiol in mouse ovarian GCs via the cytochrome P450 subfamily 19 member 1 (CYP19A1).

Conclusions: These findings improve the existing understanding of the regulation mechanism of female reproduction and estrogen synthesis.

Trial registration: Not applicable.

Background: Pathologists commonly employ the Ki67 immunohistochemistry labelling index (LI) when deciding appropriate therapeutic strategies for patients with breast cancer. However, despite several attempts at standardizing the Ki67 LI, inter-observer and inter-laboratory bias remain problematic. We developed a flow cytometric assay that employed tissue dissociation, enzymatic treatment and a gating process to analyse Ki67 in formalin-fixed paraffin-embedded (FFPE) breast cancer tissue.

Results: We demonstrated that mechanical homogenizations combined with thrombin treatment can be used to recover efficiently intact single-cell nuclei from FFPE breast cancer tissue. Ki67 in the recovered cell nuclei retained reactivity against the MIB-1 antibody, which has been widely used in clinical settings. Additionally, since the method did not alter the nucleoskeletal structure of tissues, the nuclei of cancer cells can be enriched in data analysis based on differences in size and complexity of nuclei of lymphocytes and normal mammary cells. In a clinical study using the developed protocol, Ki67 positivity was correlated with the Ki67 LI obtained by hot spot analysis by a pathologist in Japan (rho = 0.756, P < 0.0001). The number of cancer cell nuclei subjected to the analysis in our assay was more than twice the number routinely checked by pathologists in clinical settings.

Conclusions: The findings of this study showed the application of this new flow cytometry method could potentially be used to standardize Ki67 assessments in breast cancer.

Background: Grafting with dwarf rootstock is an efficient method to control plant height in fruit production. However, the molecular mechanism remains unclear. Our previous study showed that plants with Prunus mume (mume) rootstock exhibited a considerable reduction in plant height, internode length, and number of nodes compared with Prunus persica (peach) rootstock. The present study aimed to investigate the mechanism behind the regulation of plant height by mume rootstocks through transcriptomic and metabolomic analyses with two grafting combinations, 'Longyan/Mume' and 'Longyan/Peach'.

Results: There was a significant decrease in brassinolide levels in plants that were grafted onto mume rootstocks. Plant hormone signal transduction and brassinolide production metabolism gene expression also changed significantly. Flavonoid levels, amino acid and fatty acid metabolites, and energy metabolism in dwarf plants decreased. There was a notable upregulation of PmLBD3 gene expression in plant specimens that were subjected to grafting onto mume rootstocks. Auxin signalling cues promoted PmARF3 transcription, which directly controlled this upregulation. Through its binding to PmBAS1 and PmSAUR36a gene promoters, PmLBD3 promoted endogenous brassinolide inactivation and inhibited cell proliferation.

Conclusions: Auxin signalling and brassinolide levels are linked by PmLBD3. Our findings showed that PmLBD3 is a key transcription factor that regulates the balance of hormones through the auxin and brassinolide signalling pathways and causes dwarf plants in stone fruits.

Background: Cis-regulatory elements (CREs) are crucial for regulating gene expression, and G-quadruplexes (G4s), as prototypal non-canonical DNA structures, may play a role in this regulation. However, the relationship between G4s and CREs, especially with non-promoter-like functional elements, requires further systematic investigation. We aimed to investigate the associations between G4s and human cCREs (candidate CREs) inferred from the Encyclopedia of DNA Elements (ENCODE) data.

Results: We found that G4s are prominently enriched in most types of cCREs, especially those with promoter-like signatures (PLS). The co-occurrence of CTCF signals with H3K4me3 or H3K27ac signals strengthens the association between cCREs and G4s. Genetic variants in G4s, particularly within their G-runs, exhibit higher regulatory potential and deleterious effects compared to cCREs. The G-runs within G4s near transcriptional start sites (TSSs) are more evolutionarily constrained compared to G-runs in cCREs, while those far from the TSS are relatively less conserved. The presence of G4s is often linked to a more favorable local chromatin environment for the activation and execution of regulatory function of cCREs, potentially attributable to the formation of G4 secondary structures. Finally, we discovered that G4-associated cCREs exhibit widespread activation in a variety of cancers.

Conclusions: Our study suggests that G4s are integral components of human cis-regulatory elements, extending beyond their potential role in promoters. The G4 primary sequences are associated with the localization of CREs, while the G4 structures are linked to the activation of these elements. Therefore, we propose defining G4s as pivotal regulatory elements in the human genome.

Background: Venoms have repeatedly evolved over 100 occasions throughout the animal tree of life, making them excellent systems for exploring convergent evolutionary novelty. Growing evidence supports that venom evolution is predominantly driven by prey or host-related selection pressures, and the expression patterns of venom glands reflect adaptive evolution. However, it remains elusive whether the evolution of expression patterns in venom glands is likewise a convergent evolution driven by their prey/host species.

Results: We utilized parasitoid wasps that had independently adapted to Drosophila hosts as models to investigate the convergent evolution of venom gland transcriptomes in 19 hymenopteran species spanning ~ 200 million years of evolution. Comparative transcriptome analysis reveals that the global expression patterns among the venom glands of Drosophila parasitoid wasps do not achieve higher similarity compared to non-Drosophila parasitoid wasps. Further evolutionary analyses of expression patterns at the single gene, orthogroup, and Gene Ontology (GO) term levels indicate that some orthogroups/GO terms show correlation with the Drosophila parasitoid wasps. However, these groups rarely include genes highly expressed in venom glands or putative venom genes in the Drosophila parasitoid wasps.

Conclusions: Our study suggests that convergent evolution may not play a predominant force shaping gene expression levels in the venom gland of the Drosophila parasitoid wasps, offering novel insights into the co-evolution between venom and prey/host.

Background: Plenty of clinical and biomedical research has unequivocally highlighted the tremendous significance of the human microbiome in relation to human health. Identifying microbes associated with diseases is crucial for early disease diagnosis and advancing precision medicine.

Results: Considering that the information about changes in microbial quantities under fine-grained disease states helps to enhance a comprehensive understanding of the overall data distribution, this study introduces MSignVGAE, a framework for predicting microbe-disease sign associations using signed message propagation. MSignVGAE employs a graph variational autoencoder to model noisy signed association data and extends the multi-scale concept to enhance representation capabilities. A novel strategy for propagating signed message in signed networks addresses heterogeneity and consistency among nodes connected by signed edges. Additionally, we utilize the idea of denoising autoencoder to handle the noise in similarity feature information, which helps overcome biases in the fused similarity data. MSignVGAE represents microbe-disease associations as a heterogeneous graph using similarity information as node features. The multi-class classifier XGBoost is utilized to predict sign associations between diseases and microbes.

Conclusions: MSignVGAE achieves AUROC and AUPR values of 0.9742 and 0.9601, respectively. Case studies on three diseases demonstrate that MSignVGAE can effectively capture a comprehensive distribution of associations by leveraging signed information.