Remote detection of invasive plants: a review of spectral,textural and phenological approaches

Remote sensing image analysis is increasingly being used as a tool for mapping invasive plant species. Resulting distribution maps can be used to target management of early infestations and to model future invasion risk. Remote identification of invasive plants based on differences in spectral signatures is the most common approach, typically using hyperspectral data. But several studies have found that textural and phenological differences are also effective approaches for identifying invasive plants. I review examples of remote detection of invasive plants based on spectral, textural and phenological analysis and highlight circumstances where the different approaches are likely to be most effective. I also review sources and availability of remotely sensed data that could be used for mapping and suggest field data collection approaches that would support the analysis of remotely sensed data. Remote mapping of biological invasions remains a relatively specialized research topic, but the distinct cover, morphology and/or seasonality of many invaded versus native ecosystems suggests that more species could be detected remotely. Remote sensing can sometimes support early detection and rapid response directly, however, accurately detecting small, nascent populations is a challenge. However, even maps of heavily infested areas can provide a valuable tool for risk assessment by increasing knowledge about temporal and spatial patterns and predictors of invasion.     

Identifying Early Changes in Myocardial Microstructure in Hypertensive Heart Disease

The transition from healthy myocardium to hypertensive heart disease is characterized by a series of poorly understood changes in myocardial tissue microstructure. Incremental alterations in the orientation and integrity of myocardial fibers can be assessed using advanced ultrasonic image analysis. We used a modified algorithm to investigate left ventricular myocardial microstructure based on analysis of the reflection intensity at the myocardial-pericardial interface on B-mode echocardiographic images. We evaluated the extent to which the novel algorithm can differentiate between normal myocardium and hypertensive heart disease in humans as well as in a mouse model of afterload resistance. The algorithm significantly differentiated between individuals with uncomplicated essential hypertension (N = 30) and healthy controls (N = 28), even after adjusting for age and sex (P = 0.025). There was a trend in higher relative wall thickness in hypertensive individuals compared to controls (P = 0.08), but no difference between groups in left ventricular mass (P = 0.98) or total wall thickness (P = 0.37). In mice, algorithm measurements (P = 0.026) compared with left ventricular mass (P = 0.053) more clearly differentiated between animal groups that underwent fixed aortic banding, temporary aortic banding, or sham procedure, on echocardiography at 7 weeks after surgery. Based on sonographic signal intensity analysis, a novel imaging algorithm provides an accessible, non-invasive measure that appears to differentiate normal left ventricular microstructure from myocardium exposed to chronic afterload stress. The algorithm may represent a particularly sensitive measure of the myocardial changes that occur early in the course of disease progression.     

Expression of an endoglucanase from Tribolium castaneum (TcEG1) in Saccharomyces cerevisiae

Insects are a largely unexploited resource in prospecting for novel cellulolytic enzymes to improve the production of ethanol fuel from lignocellulosic biomass. The cost of lignocellulosic ethanol production is expected to decrease by the combination of cellulose degradation (saccharification) and fermentation of the resulting glucose to ethanol in a single process, catalyzed by the yeast Saccharomyces cerevisiae transformed to express efficient cellulases. While S. cerevisiae is an established heterologous expression system, there are no available data on the functional expression of insect cellulolytic enzymes for this species. To address this knowledge gap, S. cerevisiae was transformed to express the full‐length cDNA encoding an endoglucanase from the red flour beetle, Tribolium castaneum (TcEG1), and evaluated the activity of the transgenic product (rTcEG1). Expression of the TcEG1 cDNA in S. cerevisiae was under control of the strong glyceraldehyde‐3 phosphate dehydrogenase promoter. Cultured transformed yeast secreted rTcEG1 protein as a functional β‐1,4‐endoglucanase, which allowed transformants to survive on selective media containing cellulose as the only available carbon source. Evaluation of substrate specificity for secreted rTcEG1 demonstrated endoglucanase activity, although some activity was also detected against complex cellulose substrates. Potentially relevant to uses in biofuel production rTcEG1 activity increased with pH conditions, with the highest activity detected at pH 12. Our results demonstrate the potential for functional production of an insect cellulase in S. cerevisiae and confirm the stability of rTcEG1 activity in strong alkaline environments.     

Meeting report: Ocean ‘omics science,technology and cyberinfrastructure: current challenges and future requirements (August 20-23, 2013)

The National Science Foundation’s EarthCube End User Workshop was held at USC Wrigley Marine Science Center on Catalina Island, California in August 2013. The workshop was designed to explore and characterize the needs and tools available to the community that is focusing on microbial and physical oceanography research with a particular emphasis on ‘omic research. The assembled researchers outlined the existing concerns regarding the vast data resources that are being generated, and how we will deal with these resources as their volume and diversity increases. Particular attention was focused on the tools for handling and analyzing the existing data, on the need for the construction and curation of diverse federated databases, as well as development of shared, interoperable, “big-data capable” analytical tools. The key outputs from this workshop include (i) critical scientific challenges and cyber infrastructure constraints, (ii) the current and future ocean ‘omics science grand challenges and questions, and (iii) data management, analytical and associated and cyber-infrastructure capabilities required to meet critical current and future scientific challenges. The main thrust of the meeting and the outcome of this report is a definition of the ‘omics tools, technologies and infrastructures that facilitate continued advance in ocean science biology, marine biogeochemistry, and biological oceanography.     

Top‐down control of microbial activity and biomass in an Arctic soil ecosystem

Globally, soil microbes preside over vast carbon stores, and both microbial biomass and activity are known to be regulated by bottom‐up controls, that is, limitation by nutrients and energy. However, there is evidence that grazing by protozoans exerts top‐down controls on biomass. Here, we investigate top‐down control by phage on soil microbes using an experimental site near Barrow, Alaska (71°N, 157°W) during the 2007 growing season. Soil measurements were taken from sites that covered a range of microtopographical features within a drained and thawed lake basin including high‐ and low‐centred ice‐wedge polygons to estimate the availability of carbon and nitrogen for microbes. Using both field and laboratory experiments, we successfully increased both microbial biomass and respiration by decreasing phage populations. The addition of carbon and nutrients to soils had no significant effects on biomass or respiration, indicating a lack of bottom‐up controls. Additionally, we present the first use of tea extracts as a potent anti‐phage agent in soils. Our results suggest that top‐down controls, such as phage predation, are critical to regulation of microbial activities in Arctic soils.     

How old is this mutation? - a study of three Ashkenazi Jewish founder mutations

Background

Several founder mutations leading to increased risk of cancer among Ashkenazi Jewish individuals have been identified, and some estimates of the age of the mutations have been published. A variety of different methods have been used previously to estimate the age of the mutations. Here three datasets containing genotype information near known founder mutations are reanalyzed in order to compare three approaches for estimating the age of a mutation. The methods are: (a) the single marker method used by Risch et al., (1995); (b) the intra-allelic coalescent model known as DMLE, and (c) the Goldgar method proposed in Neuhausen et al. (1996), and modified slightly by our group. The three mutations analyzed were MSH2*1906 G->C, APC*I1307K, and BRCA2*6174delT.

Results

All methods depend on accurate estimates of inter-marker recombination rates. The modified Goldgar method allows for marker mutation as well as recombination, but requires prior estimates of the possible haplotypes carrying the mutation for each individual. It does not incorporate population growth rates. The DMLE method simultaneously estimates the haplotypes with the mutation age, and builds in the population growth rate. The single marker estimates, however, are more sensitive to the recombination rates and are unstable. Mutation age estimates based on DMLE are 16.8 generations for MSH2 (95% credible interval (13, 23)), 106 generations for I1037K (86-129), and 90 generations for 6174delT (71-114).

Conclusions

For recent founder mutations where marker mutations are unlikely to have occurred, both DMLE and the Goldgar method can give good results. Caution is necessary for older mutations, especially if the effective population size may have remained small for a long period of time.

     

Silencing gene expression by targeting chromosomal DNA with antigene peptide nucleic acids and duplex RNAs

The value of recognizing cellular RNA sequences by short interfering RNAs (siRNAs) in mammalian cells is widely appreciated, but what might be learned if it were also possible to recognize chromosomal DNA? Recognition of chromosomal DNA would have many applications, such as inhibiting gene expression, activating gene expression, introducing mutations, and probing chromosome structure and function. We have shown that antigene peptide nucleic acids (agPNAs) and antigene duplex RNAs (agRNAs) block gene expression and probe chromosomal DNA. Here we describe a protocol for designing antigene agents and introducing them into cells. This protocol can also be used to silence expression with PNAs or siRNAs that target mRNA. From preparation of oligomers to analysis of data, experiments with agPNAs and agRNAs require approximately 14 d and 9 d, respectively.