Spatial heterogeneity analysis of the human virome with Taylor's power law

Applicability of soil health assessment dominated by biological indicators in facility agriculture

The minimum data set (MDS) is widely used for soil health index (SHI) assessment, with the selection of indicators being crucial. However, biological indicators are less frequently used compared to physical and chemical indicators. This study aimed to establish a biologically-centered MDS for assessing soil health in tomato facility agriculture in Ningbo. Using biochemical, microbiological, and nematode data from 60 continuous cropping soils, we identified key indicators for the MDS. Principal component analysis revealed a strong correlation between the MDS and the total data set (TDS), with the final MDS including available phosphorus, electrical conductivity, β-glucosidase, urease, bacterial Chao1 index, bacterial Shannon index, Ralstonia solanacearum, nematode Shannon index, structure index, and channel index. Random forest modeling showed that the predicted SHI had a high fit with the MDS-SHI, with bacterial and nematode Shannon indices being the most influential predictors, emphasizing the critical role of biological communities in maintaining soil health. Furthermore, the study identified three distinct phases in soil health during long-term continuous cropping: healthy (0-10 years), sub-healthy (11-15 years), and recovery (16-20 years), demonstrating the soil's potential for self-recovery. By incorporating biodiversity as a core component, this biologically-focused MDS provides a more comprehensive and precise method for evaluating soil health in facility agriculture. The findings suggest that this MDS could inform future research and applications in similar agricultural systems. Moreover, the results highlight the vital role of biodiversity in agroecosystem stability, suggesting that future soil health assessments should place greater emphasis on biological indicators to better capture the complexity of soil functions.

Fungal infections and the fungal microbiome in hepatobiliary disorders

Liver and biliary diseases affect more than a billion people worldwide, with high associated morbidity and mortality. The impact of the intestinal bacterial microbiome on liver diseases has been well established. However, the fungal microbiome, or mycobiome, has been overlooked for a long time. Recently, several studies have shed light on the role of the mycobiome in the development and progression of hepatobiliary diseases. In particular, the fungal genus Candida has been found to be involved in the pathogenesis of multiple hepatobiliary conditions. Herein, we compare colonisation and infection, describe mycobiome findings in the healthy state and across the various hepatobiliary conditions, and point toward communalities. We detail how quantitation of immune responses to fungal antigens can be employed to predict disease severity, e.g. using antibodies to Saccharomyces cerevisiae or specific anti-Candida albicans antibodies. We also show how fungal products (e.g. beta-glucans, candidalysin) activate the host's immune system to exacerbate liver and biliary diseases. Finally, we describe how the gut mycobiome can be modulated to ameliorate hepatobiliary conditions.

Interspecific and intraspecific Taylor's laws for frog skin microbes

Amphibians are known to have an abundance of microorganisms colonizing their skin, and these symbionts often protect the host from disease. There are now many comprehensive studies on amphibian skin microbes, but the interspecific and intraspecific abundance distributions (or abundance heterogeneity) of amphibian skin microbes remain unclear. Furthermore, we have a very limited understanding of how the abundance and heterogeneity of microbial communities relate to the body size (or more specifically, skin surface area) of amphibian hosts. In this study, we evaluated the interspecific and intraspecific abundance distribution patterns of amphibian skin microbes and evaluated whether the symbiotic skin microbes of different anuran species share a fundamental heterogeneity scaling parameter. If scaling invariance exists, we hypothesize that a fundamental heterogeneity scaling value also exists. A total of 358 specimens of 10 amphibian host species were collected, and we used Type-I and III Taylor's power law expansions (TPLE) to assess amphibian skin microbial heterogeneity at the community and mixed-species population levels, respectively. The obtained results showed that, at the community scale, a high aggregation of the microbial abundance distribution on the skin barely changed with host size. In a mixed-species population (i.e., a community context), the abundance distribution pattern of mixed microbial species populations also does not change with host size and always remains highly aggregated. These findings suggest that while amphibian skin microbiomes located in different hosts may have different environmental conditions, they share a fundamental heterogeneity scaling parameter, and thus, scale invariance exists. Finally, we found that microhabitat area provided by the host skin is vital to the stability of the symbiotic microbial community.

Power law analysis of the human milk microbiome

The human breast milk microbiome (HMM) has far reached health implications for both mothers and infants, and understanding the structure and dynamics of milk microbial communities is therefore of critical biomedical importance. Community heterogeneity, which has certain commonalities with familiar diversity but also with certain fundamental differences, is an important aspect of community structure and dynamics. Taylor's (1961) power law (TPL) (Nature, 1961) was discovered to govern the mean-variance power function relationship of population abundances and can be used to characterize population spatial aggregation (heterogeneity) and/or temporal stability. TPL was further extended to the community level to measure community spatial heterogeneity and/or temporal stability (Ma 2015, Molecular Ecology). Here, we applied TPL extensions (TPLE) to analyze the heterogeneity of the human milk microbiome by reanalyzing 12 datasets (2115 samples) of the healthy human milk microbiome. Our analysis revealed that the TPLE heterogeneity parameter (b) is rather stable across the 12 datasets, and there were approximately no statistically significant differences among ¾ of the datasets, which is consistent with the hypothesis that the heterogeneity scaling (i.e., change across individuals) of the human microbiome, including HMM, is rather stable or even constant. For this, we built a TPLE model for the pooled 12 datasets (b = 1.906), which can therefore represent the scaling rate of community-level spatial heterogeneity of HMM across individuals. Similarly, we also analyzed mixed-species ("averaged virtual species") level heterogeneity of HMM, and it was found that the mixed-species level heterogeneity was smaller than the heterogeneity at the previously mentioned community level (1.620 vs. 1.906).

Influences of Helicobacter pylori infection on diversity, heterogeneity, and composition of human gastric microbiomes across stages of gastric cancer development

BACKGROUND

About a half of the world's population is infected with Helicobacter pylori (H. pylori), but only 1%-3% of them develop gastric cancer. As a primary risk factor for gastric cancer, the relationship between H. pylori infection and gastric microbiome has been a focus in recent years.

MATERIALS AND METHODS

We reanalyze 11 human gastric microbiome datasets with or without H. pylori, covering the healthy control (HC) and four disease stages (chronic gastritis (CG), atrophic gastritis (AG), intestinal metaplasia (IM), and gastric cancer (GC)) of gastric cancer development to quantitatively compare the influences of the H. pylori infection and disease stages on the diversity, heterogeneity, and composition of gastric microbiome. Four medical ecology approaches including (i) diversity analysis with Hill numbers, (ii) heterogeneity analysis with Taylor's power law extensions (TPLE), (iii) diversity scaling analysis with diversity-area relationship (DAR) model, and (iv) shared species analysis were applied to fulfill the data reanalysis.

RESULTS

(i) The influences of H. pylori infection on the species diversity, spatial heterogeneity, and potential diversity of gastric microbiome seem to be more prevalent than the influences of disease stages during gastric cancer development. (ii) The influences of H. pyloriinfection on diversity, heterogeneity, and composition of gastric microbiomes in HC, CG, IM, and GC stages appear more prevalent than those in AG stage.

CONCLUSION

Our study confirmed the impact of H. pylori infection on human gastric microbiomes: The influences of H. pylori infection on the diversity, heterogeneity, and composition of gastric microbiomes appear to be disease-stage dependent.

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

In nature, the interaction between pathogens and their hosts is only one of a handful of interaction relationships between species, including parasitism, predation, competition, symbiosis, commensalism, and among others. From a non-anthropocentric view, parasitism has relatively fewer essential differences from the other relationships; but from an anthropocentric view, parasitism and predation against humans and their well-beings and belongings are frequently related to heinous diseases. Specifically, treating (managing) diseases of humans, crops and forests, pets, livestock, and wildlife constitute the so-termed medical enterprises (sciences and technologies) humans endeavor in biomedicine and clinical medicine, veterinary, plant protection, and wildlife conservation. In recent years, the significance of ecological science to medicines has received rising attentions, and the emergence and pandemic of COVID-19 appear accelerating the trend. The facts that diseases are simply one of the fundamental ecological relationships in nature, and the study of the relationships between species and their environment is a core mission of ecology highlight the critical importance of ecological science. Nevertheless, current studies on the ecology of medical enterprises are highly fragmented. Here, we (i) conceptually overview the fields of disease ecology of wildlife, cancer ecology and evolution, medical ecology of human microbiome-associated diseases and infectious diseases, and integrated pest management of crops and forests, across major medical enterprises. (ii) Explore the necessity and feasibility for a unified medical ecology that spans biomedicine, clinical medicine, veterinary, crop (forest and wildlife) protection, and biodiversity conservation. (iii) Suggest that a unified medical ecology of human diseases is both necessary and feasible, but laissez-faire terminologies in other human medical enterprises may be preferred. (iv) Suggest that the evo-eco paradigm for cancer research can play a similar role of evo-devo in evolutionary developmental biology. (v) Summarized 40 key ecological principles/theories in current disease-, cancer-, and medical-ecology literatures. (vi) Identified key cross-disciplinary discovery fields for medical/disease ecology in coming decade including bioinformatics and computational ecology, single cell ecology, theoretical ecology, complexity science, and the integrated studies of ecology and evolution. Finally, deep understanding of medical ecology is of obvious importance for the safety of human beings and perhaps for all living things on the planet.

Stochastic neutral drifts seem prevalent in driving human virome assembly: neutral, near-neutral and non-neutral theoretic analyses

It is estimated that human body is inhabited by approximately 380 trillions of viruses, which exist in the form of viral communities and are collectively termed as human virome. How virome is assembled and what kind of forces maintain the composition and diversity of viral communities is still an open question. The question is of obvious importance because of its implications to human health and diseases. Here we address the question by harnessing the power of Hubbell’s unified neutral theory of biodiversity (UNTB) in terms of three neutral models including standard Hubbell’s neutral model (HNM), Sloan’s near-neutral model (SNM) and Harris et al. (2017) multi-site neutral model (MSN), further augmented by Ning et al. (2019) normalized stochasticity ratio (NSR) and Hammal et al. (2015) power analysis for the neutral test (PNT). With the five models applied to 179 virome samples, we aim to obtain robust findings given both Type-I and Type-II errors are addressed and possible alternative, non-neutral processes are detected. It was found that stochastic neutral drifts seem prevalent: approximately 65–92% at metacommunity/landscape scales and 67–80% at virus species scale. The non-neutral selection is approximately 26–28% at community scale and 23% at species scale. The false negative rate is about 2–3%, which suggested rather limited confounding effects of non-neutral process on neutrality tests. We postulate that prevalence of neutrality in human virome is likely due to extremely simple structure of viruses (stands of DNA/RNA) and their inter-species homogeneities, forming the foundation of species equivalence—the hallmark of neutral theory.