Ecology of Human Medical Enterprises: From Disease Ecology of Zoonoses, Cancer Ecology Through to Medical Ecology of Human Microbiomes

Sam, Zhanshan; Zhang, Yaping

doi:10.3389/fevo.2022.879130

Cited by 4 publications

(3 citation statements)

References 191 publications

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“…Inspired by Hutchinson's (1957) classic "The ecological theater and evolutionary play," cancer can be considered as an evolving ecosystem consisting of tumor cells, stem cells, stromal cells, immune cells, microbes, and tumor microenvironment (TME). Cancer evolutions are on multiple levels ranging from ultra-micro (cell population level), micro (individual host) and macro (population of individuals), and can be real time evolution at the ultra-microscale (Horning 2017, Reynolds et al 2020, Dujon et al 2021, Ma & Zhang 2022. What Hutchinson's (1957) title transpired is that evolution ("play") depend on ecological environment ("theater"), and the evolution of cancer cell population depends on TME, which includes microbiomes and immune cells.…”

Section: Resultsmentioning

confidence: 99%

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Immune-oncology-microbiome axis may result in AKP or anti-AKP effects in intratumor microbiomes

2024

Preprint

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An emerging consensus regarding the triangle relationship between tumor, immune cells, and microbiomes is the immune-oncology-microbiome (IOM) axis, which stipulates that microbiomes can act as a discrete enabling (or disabling) characteristic that broadly influence the acquisition of certain hallmarks of cancer, i.e., a set of functional capabilities acquired by human cells during carcinogenesis and progression to malignant tumors. Specifically, it has been postulated that polymorphic microbiomes can either induce or inhibit some of the hallmark capacities (particularly, immune evasions) via their intersecting with two other enabling characteristics (genome instability and mutation, and tumor promoting inflammation). The net effects of the microbiomes can be either protective or deleterious effects on cancer development, malignant progression, and therapy responses. Nevertheless, there is not yet a mechanistic interpretation for IOM, especially regarding intratumoral microbiomes. Here, we propose to interpret the observed relationships, in which microbiomes can be complicit, bystanders, or in rare cases, oncomicrobes or foes, to either cancer cells or immune cells, possibly depend on specific microbial taxon, with the AKP (Anna Karenina principle)--that all heathy tissue microbiomes should be similar, and tumor microbiomes should be dissimilar with each other, in analogy with Leo Tolstoy's aphorism that "all happy families look alike; each unhappy family is unhappy in its own way." Given potentially double-sword nature of microbes, both AKP and anti-AKP should exist in the IOM axis. We test the AKP with microbiome datasets of 20+ cancer types from the TCGA database and find that the ratio of AKP/anti-AKP is about 3:1.

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Section: Resultsmentioning

confidence: 99%

“…2020, Dujon et al . 2021, Ma & Zhang 2022). What Hutchinson’s (1957) title transpired is that evolution (“play”) depend on ecological environment (“theater”), and the evolution of cancer cell population depends on TME, which includes microbiomes and immune cells.…”

Section: Conclusion and Discussionmentioning

confidence: 99%

Immune-oncology-microbiome axis may result in AKP or anti-AKP effects in intratumor microbiomes

2024

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“…This is because microbes obviously can influence host physiology, health, behavior, and psychology [8]. Indeed, animal microbiome should be a critical part of disease ecology of zoonoses [45].…”

Section: Introductionmentioning

confidence: 99%

Critical complex network structures in animal gastrointestinal tract microbiomes

Ma,

Shi

2024

anim microbiome

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Background Living things from microbes to their hosts (plants, animals and humans) interact with each other, and their relationships may be described with complex network models. The present study focuses on the critical network structures, specifically the core/periphery nodes and backbones (paths of high-salience skeletons) in animal gastrointestinal microbiomes (AGMs) networks. The core/periphery network (CPN) mirrors nearly ubiquitous nestedness in ecological communities, particularly dividing the network as densely interconnected core-species and periphery-species that only sparsely linked to the core. Complementarily, the high-salience skeleton network (HSN) mirrors the pervasive asymmetrical species interactions (strictly microbial species correlations), particularly forming heterogenous pathways in AGM networks with both “backbones” and “rural roads” (regular or weak links). While the cores and backbones can act as critical functional structures, the periphery nodes and weak links may stabilize network functionalities through redundancy. Results Here, we build and analyze 36 pairs of CPN/HSN for the AGMs based on 4903 gastrointestinal-microbiome samples containing 473,359 microbial species collected from 318 animal species covering all vertebrate and four major invertebrate classes. The network analyses were performed at host species, order, class, phylum, kingdom scales and diet types with selected and comparative taxon pairs. Besides diet types, the influence of host phylogeny, measured with phylogenetic (evolutionary) timeline or “age”, were integrated into the analyses. For example, it was found that the evolutionary trends of three primary microbial phyla (Bacteroidetes/Firmicutes/Proteobacteria) and their pairwise abundance-ratios in animals do not mirror the patterns in modern humans phylogenetically, although they are consistent in terms of diet types. Conclusions Overall, the critical network structures of AGMs are qualitatively and structurally similar to those of the human gut microbiomes. Nevertheless, it appears that the critical composition (the three phyla of Bacteroidetes, Firmicutes, and Proteobacteria) in human gut microbiomes has broken the evolutionary trend from animals to humans, possibly attributable to the Anthropocene epoch and reflecting the far-reaching influences of agriculture and industrial revolution on the human gut microbiomes. The influences may have led to the deviations between modern humans and our hunter-gather ancestors and animals.

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A new hypothesis on BV etiology: dichotomous and crisscrossing categorization of complex versus simple on healthy versus BV vaginal microbiomes

2023

mSystems

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It has been estimated that bacterial vaginosis (BV) influences as many as one-third of women, but its etiology remains unclear. A traditionally held view is that dominance by Lactobacillus is the hallmark of a healthy vaginal microbiome (VM) and lack of dominance may make women BV-prone. A more recent characterization is that the human VMs can be classified into five major types, four of which possess type-specific dominant species of Lactobacillus . The remaining one (type IV) is not dominated by Lactobacillus and contains a handful of strictly anaerobic bacteria. Nevertheless, exceptions to the first hypothesis have been noticed from the very beginning, and there is not a definite relationship, suggested yet, between the five VM types and BV status. Here, we propose a novel hypothesis that assumes the existence of four VM types from dichotomous crisscrossing of “complex versus simple (high-diversity or low-dominance versus low-diversity or high-dominance)” on “healthy versus BV” (the four essential dimensions of VMs). We comprehensively test the hypothesis with 7,958 VM samples by demonstrating the statistically significant differences between the four VM types in community diversity, composition, dominance, heterogeneity, and stochasticity, and by identifying unique/enriched species in each VM type. We further verified the categorization (hypothesis) by using six machine learning (ML) algorithms, including deep learning artificial intelligence (AI) technology, to reclassify the randomly mixed VM samples into four respective types and achieved 85%–100% classification precisions. Our hypothesis provides a foundation for further investigating the etiology and automatic diagnosis of BV based on inexpensive amplicon sequencing and AI technology. IMPORTANCE BV may influence as many as one-third of women, but its etiology remains unclear. A traditional view is that dominance by Lactobacillus is the hallmark of a healthy vaginal microbiome and lack of dominance may make women BV-prone. Recent studies show that the human VMs can be classified into five major types, four of which possess type-specific dominant species of Lactobacillus . The remaining one (type IV) is not dominated by Lactobacillus and contains a handful of strictly anaerobic bacteria. Nevertheless, exceptions to the first hypothesis have been noticed from the very beginning, and there is not a definite relationship, suggested yet, between the five VM types and BV status. Here, we propose and test a novel hypothesis that assumes the existence of four VM types from dichotomous crisscrossing of “complex versus simple (high diversity or low dominance versus low diversity or high dominance)” on “healthy versus BV.” Consequently, there are simple BV versus complex BV.

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Ecology of Human Medical Enterprises: From Disease Ecology of Zoonoses, Cancer Ecology Through to Medical Ecology of Human Microbiomes

Cited by 4 publications

References 191 publications

Immune-oncology-microbiome axis may result in AKP or anti-AKP effects in intratumor microbiomes

Immune-oncology-microbiome axis may result in AKP or anti-AKP effects in intratumor microbiomes

Critical complex network structures in animal gastrointestinal tract microbiomes

A new hypothesis on BV etiology: dichotomous and crisscrossing categorization of complex versus simple on healthy versus BV vaginal microbiomes

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