抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

Background The analysis of microbial communities through DNA sequencing brings many challenges: the integration of different types of data with methods from ecology, genetics, phylogenetics, multivariate statistics, visualization and testing. With the increased breadth of experimental designs now being pursued, project-specific statistical analyses are often needed, and these analyses are often difficult (or impossible) for peer researchers to independently reproduce. The vast majority of the requisite tools for performing these analyses reproducibly are already implemented in R and its extensions (packages), but with limited support for high throughput microbiome census data. Results Here we describe a software project, phyloseq, dedicated to the object-oriented representation and analysis of microbiome census data in R. It supports importing data from a variety of common formats, as well as many analysis techniques. These include calibration, filtering, subsetting, agglomeration, multi-table comparisons, diversity analysis, parallelized Fast UniFrac, ordination methods, and production of publication-quality graphics; all in a manner that is easy to document, share, and modify. We show how to apply functions from other R packages to phyloseq-represented data, illustrating the availability of a large number of open source analysis techniques. We discuss the use of phyloseq with tools for reproducible research, a practice common in other fields but still rare in the analysis of highly parallel microbiome census data. We have made available all of the materials necessary to completely reproduce the analysis and figures included in this article, an example of best practices for reproducible research. Conclusions The phyloseq project for R is a new open-source software package, freely available on the web from both GitHub and Bioconductor.

/pdf/phyloseq-an-r-package-for-reproducible-interactive-analysis-1ez1xx3dlr.pdf

phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data.

Background: Currently, a lack of consensus exists on how best to perform and interpret quantitative real-time PCR (qPCR) experiments. The problem is exacerbated by a lack of sufficient experimental detail in many publications, which impedes a reader’s ability to evaluate critically the quality of the results presented or to repeat the experiments.

Content: The Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines target the reliability of results to help ensure the integrity of the scientific literature, promote consistency between laboratories, and increase experimental transparency. MIQE is a set of guidelines that describe the minimum information necessary for evaluating qPCR experiments. Included is a checklist to accompany the initial submission of a manuscript to the publisher. By providing all relevant experimental conditions and assay characteristics, reviewers can assess the validity of the protocols used. Full disclosure of all reagents, sequences, and analysis methods is necessary to enable other investigators to reproduce results. MIQE details should be published either in abbreviated form or as an online supplement.

Summary: Following these guidelines will encourage better experimental practice, allowing more reliable and unequivocal interpretation of qPCR results.

/pdf/the-miqe-guidelines-minimum-information-for-publication-of-27m8n04lrd.pdf

The MIQE Guidelines: Minimum Information for Publication of Quantitative Real-Time PCR Experiments

Preface to the Princeton Landmarks in Biology Edition vii Preface xi Symbols Used xiii 1. The Importance of Islands 3 2. Area and Number of Speicies 8 3. Further Explanations of the Area-Diversity Pattern 19 4. The Strategy of Colonization 68 5. Invasibility and the Variable Niche 94 6. Stepping Stones and Biotic Exchange 123 7. Evolutionary Changes Following Colonization 145 8. Prospect 181 Glossary 185 References 193 Index 201

The Theory of Island Biogeography

Large-scale recovery of genomes from isolates, single cells, and metagenomic data has been made possible by advances in computational methods and substantial reductions in sequencing costs. Although this increasing breadth of draft genomes is providing key information regarding the evolutionary and functional diversity of microbial life, it has become impractical to finish all available reference genomes. Making robust biological inferences from draft genomes requires accurate estimates of their completeness and contamination. Current methods for assessing genome quality are ad hoc and generally make use of a limited number of “marker” genes conserved across all bacterial or archaeal genomes. Here we introduce CheckM, an automated method for assessing the quality of a genome using a broader set of marker genes specific to the position of a genome within a reference genome tree and information about the collocation of these genes. We demonstrate the effectiveness of CheckM using synthetic data and a wide range of isolate-, single-cell-, and metagenome-derived genomes. CheckM is shown to provide accurate estimates of genome completeness and contamination and to outperform existing approaches. Using CheckM, we identify a diverse range of errors currently impacting publicly available isolate genomes and demonstrate that genomes obtained from single cells and metagenomic data vary substantially in quality. In order to facilitate the use of draft genomes, we propose an objective measure of genome quality that can be used to select genomes suitable for specific gene- and genome-centric analyses of microbial communities.

/pdf/checkm-assessing-the-quality-of-microbial-genomes-recovered-2792hxp0ce.pdf

CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes

Using a phyllosphere model system, we demonstrated that the term ‘carrying capacity’, as it is commonly used in microbial ecology, needs to be understood as the sum of many ‘local carrying capacities’ in order to better explain and predict the course and outcome of bacterial colonization of an environment. Using a green fluorescent protein-based bioreporter system for the quantification of reproductive success (RS) in individual Erwinia herbicola cells, we were able to reconstruct the contribution of individual immigrants to bacterial population sizes on leaves. Our analysis revealed that plant foliage represents to bacteria an environment where individual fate is determined by the local carrying capacity of the site where an immigrant cell lands. With increasing inoculation densities, the RS of most immigrants declined, suggesting that local carrying capacity under the tested conditions was linked to local nutrient availability. Fitting the observed experimental data to an adapted model of phyllosphere colonization indicated that there might exist three types of sites on leaves, which differ in their frequency of occurrence and local carrying capacity. Specifically, our data were consistent with a leaf environment that is characterized by few sites where individual immigrants can produce high numbers of offspring, whereas the remainder of the leaf offered an equal number of sites with low and medium RS. Our findings contribute to a bottom–up understanding of bacterial colonization of leaf surfaces, which includes a quantifiable role of chance in the experience at the individual level and in the outcome at the population level.

/pdf/variation-in-local-carrying-capacity-and-the-individual-fate-32xny6hkyq.pdf

Variation in local carrying capacity and the individual fate of bacterial colonizers in the phyllosphere

Arbuscular mycorrhizal (AM) fungi form symbiotic associations with the roots of most plants, thereby mediating nutrient and carbon fluxes, plant performance, and ecosystem dynamics. Although considerable effort has been expended to understand the keystone ecological position of AM symbioses, most studies have been limited in scope to recording organism occurrences and identities, as determined from morphological characters and (mainly) ribosomal sequence markers. In order to overcome these restrictions and circumvent the shortcomings of culture- and phylogeny-based approaches, we propose a shift toward plant and fungal protein-encoding genes as more immediate indicators of mycorrhizal contributions to ecological processes. A number of candidate target genes, involved in the uptake of phosphorus and nitrogen, carbon cycling, and overall metabolic activity, are proposed. We discuss the advantages and disadvantages of future protein-encoding gene marker and current (phylo-) taxonomic approaches for studying the impact of AM fungi on plant growth and ecosystem functioning. Approaches based on protein-encoding genes are expected to open opportunities to advance the mechanistic understanding of ecological roles of mycorrhizas in natural and managed ecosystems.

https://nph.onlinelibrary.wiley.com/doi/pdf/10.1111/j.1469-8137.2009.03058.x

Molecular trait indicators: moving beyond phylogeny in arbuscular mycorrhizal ecology

Increased microbial activity and nitrogen mineralization coupled to changes in microbial community structure in the rhizosphere of Bt corn

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Variation in local carrying capacity and the individual fate of bacterial colonizers in the phyllosphere

Molecular trait indicators: moving beyond phylogeny in arbuscular mycorrhizal ecology

Increased microbial activity and nitrogen mineralization coupled to changes in microbial community structure in the rhizosphere of Bt corn