One hundred and twenty-eight Bacillus thuringiensis isolates from fields of different ecological regions of Iran were collected to study the distribution and diversity of Dipteran-specific cry and cyt genes. The percentage of samples with Bt showed significant differences between different regions and also between different fields. The most Bt frequency was observed in the soil samples collected from Caspianic zone (7%) and soils of cotton (17%). Characterization of isolates was based on morphological characteristics of crystals, plasmid profiles and protein band patterns as well as PCR analysis using general and specific primers for 22 different cry and cyt genes encoding proteins active against mosquitoes. Thirty-eight different cry gene profiles were detected in this collection. Several of them were found to be different from all previously published profiles and none of the previous researches reported these numbers of profiles. Strains containing cry2-type genes were the most abundant and represent 57.1% of the isolates. Strains harboring cry24 and cry10 genes were also highly abundant (38.7 and 32.8%, respectively). cry11, cry4, cry17, cry19, cry21, cry29, cyt1, and cry9 genes were less abundant, found in 25.7, 14.3, 11.4, 1.4, 4.3, 1.4, and 10% of the strains, respectively. Among the cry2 gene containing isolates, 37.5% strains harbored cry2Aa, 55% cry2Ab, 2.5% cry2Ac, and 5% other or novel cry2-type genes. Among the cry4 gene containing isolates, 0% strains harbored cry4A, 60% cry4B, and 40% cry4C, cry4D or novel cry4 type genes. Finally, based on crystal morphology, protein patterns and PCR, 21 strains were selected as potentially high Dipteran-active for bioassays. Also our results showed that some of the isolates may harbor minimum a putative novel cry gene.

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Deaths from tuberculosis have long gripped people and threatened human health. The need for new drug compounds are critically sensed by medical scientists and practitioners due to the emergence of new strains and the slow rate of discovering novel medicines for this disease. Since plants are a rich source of diverse drug compounds, they are among the best choices to achieve new ones. The study of all plants or their compounds is an almost impossible scenario; hence bio/cheminformatics methodology can be used to reduce time and cost spent in drug discovery. For this purpose, we made several databases of anti-mycobacterial plant compounds and further found filter criteria which were able to describe more predicted bioactive compounds by the established algorithm. Also, we present the survey of the developed resource by using bio/cheminformatics tools. The presence of several anti-mycobacterial compounds in the predicted algorithm and introduction of new active compounds represent the high potential of this method. In addition, the general profile of such bioactive molecules is pinpointed using molecular descriptors and cheminformatics approach.