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

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

The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online ( http://bioinf.spbau.ru/spades ). It is distributed as open source software.

SPAdes, a new genome assembly algorithm and its applications to single-cell sequencing ( 7th Annual SFAF Meeting, 2012)

An essential textbook for any student or researcher in biology needing to design experiments, sample programs or analyse the resulting data The text begins with a revision of estimation and hypothesis testing methods, covering both classical and Bayesian philosophies, before advancing to the analysis of linear and generalized linear models Topics covered include linear and logistic regression, simple and complex ANOVA models (for factorial, nested, block, split-plot and repeated measures and covariance designs), and log-linear models Multivariate techniques, including classification and ordination, are then introduced Special emphasis is placed on checking assumptions, exploratory data analysis and presentation of results The main analyses are illustrated with many examples from published papers and there is an extensive reference list to both the statistical and biological literature The book is supported by a website that provides all data sets, questions for each chapter and links to software

/pdf/experimental-design-and-data-analysis-for-biologists-8ybva8d53x.pdf

Experimental Design and Data Analysis for Biologists

QIIME 2 development was primarily funded by NSF Awards 1565100 to J.G.C. and 1565057 to R.K. Partial support was also provided by the following: grants NIH U54CA143925 (J.G.C. and T.P.) and U54MD012388 (J.G.C. and T.P.); grants from the Alfred P. Sloan Foundation (J.G.C. and R.K.); ERCSTG project MetaPG (N.S.); the Strategic Priority Research Program of the Chinese Academy of Sciences QYZDB-SSW-SMC021 (Y.B.); the Australian National Health and Medical Research Council APP1085372 (G.A.H., J.G.C., Von Bing Yap and R.K.); the Natural Sciences and Engineering Research Council (NSERC) to D.L.G.; and the State of Arizona Technology and Research Initiative Fund (TRIF), administered by the Arizona Board of Regents, through Northern Arizona University. All NCI coauthors were supported by the Intramural Research Program of the National Cancer Institute. S.M.G. and C. Diener were supported by the Washington Research Foundation Distinguished Investigator Award.

/pdf/reproducible-interactive-scalable-and-extensible-microbiome-2g6g1rz4ph.pdf

Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2

We describe a protocol for investigating microbial growth in environmental samples via stable isotope probing (SIP) with H218O. Water is a universal substrate for all microorganisms and replication is required for DNA to become labeled with 18O. By measuring how much the DNA of each taxon becomes enriched with 18O when an environmental sample is incubated with H218O, it is feasible to quantify that population's DNA replication rate, which is a proxy for growth.

Stable Isotope Probing of Microorganisms in Environmental Samples with H218O.

https://esajournals.onlinelibrary.wiley.com/doi/pdf/10.1002/fee.1511

Biodiversity: what value should we use?

Soil microorganisms influence the global carbon cycle by transforming plant inputs into soil organic carbon (SOC), but the microbial traits that facilitate this process are unresolved. While current theory and biogeochemical models suggest microbial carbon-use efficiency and growth rate are positive predictors of SOC, recent observations demonstrate these relationships can be positive, negative, or neutral. To parse these contradictory effects, we used a 13C-labeling experiment to test whether different microbial traits influenced the transformation of plant C into SOC within the microbial habitats surrounding living root inputs (rhizosphere) versus decaying root litter (detritusphere), under both normal soil moisture and droughted conditions. In the rhizosphere, bacterial-dominated communities with fast growth, high carbon-use efficiency, and high production of extracellular polymeric substances formed microbial-derived SOC under normal moisture conditions. However, in the detritusphere – and the rhizosphere under drought – more fungal-dominated communities with slower growth but higher exoenzyme activity formed plant-derived SOC. These findings emphasize that microbial traits linked with SOC accrual are not universal, but contingent on how microorganisms allocate carbon under different resource conditions and environmental stressors.

/pdf/divergent-microbial-traits-influence-the-transformation-of-26exiqer.pdf

Divergent microbial traits influence the transformation of living versus dead root inputs to soil carbon

RNA is considered to be a short-lived molecule, indicative of cellular metabolic activity, whereas DNA is thought to turn over more slowly because living cells do not always grow and divide. To explore differences in the rates of synthesis of these nucleic acids, we used H218O quantitative stable isotope probing (qSIP) to measure the incorporation of 18O into 16S rRNA, the 16S rDNA, amoA mRNA and the amoA gene of soil Thaumarchaeota. Incorporation of 18O into the thaumarchaeal amoA mRNA pool was faster than into the 16S rRNA pool, suggesting that Thaumarchaea were metabolically active while using rRNA molecules that were likely synthetized prior to H218O addition. Assimilation rates of 18O into 16S rDNA and amoA genes were similar, which was expected because both genes are present in the same thaumarchaeal genome. The Thaumarchaea had significantly higher rRNA to rDNA ratios than bacteria, though the 18O isotopic signature of thaumarchaeal rRNA was lower than that of bacterial rRNA, further suggesting preservation of old non-labeled rRNA. Through qSIP of soil with H218O, we showed that 18O incorporation into thaumarchaeal nucleic acids was generally low, indicating slower turnover rates compared to bacteria, and potentially suggesting thaumarchaeal capability for preservation and efficient reuse of biomolecules.

/pdf/mrna-rrna-and-dna-quantitative-stable-isotope-probing-with-1ujtwbd6c9.pdf

mRNA, rRNA and DNA quantitative stable isotope probing with H218O indicates use of old rRNA among soil Thaumarchaeota

Soil carbon feedbacks to global change are uncertain, and the biological processes that govern soil organic matter decomposition are not resolved in current ecosystem models. Though it is recognized that microbial biodiversity influences decomposition rates, incorporating this relationship into ecosystem models is challenging because microbial communities are prohibitively diverse. It is likely necessary to distill microbial biodiversity by focusing on functional groups or ecological strategies. The ecological strategies that currently dominate the microbial ecology literature derive from macroecological theory, have clear weaknesses, and have had limited success when applied to predict soil carbon dynamics. Here, we present a new framework for soil microorganisms: Carbon Acquisition Ecological Strategies (CAES), and we outline a path toward incorporating microbial biodiversity into ecosystem models using this framework to enhance predictions of soil carbon feedbacks to global change. Because a microorganism's diet is central to its ecological niche and likely to covary with other ecologically significant traits, we posit that carbon acquisition may serve as a tractable foundation for developing ecological strategies. We describe four candidate ecological strategies for soil microorganisms: 1° decomposers that assimilate complex plant polymers, 2° decomposers that assimilate microbial necromass, passive consumers that assimilate dissolved organic carbon, and predatory microbes that assimilate live microbial biomass. These strategies are directly linked to soil carbon pools currently represented in ecosystem models and may provide a foundation for greater integration of microbial community dynamics into ecosystem models. 

Bruce A. Hungate

Papers

Stable Isotope Probing of Microorganisms in Environmental Samples with H218O.

Biodiversity: what value should we use?

Divergent microbial traits influence the transformation of living versus dead root inputs to soil carbon

mRNA, rRNA and DNA quantitative stable isotope probing with H218O indicates use of old rRNA among soil Thaumarchaeota

Carbon acquisition ecological strategies to connect soil microbial biodiversity and carbon cycling