Bacterial Load of Pneumococcal Serotypes Correlates with Their Prevalence and Multiple Serotypes Is Associated with Acute Respiratory Infections among Children Less Than 5 Years of Age

Background

Among pneumococcal serotypes, some serotypes are more prevalent in the nasopharynx than others; determining factors for higher prevalence remain to be fully explored. As non-vaccine serotypes have emerged after the introduction of 7-valent conjugate vaccines, study of serotype specific epidemiology is in need. When two or more serotypes co-colonize, they evolve rapidly to defend host''s immune responses; however, a clear association of co-colonization with a clinical outcome is lacking.

Methods

Children less than 5 years old who were admitted to hospital due to acute respiratory infections (ARI) (n = 595) and healthy children (n = 350) were recruited. Carriage of pneumococcus was determined by culture and lytA PCR in the nasopharyngeal samples. Serotype/serogroup detection and its quantification were done by the nanofluidic real time PCR system. Spearman''s correlation and logistic regression were used to examine a correlation of serotype/serogroup specific bacterial load with its prevalence and an association of co-colonization with ARI respectively.

Results

Serotype/serogroup specific bacterial load was correlated with its prevalence, both in ARI cases (Spearman''s rho = 0.44, n = 186; P<0.0001) and healthy children (Spearman''s rho = 0.41, n = 115; P<0.0001). The prevalence of multiple serotypes was more common in ARI cases than in healthy children (18.5% vs 7.1%; aOR 2.92, 95% CI: 1.27–6.71; P = 0.01). The dominant serotype in the co-colonization had a 2 log10 higher bacterial load than the subdominant serotype, both in ARI cases (P<0.001) and healthy children (P<0.05).

Conclusions

High bacterial load in the nasopharynx may help transmit pneumococci among hosts, and increase the chance of successful acquisition and colonization. Co-colonization of multiple serotypes of pneumococci is linked with ARI, which infers the interactions of multiple serotypes may increase their pathogenicity; however, they may compete for growth in number.     

Viral RNAs Are Unusually Compact

A majority of viruses are composed of long single-stranded genomic RNA molecules encapsulated by protein shells with diameters of just a few tens of nanometers. We examine the extent to which these viral RNAs have evolved to be physically compact molecules to facilitate encapsulation. Measurements of equal-length viral, non-viral, coding and non-coding RNAs show viral RNAs to have among the smallest sizes in solution, i.e., the highest gel-electrophoretic mobilities and the smallest hydrodynamic radii. Using graph-theoretical analyses we demonstrate that their sizes correlate with the compactness of branching patterns in predicted secondary structure ensembles. The density of branching is determined by the number and relative positions of 3-helix junctions, and is highly sensitive to the presence of rare higher-order junctions with 4 or more helices. Compact branching arises from a preponderance of base pairing between nucleotides close to each other in the primary sequence. The density of branching represents a degree of freedom optimized by viral RNA genomes in response to the evolutionary pressure to be packaged reliably. Several families of viruses are analyzed to delineate the effects of capsid geometry, size and charge stabilization on the selective pressure for RNA compactness. Compact branching has important implications for RNA folding and viral assembly.     

Artificial Neural Network Inference (ANNI): A Study on Gene-Gene Interaction for Biomarkers in Childhood Sarcomas

Objective

To model the potential interaction between previously identified biomarkers in children sarcomas using artificial neural network inference (ANNI).

Method

To concisely demonstrate the biological interactions between correlated genes in an interaction network map, only 2 types of sarcomas in the children small round blue cell tumors (SRBCTs) dataset are discussed in this paper. A backpropagation neural network was used to model the potential interaction between genes. The prediction weights and signal directions were used to model the strengths of the interaction signals and the direction of the interaction link between genes. The ANN model was validated using Monte Carlo cross-validation to minimize the risk of over-fitting and to optimize generalization ability of the model.

Results

Strong connection links on certain genes (TNNT1 and FNDC5 in rhabdomyosarcoma (RMS); FCGRT and OLFM1 in Ewing’s sarcoma (EWS)) suggested their potency as central hubs in the interconnection of genes with different functionalities. The results showed that the RMS patients in this dataset are likely to be congenital and at low risk of cardiomyopathy development. The EWS patients are likely to be complicated by EWS-FLI fusion and deficiency in various signaling pathways, including Wnt, Fas/Rho and intracellular oxygen.

Conclusions

The ANN network inference approach and the examination of identified genes in the published literature within the context of the disease highlights the substantial influence of certain genes in sarcomas.     

Impact of Combined Clenbuterol and Metoprolol Therapy on Reverse Remodelling during Mechanical Unloading

Background

Clenbuterol (Cl), a β₂ agonist, is associated with enhanced myocardial recovery during left ventricular assist device (LVAD) support, and exerts beneficial remodelling effects during mechanical unloading (MU) in rodent heart failure (HF). However, the specific effects of combined Cl+β₁ blockade during MU are unknown.

Methods and Results

We studied the chronic effects (4 weeks) of β₂-adrenoceptor (AR) stimulation via Cl (2 mg/kg/day) alone, and in combination with β₁-AR blockade using metoprolol ((Met), 250 mg/kg/day), on whole heart/cell structure, function and excitation-contraction (EC) coupling in failing (induced by left coronary artery (LCA) ligation), and unloaded (induced by heterotopic abdominal heart transplantation (HATx)) failing rat hearts. Combined Cl+Met therapy displayed favourable effects in HF: Met enhanced Cl''s improvement in ejection fraction (EF) whilst preventing Cl-induced hypertrophy and tachycardia. During MU combined therapy was less beneficial than either mono-therapy. Met, not Cl, prevented MU-induced myocardial atrophy, with increased atrophy occurring during combined therapy. MU-induced recovery of Ca²⁺ transient amplitude, speed of Ca²⁺ release and sarcoplasmic reticulum Ca²⁺ content was enhanced equally by Cl or Met mono-therapy, but these benefits, together with Cl''s enhancement of sarcomeric contraction speed, and MU-induced recovery of Ca²⁺ spark frequency, disappeared during combined therapy.

Conclusions

Combined Cl+Met therapy shows superior functional effects to mono-therapy in rodent HF, but appears inferior to either mono-therapy in enhancing MU-induced recovery of EC coupling. These results suggest that combined β₂-AR simulation +β₁-AR blockade therapy is likely to be a safe and beneficial therapeutic HF strategy, but is not as effective as mono-therapy in enhancing myocardial recovery during LVAD support.     

Whole Genome Sequencing and Analysis of Plant Growth Promoting Bacteria Isolated from the Rhizosphere of Plantation Crops Coconut,Cocoa and Arecanut

Coconut, cocoa and arecanut are commercial plantation crops that play a vital role in the Indian economy while sustaining the livelihood of more than 10 million Indians. According to 2012 Food and Agricultural organization''s report, India is the third largest producer of coconut and it dominates the production of arecanut worldwide. In this study, three Plant Growth Promoting Rhizobacteria (PGPR) from coconut (CPCRI-1), cocoa (CPCRI-2) and arecanut (CPCRI-3) characterized for the PGP activities have been sequenced. The draft genome sizes were 4.7 Mb (56% GC), 5.9 Mb (63.6% GC) and 5.1 Mb (54.8% GB) for CPCRI-1, CPCRI-2, CPCRI-3, respectively. These genomes encoded 4056 (CPCRI-1), 4637 (CPCRI-2) and 4286 (CPCRI-3) protein-coding genes. Phylogenetic analysis revealed that both CPCRI-1 and CPCRI-3 belonged to Enterobacteriaceae family, while, CPCRI-2 was a Pseudomonadaceae family member. Functional annotation of the genes predicted that all three bacteria encoded genes needed for mineral phosphate solubilization, siderophores, acetoin, butanediol, 1-aminocyclopropane-1-carboxylate (ACC) deaminase, chitinase, phenazine, 4-hydroxybenzoate, trehalose and quorum sensing molecules supportive of the plant growth promoting traits observed in the course of their isolation and characterization. Additionally, in all the three CPCRI PGPRs, we identified genes involved in synthesis of hydrogen sulfide (H₂S), which recently has been proposed to aid plant growth. The PGPRs also carried genes for central carbohydrate metabolism indicating that the bacteria can efficiently utilize the root exudates and other organic materials as energy source. Genes for production of peroxidases, catalases and superoxide dismutases that confer resistance to oxidative stresses in plants were identified. Besides these, genes for heat shock tolerance, cold shock tolerance and glycine-betaine production that enable bacteria to survive abiotic stress were also identified.     

Sequence Diversity of the Nucleoprotein Gene of Peanut bud necrosis virus Isolates from South India

Peanut bud necrosis virus (PBNV), genus Tospovirus (family Bunyaviridae), is an important virus infecting peanut and other crops in South India. PBNV isolates naturally infecting groundnut, brinjal, tomato, black gram, field bean, cowpea, cotton, jute, taro and Calotropis plants were collected from different regions of South India and characterized. Infection was confirmed by direct antigen‐coating enzyme‐linked immunosorbent assay (DAC‐ELISA) using PBNV‐specific antiserum. The coat protein gene was further amplified using PBNV coat protein‐specific primers. The amplicon (830 bp) was cloned and sequenced; sequence analysis revealed that the N gene shared 93–100% and 95–100% sequence identity with PBNV at the nucleotide and amino acid levels, respectively.     

Microsatellite Markers to Determine Population Genetic Structure in the Golden Anchovy,Coilia dussumieri

Coilia dussumieri (Valenciennes, 1848) commonly called as golden anchovy, constitutes a considerable fishery in the northern part of both the west and east coasts of India. Despite its clear-cut geographic isolation, the species is treated as a unit stock for fishery management purposes. We evaluated 32 microsatellite primer pairs from three closely related species (resource species) belonging to the family Engraulidae through cross-species amplification in C. dussumieri. Successful cross-priming was obtained with 10 loci, which were sequenced for confirmation of repeats. Loci were tested for delineating the genetic stock structure of four populations of C. dussumieri from both the coasts of India. The number of alleles per locus ranged from 8 to 18, with a mean of 12.3. Results of pairwise F _ST indicated genetic stock structuring between the east and west coast populations of India and also validated the utilization of identified microsatellite markers in population genetic structure analysis.