Dataset Information

Rapid Bioinformatic Identification of Thermostabilizing Mutations.

ABSTRACT: Ex vivo stability is a valuable protein characteristic but is laborious to improve experimentally. In addition to biopharmaceutical and industrial applications, stable protein is important for biochemical and structural studies. Taking advantage of the large number of available genomic sequences and growth temperature data, we present two bioinformatic methods to identify a limited set of amino acids or positions that likely underlie thermostability. Because these methods allow thousands of homologs to be examined in silico, they have the advantage of providing both speed and statistical power. Using these methods, we introduced, via mutation, amino acids from thermoadapted homologs into an exemplar mesophilic membrane protein, and demonstrated significantly increased thermostability while preserving protein activity.

SUBMITTER: Sauer DB

PROVIDER: S-EPMC4601007 | biostudies-other | 2015 Oct

REPOSITORIES: biostudies-other

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Publications

Rapid Bioinformatic Identification of Thermostabilizing Mutations.

Sauer David B DB Karpowich Nathan K NK Song Jin Mei JM Wang Da-Neng DN

Biophysical journal 20151001 7

Ex vivo stability is a valuable protein characteristic but is laborious to improve experimentally. In addition to biopharmaceutical and industrial applications, stable protein is important for biochemical and structural studies. Taking advantage of the large number of available genomic sequences and growth temperature data, we present two bioinformatic methods to identify a limited set of amino acids or positions that likely underlie thermostability. Because these methods allow thousands of homo ...[more]

PMID: 26445442

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Project description:Cell specific gene expression is largely regulated by different combinations of transcription factors that bind cis-elements in the upstream promoter sequence. However, experimental detection of cis-elements is difficult, expensive, and time-consuming. This provides a motivation for developing bioinformatic methods to identify cis-elements that could prioritize future experimental studies. Here, we use motif discovery algorithms to predict transcription factor binding sites involved in regulating the differences between murine rod and cone photoreceptor populations.To identify highly conserved motifs enriched in promoters that drive expression in either rod or cone photoreceptors, we assembled a set of murine rod-specific, cone-specific, and non-photoreceptor background promoter sequences. These sets were used as input to a newly devised motif discovery algorithm called Iterative Alignment/Modular Motif Selection (IAMMS). Using IAMMS, we predicted 34 motifs that may contribute to rod-specific (19 motifs) or cone-specific (15 motifs) expression patterns. Of these, 16 rod- and 12 cone-specific motifs were found in clusters near the transcription start site. New findings include the observation that cone promoters tend to contain TATA boxes, while rod promoters tend to be TATA-less (exempting Rho and Cnga1). Additionally, we identify putative sites for IL-6 effectors (in rods) and RXR family members (in cones) that can explain experimental data showing changes to cell-fate by activating these signaling pathways during rod/cone development. Two of the predicted motifs (NRE and ROP2) have been confirmed experimentally to be involved in cell-specific expression patterns. We provide a full database of predictions as additional data that may contain further valuable information. IAMMS predictions are compared with existing motif discovery algorithms, DME and BioProspector. We find that over 60% of IAMMS predictions are confirmed by at least one other motif discovery algorithm.We predict novel, putative cis-elements enriched in the promoter of rod-specific or cone-specific genes. These are candidate binding sites for transcription factors involved in maintaining functional differences between rod and cone photoreceptor populations.

Dataset Information

Rapid Bioinformatic Identification of Thermostabilizing Mutations.

Publications

Rapid Bioinformatic Identification of Thermostabilizing Mutations.

Similar Datasets

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