Owlia, P. | bioRxiv Science

bioRxiv2021

Computational analysis of transition temperatures (Tts) of proteins fused to elastin-like polypeptide (ELP): deep fake evaluation of proteins, linkers, and trailers features

The phase transition temperature (Tt) prediction of the Elastin-like polypeptides (ELPs) is not trivial because it is related to complex sets of variables such as composition, sequence length, hydrophobic characterization, hydrophilic characterization, the sequence order in the fused proteins, linkers and trailer constructs. In this paper, two unique quantitative models are presented for the prediction of the Tt of a family of ELPs that could be fused to different proteins, linkers, and trailers. The lack of need to use multiple software, peptide information, such as PDB file, as well as knowing the second and third structures of proteins are the advantages of this model besides its high accuracy and speed. One of our models could predict the Tt values of the fused ELPs by entering the protein, linker, and trailer features with R2=99%. Also, another model is able to predict the Tt value by entering the fused protein feature with R2=96%. For more reliability, our method is enriched by Artificial Intelligence (AI) to generate similar proteins. In this regard, Generative Adversarial Network (GAN) is our AI method to create fake proteins and similar values. The experimental results show that our strategy for prediction of Tt is reliable in large data. Author SummaryThe application of Elastin-like polypeptides (ELPs) as a protein tag is now developed in a variety of biotechnology aspects especially in proteins purification and drug delivery. ELPs application as a protein tag is owed to retain the phase transition behavior when ELPs fused to other proteins, linkers and tags. ELPs undergo the phase transition behavior by changing from soluble phase to insoluble phase above its inverse transition temperature (Tt) within a short time span. This biophysical behavior is usually reversible at the temperature below the Tt. There are few reports for evaluation of the Tt of ELPs types by using the dissimilar equations and algorithms. Our current predictions are the most accurate calculations presented so far by using the protein, linker and trailer effects and the results were evaluated in accordance with the available experimental data. Furthermore, our results also show that our strategy for prediction of Tt is reliable in large data.

bioinformatics↗

bioRxiv2019

Frequency of five Escherichia Coli pathotypes in Iranian adults and children with acute diarrhea

Backgroundknowledge about the distribution of Escherichia Coli (E. coli) pathotypes in Iran is limited to studies with small scale and limited scope. This nation-wide survey aims to provide a more generalizable estimate of pathogenic E. coli distribution in Iran.\n\nMethodsDuring January 2013 and January 2014, stool samples were collected from 1306 acute diarrhea cases of 15 provinces. Culture-positive E. coli samples were tested with PCR for detection of five E. coli pathotypes (STEC, ETEC, EPEC, EAEC, and EIEC). Frequency of these pathotypes was estimated for different provinces, age groups, and months/seasons.\n\nResultsOf 1305 diarrheal samples, 979 were E. coli-positive (prevalence: 75.0%; 95% CI: 72.6, 77.3%). Pathogenic E. coli was detected in 659 diarrheal samples (prevalence: 50.5%; 95% CI: 47.8, 53.2%). STEC and EIEC was the most and the least frequent pathotypes (35.4% and 0.3%, respectively). ETEC (14.0%) and EPEC (13.1%) were the second and the third frequent pathotypes, respectively. EAEC was not highly prevalent (4.3%). Fars and Razavi Khorasan provinces had the highest and lowest frequencies (88.7% and 34.8%, respectively). E. coli pathotypes were more frequent in warmer (i.e., spring and summer) than cooler (i.e., fall and winter) seasons. The highest frequency of pathogenic E. coli was observed in infants and children under 5 years (73% each). There was no association between sex and pathogenic E. coli infection.\n\nConclusionsDiarrheagenic E. coli may be an important cause of acute diarrhea in adults and children in Iran. STEC and ETEC seem to be widespread and show a peak in warmer seasons. This finding could impact the recommended use of STEC and ETEC vaccines during warmer seasons, especially for infants, young children and elderlies. Monitoring the rate of diarrheagenic E. coli infection, E. coli serotypes, and their antibiotic resistance is recommended for evaluations of time-trends and effectiveness of interventions.\n\nAuthor summaryEscherichia coli, also known as E. coli is a bacterium of the genus Escherichia that is normally found in the lower intestine of human. Most E. coli strains are harmless, but some can cause infection in the gastrointestinal tract, causing diarrhea. These pathogenic E. coli strains are classified based on their mechanism of pathogenesis. In this regard, five important E. coli strains include Shiga toxin-producing E. coli (STEC), enterotoxigenic E. coli (ETEC), enteropathogenic E. coli (EPEC), enteroaggregative E. coli (EAEC), and enteroinvasive E. coli (EIEC). In a national survey conducted in Jan 2013 till Jan 2014, we collected 1305 diarrheal samples from 15 (out of 31) provinces of Iran. Of these, 979 samples (75%) were E. coli-positive in the culture test. Molecular tests showed that 659 samples were pathogenic E. coli, suggesting that 50.5% of the diarrhea cases were induced due to pathogenic E. coli infection. The most prevalent pathogenic E. coli strains in Iran were STEC (35.4%) and ETEC (0.3%), and were more commonly detected in warmer seasons, infants, and children less than five years. So, the use of vaccines, especially for STEC and ETEC, during warmer seasons and for infants, young children and elderlies are recommended.

microbiology↗