Mitogen-activated protein kinase (MAPK) cascades are the universal signal transduction networks that regulate cell growth and development, hormone signaling, and other environmental stresses. However, their essential contribution to plant tolerance is very little known in the potato (Solanum tuberosum) plant. The current study carried out a genome-wide study of StMAPK and provided a deep insight using bioinformatics tools. In addition, the relative expression of StMAPKs was also assessed in different plant tissues. The similarity search results identified a total of 22 StMAPK genes in the potato genome. The sequence alignment also showed conserved motif TEY/TDY in most StMAPKs with conserved docking LHDXXEP sites. The phylogenetic analysis divided all 22 StMAPK genes into five groups, i.e., A, B, C, D, and E, showing some common structural motifs. In addition, most of the StMAPKs were found in a cluster form at the terminal of chromosomes. The promoter analysis predicted several stress-responsive Cis-acting regulatory elements in StMAPK genes. Gene duplication under selection pressure also indicated several purifying and positive selections in StMAPK genes. In potato, StMAPK2, StMAPK6, and StMAPK19 showed a high expression in response to heat stress. Under ABA and IAA treatment, the expression of the total 20 StMAPK genes revealed that ABA and IAA played an essential role in this defense process. The expression profiling and real-time qPCR (RT-qPCR) exhibited their high expression in roots and stems compared to leaves. These results deliver primary data for functional analysis and provide reference data for other important crops.

Endolysins, phage-derived enzymes capable of lysing bacterial cell walls, hold significant promise as novel antimicrobials against resistant Gram-positive and Gram-negative pathogens. In this study, we undertook an integrative approach combining extensive in silico analyses and experimental validation to characterize the novel endolysin LysPALS22. Initially, sixteen endolysin sequences were selected based on documented lytic activity and enzymatic diversity, and subjected to multiple sequence alignment and phylogenetic analysis, which revealed highly conserved catalytic and binding domains, particularly localized to the N-terminal region, underscoring their functional importance. Building upon these sequence insights, we generated three-dimensional structural models using Swiss-Model, EBI-EMBL, and AlphaFold Colab, where comparative evaluation via Ramachandran plots and ERRAT scores identified the Swiss-Model prediction as the highest quality structure, featuring over 90% residues in favored conformations and superior atomic interaction profiles. Leveraging this validated model, molecular docking studies were conducted in PyRx with AutoDock Vina, performing blind docking of key peptidoglycan-derived ligands such as N-Acetylmuramic Acid-L-Alanine, which exhibited the strongest binding affinity (−7.3 kcal/mol), with stable hydrogen bonding to catalytic residues ASP46 and TYR61, indicating precise substrate recognition. Visualization of docking poses using Discovery Studio further confirmed critical hydrophobic and polar interactions stabilizing ligand binding. Subsequent molecular dynamics simulations validated the stability of the LysPALS22–NAM-LA complex, showing minimal structural fluctuations, persistent hydrogen bonding, and favorable interaction energies throughout the 100 ns trajectory. Parallel to computational analyses, LysPALS22 was heterologously expressed in Escherichia coli (E. coli) and Pichia pastoris (P. pastoris), where SDS-PAGE and bicinchoninic acid assays validated successful protein production; notably, the P. pastoris-expressed enzyme displayed an increased molecular weight (~45 kDa) consistent with glycosylation, and achieved higher volumetric yields (1.56 ± 0.31 mg/mL) compared to E. coli (1.31 ± 0.16 mg/mL), reflecting advantages of yeast expression for large-scale production. Collectively, these findings provide a robust structural and functional foundation for LysPALS22, highlighting its conserved enzymatic features, specific ligand interactions, and successful recombinant expression, thereby setting the stage for future in vivo antimicrobial efficacy studies and rational engineering efforts aimed at combating multidrug-resistant Gram-negative infections.

Purpose: The gut microbiome, defined as the community of microorganisms residing in the digestive tract, is believed to play a crucial role in the development of neurological disorders, including schizophrenia. Design: Recent research indicates that individuals with schizophrenia have altered gut microbiomes, characterized by reduced levels of beneficial bacteria such as Bifidobacterium and Lactobacillus, and increased levels of potentially harmful bacteria, such as Proteobacteria. Findings: Furthermore, studies show that the communication between the gut and the brain, known as the gut-brain axis, is disrupted in individuals with schizophrenia. While the exact mechanisms underlying the association between the gut microbiome and schizophrenia are not yet fully understood, researchers suggest that changes in the gut microbiome may affect the immune system and neurotransmitters, which in turn contribute to the development of the disorder Practical Implication: Targeting the gut microbiome through interventions like probiotics and the Mediterranean diet may offer a promising therapeutic approach for individuals with schizophrenia. Conclusion: However, more research is needed to fully comprehend the complex interplay between the gut microbiome and schizophrenia, including the specific mechanisms by which the gut microbiome contributes to the development of the disorder. Keywords: Gut Microbiome. Microbiota, Immune cells, Schizophrenia

Meat serves as a prime medium for the growth of foodborne pathogens due to its rich protein content and high water activity, contributing significantly to the global burden of foodborne illnesses. This review synthesizes current advances in meat-borne bacterial pathogen detection with particular emphasis on emerging artificial intelligence (AI)-enabled applications. Major pathogens of concern, including Salmonella, Listeria monocytogenes, Escherichia coli, Campylobacter, Clostridium, and Staphylococcus aureus, are examined in relation to their relevance across the meat supply chain. Recent progress in biosensors (clustered regularly interspaced short palindromic repeats), CRISPR-based assays, isothermal amplification, and metagenomics is evaluated alongside the growing role of AI in automating signal interpretation, enhancing image-based diagnostics, and supporting early contamination prediction. AI-based systems have proved 96.4–104% recovery and 100% bacterial capture ability. Embedding AI methods in a wet lab demands technical and logical modeling, as well as learning and calibration decorum. Nonetheless, AI readiness and full-scale application for meat-borne pathogens surveillance are on the way. Furthermore, additional focus is aligned on meat-borne bacterial pathogen genomic databases, i.e., (NCBI Pathogen Detection, EnteroBase, VFDB, ComBase, and GenBank), which serve as critical training resources for AI models for outbreak tracking, virulence profiling, and antimicrobial resistance (AMR) prediction. By integrating molecular methods, genomic surveillance, and AI-driven analytics, this review presents a framework for strengthening meat safety systems. This will improve early detection capabilities and support data-driven public health interventions in the future.

SARS-CoV-2 has been found to be the leading cause of the outbreak of coronavirus disease 2019 (COVID-19) globally. The disease is triggered by a new form of coronavirus and is characterized by acute respiratory distress syndrome (ARDS) or some primary chills. It was originated from a wet market in Wuhan, China and has engulfed 6.39 million lives globally uptillseptember-2022. Historically, the world has witnessed many noticeable epidemics in the form of, SARS-CoV (2002 to 2003), H1N1 influenza in 2009, and the most recent Middle East Respiratory Syndrome coronavirus (MERS-CoV), which erupted in Saudi Arabia in 2012. Different people get this disease with different symptoms including mild to severe illness. The molecular and cellular basis of SARS-CoV-2 pathogenesis gives us in-depth mechanisms involved. Experimental investigations have elaborated bats as the primary host for viral the transmission behind COVID-19. Moreover, the anatomy of the virus revealed its RNA based on the genome, which makes its therapeutic interventions more challenging. By the involvement of pre-analytic, analytic, and post-analytical strategies, patients with acute or chronic pneumonia can be distinguished as infected or not. Artificial intelligence has embarked significant importance in the course of viral detection based on computer algorithms. Furthermore, chemical or immune-based therapies were examined for finding a permanent solution to this epidemic issue. This review would cover every emerging aspect of pathogenesis, diagnosis, management, and the latest therapeutic interventions in the course of COVID-19 treatment. By giving rapidly evolving knowledge about this virus, readers are urged to update themselves regularly.