Estimating the success of enzyme bioprospecting through metagenomics: current status and future trends

Recent reports have suggested that the establishment of industrially relevant enzyme collections from environmental genomes has become a routine procedure. Across the studies assessed, a mean number of approximately 44 active clones were obtained in an average size of approximately 53 000 clones tested using naïve screening protocols. This number could be significantly increased in shorter times when novel metagenome enzyme sequences obtained by direct sequencing are selected and subjected to high‐throughput expression for subsequent production and characterization. The pre‐screening of clone libraries by naïve screens followed by the pyrosequencing of the inserts allowed for a 106‐fold increase in the success rate of identifying genes encoding enzymes of interest. However, a much longer time, usually on the order of years, is needed from the time of enzyme identification to the establishment of an industrial process. If the hit frequency for the identification of enzymes performing at high turnover rates under real application conditions could be increased while still covering a high natural diversity, the very expensive and time‐consuming enzyme optimization phase would likely be significantly shortened. At this point, it is important to review the current knowledge about the success of fine‐tuned naïve‐ and sequence‐based screening protocols for enzyme selection and to describe the environments worldwide that have already been subjected to enzyme screen programmes through metagenomic tools. Here, we provide such estimations and suggest the current challenges and future actions needed before environmental enzymes can be successfully introduced into the market.     

Investigating the effects of point mutations on the affinity between the cyanobacterial lectin microvirin and high mannose-type glycans present on the HIV envelope glycoprotein

Human immunodeficiency virus (HIV) infections continue to exert an enormous impact on global human health. This led experts to emphasize the importance of new measures for preventing HIV infections, including the development of vaccines and novel drugs. In this context, a promising approach involves the use of lectins that can bind the surface envelope glycoprotein gp120 of HIV with high affinity, preventing viral entry. The cyanobacterial lectin microvirin (MVN) has been proposed as a candidate for development as a topical microbicide because of its ability to bind to high mannose-type glycans, potently inhibiting HIV-1 entry. Thus, the aim of this computational study was to investigate the effects of four point mutations (D53Q, D53E, D53K, and D53W) on the structure and affinity of MVN with di-mannose (MAN). Molecular dynamics simulations followed by binding free energy calculations using MM-GBSA were employed. The calculated binding free energy of ligand-receptor complexation of MVN with MAN was ?26.02 kcal mol^-1. We identified in the wild-type protein that residues I45, T59, and Q81 have a major contribution to the binding free energy of di-mannose. Among the investigated mutants, the most promising one was the D53W mutation, with a theoretical binding free energy value of ?29.16 kcal mol^-1. We suggest that this increased stability is due to the introduction of extra rigidity on the hinge region connecting two key structural elements of the MVN binding site.     

Investigating DNA Radiation Damage Using X-Ray Absorption Spectroscopy

The biological influence of radiation on living matter has been studied for years; however, several questions about the detailed mechanism of radiation damage formation remain largely unanswered. Among all biomolecules exposed to radiation, DNA plays an important role because any damage to its molecular structure can affect the whole cell and may lead to chromosomal rearrangements resulting in genomic instability or cell death. To identify and characterize damage induced in the DNA sugar-phosphate backbone, in this work we performed x-ray absorption spectroscopy at the P K-edge on DNA irradiated with either UVA light or protons. By combining the experimental results with theoretical calculations, we were able to establish the types and relative ratio of lesions produced by both UVA and protons around the phosphorus atoms in DNA.     

Habitat structure influences the song characteristics within a population of Great Tits Parus major

Capsule: The structure of Great Tit Parus major songs is shaped by the acoustic properties of the habitat within the breeding territory of individuals.

Aim: To test whether the structure of the habitat influences song structure within a population of Great Tits P. major.

Methods: We recorded Great Tit songs from 42 territories on two different days and measured the habitat structure in each territory. We also trapped the males and estimated the breeding density around each territory, so were able to control the analysis by date, breeding density and male characteristics.

Results: Song pause length was positively affected by the ground cover, while the song rate and the minimum frequency were negatively affected by the shrub cover. Male size negatively affected the peak frequency of the songs, whereas the age of the males affected the frequency range; older males sang with a broader bandwidth.

Conclusion: This study suggests that Great Tits are capable of adjusting their vocalizations in each territory, presumably to enhance transmission owing to vocal plasticity.     

The effect of intraspecific variation and heritability on community pattern and robustness

Intraspecific trait variation is widespread in nature, yet its effects on community dynamics are not well understood. Here we explore the consequences of intraspecific trait variation for coexistence in two‐ and multispecies competitive communities. For two species, the likelihood of coexistence is in general reduced by intraspecific variation, except when the species have almost equal trait means but different trait variances, such that one is a generalist and the other a specialist consumer. In multispecies communities, the only strong effect of non‐heritable intraspecific variation is to reduce expected species richness. However, when intraspecific variation is heritable, allowing for the possibility of trait evolution, communities are much more resilient against environmental disturbance and exhibit far more predictable trait patterns. Our results are robust to varying model parameters and relaxing model assumptions.     

Diabetes screening intervals based on risk stratification

Background

Guidelines for frequency of Type 2 diabetes mellitus (DM) screening remain unclear, with proposed screening intervals typically based on expert opinion. This study aims to demonstrate that HbA1c screening intervals may differ substantially when considering individual risk for diabetes.

Methods

This was a multi-institutional retrospective open cohort study. Data were collected between April 1999 to March 2014 from one urban and one rural cohort in Japan. After categorization by age, we stratified individuals based on cardiovascular disease risk (Framingham 10-year cardiovascular risk score) and body mass index (BMI). We adapted a signal-to-noise method for distinguishing true HbA1c change from measurement error by constructing a linear random effect model to calculate signal and noise of HbA1c. Screening interval for HbA1c was defined as informative when the signal-to-noise ratio exceeded 1.

Results

Among 96,456 healthy adults, 46,284 (48.0%) were male; age (range) and mean HbA1c (SD) were 48 (30–74) years old and 5.4 (0.4)%, respectively. As risk increased among those 30–44 years old, HbA1c screening intervals for detecting Type 2 DM consistently decreased: from 10.5 (BMI <18.5) to 2.4 (BMI?>?30) years, and from 8.0 (Framingham Risk Score <10%) to 2.0 (Framingham Risk Score ≥20%) years. This trend was consistent in other age and risk groups as well; among obese 30–44 year olds, we found substantially shorter intervals compared to other groups.

Conclusion

HbA1c screening intervals for identification of DM vary substantially by risk factors. Risk stratification should be applied when deciding an optimal HbA1c screening interval in the general population to minimize overdiagnosis and overtreatment.