A label-free G-quadruplex aptamer/gold nanoparticle-based colorimetric biosensor for rapid detection of bovine viral diarrhea virus genotype 1.

Bovine viral diarrhea virus (BVDV) is the cause of bovine viral diarrhea disease, one of the most economically important livestock diseases worldwide. The majority of BVD disease control programs rely on the detection and then elimination of persistent infection (PI) cattle, as the continuing source of disease. The main purpose of this study was to design and develop an accurate G-quadruplex-based aptasensor for rapid and simple detection of BVDV-1. In this work, we utilized in silico techniques to design a G-quadruplex aptamer specific for the detection of BVDV-1. Also, the rationally designed aptamer was validated experimentally and was used for developing a colorimetric biosensor based on an aptamer-gold nanoparticle system. Firstly, a pool of G-quadruplex forming ssDNA sequences was constructed. Then, based on the stability score in secondary and tertiary structures and molecular docking score, an aptamer (Apt31) was selected. In the experimental part, gold nanoparticles (AuNPs) with an average particle size of 31.7 nm were synthesized and electrostatically linked with the Apt31. The colorimetric test showed that salt-induced color change of AuNPs from red to purple-blue occurs only in the presence of BVDV-Apt31 complex, after 20 min. These results approved the specificity of Apt31 for BVDV. Furthermore, our biosensor could detect the virus at as low as 0.27 copies/ml, which is an acceptable value in comparison to the qPCR method. The specificity of the aptasensor was confirmed through cross-reactivity testing, while its selectivity was confirmed through plasma testing. The sample analysis showed 90% precision and 94% accuracy. It was concluded that the biosensor was adequately sensitive and specific for the detection of BVDV in plasma samples and could be used as a simple and rapid method on the farm.

Renal vein thrombosis due to metastatic germ cell tumor, report of a case with a very rare clinical scenario.

BACKGROUND: Renal metastasis is a rare manifestation of germ cell tumors. Extension of malignant lesions into the renal vein can complicate the scenario. CASE: This report presents a 35-year-old man with primary stage IS NSGCT. Fourteen months after radical orchiectomy he presented with metastasis in the lung, kidney, and para-aortic lymph nodes. He received multiple lines of salvage treatments including chemotherapy and surgery. Intraoperative exploration during radical nephrectomy and retroperitoneal lymphadenectomy revealed intra-renal vein involvement with a prominent teratomatous component. CONCLUSION: Defining the exact extent of malignant lesions, especially endovascular lesions, is very important to clarify how advanced the malignant lesions are. The surgeons must be aware of the risk factors that predict vascular involvement, and therefore, providing intraoperative access to vascular surgery procedures when needed.

Using several pseudo amino acid composition types and different machine learning algorithms to classify and predict archaeal phospholipases.

Phospholipases, as important lipolytic enzymes, have diverse industrial applications. Regarding the stability of extremophilic archaea's proteins in harsh conditions, analyses of unusual features of their proteins are significantly important for their utilization. This research was accomplished to in silico study of archaeal phospholipases' properties and to develop a pioneering method for distinguishing these enzymes from other archaeal enzymes via machine learning algorithms and Chou's pseudo-amino acid composition concept. The non-redundant sequences of archaeal phospholipases were collected. BioSeq-Analysis sever was used with Support Vector Machine (SVM), Random Forests (RF), Covariance Discrimination (CD), and Optimized Evidence-Theoretic K-nearest Neighbor (OET-KNN) as powerful machine learnings algorithms. Also, different Chou's pseudo-amino acid composition modes were performed and then, 5-fold cross-validation was applied to the sequences. Based on our results, the OET-KNN predictor, with 96% accuracy, yields the best performance in SC-PseAAC mode by 5-fold cross-validation. This predictor also achieved very high values of specificity (95%), sensitivity (96%), Matthews's correlation coefficient (0.92), and accuracy (96%). The present investigation yielded a robust anticipatory model for the archaeal phospholipase prediction utilizing the tenets PseAAC and OET-KNN machine learning algorithm.

A staghorn kidney stone or extraskeletal osteosarcoma of the kidney? A case report and literature review.

Extraskeletal osteosarcoma (ESOS) is a very rare entity among renal malignancies. There are few reports of renal ESOS in the database. Renal ESOS was found to have a high rate of local recurrence and distant metastasis. In most reports, the overall survival of patients was less than 1 year. We present a 51-year-old man who presented with gross hematuria and a clinical diagnosis of a staghorn stone in the left kidney. He underwent radical nephrectomy. The pathologic diagnosis of osteosarcoma was evident.

Lithium bioleaching: An emerging approach for the recovery of Li from spent lithium ion batteries.

The rapidly growing demand for lithium has resulted in a sharp increase in its price. This is due to the ubiquitous use of lithium-ion batteries (LIBs) in large-scale energy and transportation sectors as well as portable devices. Recycling of the LIBs for being the supply of critical metals hence becomes environmentally and economically viable. The presently used approaches for the recovery of spent LIBs like pyrometallurgical process can effectively recover nickel, cobalt, and copper, while lithium is usually lost in slag. Bioleaching process as an alternative method of extraction and recovery of valuable metals from the primary and secondary resources has been attracting a large pool of attraction. This method can provide higher recovery yield even for low concentration of metals which makes it viable among conventional methods. The bioleaching process can work with lower operating cost and consumed water and energy along with a simple condition, which produces less hazardous by-products ultimately. Here, we comprehensively review the biological and chemical mechanisms of the bioleaching process with a conclusive discussion to help how to extend the use of bioleaching for lithium extraction and recovery from the spent LIBs with a focus on recovery yields improvement. We elaborate on the three main types of the reported bioleaching with considering effective parameters including temperature, initial pH, pulp density, aeration, and medium and cell nutrients to sustain microorganism activity. Finally, practical challenges and future opportunities of lithium are discussed to inspire future research trends and pilot studies to realize the full potential of lithium recovery using sustainable bioleaching processes to extend a clean energy future.

Analysis and comparison of physiochemical properties, mutations and glycosylation patterns between RNA polymerase and membrane protein of SARS-CoV and SARS-CoV-2.

SARS-CoV-2 is a member of ß-genus of the coronavirus subfamily, alongside the virus that causes SARS (Severe Acute Respiratory Syndrome). As implied by their names, SARS-CoV-2 and SARS-CoV genome sequences have close kinship (about 79% genomic sequence similarity). In the current research, sequence-based physiochemical properties of RNA polymerase and membrane glycoprotein of SARS-CoV-2 and SARS-CoV were compared. In addition, impacts of substitution mutations on stability and glycosylation patterns of these proteins were studied. In comparison of physiochemical features of membrane and RNA polymerase proteins, only instability index of membrane protein was difference between SARS-CoV and SARS-CoV-2. Mutation analysis showed increase in stability of RNA polymerase and decrease in stability of membrane protein in SARS-CoV-2. Glycosylation pattern analysis showed glycosylation enhancement in both membrane and RNA polymerase proteins of SARS-CoV-2 in comparison to SARS-CoV. In conclusion, more glycosylation and stability of SARS-CoV-2 RNA polymerase could be one of the reasons of high pathogenicity property and host immune system evasion of SARS-CoV-2.

A Comparative Analysis of Allergen Proteins between Plants and Animals Using Several Computational Tools and Chou's PseAAC Concept.

BACKGROUND: A large number of allergens are derived from plant and animal proteins. A major challenge for researchers is to study the possible allergenic properties of proteins. The aim of this study was in silico analysis and comparison of several physiochemical and structural features of plant- and animal-derived allergen proteins, as well as classifying these proteins based on Chou's pseudo-amino acid composition (PseAAC) concept combined with bioinformatics algorithms. METHODS: The physiochemical properties and secondary structure of plant and animal allergens were studied. The classification of the sequences was done using the PseAAC concept incorporated with the deep learning algorithm. Conserved motifs of plant and animal proteins were discovered using the MEME tool. B-cell and T-cell epitopes of the proteins were predicted in conserved motifs. Allergenicity and amino acid composition of epitopes were also analyzed via bioinformatics servers. RESULTS: In comparison of physiochemical features of animal and plant allergens, extinction coefficient was different significantly. Secondary structure prediction showed more random coiled structure in plant allergen proteins compared with animal proteins. Classification of proteins based on PseAAC achieved 88.24% accuracy. The amino acid composition study of predicted B- and T-cell epitopes revealed more aliphatic index in plant-derived epitopes. CONCLUSIONS: The results indicated that bioinformatics-based studies could be useful in comparing plant and animal allergens.

Studying the effects of several heat-inactivated bacteria on colon and breast cancer cells.

A great number of researches over the last years are allocated to know cancer reasons, prevention and treatment strategies. Bacterial infections are one of the promoting factors in cancer development. The present study was carried out to study effects of heat-killed bacteria on cancer cell lines MCF7 and HT-29. To this purpose, four bacterial strains including Salmonella typhi, Staphylococcus epidermidis, Escherichia coli and Pseudomonas aeruginosa were assayed. Thermal inactivation method was used to kill the bacteria and preserve the bacterial surface proteins unchangeable. The concentrations of 0.01, 0.1, 0.5 and 1 mg/ml of inactivated bacteria were prepared to evaluate the effects of heat-inactivated bacterial solutions on MCF7 and HT-29 cell lines. MTT assay was used to measure the cell viability of cancer cells treated with different concentration of inactivated bacterial solutions.The MTT assay results after 48 hours showed that the heat-killed bacterial solutions were able to induce the proliferation of both cancer cell lines. In addition, the most cell viability in MCF-7 cell line was seen in samples treated with S. epidermidis, while in HT29 cells, the most one was seen in S. typhi treated samples. It was concluded that bacterial infections are cancer-deteriorating agents, and any species of bacteria is specific to certain cancerous tissue.

A Novel Prokaryotic Green Fluorescent Protein Expression System for Testing Gene Editing Tools Activity Like Zinc Finger Nuclease.

BACKGROUND: Gene editing technology has created a revolution in the field of genome editing. The three of the most famous tools in gene editing technology are zinc finger nucleases (ZFNs), transcription activator-like effector nucleases, clustered regularly interspaced short palindromic repeats (CRISPR), and CRISPR-associated systems. As their predictable nature, it is necessary to assess their efficiency. There are some methods for this purpose, but most of them are time labor and complicated. Here, we introduce a new prokaryotic reporter system, which makes it possible to evaluate the efficiency of gene editing tools faster, cheaper, and simpler than previous methods. MATERIALS AND METHODS: At first, the target sites of a custom ZFN, which is designed against a segment of ampicillin resistance gene, were cloned on both sides of green fluorescent protein (GFP) gene to construct pPRO-GFP. Then pPRO-GFP was transformed into Escherichia coli TOP10F' that contains pZFN (contains expression cassette of a ZFN against ampicillin resistant gene), or p15A-KanaR as a negative control. The transformed bacteria were cultured on three separate media that contained ampicillin, kanamycin, and ampicillin + kanamycin; then the resulted colonies were assessed by flow cytometry. RESULTS: The results of flow cytometry showed a significant difference between the case (bacteria contain pZFN) and control (bacteria contain p15A, KanaR) in MFI (Mean Fluorescence Intensity) (P < 0.0001). CONCLUSION: According to ZFN efficiency, it can bind and cut the target sites, the bilateral cutting can affect the intensity of GFP fluorescence. Our flow cytometry results showed that this ZFN could reduce the intensity of GFP color and colony count of bacteria in media containing amp + kana versus control sample.

New Achievements in Bioinformatics Prediction of Post Translational Modification of Proteins.

Post translational modification (PTM) is one of the critical levels in regulation of gene expression that determines the fate of proteins after translation in eukaryotic cells. Since the detection of PTM sites in proteins is useful for diagnosis and prevention of diseases, numerous web-tool predictors are introduced to predict various types of PTMs. In this paper, an attempt is made to summarize a number of server predictors for the prediction of PTM sites.

Zinc Finger Nuclease: A New Approach to Overcome Beta-Lactam Antibiotic Resistance.

BACKGROUND: The evolution of antibiotic-resistant bacteria (ARB) and antibiotic-resistance genes (ARGs) has been accelerated recently by the indiscriminate application of antibiotics. Antibiotic resistance has challenged the success of medical interventions and therefore is considered a hazardous threat to human health. OBJECTIVES: The present study aimed to describe the use of zinc finger nuclease (ZFN) technology to target and disrupt a plasmid-encoded ß-lactamase, which prevents horizontal gene transfer-mediated evolution of ARBs. MATERIALS AND METHODS: An engineered ZFN was designed to target a specific sequence in the ampicillin resistance gene (amp(R)) of the pTZ57R plasmid. The Escherichia coli bacteria already contained the pZFN kanamycin-resistant (kana(R)) plasmid as the case or the pP15A, kana(R) empty vector as the control, were transformed with the pTZ57R; the ability of the designed ZFN to disrupt the ß-lactamase gene was evaluated with the subsequent disturbed ability of the bacteria to grow on ampicillin (amp) and ampicillin-kanamycin (amp-kana)-containing media. The effect of mild hypothermia on the ZFN gene targeting efficiency was also evaluated. RESULTS: The growth of bacteria in the case group on the amp and amp-kana-containing media was significantly lower compared with the control group at 37°C (P < 0.001). Despite being more efficient in hypothermic conditions at 30°C (P < 0.001), there were no significant associations between the incubation temperature and the ZFN gene targeting efficiency. CONCLUSIONS: Our findings revealed that the ZFN technology could be employed to overcome ampicillin resistance by the targeted disruption of the ampicillin resistance gene, which leads to inactivation of ß-lactam synthesis. Therefore, ZFN technology could be engaged to decrease the antibiotic resistance issue with the construction of a ZFN archive against different ARGs. To tackle the resistance issue at the environmental level, recombinant phages expressing ZFNs against different ARGs could be constructed and released into both hospital and urban wastewater systems.