A thin quartz cell suitable for vacuum ultraviolet absorption and circular dichroism measurements

The design of a thin quartz cell suitable for absorption and circular dichroism measurements in the vacuum ultraviolet is described. Important features of the cell are (1) that it can be disassembled for cleaning and reproducibly reassembled with path lengths up to 0.3 mm, and (2) that strain in the windows from the compressed sample can be relieved by a sample overflow port. The latter feature allows the cell to be used for circular dichroism as well as absorption measurements.     

New preparation techniques for molecular and in‐situ analysis of ancient organic micro‐ and nanostructures

Organic microfossils preserved in three dimensions in transparent mineral matrices such as cherts/quartzites, phosphates, or carbonates are best studied in petrographic thin sections. Moreover, microscale mass spectrometry techniques commonly require flat, polished surfaces to minimize analytical bias. However, contamination by epoxy resin in traditional petrographic sections is problematic for the geochemical study of the kerogen in these microfossils and more generally for the in situ analysis of fossil organic matter. Here, we show that epoxy contamination has a molecular signature that is difficult to distinguish from kerogen with time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS). This contamination appears pervasive in organic microstructures embedded in micro‐ to nano‐crystalline carbonate. To solve this problem, a new semi‐thin section preparation protocol without resin medium was developed for micro‐ to nanoscale in situ investigation of insoluble organic matter. We show that these sections are suited for microscopic observation of Proterozoic microfossils in cherts. ToF‐SIMS reveals that these sections are free of pollution after final removal of a <10 nm layer of contamination using low‐dose ion sputtering. ToF‐SIMS maps of fragments from aliphatic and aromatic molecules and organic sulfur are correlated with the spatial distribution of organic microlaminae in a Jurassic stromatolite. Hydrocarbon‐derived ions also appeared correlated with kerogenous microstructures in Archean cherts. These developments in analytical procedures should help future investigations of organic matter and in particular, microfossils, by allowing the spatial correlation of microscopy, spectroscopy, precise isotopic microanalyses, and novel molecular microanalyses such as ToF‐SIMS.     

Sampling strategy optimization to increase statistical power in landscape genomics: A simulation‐based approach

An increasing number of studies are using landscape genomics to investigate local adaptation in wild and domestic populations. Implementation of this approach requires the sampling phase to consider the complexity of environmental settings and the burden of logistical constraints. These important aspects are often underestimated in the literature dedicated to sampling strategies. In this study, we computed simulated genomic data sets to run against actual environmental data in order to trial landscape genomics experiments under distinct sampling strategies. These strategies differed by design approach (to enhance environmental and/or geographical representativeness at study sites), number of sampling locations and sample sizes. We then evaluated how these elements affected statistical performances (power and false discoveries) under two antithetical demographic scenarios. Our results highlight the importance of selecting an appropriate sample size, which should be modified based on the demographic characteristics of the studied population. For species with limited dispersal, sample sizes above 200 units are generally sufficient to detect most adaptive signals, while in random mating populations this threshold should be increased to 400 units. Furthermore, we describe a design approach that maximizes both environmental and geographical representativeness of sampling sites and show how it systematically outperforms random or regular sampling schemes. Finally, we show that although having more sampling locations (between 40 and 50 sites) increase statistical power and reduce false discovery rate, similar results can be achieved with a moderate number of sites (20 sites). Overall, this study provides valuable guidelines for optimizing sampling strategies for landscape genomics experiments.     

Individual‐level leaf trait variation and correlation across biological and spatial scales

Even with increasing interest in the ecological importance of intraspecific trait variation (ITV) for better understanding ecological processes, few studies have quantified ITV in seedlings and assessed constraints imposed by trade‐offs and correlations among individual‐level leaf traits. Estimating the amount and role of ITV in seedlings is important to understand tree recruitment and long‐term forest dynamics. We measured ten different size, economics, and whole leaf traits (lamina and petiole) for more than 2,800 seedlings (height ≥ 10 cm and diameter at breast height < 1 cm) in 283 seedling plots and then quantified the amount of ITV and trait correlations across two biological (intraspecific and interspecific) and spatial (within and among plots) scales. Finally, we explored the effects of trait variance and sample size on the strength of trait correlations. We found about 40% (6%–63%) variation in leaf‐level traits was explained by ITV across all traits. Lamina and petiole traits were correlated across biological and spatial scales, whereas leaf size traits (e.g., lamina area) were weakly correlated with economics traits (e.g., specific lamina area); lamina mass ratio was strongly related to the petiole length. Trait correlations varied among species, plots, and different scales but there was no evidence that the strength of trait relationships was stronger at broader than finer biological and spatial scales. While larger trait variance increased the strength of correlations, the sample size was the most important factor that was negatively related to the strength of trait correlations. Our results showed that a large amount of trait variation was explained by ITV, which highlighted the importance of considering ITV when using trait‐based approaches in seedling ecology. In addition, sample size was an important factor that influenced the strength of trait correlations, which suggests that comparing trait correlations across studies should consider the differences in sample size.     

Placental tissue metabolome analysis by GC-MS: Oven-drying is a viable sample preparation method

Abstract

Analysis of the human placenta metabolome has great potential to advance the understanding of complicated pregnancies and deleterious fetal outcomes in remote populations, but samples preparation can present unique challenges. Herein, we introduce oven-drying as a simple and widely available method of sample preparation that will facilitate investigations of the placental metabolome from remote and under-studied populations. Placentae from complicated and uncomplicated pregnancies were prepared in three ways (oven-dried at 60?°C, fresh, lyophilized) for metabolome analysis via gas chromatography-mass spectrometry (GC-MS). Multiple computer models (e.g. PLS-DA, ANN) were employed to classify and determine if there was a difference in placentae metabolome and a group of metabolites with high variable importance in projection scores across the three preparations and by complicated vs. control groups. The analyses used herein were shown to be thorough and sensitive. Indeed, significant differences were detected in metabolomes of complicated vs. uncomplicated pregnancies; however, there were no statistical differences in the metabolome of placentae prepared by oven-drying vs. lyophilization vs. fresh placentae. Oven-drying is a viable sample preparation method for placentae intended for use in metabolite analysis via GC-MS. These results open many possibilities for researching metabolome patterns associated with fetal outcomes in remote and resource-poor communities worldwide.     

High throughput preparation of fly genomic DNA in 96-well format using a paint-shaker

Sample homogenization is an essential step for genomic DNA extraction, with multiple downstream applications in Molecular Biology. Genotyping hundreds or thousands of samples requires an automation of this homogenization step, and high throughput homogenizer equipment currently costs 7000 euros or more. We present an apparatus for homogenization of individual Drosophila adult flies in 96-well micro-titer dishes, which was built from a small portable paint-shaker (F5 portable paint-shaker, Ushake). Single flies are disrupted in each well that contains extraction buffer and a 4-mm metal ball. Our apparatus can hold up to five 96-well micro-titer plates. Construction of the homogenizer apparatus takes about 3–4 days, and all equipment can be obtained from a home improvement store. The total material cost is approximately 700 euros including the paint-shaker. We tested the performance of our apparatus using the ZR-96 Quick-gDNA? kit (Zymo Research) homogenization buffer and achieved nearly complete tissue homogenization after 15 minutes of shaking. PCR tests did not detect any cross contamination between samples of neighboring wells. We obtained on average 138 ng of genomic DNA per fly, and DNA quality was adequate for standard PCR applications. In principle, our tissue homogenizer can be used for isolation of DNA suitable for library production and high throughput genotyping by Multiplexed Shotgun Genotyping (MSG), as well as RNA isolation from single flies. The sample adapter can also hold and shake other items, such as centrifuge tubes (15–50 mL) or small bottles.     

Monitoring vegetation change caused by trampling: a study in the Cairngorms,Scotland

Summary

A study was made in the Cairngorms, Scotland to make recommendations for a monitoring scheme capable of detecting changes in the vegetation caused by recreational pressure following the development of a funicular railway. Four methods were used in field trials to assess percentage cover of plant species and gravel, rock and bare ground, where appropriate, in two vegetation types (open and closed). The methods used were visual estimates in 50 × 40 cm quadrats (Q), the mean of visual estimates in twenty 10 × 10 cm sub-quadrats of the 50 × 40 cm quadrats (Q₂₀), a modified point intercept method (RL) and photography. Variances between observers and between-quadrats were estimated for the different methods. The sampling design for detecting change was based on a model of variance, constructed from field trial data.

Between-observer and between-quadrat variances were related to mean percentage cover and approximated to a binomial distribution. The between-quadrat variance was larger than observer variance. The Q₂₀ method achieved appreciably better precision than the other methods. Analysis of half of the 10 × 10 cmsub-quadrats (1/2Q₂₀) selected in a checker board design achieved a relative efficiency of 78% compared with the Q₂₀. This result suggests that comparable precision to the Q₂₀ method could be achieved by choosing about 14 sub-quadrats in a larger quadrat, thus saving some time. Variation between quadrats also suggested that the Q₂₀ method was the one of choice for maximising precision. The precision of the photographic method was based on fewer data points, so is less accurate than other estimates.

Minimum sample sizes were estimated for detecting a 10% relative change of a species in open vegetation with 30% cover (i.e. a change from 30% to <27 or to >33% cover). With a 10 % Type II error rate and 5 % Type I error rate the minimum sample sizes were 47 quadrats for Q, 18 for Q ₂₀, 43 for RL, and 23 for the means of ten 10 × 10 cm sub-quadrats in open vegetation.

The most time-efficient field recording appeared to be the use of Q despite the required sample size being 2.6 times higher than that of Q₂₀. The far lower time requirement per quadrat, however, compensated for the higher numbers. The number of quadrats would depend on the specified change in percentage cover and on the statistical significance level used. For example, to detect a 10% absolute change in cover (i.e. from 30% to either <20 % or >40 % cover) at 95 % probability the net effective recording time is estimated at 5 h per vegetation type while to detect a 5 % change at 99 % probability would require c. 25 h. Larger samples may be required for other species or for species with a low initial cover.