Linear discriminant analysis-based estimation of the false discovery rate for phosphopeptide identifications

The development of liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) has made it possible to characterize phosphopeptides in an increasingly large-scale and high-throughput fashion. However, extracting confident phosphopeptide identifications from the resulting large data sets in a similar high-throughput fashion remains difficult, as does rigorously estimating the false discovery rate (FDR) of a set of phosphopeptide identifications. This article describes a data analysis pipeline designed to address these issues. The first step is to reanalyze phosphopeptide identifications that contain ambiguous assignments for the incorporated phosphate(s) to determine the most likely arrangement of the phosphate(s). The next step is to employ an expectation maximization algorithm to estimate the joint distribution of the peptide scores. A linear discriminant analysis is then performed to determine how to optimally combine peptide scores (in this case, from SEQUEST) into a discriminant score that possesses the maximum discriminating power. Based on this discriminant score, the p- and q-values for each phosphopeptide identification are calculated, and the phosphopeptide identification FDR is then estimated. This data analysis approach was applied to data from a study of irradiated human skin fibroblasts to provide a robust estimate of FDR for phosphopeptides. The Phosphopeptide FDR Estimator software is freely available for download at http://ncrr.pnl.gov/software/.     

Comparative proteomics of human monkeypox and vaccinia intracellular mature and extracellular enveloped virions.

Orthopoxviruses are among the largest and most complex of the animal viruses. In response to the recent emergence of monkeypox in Africa and the threat of smallpox bioterrorism, two orthopoxviruses with different pathogenic potentials, human monkeypox virus and vaccinia virus, were proteomically compared with the goal of identifying proteins required for pathogenesis. Orthopoxviruses were grown in HeLa cells to two different viral forms (intracellular mature virus and extracellular enveloped virus), purified by sucrose gradient ultracentrifugation, denatured using RapiGest surfactant, and digested with trypsin. Unfractionated samples and strong cation exchange HPLC fractions were analyzed by high-resolution reversed-phase nano-LC-MS/MS, and analyses of the MS/MS spectra using SEQUEST and X! Tandem resulted in the confident identification of hundreds of monkeypox, vaccinia, and copurified host-cell proteins. The unfractionated samples were additionally analyzed by LC-MS using an LTQ-Orbitrap, and the accurate mass and elution time tag approach was used to perform quantitative comparisons. Possible pathophysiological roles of differentially abundant Orthopoxvirus proteins are discussed. Data, processed results, and protocols are available at http://www.proteomicsresource.org/.     

Ecologically heterogeneous populations of the invasive ant Wasmannia auropunctata within its native and introduced ranges

Abstract 1. The biology of most invasive species in their native geographical areas remains largely unknown. Such studies are, however, crucial in shedding light on the ecological and evolutionary processes underlying biological invasions. 2. The present study focuses on the little fire ant Wasmannia auropunctata, a species native to Central and South America that has been widely introduced and which has become invasive throughout the tropics. We characterise and compare several ecological traits of native populations in French Guiana with those in one of its introduced ranges, New Caledonia. 3. We found ecologically heterogeneous populations of W. auropunctata coexisting in the species’ native geographical area. First, we found populations restricted to naturally perturbed areas (particularly floodplains) within the primary forest, and absent from the surrounding forest areas. These populations were characterised by low nest and worker densities. Second, we found dominant populations in recent anthropogenic areas (e.g. secondary forest or forest edge along road) characterised by high nest and worker densities, and associated with low ant species richness. The local dominance of W. auropunctata in such areas can be due to the displacement of other species (cause) or the filling‐up of empty habitats unsuitable to other ants (effect). With respect to their demographic features and ant species richness, the populations of native anthropogenic habitats were to a large extent similar to the invasive populations introduced into remote areas. 4. The results point to the need for greater research efforts to better understand the ecological and demographic features of invasive species within their native ranges.     

Carbon accumulation in agricultural soils after afforestation: a meta-analysis

Deforestation usually results in significant losses of soil organic carbon (SOC). The rate and factors determining the recovery of this C pool with afforestation are still poorly understood. This paper provides a review of the influence of afforestation on SOC stocks based on a meta-analysis of 33 recent publications (totaling 120 sites and 189 observations), with the aim of determining the factors responsible for the restoration of SOC following afforestation. Based on a mixed linear model, the meta-analysis indicates that the main factors that contribute to restoring SOC stocks after afforestation are: previous land use, tree species planted, soil clay content, preplanting disturbance and, to a lesser extent, climatic zone. Specifically, this meta-analysis (1) indicates that the positive impact of afforestation on SOC stocks is more pronounced in cropland soils than in pastures or natural grasslands; (2) suggests that broadleaf tree species have a greater capacity to accumulate SOC than coniferous species; (3) underscores that afforestation using pine species does not result in a net loss of the whole soil-profile carbon stocks compared with initial values (agricultural soil) when the surface organic layer is included in the accounting; (4) demonstrates that clay-rich soils (> 33%) have a greater capacity to accumulate SOC than soils with a lower clay content (< 33%); (5) indicates that minimizing preplanting disturbances may increase the rate at which SOC stocks are replenished; and (6) suggests that afforestation carried out in the boreal climate zone results in small SOC losses compared with other climate zones, probably because trees grow more slowly under these conditions, although this does not rule out gains over time after the conversion. This study also highlights the importance of the methodological approach used when developing the sampling design, especially the inclusion of the organic layer in the accounting.     

Assessing vegetation recovery from energy development using a dynamic reference approach

Ecologically relevant references are useful for evaluating ecosystem recovery, but references that are temporally static may be less useful when environmental conditions and disturbances are spatially and temporally heterogeneous. This challenge is particularly acute for ecosystems dominated by sagebrush (Artemisia spp.), where communities may require decades to recover from disturbance. We demonstrated application of a dynamic reference approach to studying sagebrush recovery using three decades of sagebrush cover estimates from remote sensing (1985–2018). We modelled recovery on former oil and gas well pads (n = 1200) across southwestern Wyoming, USA, relative to paired references identified by the Disturbance Automated Reference Toolset. We also used quantile regression to account for unmodelled heterogeneity in recovery, and projected recovery from similar disturbance across the landscape. Responses to weather and site‐level factors often differed among quantiles, and sagebrush recovery on former well pads increased more when paired reference sites had greater sagebrush cover. Little (<5%) of the landscape was projected to recover within 100 years for low to mid quantiles, and recovery often occurred at higher elevations with cool and moist annual conditions. Conversely, 48%–78% of the landscape recovered quickly (within 25 years) for high quantiles of sagebrush cover. Our study demonstrates advantages of using dynamic reference sites when studying vegetation recovery, as well as how additional inferences obtained from quantile regression can inform management.     

Bootstrapping phylogenies inferred from rearrangement data

ABSTRACT: Large-scale sequencing of genomes has enabled the inference of phylogenies based on the evolution of genomic architecture, under such events as rearrangements, duplications, and losses. Many evolutionary models and associated algorithms have been designed over the last few years and have found use in comparative genomics and phylogenetic inference. However, the assessment of phylogenies built from such data has not been properly addressed to date. The standard method used in sequence-based phylogenetic inference is the bootstrap, but it relies on a large number of homologous characters that can be resampled; yet in the case of rearrangements, the entire genome is a single character. Alternatives such as the jackknife suffer from the same problem, while likelihood tests cannot be applied in the absence of well established probabilistic models. We present a new approach to the assessment of distance-based phylogenetic inference from whole-genome data; our approach combines features of the jackknife and the bootstrap and remains nonparametric. For each feature of our method, we give an equivalent feature in the sequence-based framework; we also present the results of extensive experimental testing, in both sequence-based and genome-based frameworks. Through the feature-by-feature comparison and the experimental results, we show that our bootstrapping approach is on par with the classic phylogenetic bootstrap used in sequence-based reconstruction, and we establish the clear superiority of the classic bootstrap for sequence data and of our corresponding new approach for rearrangement data over proposed variants. Finally, we test our approach on a small dataset of mammalian genomes, verifying that the support values match current thinking about the respective branches. Our method is the first to provide a standard of assessment to match that of the classic phylogenetic bootstrap for aligned sequences. Its support values follow a similar scale and its receiver-operating characteristics are nearly identical, indicating that it provides similar levels of sensitivity and specificity. Thus our assessment method makes it possible to conduct phylogenetic analyses on whole genomes with the same degree of confidence as for analyses on aligned sequences. Extensions to search-based inference methods such as maximum parsimony and maximum likelihood are possible, but remain to be thoroughly tested.