ATD Collaborative Research: New theorems and algorithms for comprehensive analysis of metagenomic data via statistical phylogenetics

目前的全元基因组分析工具主要基于序列相似性(组装、BLAST)和分类(“分类”方法)；虽然这些方法很有用，但也有以下局限性。组装方法需要读取重叠，因此只重建混合样本中最丰富的有机体。序列相似性方法，如BLAST，不能将读数与祖先生物联系起来，也不能表明突变的进化意义。分类学方法过于粗糙，无法反映可能表征生物威胁的微妙的DNA序列变化。研究人员建议通过发展以下方法的理论基础来克服这些限制：即使在读取计数很小的情况下，也重建环境样本中DNA的细胞区划；通过与现有基因组进行系统发育比较来检测合成基因组和元基因组样本中定向进化的证据；检测给定观察位置或观察时间的异常遗传物质的组合；从统计上区分微生物群落组成的有意义的变化和噪音，即使这些变化发生在使用现有方法可以检测到的水平以下。基因工程工具掌握在许多国家的科学家手中；这些工具可用于合成生物武器。防止这些武器造成的伤亡取决于及时发现和识别这些武器。虽然高通量DNA测序可以用于监测生物威胁，但目前可用于分析其产生的丰富信息的工具不足以对威胁风险进行统计分析。通过对进化信号进行统计分析，生物防御监测方法可以产生一种直接从“元基因组”数据中检测遗传异常和威胁的方法：来自环境样本的高通量鸟枪测序数据。

Current whole-metagenome analysis tools are primarily based on sequence similarity (assembly, BLAST) and taxonomies ("binning" approaches); while useful, these approaches have the following limitations. Assembly methods require read overlap and thus only reconstruct the most abundant organisms in a mixed sample. Sequence similarity approaches such as BLAST cannot relate reads to ancestral organisms and do not indicate the evolutionary significance of mutations. Taxonomic methods are too coarse to reflect the subtle DNA sequence changes that may characterize a biological threat. The investigators propose to overcome these limitations by developing the theoretical underpinnings of methods to: reconstruct the cellular compartmentalization of DNA in environmental samples, even when read counts are small, detect synthetic genomes and evidence of directed evolution within a metagenomic sample by performing a phylogenetic comparison with extant genomes, detect combinations of genetic material that are anomalous given their location or time of observation, statistically distinguish meaningful shifts in microbial community composition from noise, even when those shifts happen at a level below that detectable using currently available methods.The tools of genetic engineering are in the hands of scientists of many countries; these tools can be used to synthesize biological weapons. Prevention of casualties from these weapons depends on their prompt detection and identification. Although high-throughput DNA sequencing could be used to monitor biological threats, the currently available tools for analyzing the wealth of information it generates are insufficient to statistically analyze threat risk. A biodefense monitoring approach informed by a statistical analysis of evolutionary signal could yield a means to detect genetic anomalies and threats directly from "metagenomic" data: high throughput shotgun sequencing data from environmental samples.