Secretory and GM1 receptor binding role of N-terminal region of LTB in Vibrio cholerae

Heat labile enterotoxin from enterotoxigenic Escherichia coli is similar to cholera toxin (CT) and is a leading cause of diarrhea in developing countries. It consists of an enzymatically active A subunit (LTA) and a carrier pentameric B subunit (LTB). In the current study, we evaluated the importance of the N-terminal region of LTB by mutation analysis. Deletion of the glutamine (ΔQ3) residue and a substitution mutation E7G in the α1 helix region led to defects in LTB protein secretion. Deletion of the proline residue (ΔP2) caused a decrease in α helicity. The ΔP2 mutant affected GM₁ ganglioside receptor binding activity without affecting LTB pentamer formation. Upon refolding/reassembly, the ΔP2 mutant showed defective biological activity. The single substitution mutation (E7D) strengthened the helix, imparting structural stability and thereby improved the GM₁ ganglioside receptor binding activity. Our results demonstrate the important role of N-terminal α1 helix in maintaining the structural stability and the integrity of GM₁ ganglioside receptor binding activity.     

Purification of a bifunctional amylase/protease inhibitor from ragi (Eleusine coracana) by chromatography and its use as an affinity ligand

An ammonium sulphate fraction (20–60%) of bifunctional amylase/protease inhibitor from ragi (Eleusine coracana) was purified by affinity chromatography to give 6.59-fold purity with 81.48% yield. The same ammonium sulphate fraction was also subjected to ion exchange chromatography and was purified 4.28-fold with 75.95% yield. The ion exchange fraction was subjected to gel filtration and the inhibitor was purified to 6.67-fold with 67.36% yield. Further sodium dodecyl sulphate-polyacrylamide gel electrophoresis (SDS-PAGE) was performed to check the homogeneity of purified amylase/trypsin inhibitor obtained through affinity, ion exchange and gel chromatography. The molecular weight of the inhibitor was found to be 14 kDa. This purified inhibitor was used as affinity ligand for the purification of a commercial preparation of pancreatic amylase.     

Development and validation of a simple liquid chromatographic method with ultraviolet detection for the determination of imatinib in biological samples

The aim of this study was to develop a rapid and sensitive HPLC method with UV detection for the estimation of imatinib from the plasma of patients with chronic myeloid leukemia (CML). The robustness of the method was checked by conducting first dose pharmacokinetics on blood samples from four patients who had been administered Gleevec (100 mg) in an oral dose. Samples were prepared in a simple and single step by precipitating the plasma proteins with methanol and injecting 50 microl aliquot from supernatant was subjected for analysis. Assay was conducted using a C8 column (250 mm x 4.6 mm, 5 microm particle size) under isocratic elution with 0.02 M potassium dihydrogen phosphate-acetonitrile (7:3, v/v) at a flow rate of 1 ml/min and detected using photodiode array at 265 nm. Calibration plots in spiked plasma were linear in a concentration range of 0.05-25 microg/ml. The inter and intra-day variation of standard curve was <4% (R.S.D.). This method could be a simple and quick method for the estimation of imatinib from the patient's plasma.     

A comparison of absolute performance of different correlative and mechanistic species distribution models in an independent area

To investigate the comparative abilities of six different bioclimatic models in an independent area, utilizing the distribution of eight different species available at a global scale and in Australia. Global scale and Australia. We tested a variety of bioclimatic models for eight different plant species employing five discriminatory correlative species distribution models (SDMs) including Generalized Linear Model (GLM), MaxEnt, Random Forest (RF), Boosted Regression Tree (BRT), Bioclim, together with CLIMEX (CL) as a mechanistic niche model. These models were fitted using a training dataset of available global data, but with the exclusion of Australian locations. The capabilities of these techniques in projecting suitable climate, based on independent records for these species in Australia, were compared. Thus, Australia is not used to calibrate the models and therefore it is as an independent area regarding geographic locations. To assess and compare performance, we utilized the area under the receiver operating characteristic (ROC) curves (AUC), true skill statistic (TSS), and fractional predicted areas for all SDMs. In addition, we assessed satisfactory agreements between the outputs of the six different bioclimatic models, for all eight species in Australia. The modeling method impacted on potential distribution predictions under current climate. However, the utilization of sensitivity and the fractional predicted areas showed that GLM, MaxEnt, Bioclim, and CL had the highest sensitivity for Australian climate conditions. Bioclim calculated the highest fractional predicted area of an independent area, while RF and BRT were poor. For many applications, it is difficult to decide which bioclimatic model to use. This research shows that variable results are obtained using different SDMs in an independent area. This research also shows that the SDMs produce different results for different species; for example, Bioclim may not be good for one species but works better for other species. Also, when projecting a “large” number of species into novel environments or in an independent area, the selection of the “best” model/technique is often less reliable than an ensemble modeling approach. In addition, it is vital to understand the accuracy of SDMs' predictions. Further, while TSS, together with fractional predicted areas, are appropriate tools for the measurement of accuracy between model results, particularly when undertaking projections on an independent area, AUC has been proved not to be. Our study highlights that each one of these models (CL, Bioclim, GLM, MaxEnt, BRT, and RF) provides slightly different results on projections and that it may be safer to use an ensemble of models.     

Population genetic structure and phylogeography of cyprinid fish, <Emphasis Type="Italic">Labeo dero</Emphasis> (Hamilton, 1822) inferred from allozyme and microsatellite DNA marker analysis

We examined population structure of Labeo dero (Hamilton, 1822) from different riverine locations in India using 10 polymorphic allozyme and eight microsatellite loci. For analysis, 591 different tissue samples were obtained from commercial catches covering a wide geographic range. Allozyme variability (An = 1.28–1.43, Ho = 0.029–0.071) was much lower than for microsatellites (An = 4.625–6.125, Ho = 0.538–0.633). Existence of rare alleles was found at three allozyme (MDH-2*, GPI* and PGDH*) and at two microsatellite loci (R-3* and MFW-15*). Deviation from Hardy–Weinberg equilibrium (P < 0.05, after the critical probability levels were adjusted for sequential Bonferroni adjustment) could be detected at three loci (EST-1*, -2* and XDH*) whereas, after correction for null alleles, two microsatellite loci (MFW-1*,-15*) deviated from HWE in the river Yamuna. Fst for all the samples combined over all allozyme loci was found to be 0.059 suggesting that 5.9% of the total variation was due to genetic differentiation while microsatellite analysis yielded 0.019 which was concordant to mean Rst (0.02). Hierarchical partition of genetic diversity (AMOVA) showed that greater variability (approx. 95%) was due to within population component than between geographical regions. Based on distribution of genetic differentiation detected by both markers, at least five different genetic stocks of L. dero across its natural distribution could be identified. These results are useful for the evaluation and conservation of L. dero in natural water bodies.     

Genome-wide association study for candidate genes controlling seed yield and its components in rapeseed (Brassica napus subsp. napus)

Genetic improvement of seed yield per plant (SY) is one of the major objectives in Brassica napus breeding programme. SY, being a complex quantitative trait is directly and indirectly influenced by yield-component traits such as siliqua length (SL), number of seeds per siliqua (NSS), and thousand seed weight (TSW). Therefore, concurrent improvement in SL, NSS and TSW can lead to higher SY in B. napus. This study was conducted to identify significant SNPs and putative candidate genes governing SY and its component traits (SL, NSS, TSW). All these traits were evaluated in a diverse set of 200 genotypes representing diversity from wide geographical locations. Of these, a set of 125 genotypes were chosen based on pedigree diversity and multi-location trait variation for genotyping by sequencing (GBS). Best linear unbiased predictors (BLUPs) of all the traits were used for genome-wide association study (GWAS) with 85,126 SNPs obtained from GBS. A total of 16, 18, 27 and 18 SNPs were found to be significantly associated for SL, NSS, TSW and SY respectively. Based on linkage disequilibrium decay analysis, 150 kb genomic region flanking the SNP was used for the identification of underlying candidate genes for each test trait. Important candidate genes involved in phytohormone signaling (WAT1, OSR1, ARR8, CKX1, REM7, REM9, BG1) and seed storage proteins (Cruciferin) were found to have significant influence on seed weight and yield. Genes involved in sexual reproduction and fertilization (PERK7, PERK13, PRK3, GATA15, NFD6) were found to determine the number of seeds per siliqua. Several genes found in this study namely ATS3A, CKX1, SPL2, SPL6, SPL9, WAT1 showed pleiotropic effect with yield component traits. Significant SNPs and putative candidate genes identified for SL, NSS, TSW and SY could be used in marker-assisted breeding for improvement of crop yield in B. napus. Genotypes identified with high SL, NSS, TSW and SY could serve as donors in crop improvement programs in B. napus.Supplementary InformationThe online version contains supplementary material available at 10.1007/s12298-021-01060-9.     

AI-supported modified risk staging for multiple myeloma cancer useful in real-world scenario

Introduction: An efficient readily employable risk prognostication method is desirable for MM in settings where genomics tests cannot be performed owing to geographical/economical constraints. In this work, a new Modified Risk Staging (MRS) has been proposed for newly diagnosed Multiple Myeloma (NDMM) that exploits six easy-to-acquire clinical parameters i.e. age, albumin, β2-microglobulin (β2M), calcium, estimated glomerular filtration rate (eGFR) and hemoglobin.Materials and Methods: MRS was designed using a training cohort of 716 NDMM patients of our inhouse MM Indian (MMIn) cohort and validated on MMIn (n=354) cohort and MMRF (n=900) cohort. K-adaptive partitioning (KAP) was used to find new thresholds for the parameters. Risk staging rules, obtained via training a J48 classifier, were used to build MRS.Results: New thresholds were identified for albumin (3.6 g/dL), β2M (4.8 mg/L), calcium (11.13 mg/dL), eGFR (48.1 mL/min), and hemoglobin (12.3 g/dL) using KAP on the MMIn dataset. On the MMIn dataset, MRS outperformed ISS for OS prediction in terms of C-index, hazard ratios, and its corresponding p-values, but performs comparable in prediction of PFS. On both MMIn and MMRF datasets, MRS performed better than RISS in terms of C-index and p-values. A simple online tool was also designed to allow automated calculation of MRS based on the values of the parameters.Discussion: Our proposed ML-derived yet simple staging system, MRS, although does not employ genetic features, outperforms RISS as confirmed by better separability in KM survival curves and higher values of C-index on both MMIn and MMRF datasets.Funding: Grant: BT/MED/30/SP11006/2015 (Department of Biotechnology, Govt. of India), Grant: DST/ICPS/CPS-Individual/2018/279(G) (Department of Science and Technology, Govt. of India), UGC-Senior Research Fellowship.     

Larvicidal activity of Pseudocalymma alliaceum and Allium sativum against Culex quinquefasciatus (Say)

The larvicidal activity of the plant extracts Pseudocalymma alliaceum and Allium sativum were determined against Culex quinquefasciatus. The hexane extract of P. alliaceum and the petroleum ether extract of A. sativum exhibited larvicidal efficacy against Cx. quinquefasciatus larvae. Extracts of P. alliaceum resulted in concentrations that produced 50% mortality LC₅₀ and LC₉₀ values of 2.49 and 15.06 ppm, respectively, after 24 h and 1.16 and 8.45 ppm after 48 h. Extracts of A. sativum resulted in LC₅₀ and LC₉₀ values of 8.38 and 29.15 ppm after 24 h and 7.28 and 44.19 ppm after 48 h of exposure, respectively. The results indicate that the plant extract component(s) present in the hexane extract of P. alliaceum leaves demonstrated greater potential as an efficient larvicide than A. sativum against Cx. quinquefasciatus.