While the field of computational protein design has witnessed amazing progression in recent years, folding properties still constitute a significant barrier towards designing new and larger proteins. In order to assess and improve folding properties of designed proteins, we have developed a genetics-based folding assay and selection system based on the essential enzyme, orotate phosphoribosyl transferase from Escherichia coli. This system allows for both screening of candidate designs with good folding properties and genetic selection of improved designs. Thus, we identified single amino acid substitutions in two failed designs that rescued poorly folding and unstable proteins. Furthermore, when these substitutions were transferred into a well-structured design featuring a complex folding profile, the resulting protein exhibited native-like cooperative folding with significantly improved stability. In protein design, a single amino acid can make the difference between folding and misfolding, and this approach provides a useful new platform to identify and improve candidate designs.
Intrahippocampal injections of aggregated amyloid-beta (Abeta)1-42 in rats result in memory impairment and in reduction of hippocampal 5-HT2A receptor levels. In order to investigate how changes in 5-HT2A levels and functionality relate to the progressive accumulation of Abeta protein, we studied 5-HT2A receptor regulation in double transgenic AbetaPPswe/PS1dE9 mice which display excess production of Abeta and age-dependent increase in amyloid plaques. Three different age-groups, 4-month-old, 8- month-old, and 11-month-old were included in the study. [3H]-MDL100907, [3H]-escitalopram, and [11C]-PIB autoradiography was performed for measuring 5-HT2A receptor, serotonin transporter (SERT), and Abeta plaque levels in medial prefrontal cortex (mPFC), prefrontal cortex (PFC), frontoparietal cortex (FPC), dorsal and ventral hippocampus, and somatosensory cortex. To investigate 5-HT2A receptor functionality, animals were treated with the 5-HT2A receptor agonist DOI and head-twitch response (HTR) subsequently recorded. Expression level of the immediate early gene c-fos was measured by in situ hybridization. We found that the age-related increase in Abeta plaque burden was accompanied by a significant decrease in 5-HT2A receptor binding in mPFC in the 11-month-old group. The changes in 5-HT2A receptor binding correlated negatively with [11C]-PIB binding and were not accompanied by decreases in SERT binding. Correspondingly, 11-month-old transgenic mice showed diminished DOI-induced HTR and reduced increase in expression of c-fos mRNA in mPFC and FPC. These observations point towards a direct association between Abeta accumulation and changes in 5-HT2A receptor expression that is independent of upstream changes in the serotonergic system.
Diabetes is a diverse and complex disease, with considerable variation in phenotypic manifestation and severity. This variation hampers the study of etiological differences and reduces the statistical power of analyses of associations to genetics, treatment outcomes, and complications. We address these issues through deep, fine-grained phenotypic stratification of a diabetes cohort. Text mining the electronic health records of 14,017 patients, we matched two controlled vocabularies (ICD-10 and a custom vocabulary developed at the clinical center Steno Diabetes Center Copenhagen) to clinical narratives spanning a 19 year period. The two matched vocabularies comprise over 20,000 medical terms describing symptoms, other diagnoses, and lifestyle factors. The cohort is genetically homogeneous (Caucasian diabetes patients from Denmark) so the resulting stratification is not driven by ethnic differences, but rather by inherently dissimilar progression patterns and lifestyle related risk factors. Using unsupervised Markov clustering, we defined 71 clusters of at least 50 individuals within the diabetes spectrum. The clusters display both distinct and shared longitudinal glycemic dysregulation patterns, temporal co-occurrences of comorbidities, and associations to single nucleotide polymorphisms in or near genes relevant for diabetes comorbidities.
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