Browsing by Author "Rattinam, Rajesh"

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Capillary hydrodynamic chromatography reveals temporal profiles of cell aggregates
(2016-03-03)
Tang, Ya-Ru
;
Huang, Hsin-Yi
;
Hu, Jie-Bi
;
Rattinam, Rajesh
;
Li, Chun-Hsien
Microbial cells are known to form aggregates. Such aggregates can be found in various matrices; for example, functional drinks. Capillary hydrodynamic chromatography (HDC) enables separation of particles by size using nanoliter-scale volumes of samples. Here we propose an approach based on HDC for characterisation of real samples containing aggregated and non-aggregated bacterial and fungal cells. Separation of cells and cell aggregates in HDC arises from the parabolic flow profile under laminar flow conditions. In the presented protocol, hydrodynamic separation is coupled with different on-line and offline detectors (light absorption/scattering and microscopy). The method has successfully been applied in the monitoring of dynamic changes in the microbiome of probiotic drinks. Chromatographic profiles of yogurt and kefir samples obtained at different times during fermentation are in a good agreement with microscopic images. Moreover, thanks to the implementation of an area imaging detector, capillary HDC could be multiplexed and used to profile spatial gradients in cell suspensions, which arise in the course of sedimentation of cells and cell aggregates. This result shows compatibility of sedimentation analysis and capillary HDC. We believe that the approach may find applications in the profiling of functional foods and other matrices containing aggregated bioparticles. (C) 2016 Elsevier B.V. All rights reserved.
In silico structure-based design of enhanced peptide inhibitors targeting RNA polymerase PA(N)-PB1(C) interaction
(2019-02-01)
Arivajiagane, Arundhathi
;
Varadharajulu, Narendrakumar Ravi
;
Seerangan, Kumar
;
Rattinam, Rajesh
;
分子醫學與生物工程研究所
Developing antivirals for influenza A virus (FluA) has become more challenging due to high range of antigenic mutation and increasing numbers of drug-resistant viruses. Finding a selective inhibitor to target highly conserved region of protein-protein interactions interface, thereby increasing its efficiency against drug resistant virus could be highly beneficial. In this study, we used in silico approach to derive FluAPep1 from highly conserved region, PA(N)-PB1(C) interface and generated 121 FluAPep1 analogues. Interestingly, we found that the FluAPep1 interaction region in the PA(N) domain are highly conserved in many FluA subtypes. Especially, FluAPep1 targets two pandemic FluA strains, H1N1/avian/2009 and H3N2/Victoria/1975. All of these FluA subtypes PA(N) domain (H1N1/H3N2CAN/H3N2VIC/H7N1/H7N2) were superimposed with PA(N) domain from H17N10 and the calculated root mean standards deviations were less than 3 angstrom. FlexPepDock analysis revealed that FluAPep1 exhibited higher binding affinity (score -246.155) with the PA(N) domain. In addition, around 86% of non-hot spot mutated peptides (FluAPep28-122) showed enhanced binding affinity with PA(N) domain. ToxinPred analysis confirmed that designed peptides were non-toxic. Thus, FluAPep1 and its analogues has potential to be further developed into an antiviral treatment against FluA infection.