RESUMEN
Plants are often seen as a potent tool in the recombinant protein production industry. However, unlike bacterial expression, it is not a popular method due to the low yield and difficulty of protein extraction and purification. Therefore, developing a new high efficient and easy to purify platform is crucial. One of the best approaches to make extraction easier is to utilize the Extensin Signal peptide (EXT) to translocate the recombinant protein to the outside of the cell, along with incorporating an Elastin-like polypeptide tag (ELP) to enhance purification and accumulation rates. In this research, we transiently expressed Shigella dysenteriae's IpaDSTxB fused to both NtEXT and ELP in both Nicotiana tabacum and Medicago sativa. Our results demonstrated that N. tabacum, with an average yield of 6.39 ng/µg TSP, outperforms M. sativa, which had an average yield of 3.58 ng/µg TSP. On the other hand, analyzing NtEXT signal peptide indicated that merging EXT to the constructs facilitates translocation of IpaDSTxB to the apoplast by 78.4% and 65.9% in N. tabacum and M. sativa, respectively. Conversely, the mean level for constructs without EXT was below 25% for both plants. Furthermore, investigation into the orientation of ELP showed that merging it to the C-terminal of IpaDSTxB leads to a higher accumulation rate in both N. tabacum and M. sativa by 1.39 and 1.28 times, respectively. It also facilitates purification rate by over 70% in comparison to 20% of the 6His tag. The results show a highly efficient and easy to purify platform for the expression of heterologous proteins in plant.
Asunto(s)
Proteínas Bacterianas , Elastina , Nicotiana , Señales de Clasificación de Proteína , Proteínas Recombinantes de Fusión , Shigella dysenteriae , Nicotiana/genética , Nicotiana/metabolismo , Señales de Clasificación de Proteína/genética , Proteínas Bacterianas/genética , Proteínas Bacterianas/química , Proteínas Bacterianas/aislamiento & purificación , Proteínas Bacterianas/biosíntesis , Proteínas Bacterianas/metabolismo , Elastina/genética , Elastina/química , Elastina/metabolismo , Proteínas Recombinantes de Fusión/genética , Proteínas Recombinantes de Fusión/química , Proteínas Recombinantes de Fusión/aislamiento & purificación , Proteínas Recombinantes de Fusión/biosíntesis , Proteínas Recombinantes de Fusión/metabolismo , Shigella dysenteriae/genética , Medicago sativa/genética , Medicago sativa/metabolismo , Medicago sativa/química , Medicago sativa/microbiología , Expresión Génica , Proteínas de Plantas/genética , Proteínas de Plantas/biosíntesis , Proteínas de Plantas/aislamiento & purificación , Proteínas de Plantas/química , Proteínas de Plantas/metabolismo , Glicoproteínas/genética , Glicoproteínas/química , Glicoproteínas/aislamiento & purificación , Glicoproteínas/biosíntesis , Glicoproteínas/metabolismo , Polipéptidos Similares a ElastinaRESUMEN
Shigella dysenteriae, is a Gram-negative bacterium that emerged as the second most significant cause of bacillary dysentery. Antibiotic treatment is vital in lowering Shigella infection rates, yet the growing global resistance to broad-spectrum antibiotics poses a significant challenge. The persistent multidrug resistance of S. dysenteriae complicates its management and control. Hence, there is an urgent requirement to discover novel therapeutic targets and potent medications to prevent and treat this disease. Therefore, the integration of bioinformatics methods such as subtractive and comparative analysis provides a pathway to compute the pan-genome of S. dysenteriae. In our study, we analysed a dataset comprising 27 whole genomes. The S. dysenteriae strain SD197 was used as the reference for determining the core genome. Initially, our focus was directed towards the identification of the proteome of the core genome. Moreover, several filters were applied to the core genome, including assessments for non-host homology, protein essentiality, and virulence, in order to prioritize potential drug targets. Among these targets were Integration host factor subunit alpha and Tyrosine recombinase XerC. Furthermore, four drug-like compounds showing potential inhibitory effects against both target proteins were identified. Subsequently, molecular docking analysis was conducted involving these targets and the compounds. This initial study provides the list of novel targets against S. dysenteriae. Conclusively, future in vitro investigations could validate our in-silico findings and uncover potential therapeutic drugs for combating bacillary dysentery infection.
Asunto(s)
Antibacterianos , Simulación por Computador , Disentería Bacilar , Simulación del Acoplamiento Molecular , Shigella dysenteriae , Shigella dysenteriae/efectos de los fármacos , Shigella dysenteriae/genética , Shigella dysenteriae/patogenicidad , Humanos , Antibacterianos/farmacología , Disentería Bacilar/microbiología , Disentería Bacilar/tratamiento farmacológico , Genoma Bacteriano , Proteínas Bacterianas/genética , Proteínas Bacterianas/metabolismo , Biología Computacional/métodosRESUMEN
Shiga toxin producing bacteria are potential causes of serious human disease such as hemorrhagic colitis, severe inflammations of ileocolonic regions of gastrointestinal tract, thrombocytopenia, septicemia, malignant disorders in urinary ducts, hemolytic uremic syndrome (HUS) Shiga toxin 1 (stx1), shiga toxin 2 (stx2), or a combination of both are responsible for most clinical symptoms of these diseases. A lot of methods have been developed so far to detect shiga toxins such as cell culture, ELISA, and RFPLA, but due to high costs and labor time in addition to low sensitivity, they have not received much attention. In this study, PCR-ELISA method was used to detect genes encoding shiga toxins 1 and 2 (stx1 and stx2). To detect stx1 and stx2 genes, two primer pairs were designed for Multiplex-PCR then PCR-ELISA. PCR products (490 and 275, respectively) were subsequently verified by sequencing. Sensitivity and specificity of PCR-ELISA method were determined by using genome serial dilution and Enterobacteria strains. PCR-ELISA method used in this study proved to be a rapid and precise approach to detect different types of shiga toxins and can be used to detect bacterial genes encoding shiga toxins.