Characterization of domain-specific interaction of synthesized dye with serum proteins by spectroscopic and docking approaches along with determination of in vitro cytotoxicity and antiviral activity

The interaction between a synthesized dye with proteins, bovine, and human serum albumin (BSA, HSA, respectively) under physiological conditions has been characterized in detail, by means of steady-state and time-resolved fluorescence, UV–vis absorption, and circular dichroism (CD) techniques. An extensive time-resolved fluorescence spectroscopic characterization of the quenching process has been undertaken in conjugation with temperature-dependent fluorescence quenching studies to divulge the actual quenching mechanism. From the thermodynamic observations, it is clear that the binding process is a spontaneous molecular interaction, in which van der Waals and hydrogen bonding interactions play the major roles. The UV–vis absorption and CD results confirm that the dye can induce conformational and micro-environmental changes of both the proteins. In addition, the dye binding provokes the functionality of the native proteins in terms of esterase-like activity. The average binding distance (r) between proteins and dye has been calculated using FRET. Cytotoxicity and antiviral effects of the dye have been found using Vero cell and HSV-1F virus by performing MTT assay. The AutoDock-based docking simulation reveals the probable binding location of dye within the sub-domain IIA of HSA and IB of BSA.     

Cardiolipin-mediated PPARγ S112 phosphorylation impairs IL-10 production and inflammation resolution during bacterial pneumonia

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Dimension reduction for integrative survival analysis

We propose a constrained maximum partial likelihood estimator for dimension reduction in integrative (e.g., pan-cancer) survival analysis with high-dimensional predictors. We assume that for each population in the study, the hazard function follows a distinct Cox proportional hazards model. To borrow information across populations, we assume that each of the hazard functions depend only on a small number of linear combinations of the predictors (i.e., “factors”). We estimate these linear combinations using an algorithm based on “distance-to-set” penalties. This allows us to impose both low-rankness and sparsity on the regression coefficient matrix estimator. We derive asymptotic results that reveal that our estimator is more efficient than fitting a separate proportional hazards model for each population. Numerical experiments suggest that our method outperforms competitors under various data generating models. We use our method to perform a pan-cancer survival analysis relating protein expression to survival across 18 distinct cancer types. Our approach identifies six linear combinations, depending on only 20 proteins, which explain survival across the cancer types. Finally, to validate our fitted model, we show that our estimated factors can lead to better prediction than competitors on four external datasets.     

DNA barcoding to map the microbial communities: current advances and future directions

During the last two decades, the DNA barcode development towards microbial community has increased dramatically. DNA barcode development is related to error-free and quick species identification which aid in understanding the microbial biodiversity, as well as the diseases related to microbial species. Here, we seek to evaluate the so-called barcoding initiatives for the microbial communities and the emerging trends in this field. In this paper, we describe the development of DNA marker-based DNA barcoding system, comparison between routine species identification and DNA barcode, and microbial biodiversity and DNA barcode for microbial communities. Two major topics, such as the molecular diversity of viruses and barcode for viruses have been discussed at the same time. We demonstrate the current status and the maker of DNA barcode for bacteria, algae, fungi, and protozoa. Furthermore, we argue about the promises, limitations, and present and future challenges of microbial barcode development.     

Nutrient modulation based process engineering strategy for improved butanol production from Clostridium acetobutylicum

The present study demonstrates a process engineering strategy to achieve high butanol titer and productivity from wild type Clostridium acetobutylicum MTCC 11274. In the first step, two different media were optimized with the objectives of maximizing the biomass and butanol productivity, respectively. In the next step, attributes of these two media compositions were integrated to design a two-stage fed-batch process which resulted in maximal butanol productivity of 0.55 g L⁻¹ h⁻¹ with titer of 13.1 g L⁻¹. Further, two-stage fed-batch process along with combinatorial use of magnesium limitation and calcium supplementation resulted in the highest butanol titer and productivity of 16.5 g L⁻¹ and 0.59 g L⁻¹ h⁻¹, respectively. Finally, integration of the process with gas stripping and modulation of feeding duration resulted in a cumulative butanol titer of 54.3 g L⁻¹ and productivity of 0.58 g L⁻¹ h⁻¹. The strategy opens up possibility of developing a viable butanol bioprocess. © 2019 American Institute of Chemical Engineers Biotechnol. Prog., 35: e2771, 2019.     

Induction of sister chromatid exchanges by heavy metal salts in root meristem cells ofAllium cepa L.

Four heavy metal salts, nickel sulphate, mercuric chloride, cadmium sulphate and zinc sulphate, were tested for induction of sister chromatid exchange (SCE) in root meristem cells ofAllium cepa. A simple modified Feulgen staining procedure was employed for SCE-analysis. Maleic hydrazide and paraquat were included for comparison. An evaluation of genotoxicity of the above test chemicals made on the basis of SCE-assay was found positive for all the test chemicals with exception of zinc sulphate which gave a weak positive result.