Ma Zhanshan Sam
Computational Biology and Medical Ecology Lab, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China.
Department of Entomology, College of Plant Protection, Hebei Agricultural University, Baoding, China.
BMC Biol. 2024 Dec 5;22(1):283. doi: 10.1186/s12915-024-02024-7.
Differentiating the microbiome changes associated with diseases is challenging but critically important. Majority of existing efforts have been focused on a community level, but the discerning power of community or holistic metrics such as diversity analysis seems limited. This prompts many researchers to believe that the promise should be downward to species or even strain level-effectively and efficiently identifying unique or enriched species in diseased microbiomes with statistical rigor. Nevertheless, virtually, all species-level approaches such as differential abundance and differential network analysis methods exclusively rely on species abundances without considering species distribution information, while it can be said that distribution is equally, if not more, important than abundance in shaping the spatiotemporal heterogeneity of community compositions.
Here, we fill the gap by developing a novel framework-species specificity and specificity diversity (SSD)-that synthesizes both abundance and distribution information to differentiate microbiomes, at both species and community scales, under different environmental gradients such as the healthy and diseased treatments. The proposed SSD framework consists of three essential elements. The first is species specificity (SS), a concept that reincarnates the traditional specialist-generalist continuum and is defined by Mariadassou et al. (Ecol Lett 18:974-82, 2015). The SS synthesizes a species' local prevalence (distribution) and global abundance information and attaches specificity measure to each species in a specific habitat (e.g., healthy or diseased treatment). The second element is a new concept to introduce here, the (species) specificity diversity (SD), which is inspired by traditional species (abundance) diversity in community ecology and measures the diversity of specificity (a proxy for metacommunity heterogeneity, essentially) with Renyi's entropy. The third element is a pair of statistical tests based on the principle of permutation tests.
The SSD framework can (i) identify and catalogue lists of unique species (US), significantly enriched species (ES) in each treatment based on SS and specificity permutation (SP) test and (ii) measure the holistic differences between assemblages (or treatments) based on SD and specificity diversity permutation (SDP) test. Both capacities can be enabling technologies for general comparative microbiome research including risk assessment, diagnosis, and treatment of microbiome-associated diseases.
区分与疾病相关的微生物组变化具有挑战性，但至关重要。现有的大多数研究都集中在群落水平上，然而，群落或整体指标（如多样性分析）的辨别能力似乎有限。这促使许多研究人员认为，应该深入到物种甚至菌株水平——以有效且高效的方式，通过严格的统计学方法，识别患病微生物组中独特或富集的物种。然而，实际上，几乎所有物种水平的方法，如差异丰度分析和差异网络分析方法，都仅依赖于物种丰度，而没有考虑物种分布信息，尽管可以说，在塑造群落组成的时空异质性方面，分布即便不比丰度更重要，也同样重要。
在此，我们通过开发一种新的框架——物种特异性和特异性多样性（SSD）来填补这一空白，该框架综合了丰度和分布信息，以便在不同环境梯度（如健康和患病处理）下，在物种和群落尺度上区分微生物组。所提出的SSD框架由三个基本要素组成。第一个是物种特异性（SS），这一概念复兴了传统的专性种 - 广适种连续统，由玛丽亚达苏等人（《生态学快报》18:974 - 82，2015年）定义。SS综合了一个物种的局部发生率（分布）和全局丰度信息，并为特定栖息地（如健康或患病处理）中的每个物种赋予特异性度量。第二个要素是在此引入的一个新概念，即（物种）特异性多样性（SD），它受群落生态学中传统物种（丰度）多样性的启发，并用雷尼熵来度量特异性多样性（本质上是一个用于衡量集合群落异质性的指标）。第三个要素是基于置换检验原理的一对统计检验。
SSD框架能够（i）基于SS和特异性置换（SP）检验，识别并编目每种处理中独特物种（US）和显著富集物种（ES）的列表，以及（ii）基于SD和特异性多样性置换（SDP）检验，测量不同组合（或处理）之间的整体差异。这两种能力都可以成为通用比较微生物组研究的赋能技术，包括微生物组相关疾病的风险评估、诊断和治疗。
