Verification and Rapid Identification of Soybean Rhizobia in Indian Soils

Sixty root nodule isolates of soybean rhizobia indigenous to eight field sites in India were characterized using PCR-RFLP for repeated sequence RSα a 1195-bp DNA fragment, indole acetic acid production, and nitrogenase activity. Site-dependent variations were observed in terms of IAA production and nitrogenase activities. RSα was conserved in slow-growing soybean rhizobia across locations and sites and was absent in other Rhizobiaceae members and other bacterial genera. The results suggest that RSα can be a useful molecular marker for slow-growing soybean rhizobia. The study also showed the low presence of soybean nodulating fast growers in Indian soils.     

Losing the trait without losing the signal: Evolutionary shifts in communicative colour signalling

Colour signalling traits are often lost over evolutionary time, perhaps because they increase vulnerability to visual predators or lose relevance in terms of sexual selection. Here, we used spectrometric and phylogenetic comparative analyses to ask whether four independent losses of a sexually selected blue patch are spectrally similar, and whether these losses equate to a decrease in conspicuousness or to loss of a signal. We found that patches were lost in two distinct ways: either increasing reflectance primarily at very long or at very short wavelengths, and that species with additional colour elements (UV, green and pink) may be evolutionary intermediates. In addition, we found that patch spectral profiles of all species were closely aligned with visual receptors in the receiver's retina. We found that loss of the blue patch makes males less conspicuous in terms of chromatic conspicuousness, but more conspicuous in terms of achromatic contrast, and that sexual dimorphism often persists regardless of patch loss. Dorsal surfaces were considerably more cryptic than were ventral surfaces, and species in which male bellies were the most similar in conspicuousness to their dorsal surfaces were also the most sexually dimorphic. These results emphasize the consistent importance of sexual selection and its flexible impact on different signal components through evolutionary time.     

Genotype-Phenotype Correlations in CYP1B1-Associated Primary Congenital Glaucoma Patients Representing Two Large Cohorts from India and Brazil

BackgroundPrimary congenital glaucoma (PCG), occurs due to the developmental defects in the trabecular meshwork and anterior chamber angle in children. PCG exhibits genetic heterogeneity and the CYP1B1 gene has been widely implicated worldwide. Despite the diverse mutation spectra, the clinical implications of these mutations are yet unclear. The present study attempted to delineate the clinical profile of PCG in the background of CYP1B1 mutations from a large cohort of 901 subjects from India (n=601) and Brazil (n=300).MethodsGenotype-phenotype correlations was undertaken on clinically well characterized PCG cases from India (n=301) and Brazil (n=150) to assess the contributions of CYP1B1 mutation on a set of demographic and clinical parameters. The demographic (gender, and history of consanguinity) and quantitative clinical (presenting intraocular pressure [IOP] and corneal diameter [CD]) parameters were considered as binary and continuous variables, respectively, for PCG patients in the background of the overall mutation spectra and also with respect to the prevalent mutations in India (R368H) and Brazil (4340delG). All these variables were fitted in a multivariate logistic regression model using the Akaike Information Criterion (AIC) to estimate the adjusted odds ratio (OR) using the R software (version 2.14.1).ResultsThe overall mutation spectrum were similar across the Indian and Brazilian PCG cases, despite significantly higher number of homozygous mutations in the former (p=0.024) and compound heterozygous mutations in the later (p=0.012). A wide allelic heterogeneity was observed and only 6 mutations were infrequently shared between these two populations. The adjusted ORs for the binary (demographic) and continuous (clinical) variables did not indicate any susceptibility to the observed mutations (p>0.05).ConclusionsThe present study demonstrated a lack of genotype-phenotype correlation of the demographic and clinical traits to CYP1B1 mutations in PCG at presentation. However, the susceptibility of these mutations to the long-term progression of these traits are yet to be deciphered.     

Prevalence of Escherichia coli in surface waters of Southeast Asian cities

Surface water samples were collected from rivers which fed into large urban areas within Vietnam, Indonesia, Cambodia, and Thailand and were processed to enumerate Escherichia coli. Selected isolates were further characterized using PCR to detect the presence of specific virulence genes. Analyzing the four countries together, the approximate mean cfu/100 ml for E. coli counts in the dry season were log 4.3, while counts in the wet season were log 2.8. Of the 564 E. coli isolates screened for the presence of pathogenic genes, 3.9 % possessed at least one virulence gene. The most common pathogenic types found were Shiga toxin-producing E. coli isolates. These results reinforce the importance of monitoring urban surface waters for fecal contamination, that E. coli in these water environments may serve as opportunistic pathogens, and may help in determining the impact water usage from these rivers have on the public health of urban populations in Southeast Asia.     

Solid cancer risk dependence on the Pasquill–Gifford atmospheric stability classes in a radiological event

In a radiological event, the lack of preliminary information about the site of explosion and the difficulty in predicting the accurate path and distribution of radioactive plumes makes it difficult to predict expected health effects of exposed individuals. So far, in such a health evaluation, radiation-induced stochastic health effects such as cancer are not included. The Pasquill–Gifford atmospheric classes generally allow connecting atmospheric stability with dispersion of radioactive contaminants to the environment. In this work, an environmental release of radioactive Cs-137 was simulated and the resulting relative risk for solid cancer incidence among the affected population calculated. The HotSpot health physics code was used to simulate the radioactive atmospheric dispersion and calculate the Total Effective Dose Equivalent (TEDE), which was then used to estimate the relative risk of cancer incidence. The main results from this work suggest that the relative cancer risk and atmospheric stability classes are linked by differences in the TEDE. Such a finding may support triage, because it adds additional information on the potentially affected population at the early stages of an emergency response.     

Evaluating the Growth Potential of Pathogenic Bacteria in Water

The degree to which a water sample can potentially support the growth of human pathogens was evaluated. For this purpose, a pathogen growth potential (PGP) bioassay was developed based on the principles of conventional assimilable organic carbon (AOC) determination, but using pure cultures of selected pathogenic bacteria (Escherichia coli O157, Vibrio cholerae, or Pseudomonas aeruginosa) as the inoculum. We evaluated 19 water samples collected after different treatment steps from two drinking water production plants and a wastewater treatment plant and from ozone-treated river water. Each pathogen was batch grown to stationary phase in sterile water samples, and the concentration of cells produced was measured using flow cytometry. In addition, the fraction of AOC consumed by each pathogen was estimated. Pathogen growth did not correlate with dissolved organic carbon (DOC) concentration and correlated only weakly with the concentration of AOC. Furthermore, the three pathogens never grew to the same final concentration in any water sample, and the relative ratio of the cultures to each other was unique in each sample. These results suggest that the extent of pathogen growth is affected not only by the concentration but also by the composition of AOC. Through this bioassay, PGP can be included as a parameter in water treatment system design, control, and operation. Additionally, a multilevel concept that integrates the results from the bioassay into the bigger framework of pathogen growth in water is discussed. The proposed approach provides a first step for including pathogen growth into microbial risk assessment.Pathogenic bacteria can survive and also grow in low-nutrient aquatic environments, such as surface waters or man-made water treatment systems (2, 17, 30). Studies on pathogen survival and/or die-off (including disinfection) in water are common, but little is known about the fundamental factors governing their growth in the environment (34, 35). Understanding the growth of pathogenic bacteria in aquatic ecosystems is essential for a holistic approach to microbial risk assessment as well as for improving drinking water treatment design and operation.A key factor governing growth of all organisms is nutrient availability. All human pathogens are heterotrophs, utilizing organic compounds as their carbon and energy source. Natural organic matter in water comprises a broad spectrum of many different compounds; it is usually determined as a bulk parameter, such as dissolved organic carbon (DOC). Only a fraction (0.1 to 44%) of this DOC pool is readily available for bacterial growth (18, 33). This bioavailable fraction is quantified using bioassays, such as the biodegradable dissolved organic carbon (BDOC) assay (27) or the assimilable organic carbon (AOC) assay (31). Typically, AOC represents small molecules readily available for growth, whereas BDOC can also include larger molecular compounds, which require predegradation before they can be taken up by microbial cells. Results from both of these assays are commonly used as indicators for bacterial growth potential and have previously been associated with regrowth and biofilm formation in drinking water distribution systems (7, 20, 32).Previous studies have pointed toward an apparent correlation between the concentration of AOC and the presence of enteric bacteria. For example, during two large surveys of drinking water treatment systems across North America, the occurrence (presence/absence) of coliform bacteria was found to be elevated above an AOC concentration of 100 μg liter⁻¹ (4, 21). Other studies also found that AOC concentrations were directly correlated to growth of pathogenic bacteria (30, 34, 35). However, AOC is a bulk parameter, which includes many different substrates (e.g., amino acids, sugars, and fatty acids) readily available for heterotrophic growth. Hence, its composition can differ distinctly, and it is assumed that every aquatic environment carries a complex and unique “fingerprint” of utilizable organic carbon compounds (22). Moreover, the spectrum of growth-supporting substrates (carbon compounds) of individual bacterial strains is specific—a fact also used for the classification of bacteria for taxonomic purposes. This principle has been integrated into conventional AOC assays, where the specific substrate spectrum of different pure cultures can be used to quantify different types of compounds present in water (26, 33). The term “pathogenic bacteria” is a collective term for many different bacterial species that can all cause disease in humans but their individual substrate spectra are unique for each species. Thus, we have hypothesized that the total concentration of AOC alone is not a sufficient parameter for describing the growth potential of pathogenic bacteria; the quality of the available carbon compounds has to be considered as well.There is no existing method that is capable of fractionating organic carbon in a way that allows for the quantification of individual compounds that support growth of specific pathogens. In this study, we have developed a pathogen growth potential (PGP) assay by combining the conventional AOC assay (31) with flow cytometric quantification of bacterial growth (11) and using pathogens as inocula. The PGP assay yields two main results, namely, (i) the extent of pathogen growth, and (ii) the relative fraction of AOC consumed by a pathogen. With this approach, we investigated the growth potential of three model pathogens from three different genera, namely, Escherichia coli O157, Vibrio cholerae O1, and Pseudomonas aeruginosa, in a broad range of water samples, differing considerably in their origin and quality.