{"id":15749,"date":"2022-06-24T13:47:43","date_gmt":"2022-06-24T06:47:43","guid":{"rendered":"https:\/\/bgrssb.icgbio.ru\/2022\/?p=15749"},"modified":"2022-09-20T10:32:31","modified_gmt":"2022-09-20T03:32:31","slug":"bacregdb-a-database-of-bacterial-regulatory-elements-with-structural-evidence","status":"publish","type":"post","link":"https:\/\/bgrssb.icgbio.ru\/2022\/2022\/06\/24\/bacregdb-a-database-of-bacterial-regulatory-elements-with-structural-evidence\/","title":{"rendered":"BacRegDB: a database of bacterial regulatory elements with structural evidence"},"content":{"rendered":"<p><em>by Pavel Vychyk | Duvalov E. | Digris A. | Skakun V. | Nikolaichik Y. | Department of Molecular Biology,<\/em><br \/>\n<em>Belarusian State University, Minsk, Belarus | Department of Systems Analysis and Computer Modelling,<\/em><br \/>\n<em>Belarusian State University, Minsk, Belarus<\/em><\/p>\n<p><strong>Motivation and Aim<\/strong>:<br \/>\nMost of the available bacterial genome annotations provide information about ORFs and<br \/>\ntheir products. Adding regulatory elements to the annotation shows which transcription<br \/>\nfactor (TF) controls them and when the genes might be expressed, allows answering basic<br \/>\nquestions and facilitates constructing strains with desired properties.<br \/>\nOur aim in this work was to develop a new TF binding site database permitting reliable<br \/>\nautomated transfer of regulatory information between bacterial genome sequences.<br \/>\n<strong>Methods and Algorithms<\/strong>: We have previously proposed a 3D-structure based strict formal<br \/>\ncriterion for applying regulatory information to any bacterial genome &#8211; CR-tag &#8211; the amino<br \/>\nacid residues of a TF that specifically contacts the nitrogenous bases of the regulatory<br \/>\nelement in genomic DNA.<br \/>\nFor each TF present in RegulonDB, CollecTF, RegpreSize databases, our automated de novo<br \/>\nTFBS inference pipeline was run to collect TF gene-linked operators from all genomes<br \/>\nencoding TFs with the same CR-tag. Hidden Markov models for each motif were built with<br \/>\nthreshold cutoff scores manually set to find known operators with minimum or no false<br \/>\npositive hits.<br \/>\n<strong>Results<\/strong>: The database currently covers only TFBS and has two divisions: the core and the<br \/>\nextended collection. The core includes 237 regulatory elements and has undergone manual<br \/>\ncuration including verification of experimental evidence and determination of threshold<br \/>\nscores for HMM models. Each core record has manually assigned experimental evidence<br \/>\ncodes and is linked to the corresponding literature. The extended collection includes<br \/>\ninformation on over 3000 regulatory elements exported from various databases with<br \/>\nmajority of information coming from RegPrecise.<br \/>\n<strong>Conclusion<\/strong>: The advantage of BacRegBD is the CR-tag concept \u2013 a fingerprint uniquely matching transcription factors with their operators. All regulatory motif records in the<br \/>\ndatabase are associated with a CR-tag and, therefore, can be correctly used to annotate<br \/>\nsimilar elements in any genomes encoding a TF with an identical CR-tag.<\/p>\n<a href=\"https:\/\/bgrssb.icgbio.ru\/2022\/wp-content\/uploads\/sites\/3\/2022\/06\/bgrssb2022-6.pdf\" class=\"pdfemb-viewer\" style=\"\" data-width=\"max\" data-height=\"max\"  data-toolbar=\"bottom\" data-toolbar-fixed=\"off\">bgrssb2022-6<br\/><\/a>\n","protected":false},"excerpt":{"rendered":"<p>by Pavel Vychyk | Duvalov E. | Digris A. | Skakun V. | Nikolaichik Y. | Department of Molecular Biology, Belarusian State University, Minsk, Belarus | Department of Systems Analysis and Computer Modelling, Belarusian State University, Minsk, Belarus Motivation and Aim: Most of the available bacterial genome annotations provide information about ORFs and their products. [&hellip;]<\/p>\n","protected":false},"author":3967,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[5],"tags":[220,171],"_links":{"self":[{"href":"https:\/\/bgrssb.icgbio.ru\/2022\/wp-json\/wp\/v2\/posts\/15749"}],"collection":[{"href":"https:\/\/bgrssb.icgbio.ru\/2022\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/bgrssb.icgbio.ru\/2022\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/bgrssb.icgbio.ru\/2022\/wp-json\/wp\/v2\/users\/3967"}],"replies":[{"embeddable":true,"href":"https:\/\/bgrssb.icgbio.ru\/2022\/wp-json\/wp\/v2\/comments?post=15749"}],"version-history":[{"count":2,"href":"https:\/\/bgrssb.icgbio.ru\/2022\/wp-json\/wp\/v2\/posts\/15749\/revisions"}],"predecessor-version":[{"id":15752,"href":"https:\/\/bgrssb.icgbio.ru\/2022\/wp-json\/wp\/v2\/posts\/15749\/revisions\/15752"}],"wp:attachment":[{"href":"https:\/\/bgrssb.icgbio.ru\/2022\/wp-json\/wp\/v2\/media?parent=15749"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/bgrssb.icgbio.ru\/2022\/wp-json\/wp\/v2\/categories?post=15749"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/bgrssb.icgbio.ru\/2022\/wp-json\/wp\/v2\/tags?post=15749"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}