A bacterial ortholog of class II lysyl-tRNA synthetase activates lysine

Aminoacyl-tRNA synthetases produce aminoacyl-tRNAs, essential substrates for accurate protein synthesis. Beyond their central role in translation some of these enzymes or their orthologs are recruited for alternative functions, not always related to their primary cellular role. We investigate here the enzymatic properties of GenX (also called PoxA and YjeA), an ortholog of bacterial class II lysyl-tRNA synthetase. GenX is present in most Gram-negative bacteria and is homologous to the catalytic core of lysyl-tRNA synthetase, but it lacks the amino terminal anticodon binding domain of the latter enzyme. We show that, in agreement with its well-conserved lysine binding site, GenX can activate in vitro l-lysine and lysine analogs, but does not acylate tRNA^Lys or other cellular RNAs.     

Bacterial decolorization and detoxification of black liquor from rayon grade pulp manufacturing paper industry and detection of their metabolic products

This study deals with the decolorization of black liquor (BL) by isolated potential bacterial consortium comprising Serratia marcescens (GU193982), Citrobacter sp. (HQ873619) and Klebsiella pneumoniae (GU193983). The decolorization of BL was studied by using the different nutritional as well as environmental parameters. In this study, result revealed that the ligninolytic activities were found to be growth associated and the developed bacterial consortium was efficient for the reduction of COD, BOD and color up to 83%, 74% and 85%, respectively. The HPLC analysis of degraded samples of BL has shown the reduction in peak area compared to control. Further, the GC-MS analysis showed that, most of the compounds detected in control were diminished after bacterial treatment while, formic acid hydrazide, 4-cyclohexane-1,2-dicarboxylic acid, carbamic acid, 1,2-benzenedicarboxylic acid and erythropentanoic acid were found as new metabolites. Further, the seed germination test using Phaseolus aureus has supported the detoxification of bacterial decolorized BL.     

GABAA-R α4 Subunits are Required for the Low Dose Locomotor Stimulatory Effect of Alphaxalone,But Not for Several Other Behavioral Responses to Alphaxalone,Etomidate or Propofol

γ-Aminobutyric acid type A receptors (GABA_A-Rs) are considered to be the primary molecular targets of injectable anesthetics such as propofol, etomidate and the neurosteriod, alphaxalone. A number of studies have sought to understand the specific GABA_A-R subtypes involved in the mechanism of action of these three drugs. Here, we investigated the role of α4-subunit containing GABA_A-Rs in the neurobehavioral responses to these drugs. Drug responses in α4 subunit knockout (KO) mice were compared to wild type (WT) littermate controls. While etomidate and propofol are currently used as injectable anesthetics, alphaxalone belongs to the class of neurosteroid drugs having anesthetic effects. Low dose effects of etomidate and alphaxalone were studied using an open field assay. The moderate and high dose effects of all three anesthetics were measured using the rotarod and loss of righting reflex assays, respectively. The locomotor stimulatory effect of alphaxalone was reduced significantly in α4 KO mice compared to WT controls. Neither the low dose sedating effect of etomidate, nor the moderate/high dose effect of any of the drugs differed between genotypes. These results suggest that α4 subunit-containing GABA_A-Rs are required for the low dose, locomotor stimulatory effect of alphaxalone but are not required for the sedating effect of etomidate or the moderate/high dose effects of etomidate, propofol or alphaxalone on motor ataxia and loss of righting reflex.     

Prediction and validation of the unexplored RNA‐binding protein atlas of the human proteome

Detecting protein‐RNA interactions is challenging both experimentally and computationally because RNAs are large in number, diverse in cellular location and function, and flexible in structure. As a result, many RNA‐binding proteins (RBPs) remain to be identified. Here, a template‐based, function‐prediction technique SPOT‐Seq for RBPs is applied to human proteome and its result is validated by a recent proteomic experimental discovery of 860 mRNA‐binding proteins (mRBPs). The coverage (or sensitivity) is 42.6% for 1217 known RBPs annotated in the Gene Ontology and 43.6% for 860 newly discovered human mRBPs. Consistent sensitivity indicates the robust performance of SPOT‐Seq for predicting RBPs. More importantly, SPOT‐Seq detects 2418 novel RBPs in human proteome, 291 of which were validated by the newly discovered mRBP set. Among 291 validated novel RBPs, 61 are not homologous to any known RBPs. Successful validation of predicted novel RBPs permits us to further analysis of their phenotypic roles in disease pathways. The dataset of 2418 predicted novel RBPs along with confidence levels and complex structures is available at http://sparks-lab.org (in publications) for experimental confirmations and hypothesis generation. Proteins 2014; 82:640–647. © 2013 Wiley Periodicals, Inc.     

Missing value imputation in high-dimensional phenomic data: imputable or not,and how?

Background

In modern biomedical research of complex diseases, a large number of demographic and clinical variables, herein called phenomic data, are often collected and missing values (MVs) are inevitable in the data collection process. Since many downstream statistical and bioinformatics methods require complete data matrix, imputation is a common and practical solution. In high-throughput experiments such as microarray experiments, continuous intensities are measured and many mature missing value imputation methods have been developed and widely applied. Numerous methods for missing data imputation of microarray data have been developed. Large phenomic data, however, contain continuous, nominal, binary and ordinal data types, which void application of most methods. Though several methods have been developed in the past few years, not a single complete guideline is proposed with respect to phenomic missing data imputation.

Results

In this paper, we investigated existing imputation methods for phenomic data, proposed a self-training selection (STS) scheme to select the best imputation method and provide a practical guideline for general applications. We introduced a novel concept of “imputability measure” (IM) to identify missing values that are fundamentally inadequate to impute. In addition, we also developed four variations of K-nearest-neighbor (KNN) methods and compared with two existing methods, multivariate imputation by chained equations (MICE) and missForest. The four variations are imputation by variables (KNN-V), by subjects (KNN-S), their weighted hybrid (KNN-H) and an adaptively weighted hybrid (KNN-A). We performed simulations and applied different imputation methods and the STS scheme to three lung disease phenomic datasets to evaluate the methods. An R package “phenomeImpute” is made publicly available.

Conclusions

Simulations and applications to real datasets showed that MICE often did not perform well; KNN-A, KNN-H and random forest were among the top performers although no method universally performed the best. Imputation of missing values with low imputability measures increased imputation errors greatly and could potentially deteriorate downstream analyses. The STS scheme was accurate in selecting the optimal method by evaluating methods in a second layer of missingness simulation. All source files for the simulation and the real data analyses are available on the author’s publication website.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-014-0346-6) contains supplementary material, which is available to authorized users.     

MTHFR C677T Predisposes to POAG but Not to PACG in a North Indian Population: A Case Control Study

Hyperhomocysteinemia induced by the C677T genetic variant in MTHFR (methylenetetrahydrofolate reductase) has been implicated in neuronal cell death of retinal ganglion cells (RGC), which is a characteristic feature of glaucoma. However, association of MTHFR C677T with glaucoma has been controversial because of inconsistent results across association studies. Association between MTHFR C677T and glaucoma has not been reported in Indian population. Therefore, with a focus on neurodegenerative death of RGC in glaucoma, the current study aimed to investigate association of MTHFR C677T with Primary Open Angle Glaucoma (POAG) and Primary Angle Closure Glaucoma (PACG) in a North Indian population. A total of 404 participants (231 patients and 173 controls) were included in this study. Genotyping was performed by Polymerase Chain Reaction-Restriction Fragment Length Polymorphism. A few random samples were also tested by direct sequencing. Genotypic and allelic distributions of the POAG and PACG cohorts were compared to that of controls by chi-square test and odds ratios were reported with 95% confidence intervals. Genotypic and allelic distributions between POAG cases and controls were significantly different (p = 0.03 and p = 0.01 respectively). Unlike POAG, we did not find significant difference in the genotypic and allelic distributions of C677T between PACG cases and controls (p>0.05). We also observed a higher proportion of TT associated POAG in females than that in males. However, this is a preliminary indication of gender specific risk of C677T that needs to be replicated in a larger cohort of males and females. The present investigation on MTHFR C677T and glaucoma reveals that the TT genotype and T allele of this polymorphism are significant risk factors for POAG but not for PACG in North Indian population. Ours is the first report demonstrating association of MTHFR C677T with POAG but not PACG in individuals from North India.     

COVID‐19 lockdown frees wildlife to roam but increases poaching threats in Nepal

To contain transmission of COVID‐19, lockdowns or strict restrictions of people''s mobility outside their residences were instituted in a majority of countries worldwide, including Nepal, where the first phase of nationwide lockdown was observed from 24 March to 21 July 2020. This sudden halt in human outdoor activities brought positive and negative impacts on forests and wildlife. We undertook a study to learn the impact of the COVID‐19 lockdown on wildlife and forests in the protected areas (PAs) of Nepal. Between July and September 2020, data on illegal activities recorded by the staff of PAs and also those reported by media were collected and analyzed. Key informant interviews (KII) were done with the park officers and security personnel by virtual communication (telephone, messenger app, and video call) to collect detailed information and for corroboration. The collected data were categorized into four groups: (a) wildlife killed, (b) wildlife injured, (c) arrest incidents related to forest crime, and (d) arrest incidents related to wildlife crime. Data from the fiscal year 2019–2020 were analyzed, comparing before lockdown and after. Among 20 PAs investigated during the lockdown, the study found substantial increases in wildlife death in two PAs, Banke National Park, and Bardia National Park. Similarly, Chitwan National Park (CNP) and Shivapuri Nagarjun National Park (SNNP) witnessed a rise in wildlife poaching. CNP and SNNP are located close to densely populated cities and also have human settlements in their peripheries. Wildlife was sighted freely roaming inside PAs during the lockdown, presumably because the absence of visitors and human activities during the lockdown decreased disturbance. Thus, the wildlife was enjoying the freedom of movement on the one hand, and on the other hand was threatened by poachers, many of whom were laid off from other activities and were taking advantage of the lapse in security.