Biology subjects

Rao, N.

Publications and source records attributed to Rao, N..

3 recordsLinked to original sources

bioRxiv2019

Intertrial Variability in Human Corticospinal Activity during Grasp Force Planning

Neuronal firing rate variability during planning has been found to contribute to trial-to-trial variability in primate behavior. However, in humans, whether planning related mechanisms contribute to trial-to-trial behavioral variability remains unknown. We investigated the time-course of trial-to-trial variability in corticospinal excitability (CSE) using transcranial magnetic stimulation (TMS) while subjects planned to perform a self-paced reach-to-grasp task. We hypothesized that CSE variability will be modulated during task planning and that such a modulation would explain trial-to-trial behavioral variability. Able-bodied individuals were visually cued to plan their grip force before exertion of either 30% or 5% of maximum force on an object. TMS was delivered at different time points following a cue that instructed the force level. We first modeled the relation between CSE magnitude and its variability at rest (n=12) to study the component of CSE variability during task planning that was not related to changes in CSE magnitude (n=12). We found an increase in CSE variability during task planning at 30% but not at 5% of force. This effect was temporally dissociated from the decrease in CSE magnitude. Importantly, the increase in CSE variability during planning explained 64% of inter-individual differences in time to peak force rate trial-to-trial variability. These results were found to be repeatable across studies and robust to different analysis methods. Our findings suggest that the planning-related mechanisms underlying modulation in CSE variability and CSE magnitude are distinct. Notably, the extent of modulation in planning-related variability in corticospinal system within individuals may explain their trial-to-trial behavioral variability.

neuroscience↗

bioRxiv2019

Substrate structure and computation guided engineering of a Lipase for Omega-3 fatty acid selectivity

Optimum health benefits of omega-3 fatty acids ({omega}-3 FAs) require it to be concentrated in its natural sources. Fatty acid selectivity of lipase governs the efficacy of the production of lipase-mediated {omega}-3 FAs concentrates. We attempted to improve the fatty acid selectivity of a lipase from thermophilic bacterium Geobacillus thermoleovorans (GTL) by two approaches. In a semi-rational approach, six amino acid positions of GTL interacting with the substrate, were identified by docking and were subjected to site-saturation mutagenesis. Three best substitutions were incorporated into GTL(CM-GTL). Hydrolysis of oil by lipase was monitored in a pH-Stat and the fatty acids released at various time points were analyzed by GC-MS.CM-GTL showed a significant improvement in discrimination against DHA during hydrolysis. In the second approach based on rational design, the active site was narrowed by incorporating heavier amino acids in the lining of acyl-binding pocket to hinder access to bulky {omega}-3 FAs. For this purpose, two amino acids surrounding the opening of the acyl pocket were replaced with the next heavier amino acids and the affinities were evaluated in silico. The double mutant, thus deigned, was found to be excellent in discriminating the {omega}-3 FAs during hydrolysis of triglycerides. Engineering the binding pocket of a complex substrate, such as a triglyceride, with the supportive information on substrate structure and its binding modes with the enzyme provided by computational methods, has resulted in designing two efficient lipase variants with improved substrate selectivity.

biochemistry↗

bioRxiv2018

CasLocusAnno: a web-based server for annotating Cas loci and their corresponding (sub)types

CRISPR-Cas systems are prevalent in bacterial and archaeal genomes, and these systems provide a powerful adaptive immune system against predation by phages and other mobile genetic elements (MGEs). They also contribute to other functions, such as gene regulation in prokaryotic organisms. Determining Cas proteins and Cas loci can help mine Cas proteins and facilitate the identification of Cas-associated accessory proteins. Therefore, the purpose of this work is to develop a web-based server, CasLocusAnno, to annotate Cas proteins and Cas loci and to classify them according to (sub)type based on a previous study. CasLocusAnno can annotate Cas proteins and Cas loci and assign their (sub)types within {bsim}28 seconds for whole protein sequence submissions, with protein sequence numbers ranging from {bsim}30 to {bsim}10500. Comparison with Makarova et al.s benchmark data demonstrates that CasLocusAnno can accurately identify Cas loci and (sub)types. In addition, CasLocusAnno can identify Cas proteins with higher accuracy and a lower additional prediction rate (APR) than two excellent software programs, CRISPRCasFinder and MacSyFinder. The domain alignment of a Cas protein can be easily browsed in the annotation results. Our server can be freely accessed at http://cefg.uestc.edu.cn/CasLocusAnno/.

bioinformatics↗