Bioinformatics and Biology Insights最新文献

Gene regulatory networks are powerful tools for modeling genetic interactions that control the expression of genes driving cell differentiation, and single-cell sequencing offers a unique opportunity to build these networks with high-resolution genomic data. There are many proposed computational methods to build these networks using single-cell data, and different approaches are used to benchmark these methods. However, a comprehensive discussion specifically focusing on benchmarking approaches is missing. In this article, we lay the GRN terminology, present an overview of common gold-standard studies and data sets, and define the performance metrics for benchmarking network construction methodologies. We also point out the advantages and limitations of different benchmarking approaches, suggest alternative ground truth data sets that can be used for benchmarking, and specify additional considerations in this context.

This study was conducted to assess the possible antidiabetic potential of Conyza bonariensis by employing in vitro as well as in vivo assessments. The dried plant material was extracted in methanol, ethanol, and water. The in vitro results showed that the ethanolic extract (EthCb) was found to have higher antioxidant and antidiabetic potential as compared with the aqueous (AqCb) and methanolic extracts (MthCb) so it was further evaluated in the in vivo trial using a diabetic rat model. Diabetes was induced in male Wistar rats by administering 5% sucrose in drinking water and a cafeteria diet for 8 weeks, followed by nicotinamide and streptozotocin administration. Subsequently, the diabetic rats were divided into 4 groups (n = 8 each): Positive control (no treatment), standard control (Metformin @ 10 mg/kg bw), treatment 1 (C. bonariensis ethanolic extract @ 200 mg/kg bw), and treatment 2 (C. bonariensis ethanolic extract @ 400 mg/kg bw). In addition, there was a negative control group of 8 rats without diabetes induction or treatment. After 21 days of treatment, blood samples were collected from all rats. The serum was evaluated through different means for glucose level, lipid profile, oxidative stress, carbohydrate metabolic enzymes and thyroid hormones. ANOVA was used to evaluate the data statistically. Total oxidant status (TOS) and the serum glucose levels of the streptozotocin-treated rats were reduced significantly (P ⩽ .05) in Conyza bonariensis treated group. Whereas total antioxidant capacity (TAC) along with enzymes like paraoxonase and arylesterase were increased in Conyza bonariensis treated group. The antihyperlipidemic activity was also observed in Conyza bonariensis treated group Interestingly the subnormal levels of T3 and T4 which were observed in the PC group were also normalized in both treatment groups. This study demonstrated the antidiabetic as well as antioxidant activity of different extracts of Conyza bonariensis.

Background and objective: The primary cilium is a small protrusion found on most mammalian cells. It acts as a cellular antenna, being involved in various cell signaling pathways. The length of the primary cilium affects its function. To study the impact of physical or chemical stimuli on cilia, their lengths must be determined easily and reproducibly.

Methods: We have developed and evaluated an open-source R package called detectCilia to detect and measure primary cilia automatically. As a case study to demonstrate the capability of our tool, we compared the influence of 4 different cell culture media compositions on the lengths of primary cilia in human chondrocytes. These media compositions include (1) insulin-transferrin-selenium (ITS); (2) ITS and dexamethasone (Dexa); (3) ITS, Dexa, insulin-like growth factor 1 (IGF-1), and transforming growth factor beta 1 (TGF-β1); and (4) fetal bovine serum (FBS).

Results: The assessment of detectCilia included a comparison with 2 similar tools: ACDC (Automated Cilia Detection in Cells) and CiliaQ. Several differences and advantages of our package make it a valuable addition to these tools. In the case study, we have observed variations in the ciliary lengths associated with using different media compositions.

Conclusions: We conclude that detectCilia can automatically and reproducibly detect and measure primary cilia in confocal microscopy images with low false-positive rates without requiring extensive user interaction.

Compositionally biased regions (CBRs), ie, tracts that are dominated by a subset of residue types, are common features of eukaryotic proteins. These are often found bounded within or almost coterminous with intrinsically disordered or 'natively unfolded' parts. Here, it is investigated how the function of such intrinsically disordered compositionally biased regions (ID-CBRs) is directly linked to their compositional traits, focusing on the well-characterized yeast (Saccharomyces cerevisiae) proteome as a test case. The ID-CBRs that are clustered together using compositional distance are discovered to have clear functional linkages at various levels of diversity. The specific case of the Sup35p and Rnq1p proteins that underlie causally linked prion phenomena ([PSI+] and [RNQ+]) is highlighted. Their prion-forming ID-CBRs are typically clustered very close together indicating some compositional engendering for [RNQ+] seeding of [PSI+] prions. Delving further, ID-CBRs with distinct types of residue patterning such as 'blocking' or relative segregation of residues into homopeptides are found to have significant functional trends. Specific examples of such ID-CBR functional linkages that are discussed are: Q/N-rich ID-CBRs linked to transcriptional coactivation, S-rich to transcription-factor binding, R-rich to DNA-binding, S/E-rich to protein localization, and D-rich linked to chromatin remodelling. These data may be useful in informing experimental hypotheses for proteins containing such regions.

The initial step in pre-mRNA splicing involves formation of a spliceosome commitment complex (CC) or E-complex by factors that serve to bind and mark the exon-intron boundaries that will undergo splicing. The CC component U1 snRNP assembles at the 5'-splice site (ss), whereas SF1, U2AF2, and U2AF1 define the 3'-ss of the intron. A PRP40 protein bridges U1 snRNP with factors at the 3'-ss. To determine how defects in CC components impact cancers, we analyzed human gastrointestinal (GI) cancer patient tissue and clinical data from cBioPortal. cBioPortal datasets were analyzed for CC factor alterations and patient outcomes in GI cancers (bowel, stomach, esophagus, pancreas, and liver). In addition, co-expression datasets were used to determine the splicing targets of the CC. Our analysis found that frequency of genetic changes was low (1%-13%), but when combined with changes in expression levels, there was an overall surprisingly high incidence of CC component (>30%) alterations in GI cancers. Colon cancer patients carrying BRAF driver gene mutations had high incidences of CC alterations (19%-61%), whereas patients with APC, KRAS, or TP53 gene mutations had low (<5%) incidences of CC alterations. Most significantly, patients with mutations in CC genes exhibited a consistent trend of favorable survival rates, indicating that mutations that impair or lower CC component expression favor patient survival. Conversely, patients with high CC expression had worse survival. Pathway analysis indicates that the CC regulates specific metabolic and tumor suppressor pathways. Metabolic pathways involved in cell survival, nutrition, biosynthesis, autophagy, cellular movement (invasion), or immune surveillance pathways correlated with CC factor upregulation, whereas tumor suppressor pathways, which regulate cell proliferation and apoptosis, were inversely correlated with CC factor upregulation. This study demonstrates the versatility of in silico analysis to determine molecular function of large macromolecular complexes such as the spliceosome CC. Furthermore, our analysis indicates that therapeutic lowering of CC levels in colon cancer patients may enhance patient survival.

Deubiquitinating enzymes (DUBs) prevent ubiquitination by eliminating ubiquitin from their substrates. Deubiquitinating enzymes have important roles in a number of cell biology subfields that are highly relevant to diseases like neurodegeneration, cancer, autoimmune disorders, and long-term inflammation. Deubiquitinating enzymes feature a well-defined active site and, for the most part, catalytic cysteine, which makes them appealing targets for small-molecule drug development. Ubiquitin-specific protease 46 (USP46) is a member of the ubiquitin-specific protease family, the largest subfamily of DUBs. Over the past 10 years, some studies have steadily demonstrated the significance of USP46 in several biological processes, although it was identified later and early research progress was modest. Specifically, in the last few years, the carcinogenic properties of USP46 have become more apparent. In the current review, we provide a comprehensive overview of the current knowledge about USP46 including its characteristics, structure, inhibitors, function in diseases, especially in the nervous system, and the correlation of USP46 with cancers.

Background: The ability to predict and comprehend molecular interactions offers significant insights into the biological functions of proteins. The interaction between surface protein 47 of Plasmodium falciparum (Pfs47) and receptor of the protein 47 (P47Rec) has attracted increased attention due to their role in parasite evasion of the mosquito immune system and the concept of geographical coevolution between species. The aims of this study were as follows: to apply a bioinformatics approach to investigate the interaction between Pfs47 and P47Rec proteins and to identify the potential binding sites, protein orientations and receptor specificity sites concerning the geographical origins of the vectors and the parasite.

Methods: Public sequences of the pfs47 and p47rec genes were downloaded and subsequently filtered to predict functional and structural annotations of the Pfs47-P47Rec complex. Phylogenetic analyses of both proteins were carried out. In addition, the p47Rec gene was subjected to sequencing and subsequent analysis in 2 distinct Anopheles species collected in Honduras.

Results: The examination of motifs reveals a significant degree of conservation in pfs47, suggesting that Pfs47 might have undergone recent evolutionary development and adaptation. Structural models and docking analyses supported the theory of selectivity of Plasmodium falciparum strains towards their vectors in diverse geographical regions. A detailed description of the putative interaction between the Pfs47-P47Rec complex is shown.

Conclusions: The study identifies coevolutionary patterns between P47Rec and Pfs47 related to the speciation and geographic dispersion of Anopheles species and Plasmodium falciparum, with Pfs47 evolving more recently than P47Rec. This suggests a link between the parasite's adaptability and existing anopheline species across different regions. P47Rec likely has a cytoplasmic localization due to its lack of membrane attachment elements. However, these findings are based on simulations and require validation through methods like cryo-electron microscopy. A significant limitation is the scarcity of sequences in global databases, which restricts precise interaction modelling. Further research with diverse parasite isolates and anopheline species is recommended to enhance understanding of these proteins' structure and interaction.

Estrogen receptor alpha (ERα) plays a critical role in breast cancer (BC) progression, with endocrine therapy being a key treatment for ERα + BC. However, resistance often arises due to somatic mutations in the ERα ligand-binding domain (LBD). Lasofoxifene, a third-generation selective estrogen receptor modulator, has shown promise against Y537S and D538G mutations. However, the emergence of a novel F404 mutation in patients with pre-existing LBD mutations raises concerns about its impact on lasofoxifene efficacy. This study investigates the impact of the dual Y537S and F404V mutations on lasofoxifene's efficacy. Using molecular dynamics simulations and molecular mechanics/Poisson-Boltzmann surface area (MM-PBSA) free energy calculations, we found that the dual mutation reduces lasofoxifene binding affinity and binding free energy, disrupts crucial protein-ligand interactions, and induces significant conformational changes in the ligand-binding pocket. These alterations are likely due to the loss of the pi-pi stacking interaction in the F404V mutation. These findings suggest a potential reduction in lasofoxifene efficacy due to the dual mutation. Further experimental validation is required to confirm these results and fully understand the impact of dual mutations on lasofoxifene's effectiveness in ERα + metastatic BC.

CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) is a naturally occurring genetic defense system in bacteria and archaea. It is comprised of a series of DNA sequence repeats with spacers derived from previous exposures to plasmid or phage. Further understanding and applications of CRISPR system have revolutionized our capacity for gene or genome editing of prokaryotes and eukaryotes. The CRISPR systems are classified into 3 distinct types: type I, type II, and type III, each of which possesses an associated signature protein, Cas3, Cas9, and Cas10, respectively. As the CRISPR loci originated from earlier independent exposures of foreign genetic elements, it is likely that their associated signature proteins may have evolved rapidly. Also, their functional domain structures might have experienced different selective pressures, and therefore, they have differentially diverged in their amino acid sequences. We employed genomic, phylogenetic, and structure-function constraint analyses to reveal the evolutionary distribution, phylogenetic relationship, and structure-function constraints of Cas3, Cas9, and Cas10 proteins. Results reveal that all 3 Cas-associated proteins are highly represented in the phyla Bacteroidetes, Firmicutes, and Proteobacteria, including both pathogenic and non-pathogenic species. Genomic analysis of homologous proteins demonstrates that the proteins share 30% to 50% amino acid identity; therefore, they are low to moderately conserved and evolved rapidly. Phylogenetic analysis shows that 3 proteins originated monophyletically; however, the evolution rates were different among different branches of the clades. Furthermore, structure-function constraint analysis reveals that both Cas3 and Cas9 proteins experiences low to moderate levels of negative selection, and several protein domains of Cas3 and Cas9 proteins are highly conserved. To the contrary, most protein domains of Cas10 proteins experience neutral or positive selection, which supports rapid genetic divergence and less structure-function constraints.

Single-cell RNA sequencing (scRNA-seq) allows for an unbiased assessment of cellular phenotypes by enabling the extraction of transcriptomic data. An important question in downstream analysis is how to evaluate biological similarities and differences between samples in high dimensional space. This becomes especially complex when there is cellular heterogeneity within the samples. Here, we present scCompare, a computational pipeline for comparison of scRNA-seq data sets. Phenotypic identities from a known data set are transferred onto another data set using correlation-based mapping to average transcriptomic signatures from each cluster of cells' annotated phenotype. Statistically derived lower cutoffs for phenotype inclusivity allow for cells to be unmapped if they are distinct from the known phenotypes, facilitating potential novel cell type detection. In a comparison of our tool using scRNA-seq data sets from human peripheral blood mononuclear cells (PBMCs), we show that scCompare outperforms single-cell variational inference (scVI) in higher precision and sensitivity for most of the cell types. scCompare was used on a cardiomyocyte data set where it confirmed the discovery of a distinct cluster of cells that differed between the 2 protocols for differentiation. Further use of scCompare on cell atlas data sets revealed insights into the cellular heterogeneity underpinning biological diversity between samples. In addition, we used a cell atlas to better understand the effect of key parameters used in the scCompare pipeline. We envision that scCompare will be of value to the research community when comparing large scRNA-seq data sets.