Genome-wide characterization and expression analysis of GATA transcription factors under combination of light wavelengths and drought stress in potato.

GATA is one of the prominent transcription factor families conserved among many organisms in eukaryotes and has different biological roles in many pathways, particularly in light regulation in plants. Although GATA transcription factors (TFs) have been identified in different crop species, their roles in abiotic stress tolerance have not been studied in potato. In this study, we identified 32 GATA TFs in potato (Solanum tuberosum) by in silico analyses, and expression levels of selected six genes were investigated in drought-tolerant (Sante) and sensitive (Agria) cultivars under light, drought, and combined (light + drought) stress conditions. According to the phylogenetic results, StGATA TFs were divided into four main groups (I, II, III, and IV) and different sub-groups in I and II (eight and five, respectively). StGATA genes were uniformly localized to each chromosome with a conserved exon/intron structure. The presence of cis-elements within the StGATA family further supported the possible involvement in abiotic stress tolerance and light response, tissue-specific expression, and hormonal regulation. Additional PPI investigations showed that these networks, especially for Groups I, II, and IV, play a significant role in response to light and drought stress. Six StGATAs were chosen from these groups for expressional profiling, and their expression in both Sante and Agria was mainly downregulated under purple and red lights, drought, and combined stress (blue + drought and purple + drought). The interactomes of selected StGATAs, StGATA3, StGATA24, and StGATA29 were analyzed, and the accessions with GATA motifs were checked for expression. The results showed that the target proteins, cyclin-P3-1, SPX domain-containing protein 1, mitochondrial calcium uniporter protein 2, mitogen-activated protein kinase kinase kinase YODA, and splicing factor 3 B subunit 4-like, mainly play a role in phytochrome-mediated stomatal patterning, development, and activity. Understanding the interactions between drought stress and the light response mechanisms in potato plants is essential. It will eventually be possible to enhance potato resilience to climate change by manipulating the TFs that play a role in these pathways.

Use of Immunoglobulin Y Antibodies: Biosensor-based Diagnostic Systems and Prophylactic and Therapeutic Drug Delivery Systems for Viral Respiratory Diseases.

Respiratory viruses have caused many pandemics from past to present and are among the top global public health problems due to their rate of spread. The recently experienced COVID-19 pandemic has led to an understanding of the importance of rapid diagnostic tests to prevent epidemics and the difficulties of developing new vaccines. On the other hand, the emergence of resistance to existing antiviral drugs during the treatment process poses a major problem for society and global health systems. Therefore, there is a need for new approaches for the diagnosis, prophylaxis, and treatment of existing or new types of respiratory viruses. Immunoglobulin Y antibodies (IgYs) obtained from the yolk of poultry eggs have significant advantages, such as high production volumes, low production costs, and high selectivity, which enable the development of innovative and strategic products. Especially in diagnosing respiratory viruses, antibody-based biosensors in which these antibodies are integrated have the potential to provide superiority in making rapid and accurate diagnosis as a practical diagnostic tool. This review article aims to provide information on using IgY antibodies in diagnostic, prophylactic, and therapeutic applications for respiratory viruses and to provide a perspective for future innovative applications.

Comprehensive investigation of cucumber heat shock proteins under abiotic stress conditions: A multi-omics survey.

Heat-shock proteins (Hsps) are a family of proteins essential in preserving the vitality and functionality of proteins under stress conditions. Cucumber (Cucumis sativus) is a widely grown plant with high nutritional value and is used as a model organism in many studies. This study employed a genomics, transcriptomics, and metabolomics approach to investigate cucumbers' Hsps against abiotic stress conditions. Bioinformatics methods were used to identify six Hsp families in the cucumber genome and to characterize family members. Transcriptomics data from the Sequence Read Archive (SRA) database was also conducted to select CsHsp genes for further study. Real-time PCR was used to evaluate gene expression levels under different stress conditions, revealing that CssHsp-08 was a vital gene for resistance to stress conditions; including drought, salinity, cold, heat stresses, and ABA application. Gas Chromatography-Mass Spectrometry (GC-MS) analysis of plant extracts revealed that amino acids accumulate in leaves under high temperatures and roots under drought, while sucrose accumulates in both tissues under applied most stress factors. The study provides valuable insights into the structure, organization, evolution, and expression profiles of the Hsp family and contributes to a better understanding of plant stress mechanisms. These findings have important implications for developing crops that can withstand environmental stress conditions better.

bHLHDB: A next generation database of basic helix loop helix transcription factors based on deep learning model.

The basic helix loop helix (bHLH) superfamily is a large and diverse protein family that plays a role in various vital functions in nearly all animals and plants. The bHLH proteins form one of the largest families of transcription factors found in plants that act as homo- or heterodimers to regulate the expression of their target genes. The bHLH transcription factor is involved in many aspects of plant development and metabolism, including photomorphogenesis, light signal transduction, secondary metabolism, and stress response. The amount of molecular data has increased dramatically with the development of high-throughput techniques and wide use of bioinformatics techniques. The most efficient way to use this information is to store and analyze the data in a well-organized manner. In this study, all members of the bHLH superfamily in the plant kingdom were used to develop and implement a relational database. We have created a database called bHLHDB (www.bhlhdb.org) for the bHLH family members on which queries can be conducted based on the family or sequences information. The Hidden Markov Model (HMM), which is frequently used by researchers for the analysis of sequences, and the BLAST query were integrated into the database. In addition, the deep learning model was developed to predict the type of TF with only the protein sequence quickly, efficiently, and with 97.54% accuracy and 97.76% precision. We created a unique and next-generation database for bHLH transcription factors and made this database available to the world of science. We believe that the database will be a valuable tool in future studies of the bHLH family.