Friendly microbes help rice to grow and suppress its pathogens: Trichoderma and Bacillus Vs Xanthomonas in rice

Use of biological control for the management of diseases has gained huge awareness and importance in the present situation of climate change and food residues. Biocontrol agents play interesting role in developing plant health and provide protection against biotic and abiotic stresses. In this study, we isolated Trichoderma and Bacillus sp. isolated from soil samples collected from rice fields in Kharif 2019. Profiling based on the pH of the soil, the fungal bioagents were more present in slightly acidic to neutral pH (5.8-7.2) whereas bacterial bioagents in slightly neutral to basic (7.4-8.3). The isolates were screened for their ability to produce phytohormones, cell-wall degrading enzyme and biofilm. Based on biochemical screening two Trichoderma isolates (T6 and T7) and two Bacillus isolates (B1and B5) were subjected to glasshouse studies. Per cent diseased leaf area and lesion length of plants treated with B1 were found to be effective against pathogen. However, the plant growth promotion was more enhanced by T6. Scanning electron microscopy and molecular characterisation along with their phylogenetic analysis proved the identity of isolate B1 as Bacillus subtilis and T6 as Trichoderma atroviride.

Inherited Proteoglycan Biosynthesis Defects—Current Laboratory Tools and Bikunin as a Promising Blood Biomarker

Proteoglycans consist of proteins linked to sulfated glycosaminoglycan chains. They constitute a family of macromolecules mainly involved in the architecture of organs and tissues as major components of extracellular matrices. Some proteoglycans also act as signaling molecules involved in inflammatory response as well as cell proliferation, adhesion, and differentiation. Inborn errors of proteoglycan metabolism are a group of orphan diseases with severe and irreversible skeletal abnormalities associated with multiorgan impairments. Identifying the gene variants that cause these pathologies proves to be difficult because of unspecific clinical symptoms, hardly accessible functional laboratory tests, and a lack of convenient blood biomarkers. In this review, we summarize the molecular pathways of proteoglycan biosynthesis, the associated inherited syndromes, and the related biochemical screening techniques, and we focus especially on a circulating proteoglycan called bikunin and on its potential as a new biomarker of these diseases.

A rare but treatable inborn error of metabolism: Arginine glycine amidinotransferase (AGAT) deficiency

AGAT deficiency is a rare and treatable autosomal recessive disorder. The symptoms are early-onset developmental mild to moderate intellectual disability, delayed speech acquisition, behavioral problems or proximal muscle weakness. Biochemical screening for creatine, creatinine and urinary guanidinoacetate and genetic tests are used for diagnosis. Electromyography may be normal or may have a myopathic pattern with low amplitude polyphasic waves. Muscle biopsy may show abnormalities including small myocytes. Creatine supplementation can fully prevent the neurological disability, if the treatment is started early in life; the muscular function improves irrespective of the supplementation moment.

Exploring protein hotspots by optimized fragment pharmacophores

Fragment-based drug design has introduced a bottom-up process for drug development, with improved sampling of chemical space and increased effectiveness in early drug discovery. Here, we combine the use of pharmacophores, the most general concept of representing drug-target interactions with the theory of protein hotspots, to develop a design protocol for fragment libraries. The SpotXplorer approach compiles small fragment libraries that maximize the coverage of experimentally confirmed binding pharmacophores at the most preferred hotspots. The efficiency of this approach is demonstrated with a pilot library of 96 fragment-sized compounds (SpotXplorer0) that is validated on popular target classes and emerging drug targets. Biochemical screening against a set of GPCRs and proteases retrieves compounds containing an average of 70% of known pharmacophores for these targets. More importantly, SpotXplorer0 screening identifies confirmed hits against recently established challenging targets such as the histone methyltransferase SETD2, the main protease (3CLPro) and the NSP3 macrodomain of SARS-CoV-2.

TMPRSS2 inhibitor discovery facilitated through an in silico and biochemical screening platform

The COVID-19 pandemic has highlighted the need for new antiviral targets, as many of the currently approved drugs have proven ineffective against mitigating SARS-CoV-2 infections. The host transmembrane serine protease TMPRSS2 is a highly promising antiviral target, as it plays a direct role in priming the spike protein before viral entry occurs. Further, unlike other targets such as ACE2, TMPRSS2 has no known biological role. Here we utilize virtual screening to curate large libraries into a focused collection of potential inhibitors. Optimization of a recombinant expression and purification protocol for the TMPRSS2 peptidase domain facilitates subsequent biochemical screening and characterization of selected compounds from the curated collection in a kinetic assay. In doing so, we demonstrate that serine protease inhibitors camostat, nafamostat, and gabexate inhibit through a covalent mechanism. We further identify new non-covalent compounds as TMPRSS2 protease inhibitors, demonstrating the utility of a combined virtual and experimental screening campaign in rapid drug discovery efforts.

In vitro Anticoccidial, Antioxidant Activities and Biochemical Screening of Methanolic and Aqueous Leaves Extracts of Selected Plants

Avian coccidiosis, a protozoan parasitic disease caused by genus Eimeria. Due to emergence of drug resistant Eimeria species, this study was aimed to evaluate anticoccidial potentials of Ficus racemosa, Cassia fistula and Syzygium cumini leaves extracts. In vitro anticoccidial efficacy of extracts was evaluated by oocysts sporulation inhibition and sporozoites viability inhibition assays of mixed Eimeria species oocysts. The set up was examined after 48hrs of incubation. DPPH radical scavenging activity, ferric reducing antioxidant power and total antioxidant capacity were used for the evaluation of antioxidant potential of extracts. Among tested extracts maximum oocysts sporulation inhibition 86.81±2.35% and sporozoites viability inhibition was 86.73±1.67% at concentration 30 mg/ml of C. fistula methanolic leaves extract against E. mitis and E. tenella respectively. Highest radical scavenging capacity 67.82±0.00 and reducing power 2.17±0.01 was shown by F. racemosa and C. fistula methanolic leaves extract respectively. Maximum total antioxidant power was observed in C. fistula 30.95±0.35 and F. racemosa 21.93±1.41µg/mg methanolic leaves extracts. Antioxidant compounds including phenols, flavonoids, alkaloids, saponins, carbohydrates etc. were detected through biochemical screening of selected plants extracts. The maximum amount of phenols 32.50±0.00µg/ml and flavonoids 40.00±1.00µg/ml were recorded in C. fistula methanolic extracts. It is concluded that selected plants methanolic extracts possess best anticoccidial and antioxidant activities due to presence of medicinally important phytochemicals. Further research is needed for identification and isolation of anticoccidial active compounds from these plants that can be used in the formulation of drugs against coccidiosis

Prediction Model of the Course and Outcome of Pregnancy

The significance of predicting preterm births is determined by their consistently high frequency, high perinatal mortality of premature babies, significant labor and economic costs associated with their care, and the risk of child disability. Based on the analysis of modern literature, we established that most of the predictive methods used in modern obstetrics require additional examinations, financial costs and a certain amount of time, which reduces their effectiveness in cases of the threat of preterm birth. The purpose of the work was to develop and test prediction models of the outcome of pregnancy according to the indicators of laboratory and instrumental studies. Material and methods. The most informative indicators of the health state of 83 pregnant women (41 of them was with a favorable pregnancy outcome and 42 women were with preterm birth and / or antenatal fetal death) were selected to develop prediction models of the outcome of pregnancy (urgent or preterm birth). The models were tested using indicators of 17 pregnant women (11 with urgent birth and 6 with preterm birth). In all women, laboratory and instrumental indicators were determined in accordance with the existing standard of management of pregnancy. Fuzzy logic was used to develop prediction models of the outcome of pregnancy. Results and discussion. Using statistical criteria showed that the outcome of pregnancy in women without signs of threat of preterm birth was associated with the values of clinical (erythrocyte sedimentation rate) and biochemical (content of aspartate aminotransferase and bilirubin) blood tests, biochemical screening (content of estriol, plasma protein-A, associated with pregnancy), indicators of ultrasound (blood flow velocity in the middle cerebral artery and right uterine artery). In women with signs of threat of preterm birth, informative indicators were the content of estriol and bilirubin in the blood, as well as the value of erythrocyte sedimentation rate. Model-A, built on the basis of indicators of biochemical screening, had an overall accuracy of 84%, 86% of sensitivity, and 82% of specificity, which indicated a fairly high probability of identifying pregnant women, who were predicted both urgent and preterm birth from the entire sample. Model C, built on the basis of indicators of Doppler measurements, showed an overall accuracy of 96.4%, 100% of sensitivity and 94% of specificity, which allowed using it to predict the outcome of pregnancy. Model-AC, which uses the results of models A and C, allows classifying women by pregnancy without errors, i.e. the accuracy, sensitivity and specificity of such a combined model was 100%. Model-D for predicting preterm birth in pregnant women with signs of threat of abortion and/or preterm birth was synthesized according to the indicators of clinical and biochemical blood tests, taking into account the concentration of estriol. Testing of the model-D showed an overall accuracy of 96.3%, 100% of sensitivity, and 86% of specificity, which indicates a sufficiently high probability of identifying pregnant women, who were predicted both urgent and preterm birth. Conclusion. Using the developed prediction models will allow diagnosing and predicting preterm birth in each pregnant woman individually at an early (preclinical) stage, which contributes to the timely implementation of precaution measures to prevent the development of preterm birth