Bioremediation of Chromium-Contaminated Groundwater Using Chromate Reductase from <i>Pseudomonas putida</i>: An <i>In Silico</i> Approach

Chromium is a toxic heavy metal abundantly present in the environment, specifically in groundwater. The groundwater in Saudi Arabia was assessed for heavy metal presence; chromium was detected at a high concentration in Madinah. Many researchers have used various bioprocesses over the last few decades to mitigate Cr(VI) toxicity. The genus Pseudomonas member Pseudomonas putida is widely dispersed in the natural environment. P. putida is chromate-resistant and has a high chromate reduction rate. Bioremediation procedures can eradicate the most potently toxic metal, Cr(VI), in water, air, and soil. Chromate reductase (ChrR) is a bacterial enzyme from P. putida that can be utilized in bioremediation to remove chromate from the environment in a cost-effective and environmentally safe approach. To comprehend the role of ChrR in reducing Cr(VI) to Cr(III), a thorough sequence analysis was followed by constructing models for wild-type and mutants by applying several homology modeling techniques. The protein structure quality of the generated models was evaluated, and the best model was adopted for further optimization by employing an energy minimization technique. Molecular docking studies investigated the intra-molecular interaction between wild-type and mutant ChrR and Cr(VI). Our study is a novel method for determining the 3D structure and interaction of ChrR with Cr(VI) to convert it to a less hazardous form (III). Additionally, it provides stable mutants: Arg83Trp, Gly124Ile, and His127Trp, with a high binding affinity for Cr(VI), which can be considered for protein engineering to produce stable and efficacious enzymes to reduce Cr(VI) to a less toxic form

An In Silico Bioremediation Study to Identify Essential Residues of Metallothionein Enhancing the Bioaccumulation of Heavy Metals in <i>Pseudomonas aeruginosa</i>

Microorganisms are ubiquitously present in the environment and exert significant influence on numerous natural phenomena. The soil and groundwater systems, precipitation, and effluent outfalls from factories, refineries, and waste treatment facilities are all sources of heavy metal contamination. For example, Madinah, Saudi Arabia, has alarmingly high levels of lead and cadmium. The non-essential minerals cadmium (Cd) and lead (Pb) have been linked to damage to vital organs. Bioremediation is an essential component in the process of cleaning up polluted soil and water where biological agents such as bacteria are used to remove the contaminants. It is demonstrated that Pseudomonas aeruginosa (P. aeruginosa) isolated from activated sludge was able to remove Cd and Pb from water. The protein sequence of metallothionein from P. aeruginosa was retrieved to explore it for physicoparameters, orthologs, domain, family, motifs, and conserved residues. The homology structure was generated, and models were validated. Docking of the best model with the heavy metals was carried out to inspect the intramolecular interactions. The target protein was found to belong to the “metallothionein_pro” family, containing six motifs, and showed a close orthologous relationship with other heavy metal-resistant bacteria. The best model was generated by Phyre2. In this study, three key residues of metallothionein were identified that participate in heavy metal (Pb and Cd) binding, viz., Ala33, Ser34, and Glu59. In addition, the study provides an essential basis to explore protein engineering for the optimum use of metallothionein protein to reduce/remove heavy metals from the environment

A Prospective Cohort Study (OUTSTRIP-COVID) on Functional and Spirometry Outcomes in COVID-19 ICU Survivors at 3 Months

Purpose: COVID-19 pandemic resulted in a significant number of critical care admissions secondary to severe pneumonia and acute respiratory distress syndrome. We evaluated the short-, medium-and long-term outcomes of lung function and quality of life in this prospective cohort study and reported the outcomes at 7 weeks and 3 months from discharge from intensive care unit. Methods: A prospective cohort study of ICU survivors with COVID-19 was conducted from August 2020 to May 2021 to evaluate baseline demographic and clinical variables as well as determine lung function, exercise capacity, and health-related quality of life (HRQOL) using spirometry and 6-minute walk test (6MWT) conducted in accordance with American Thoracic Society standards, and SF-36 (Rand), respectively. SF-36 is a generic 36 question standardized health survey. Descriptive and inferential statistics (alpha = 0.05) were used to analyse the data. Results: At baseline, 100 participants were enrolled in the study of whom 76 followed up at 3 months. Majority of the patients were male (83%), Asians (84%) and less than 60 years of age (91%). HRQOL showed significant improvement in all domains of SF-36, except in emotional wellbeing. Spirometry variables also showed significant improvement in all variables over time with greatest improvement in percentage predicted Forced expiratory volume 1 (79% vs 88% p < 0.001). 6MWT showed significant improvement in variables of walk distance, dyspnea, and fatigue with greatest improvement in change in oxygen saturation (3% vs 1.44% p < 0.001). Intubation status did not impact the changes in SF-36, spirometry or 6MWT variables. Conclusion: Our findings suggest that ICU survivors of COVID-19 have significant improvement in their lung function, exercise capacity and HRQOL within 3 months of ICU discharge regardless of intubation status

Clinical, Radiological, and Outcome Characteristics of Acute Pulmonary Embolism: A 5-year Experience from an Academic Tertiary Center

Background: Acute pulmonary embolism (PE) is a common and potentially life-threatening condition. This comprehensive study from a Gulf Cooperation Council (GCC) country aimed to evaluate the clinical, radiological, and outcome characteristics associated with acute PE. Methods: This retrospective observational study analyzed data of patients with confirmed acute PE who were admitted to the largest academic tertiary center in the State of Qatar from January 1, 2014, to December 31, 2018. Data on the clinical presentation, radiologic, and echocardiographic findings, as well as outcomes were collected. Results: A total of 436 patients were diagnosed with acute PE during the study period (male, 53%). Approximately 56% of the patients were, 50 years old at presentation, with a median age of 47 years. In approximately 69% of cases, the PE occurred outside the hospital. The main associated comorbidities were obesity (34.6%), hypertension (29.4%), and diabetes (25%). Immobilization (25.9%) and recent surgery (20.6%) were the most common risk factors. The most frequent presenting symptom was dyspnea (39.5%), and the most frequent signs were tachycardia (49.8%) and tachypnea (45%). Cardiac arrest was the initial presentation in 2.2% of cases. Chest X-ray findings were normal in 41%. On computed tomography pulmonary angiography (CTPA), 41.3% of the patients had segmental PE, 37.1% had central PE, and 64.1% had bilateral PE. The main electrocardiographic (ECG) abnormality was sinus tachycardia (98%). In patients who underwent echocardiography, right ventricular (RV) enlargement was the main echocardiographic finding (36.4%). Low-, intermediate-, and high-risk PE constituted 49.8%, 31.4%, and 18.8% of the cases, respectively. Thrombolysis was prescribed in 8.3% of the total and 24.4% of the high-risk PE cases. Complications of PE and its treatment (from admission up to 6 months post-discharge) included minor bleeding (14%), major bleeding (5%), PE recurrence (4.8%), and chronic thromboembolic pulmonary hypertension (CTEPH) (5%). A total of 15 (3.4%) patients died from PE. Conclusions: Acute PE can manifest with complex and variable clinical and radiological syndromes. Striking findings in this study are the younger age of acute PE occurrence and the low PE-related mortality rate.The publication of this article was funded by the Medical Research Center at Hamad Medical Corporation

The Stroke RiskometerTM App: Validation of a data collection tool and stroke risk predictor

Background: The greatest potential to reduce the burden of stroke is by primary prevention of first-ever stroke, which constitutes three quarters of all stroke. In addition to population-wide prevention strategies (the 'mass' approach), the 'high risk' approach aims to identify individuals at risk of stroke and to modify their risk factors, and risk, accordingly. Current methods of assessing and modifying stroke risk are difficult to access and implement by the general population, amongst whom most future strokes will arise. To help reduce the burden of stroke on individuals and the population a new app, the Stroke RiskometerTM, has been developed. We aim to explore the validity of the app for predicting the risk of stroke compared with current best methods. Methods: 752 stroke outcomes from a sample of 9501 individuals across three countries (New Zealand, Russia and the Netherlands) were utilized to investigate the performance of a novel stroke risk prediction tool algorithm (Stroke RiskometerTM) compared with two established stroke risk score prediction algorithms (Framingham Stroke Risk Score [FSRS] and QStroke). We calculated the receiver operating characteristics (ROC) curves and area under the ROC curve (AUROC) with 95% confidence intervals, Harrels C-statistic and D-statistics for measure of discrimination, R2 statistics to indicate level of variability accounted for by each prediction algorithm, the Hosmer-Lemeshow statistic for calibration, and the sensitivity and specificity of each algorithm. Results: The Stroke RiskometerTM performed well against the FSRS five-year AUROC for both males (FSRS=75·0% (95% CI 72·3%-77·6%), Stroke RiskometerTM=74·0(95% CI 71·3%-76·7%) and females [FSRS=70·3% (95% CI 67·9%-72·8%, Stroke RiskometerTM=71·5% (95% CI 69·0%-73·9%)], and better than QStroke [males - 59·7% (95% CI 57·3%-62·0%) and comparable to females=71·1% (95% CI 69·0%-73·1%)]. Discriminative ability of all algorithms was low (C-statistic ranging from 0·51-0·56, D-statistic ranging from 0·01-0·12). Hosmer-Lemeshow illustrated that all of the predicted risk scores were not well calibrated with the observed event data (P<0·006). Conclusions: The Stroke RiskometerTM is comparable in performance for stroke prediction with FSRS and QStroke. All three algorithms performed equally poorly in predicting stroke events. The Stroke RiskometerTM will be continually developed and validated to address the need to improve the current stroke risk scoring systems to more accurately predict stroke, particularly by identifying robust ethnic/race ethnicity group and country specific risk factors. International Journal of Strok