Bioinformatics and Biology Insights最新文献

Rhoptry protein 18 (ROP18) is a key virulence factor secreted into host cells during the invasion of Toxoplasma gondii (T. gondii) and plays an important role in the pathogenesis of infection. Due to its potential as a vaccine candidate, this study aimed to characterize several properties of the T. gondii ROP18 (TgROP18) protein to support its inclusion in vaccine formulations. Using a range of bioinformatics tools, we investigated its T-cell and B-cell epitopes, physicochemical properties, subcellular localization, transmembrane domains, and tertiary and secondary structures. Our analysis revealed 48 post-translational modification sites in TgROP18. The secondary structure was composed of 4.87% beta-turns, 38.45% random coils, 42.42% alpha helices, and 14.26% extended strands. Several potential T- and B-cell epitopes were identified on ROP18. The Ramachandran plot of both crude and refined models showed that 85.8% and 95.3% of the amino acid residues, respectively, fell within favored regions, indicating energetically stable conformations. Allergenicity and antigenicity assessments indicated that TgROP18 is a nonallergenic, immunogenic protein. Predictions using the C-ImmSim server suggest that TgROP18 can stimulate humoral and cell-mediated immune responses, based on antibody titers and cytokine profiles following antigen administration. These findings provide baseline data for future investigations focused on the potential of TgROP18 in developing therapeutic strategies against toxoplasmosis.

Introduction: Breast cancer (BC) is a heterogeneous disease involving a network of numerous extracellular signal transduction pathways. The phosphoinositide 3-kinase (PI3K)/serine/threonine kinase (Akt)/mechanistic target of rapamycin (mTOR) pathway is crucial for understanding the BC development. Phosphoinositide 3-kinase, phosphatase and tensin homolog (PTEN), mTOR, Akt, 3-phosphoinositide-dependent kinase 1 (PDK1), FoxO1, glycogen synthase kinase 3 (GSK-3), mouse double minute 2 (MDM2), H-Ras, and proapoptotic B-cell lymphoma 2 (BCL-2) family protein (BAD) proteins are key drivers of this pathway and potential therapeutic targets. Pleurotus ostreatus is an edible mushroom that is rich in flavonoids and phenols that can serve as potential inhibitors of proteins in the PI3K/Akt/mTOR pathway.

Aim: This study evaluated the anticancer properties of P ostreatus through a structure-based virtual screening of 22 biologically active compounds present in the mushroom.

Method: Model optimization was carried out on PI3K, PTEN, mTOR, Akt, PDK1, FoxO1, GSK-3, MDM2, H-Ras, and BAD proteins in the PI3K/Akt/mTOR pathway and molecular docking of compounds/control inhibitors in the binding pocket were simulated AutoDock Vina in PyRx. The drug likeness, pharmacokinetic, and pharmacodynamic features of prospective docking leads were all anticipated.

Result: Several potent inhibitors of the selected key driver proteins in PI3K/Akt/mTOR pathway were identified from P ostreatus. Ellagic acid with binding affinities of -8.0, -8.0, -8.1, -8.2, -6.2, and -7.1 kcal/mol on PI3K, Akt, PDK1, GSK-3, MDM2, and BAD, respectively, had better binding affinity compared with their reference drugs. Likewise, apigenin (-7.8 kcal/mol), chrysin (-7.8 kcal/mol), quercetin (-6.4 kcal/mol), and chlorogenic acid (-6.2 kcal/mol) had better binding affinities to PTEN, mTOR, FoxO1, and H-Ras proteins, respectively.

Conclusion: Ellagic acid, apigenin, luteolin, quercetin, chlorogenic acid, chrysin, and naringenin phytochemicals are seen as the better lead molecules due to their ability to strongly bind to the proteins under study in this pathway. Analogs of these compounds can also be designed as potential drugs.

Aims: Antibiotic resistance is currently a major challenge to scientists. Thus, attempts have been made to develop new compounds with antimicrobial activity. In this research, a new antimicrobial peptide with antibacterial activity was isolated from the plant Urtica dioica.

Methods: A new antimicrobial peptide, named cliotide U1, was purified through precipitation with ammonium sulfate and reverse-phase high-performance liquid chromatography. In silico methods analyzed the physicochemical properties of cliotide U1. The properties of the peptide, including antibacterial activity, pH stability, heat stability, cytotoxicity, and hemolytic activity, were also examined.

Findings: The purified peptide was composed of 35 amino acids with a hydrophobicity ratio of 63% and a net charge of + 5. The antibacterial activity of cliotide U1 was observed against gram-negative and gram-positive bacteria with a minimum inhibitory concentration (MIC) of 1 to 4 µM. Cliotide U1 had less than 2% cytotoxic activity at the MIC range against the human embryonic kidney cell line 293 with no clear hemolytic activity. The stability of cliotide U1 was preserved at various temperatures (10-60°C) and pH (6-9).

Conclusion: Our results demonstrated that cliotide U1 had potent antibacterial potential against gram-negative and gram-positive bacteria. Considering its properties, cliotide U1 can be introduced as a novel antibacterial candidate for expanding new therapeutic drugs.

Nucleotide-binding domain leucine-rich repeat (NLR) proteins are a key component of the plant innate immune system. In plant genomes, NLRs exhibit considerable presence/absence variation and sequence diversity. Recent advances in sequencing technologies have made the generation of high-quality novel plant genome assemblies considerably more straightforward. Accurately identifying NLRs from these genomes is a prerequisite for improving our understanding of NLRs and identifying novel sources of disease resistance. While several tools have been developed to predict NLRs, they are hampered by low accuracy, speed, and availability. Here, the NLR annotation tool Resistify is presented. Resistify is an easy-to-use, rapid, and accurate tool to identify and classify NLRs from protein sequences. Applying Resistify to the RefPlantNLR database demonstrates that it can correctly identify NLRs from a diverse range of species. Applying Resistify in combination with tools to identify transposable elements to a panel of Solanaceae genomes reveals a previously undescribed association between NLRs and Helitron transposable elements.

In recent years, several machine learning (ML) approaches have been proposed to predict gene expression signal and chromatin features from the DNA sequence alone. These models are often used to deduce and, to some extent, assess putative new biological insights about gene regulation, and they have led to very interesting advances in regulatory genomics. This article reviews a selection of these methods, ranging from linear models to random forests, kernel methods, and more advanced deep learning models. Specifically, we detail the different techniques and strategies that can be used to extract new gene-regulation hypotheses from these models. Furthermore, because these putative insights need to be validated with wet-lab experiments, we emphasize that it is important to have a measure of confidence associated with the extracted hypotheses. We review the procedures that have been proposed to measure this confidence for the different types of ML models, and we discuss the fact that they do not provide the same kind of information.

Transposable elements (TEs) or transposons are thought to play roles in animal physiological processes, such as germline, early embryonic, and brain development, as well as aging. However, their roles have not been systematically investigated through experimental studies. In this study, we created a catalog of genes directly involved in replication, excision, or integration of transposon-coding DNA, which we refer to as transposon DNA processing genes (TDPGs). Specifically, to bridge the gap to experimental studies, we sought potentially functional TDPGs which maintain intact open reading frames and the amino acids at their catalytic cores on the latest long-read genome assembly of Caenorhabditis elegans, VC2010. Among 52 519 TE loci, we identified 145 potentially functional TDPGs encoded in long terminal repeat elements, long interspersed nuclear elements, terminal inverted repeat elements, Helitrons, and Mavericks/Polintons. Our TDPG catalog, which contains a feasible number of genes, allows for the experimental manipulation of TE mobility in vivo, regardless of whether the TEs are autonomous or non-autonomous, thereby potentially promoting the study of the physiological functions of TE mobility.

Clinical and experimental studies have demonstrated that type 2 diabetes mellitus (T2DM) affects the brain structure and function, in particular the hippocampus, leading to cognitive impairments. However, the molecular mechanisms underlying cognitive deficits induced by T2DM are not fully understood. In this study, we aimed to investigate the effects of T2DM on behavior, the proteome profile in the hippocampus, and the potential molecular pathways involved in the development of cognitive dysfunction in T2DM mice. We found that the diabetic mice exhibited cognitive impairment in the novel object location recognition test and the novel object recognition test. The proteomic analysis revealed that various molecular pathways were involved in this context. These included the upregulation of proteins in the protein synthesis and folding pathway (EIF5A, RSP24, and PPIB), endocytosis and cellular trafficking (VPS24, SNX12, and ARP2/3), cannabinoid receptor interacting (CRIP1), ubiquitination (SKP1), and oxidative stress response (NUDT3). Downregulated proteins were related to mitochondria function (ANT1), neuronal development (ELP1), protein glycosylation (RPN2), and endocytosis (VPS4). Our study shows that T2DM mice exhibit neurocognitive impairment, which is linked to the dysregulation of hippocampal proteins involved in various molecular pathways. These findings contribute to a better understanding of the pathophysiology of T2DM-related cognitive impairment and may identify molecular targets for drug development to treat T2DM-associated cognitive impairment conditions.

Genomic repeats are functionally ubiquitous structural units found in all genomes. Studying these repeats of different origins is essential for understanding the evolution and adaptation of a given organism. These repeating patterns have manifold signatures and structures with varying degrees of homology, making their identification challenging. To address this challenge, we developed a new algorithm and software that can rapidly and accurately detect any repeated sequences de novo with varying degrees of homology in genomic sequences in interspersed or clustered repeats. Numerous forms of repeated sequences and complex patterns can be identified, even for complex sequence variants and implicit or mixed types of repeat blocks. Direct and inverted-repeat elements, perfect and imperfect microsatellite repeats, and any short or long tandem repeat belonging to a wide range of higher-order repeat structures of telomeres or large satellite sequences can be detected. By combining precision and versatility, our tool contributes significantly to elucidating the intricate landscape of genomic repeats.

COVID-19 caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) had an adverse effect globally because it caused a global pandemic with several million deaths. This virus possesses spike protein that is cleaved or activated by Furin-like protease enzymes occurring by mammalian lung or respiratory cells to enter the mammalian body. The addition of the Furin cleavage site in SARS-CoV-2 makes it a more infectious and emerging virus than its ancestor's viruses. Phylogenetic relationships of coronavirus spike proteins have analyzed and mapped Furin recognition motif on the tree using bioinformatics tools such as GTEx, KEGG, GO, NCBI, PolyPhen-2, SNAP2, PANTHER, Hidden Markov Models (Fathmm), Phd-single-nucleotide polymorphism (SNP), I-TASSER, Modpred, Phobius, SIFT, iPTREE-STAB, and PROVEAN. During this study, it has been found that in certain regions, Furin SNPs have some relation with the susceptibility to SARS-CoV-2. Whereas in other regions, the effects are very negligible. Finally, our study demonstrates that Furin SNPs have a strong relationship with susceptibility to SARS-CoV-2. As it helps to cleave the spike protein of the virus, thus it can be targeted to inhibit at a particular site to prevent the SARS-CoV-2 from the entrance into the body.

Salmonella enterica is a gram-negative bacterium that demonstrates a remarkable ability to acquire antibiotic resistance genes (ARGs). The role of the CRISPR-Cas system in influencing antibiotic resistance in S. enterica is still under investigation. This study explores the distribution and impact of CRISPR-Cas systems on antibiotic resistance by analyzing 316 S. enterica genomes. We conducted sequence alignments, phylogenetic analyses, and conservation studies on Cas genes, direct repeats (DRs), and leader sequences. Promoter predictions and RNA secondary structure analyses were also performed. ARGs were identified, and their correlation with Cas gene clusters was evaluated. Our findings revealed that 82.33% of strains possess complete CRISPR-Cas systems, while 17.66% have orphan CRISPRs. We identified 290 distinct DRs, most of which formed stable stem-loop structures, although no promoter regions were detected within the leader sequences. Most spacers were chromosome-targeting, with a smaller proportion homologous to phages and plasmids. Importantly, strains with complete CRISPR-Cas systems showed a higher incidence of ARGs compared with those with orphan or no CRISPR systems. Specifically, the incidence of ARGs was 54.3% higher in strains with complete CRISPR-Cas systems than in strains without CRISPR-Cas systems, and 15.1% higher than in strains with orphan CRISPRs. Spearman's correlation analysis confirmed a statistically significant but weak correlation between the presence of Cas genes and the frequency of ARGs (P-value = 3.892e-06). These results suggest that CRISPR-Cas systems may play a role in the acquisition of ARGs, potentially through mutations under antibiotic pressure. Future studies should investigate mutations, particularly in Cas3-the signature protein of type I CRISPR-Cas systems. In addition, experimental validation, such as culturing S. enterica strains with complete CRISPR-Cas systems under different antibiotic conditions, followed by sequencing to assess the uptake or absence of newly acquired ARGs, would help clarify the potential role of CRISPR-Cas systems in bacterial adaptation to antimicrobial pressures.