Whole genome resequencing of tobacco (<Emphasis Type="Italic">Nicotiana tabacum</Emphasis> L.) genotypes and high-throughput SNP discovery

Genome-wide single-nucleotide polymorphisms (SNPs) are highly useful in unraveling genetic insights and are essential to accelerate selections for genetic improvement in tobacco. The discovery of genome-wide SNPs in tobacco is very complex due to its high level of repetitive genome and polyploidy. At present, publicly available genomic data on SNPs are very limited, which warrants the need for high-throughput SNPs for application in tobacco breeding. In this research paper, we describe our efforts on SNP discovery by whole genome resequencing of 18 flue-cured Virginia (FCV) tobacco genotypes and annotation of SNPs in the tobacco genome. A large amount of data of about 225 GB per genotype was generated, with an average read depth of 50× using paired-end next-generation sequencing (NGS) with the HiSeq 2500 platform. The discovery of a large number of SNPs and indels was attempted to assist mapping and, thus, the selection processes to develop superior tobacco breeding lines. Discovered SNPs, their functional annotation, mapping to the reference genome, and their relative positioning in the linkage group are discussed in this paper.     

Phylogeny of the M superhaplogroup inferred from complete mitochondrial genome sequence of Indian specific lineages

Background  

Phylogenetic analysis of human complete mitochondrial DNA sequences has largely contributed to resolving phylogenies and antiquity of different lineages belonging to the majorhaplogroups L, N and M (East-Asian lineages). In the absence of whole mtDNA sequence information of M lineages reported in India that exhibits highest diversity within the sub-continent, the present study was undertaken to provide a detailed analysis of this haplogroup to precisely characterize the lineages and unravel their intricate phylogeny.     

SOCCER: Self-Optimization of Energy-efficient Cloud Resources

Cloud data centers often schedule heterogeneous workloads without considering energy consumption and carbon emission aspects. Tremendous amount of energy consumption leads to high operational costs and reduces return on investment and contributes towards carbon footprints to the environment. Therefore, there is need of energy-aware cloud based system which schedules computing resources automatically by considering energy consumption as an important parameter. In this paper, energy efficient autonomic cloud system [Self-Optimization of Cloud Computing Energy-efficient Resources (SOCCER)] is proposed for energy efficient scheduling of cloud resources in data centers. The proposed work considers energy as a Quality of Service (QoS) parameter and automatically optimizes the efficiency of cloud resources by reducing energy consumption. The performance of the proposed system has been evaluated in real cloud environment and the experimental results show that the proposed system performs better in terms of energy consumption of cloud resources and utilizes these resources optimally.     

Development of an in vitro Bioassay for Recombinant Human Erythropoietin (rHuEPO) Based on Proliferative Stimulation of an Erythroid Cell Line and Analysis of Sialic Acid Dependent Microheterogeneity: UT-7 Cell Bioassay

Determination of biological activity and its comparison with clinical behavior is important in the quality assessment of therapeutic glycoproteins. In vivo studies are usually employed for evaluating bioactivity of these glycomolecules. However, alternative methods are required to simplify the bioassay and avoid ethical issues associated with in vivo studies. Negatively charged sialic acid residues are known to be critical for in vivo bioactivity of rHuEPO. To address this need, we employed the human acute myeloid leukemia cell line UT-7 for the determination of proliferative stimulation induced by rHuEPO. Relative potencies of various intact and sugar-trimmed rHuEPO preparations were estimated using the International Standard for Human r-DNA derived EPO (87/684) as a reference for bioactivity. The cellular response was measured with a multi-channel photometer using a colorimetric microassay, based on the metabolism of the Resazurin sodium by cell viability. For a resourceful probing of physiological features of rHuEPO with significance, we obtained partly or completely desialylated rHuEPO digested by the neuraminidase enzyme without degradation of carbohydrates. Two-fold higher specific activity was shown by asialoerythropoietin in in vitro analysis compared with the sialoerythropoietin. Further, computational studies were also carried out to construct the 3D model of the erythropoietin (EPO) protein structure using standard comparative modeling methods. The quality of the model was validated using Procheck and protein structure analysis (ProSA) server tools. N–glycan units were constructed; moreover, EPO protein was glycosylated at potential glycosylation amino acid residue sites. The method described should be suitable for potency assessments of pharmaceutical formulations of rHuEPO (European Pharmacopeia, 2016).     

Generation and functional characterization of anti-human and anti-mouse IL-36R antagonist monoclonal antibodies

Deficiency of interleukin (IL)-36 receptor antagonist (DITRA) syndrome is a rare autosomal recessive disease caused by mutations in IL36RN. IL-36R is a cell surface receptor and a member of the IL1R family that is involved in inflammatory responses triggered in skin and other epithelial tissues. Accumulating evidence suggests that IL-36R signaling may play a role in the pathogenesis of psoriasis. Therapeutic intervention of IL-36R signaling offers an innovative treatment paradigm for targeting epithelial cell-mediated inflammatory diseases such as the life-threatening psoriasis variant called generalized pustular psoriasis (GPP). We report the discovery and characterization of MAB92, a potent, high affinity anti-human IL-36 receptor antagonistic antibody that blocks human IL-36 ligand (α, β and γ)-mediated signaling. In vitro treatment with MAB92 directly inhibits human IL-36R-mediated signaling and inflammatory cytokine production in primary human keratinocytes and dermal fibroblasts. MAB92 shows exquisite species specificity toward human IL-36R and does not cross react to murine IL-36R. To enable in vivo pharmacology studies, we developed a mouse cross-reactive antibody, MAB04, which exhibits overlapping binding and pharmacological activity as MAB92. Epitope mapping indicates that MAB92 and MAB04 bind primarily to domain-2 of the human and mouse IL-36R proteins, respectively. Treatment with MAB04 abrogates imiquimod and IL-36-mediated skin inflammation in the mouse, further supporting an important role for IL-36R signaling in epithelial cell-mediated inflammation.     

Photophysics of ruthenium(II) complexes carrying amino acids in the ligand 2,2′-bipyridine and intramolecular electron transfer from methionine to photogenerated Ru(III)

New ruthenium(II) complexes carrying methionine and phenylalanine in the bipyridine ligand, [Ru(bpy)₂(4-Me-4′-(CONH-l-methionine methyl ester)-2,2′-bipyridine)](PF₆)₂ (IV) and [Ru(bpy)₂(4-Me-4′-(CONH-l-phenylalanine ethyl ester)-2,2′-bpy)](PF₆)₂(V) have been synthesized and characterized and their photophysical properties studied. Flash photolysis measurements of complex IV, in the presence of an electron acceptor, methyl viologen (MV²⁺) show that an intermolecular electron transfer from the excited state of Ru(II) in complex IV, to MV²⁺ takes place, forming Ru(III) and the methyl viologen cation radical, MV⁺. The formation of MV⁺ in this system is confirmed using time-resolved transient absorption spectroscopy. This intermolecular electron transfer is followed by intramolecular electron transfer from the thioether moiety (methionine) to the photogenerated Ru(III), regenerating Ru(II).     

FIEFDom: a transparent domain boundary recognition system using a fuzzy mean operator

Protein domain prediction is often the preliminary step in both experimental and computational protein research. Here we present a new method to predict the domain boundaries of a multidomain protein from its amino acid sequence using a fuzzy mean operator. Using the nr-sequence database together with a reference protein set (RPS) containing known domain boundaries, the operator is used to assign a likelihood value for each residue of the query sequence as belonging to a domain boundary. This procedure robustly identifies contiguous boundary regions. For a dataset with a maximum sequence identity of 30%, the average domain prediction accuracy of our method is 97% for one domain proteins and 58% for multidomain proteins. The presented model is capable of using new sequence/structure information without re-parameterization after each RPS update. When tested on a current database using a four year old RPS and on a database that contains different domain definitions than those used to train the models, our method consistently yielded the same accuracy while two other published methods did not. A comparison with other domain prediction methods used in the CASP7 competition indicates that our method performs better than existing sequence-based methods.