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Ma ZS. Towards a unified medical microbiome ecology of the OMU for metagenomes and the OTU for microbes. BMC Bioinformatics 2024; 25:137. [PMID: 38553666 PMCID: PMC10979563 DOI: 10.1186/s12859-023-05591-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Accepted: 11/30/2023] [Indexed: 04/02/2024] Open
Abstract
BACKGROUND Metagenomic sequencing technologies offered unprecedented opportunities and also challenges to microbiology and microbial ecology particularly. The technology has revolutionized the studies of microbes and enabled the high-profile human microbiome and earth microbiome projects. The terminology-change from microbes to microbiomes signals that our capability to count and classify microbes (microbiomes) has achieved the same or similar level as we can for the biomes (macrobiomes) of plants and animals (macrobes). While the traditional investigations of macrobiomes have usually been conducted through naturalists' (Linnaeus & Darwin) naked eyes, and aerial and satellite images (remote-sensing), the large-scale investigations of microbiomes have been made possible by DNA-sequencing-based metagenomic technologies. Two major types of metagenomic sequencing technologies-amplicon sequencing and whole-genome (shotgun sequencing)-respectively generate two contrastingly different categories of metagenomic reads (data)-OTU (operational taxonomic unit) tables representing microorganisms and OMU (operational metagenomic unit), a new term coined in this article to represent various cluster units of metagenomic genes. RESULTS The ecological science of microbiomes based on the OTU representing microbes has been unified with the classic ecology of macrobes (macrobiomes), but the unification based on OMU representing metagenomes has been rather limited. In a previous series of studies, we have demonstrated the applications of several classic ecological theories (diversity, composition, heterogeneity, and biogeography) to the studies of metagenomes. Here I push the envelope for the unification of OTU and OMU again by demonstrating the applications of metacommunity assembly and ecological networks to the metagenomes of human gut microbiomes. Specifically, the neutral theory of biodiversity (Sloan's near neutral model), Ning et al.stochasticity framework, core-periphery network, high-salience skeleton network, special trio-motif, and positive-to-negative ratio are applied to analyze the OMU tables from whole-genome sequencing technologies, and demonstrated with seven human gut metagenome datasets from the human microbiome project. CONCLUSIONS All of the ecological theories demonstrated previously and in this article, including diversity, composition, heterogeneity, stochasticity, and complex network analyses, are equally applicable to OMU metagenomic analyses, just as to OTU analyses. Consequently, I strongly advocate the unification of OTU/OMU (microbiomes) with classic ecology of plants and animals (macrobiomes) in the context of medical ecology.
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Affiliation(s)
- Zhanshan Sam Ma
- Computational Biology and Medical Ecology Lab, State Key Lab of Genetic Resources and Evolution, Center for Excellence in Animal Evolution and Genetics, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China.
- Microbiome Medicine and Advanced AI Lab, Cambridge, MA, 02138, USA.
- Faculty of Arts and Science, Harvard University, Cambridge, MA, 02138, USA.
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Xiao W, Ma ZS. Influences of Helicobacter pylori infection on diversity, heterogeneity, and composition of human gastric microbiomes across stages of gastric cancer development. Helicobacter 2022; 27:e12899. [PMID: 35678078 DOI: 10.1111/hel.12899] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Revised: 04/09/2022] [Accepted: 04/21/2022] [Indexed: 12/15/2022]
Abstract
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.
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Affiliation(s)
- Wanmeng Xiao
- Computational Biology and Medical Ecology Lab, State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China.,Kunming College of Life Sciences, University of Chinese Academy of Sciences, Kunming, China
| | - Zhanshan Sam Ma
- Computational Biology and Medical Ecology Lab, State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China.,Kunming College of Life Sciences, University of Chinese Academy of Sciences, Kunming, China.,Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China
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3
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Ma Z(S, Zhang YP. Ecology of Human Medical Enterprises: From Disease Ecology of Zoonoses, Cancer Ecology Through to Medical Ecology of Human Microbiomes. Front Ecol Evol 2022. [DOI: 10.3389/fevo.2022.879130] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
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.
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Wetherington MT, Nagy K, Dér L, Noorlag J, Galajda P, Keymer JE. Variance in Landscape Connectivity Shifts Microbial Population Scaling. Front Microbiol 2022; 13:831790. [PMID: 35464924 PMCID: PMC9020879 DOI: 10.3389/fmicb.2022.831790] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Accepted: 03/10/2022] [Indexed: 12/03/2022] Open
Abstract
Understanding mechanisms shaping distributions and interactions of soil microbes is essential for determining their impact on large scale ecosystem services, such as carbon sequestration, climate regulation, waste decomposition, and nutrient cycling. As the functional unit of soil ecosystems, we focus our attention on the spatial structure of soil macroaggregates. Emulating this complex physico-chemical environment as a patchy habitat landscape we investigate on-chip the effect of changing the connectivity features of this landscape as Escherichia coli forms a metapopulation. We analyze the distributions of E. coli occupancy using Taylor's law, an empirical law in ecology which asserts that the fluctuations in populations is a power law function of the mean. We provide experimental evidence that bacterial metapopulations in patchy habitat landscapes on microchips follow this law. Furthermore, we find that increased variance of patch-corridor connectivity leads to a qualitative transition in the fluctuation scaling. We discuss these results in the context of the spatial ecology of microbes in soil.
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Affiliation(s)
- Miles T. Wetherington
- Department of Ecology, School of Biological Sciences, P. Catholic University of Chile, Santiago, Chile
- Institute of Biophysics, Biological Research Centre, Szeged, Hungary
- School of Applied and Engineering Physics, Cornell University, Ithaca, NY, United States
- *Correspondence: Miles T. Wetherington
| | - Krisztina Nagy
- Institute of Biophysics, Biological Research Centre, Szeged, Hungary
| | - László Dér
- Institute of Biophysics, Biological Research Centre, Szeged, Hungary
| | - Janneke Noorlag
- Department of Natural Sciences and Technology, University of Aysén, Coyhaique, Chile
| | - Peter Galajda
- Institute of Biophysics, Biological Research Centre, Szeged, Hungary
| | - Juan E. Keymer
- Department of Natural Sciences and Technology, University of Aysén, Coyhaique, Chile
- Juan E. Keymer
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Ma ZS. Spatial heterogeneity analysis of the human virome with Taylor's power law. Comput Struct Biotechnol J 2021; 19:2921-2927. [PMID: 34136092 PMCID: PMC8164015 DOI: 10.1016/j.csbj.2021.04.069] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Revised: 04/27/2021] [Accepted: 04/27/2021] [Indexed: 01/16/2023] Open
Abstract
Spatial heterogeneity is a fundamental characteristic of organisms from viruses to humans. Measuring heterogeneity is challenging, especially for naked-eye invisible viruses, but of obvious importance. For example, spatial heterogeneity of virus distribution may strongly influence infection spreading and outbreaks in the case of pathogenic viruses; the spatial distribution (i.e., the inter-subject heterogeneity) of commensal viruses within/on our bodies can influence the competition, coexistence, and dispersal of viruses within or between our bodies. Taylor's power law (TPL) was first discovered in the 1960s to describe the spatial distributions of plant and/or animal populations, and since then it has been verified by numerous experimental and theoretical studies. Recently, TPL has been extended from population to community level and applied to bacterial communities. Here we report the first comprehensive testing of the TPL fitted to human virome datasets. It was found that the human virome follows the TPL as bacterial communities do. Furthermore, the TPL heterogeneity scaling parameter of human virome is virtually the same as that of the human bacterial microbiome (1.916 vs. 1.926). We postulate that the extreme closeness of human viruses and bacteria in heterogeneity scaling coefficients could be attributed to the fact that most of the viruses that were annotated in this study actually belong to bacteriophages (86% viral OTUs) that "piggyback" on their bacterial hosts, and their distributions are likely host-dependent. The scaling parameter, which measures the inter-subject heterogeneity changes, should be an innate property of human microbiomes including both bacteria and viruses. It is similar to the acceleration coefficient of the gravity (g = 9.8) as specified by Newton's law, which is invariant on the earth. Nevertheless, we caution that our postulation is contingent on an implicit assumption that the proportion of bacteriophages to total virome may not change significantly when more virus species can be identified in future.
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Affiliation(s)
- Zhanshan Sam Ma
- Computational Biology and Medical Ecology Lab, State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China.,Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China
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Ma Z(S. Predicting the Outbreak Risks and Inflection Points of COVID-19 Pandemic with Classic Ecological Theories. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2020; 7:2001530. [PMID: 33042733 PMCID: PMC7536942 DOI: 10.1002/advs.202001530] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/25/2020] [Revised: 08/07/2020] [Indexed: 05/07/2023]
Abstract
Predicting the outbreak risks and/or the inflection (turning or tipping) points of COVID-19 can be rather challenging. Here, it is addressed by modeling and simulation approaches guided by classic ecological theories and by treating the COVID-19 pandemic as a metapopulation dynamics problem. Three classic ecological theories are harnessed, including TPL (Taylor's power-law) and Ma's population aggregation critical density (PACD) for spatiotemporal aggregation/stability scaling, approximating virus metapopulation dynamics with Hubbell's neutral theory, and Ma's diversity-time relationship adapted for the infection-time relationship. Fisher-Information for detecting critical transitions and tipping points are also attempted. It is discovered that: (i) TPL aggregation/stability scaling parameter (b > 2), being significantly higher than the b-values of most macrobial and microbial species including SARS, may interpret the chaotic pandemic of COVID-19. (ii) The infection aggregation critical threshold (M 0) adapted from PACD varies with time (outbreak-stage), space (region) and public-health interventions. Exceeding M 0, local contagions may become aggregated and connected regionally, leading to epidemic/pandemic. (iii) The ratio of fundamental dispersal to contagion numbers can gauge the relative importance between local contagions vs. regional migrations in spreading infections. (iv) The inflection (turning) points, pair of maximal infection number and corresponding time, are successfully predicted in more than 80% of Chinese provinces and 68 countries worldwide, with a precision >80% generally.
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Affiliation(s)
- Zhanshan (Sam) Ma
- Computational Biology and Medical Ecology LabState Key Laboratory of Genetic Resources and EvolutionKunming Institute of ZoologyChinese Academy of SciencesKunming650223China
- Center for Excellence in Animal Evolution and GeneticsChinese Academy of SciencesKunming650223China
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Sun Y, Li L, Lai A, Xiao W, Wang K, Wang L, Niu J, Luo J, Chen H, Dai L, Miao Y. Does Ulcerative Colitis Influence the Inter-individual Heterogeneity of the Human Intestinal Mucosal Microbiome? Evol Bioinform Online 2020; 16:1176934320948848. [PMID: 33100827 PMCID: PMC7549164 DOI: 10.1177/1176934320948848] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2020] [Accepted: 07/16/2020] [Indexed: 12/11/2022] Open
Abstract
The dysbiosis of the gut microbiome associated with ulcerative colitis (UC) has
been extensively studied in recent years. However, the question of whether UC
influences the spatial heterogeneity of the human gut mucosal microbiome has not
been addressed. Spatial heterogeneity (specifically, the inter-individual
heterogeneity in microbial species abundances) is one of the most important
characterizations at both population and community scales, and can be assessed
and interpreted by Taylor’s power law (TPL) and its community-scale extensions
(TPLEs). Due to the high mobility of microbes, it is difficult to investigate
their spatial heterogeneity explicitly; however, TPLE offers an effective
approach to implicitly analyze the microbial communities. Here, we investigated
the influence of UC on the spatial heterogeneity of the gut microbiome with
intestinal mucosal microbiome samples collected from 28 UC patients and healthy
controls. Specifically, we applied Type-I TPLE for measuring community spatial
heterogeneity and Type-III TPLE for measuring mixed-species population
heterogeneity to evaluate the heterogeneity changes of the mucosal microbiome
induced by UC at both the community and species scales. We further used
permutation test to determine the possible differences between UC patients and
healthy controls in heterogeneity scaling parameters. Results showed that UC did
not significantly influence gut mucosal microbiome heterogeneity at either the
community or mixed-species levels. These findings demonstrated significant
resilience of the human gut microbiome and confirmed a prediction of TPLE: that
the inter-subject heterogeneity scaling parameter of the gut microbiome is an
intrinsic property to humans, invariant with UC disease.
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Affiliation(s)
- Yang Sun
- Department of Gastroenterology, The First Affiliated Hospital of Kunming Medical University, Yunnan Institute of Digestive Disease, Kunming, China
| | - Lianwei Li
- Computational Biology and Medical Ecology Lab, State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China.,Kunming College of Life Sciences, University of Chinese Academy of Sciences, Kunming, China
| | - Aiyun Lai
- Department of Rheumatology and Immunology, The First Affiliated Hospital of Kunming Medical University, Yunnan Institute of Digestive Disease, Kunming, China
| | - Wanmeng Xiao
- Computational Biology and Medical Ecology Lab, State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China.,Kunming College of Life Sciences, University of Chinese Academy of Sciences, Kunming, China
| | - Kunhua Wang
- Department of General Surgery, The First Affiliated Hospital of Kunming Medical University, Yunnan Institute of Digestive Disease, Kunming, China
| | - Lan Wang
- Department of Gastroenterology, The First Affiliated Hospital of Kunming Medical University, Yunnan Institute of Digestive Disease, Kunming, China
| | - Junkun Niu
- Department of Gastroenterology, The First Affiliated Hospital of Kunming Medical University, Yunnan Institute of Digestive Disease, Kunming, China
| | - Juan Luo
- Department of Gastroenterology, The First Affiliated Hospital of Kunming Medical University, Yunnan Institute of Digestive Disease, Kunming, China
| | - Hongju Chen
- Computational Biology and Medical Ecology Lab, State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China.,Kunming College of Life Sciences, University of Chinese Academy of Sciences, Kunming, China.,College of Mathematics, Honghe University, Mengzi, China
| | - Lin Dai
- Faculty of Science, Kunming University of Science and Technology, Kunming, China
| | - Yinglei Miao
- Department of Gastroenterology, The First Affiliated Hospital of Kunming Medical University, Yunnan Institute of Digestive Disease, Kunming, China
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Li L, Ma ZS. Species Sorting and Neutral Theory Analyses Reveal Archaeal and Bacterial Communities Are Assembled Differently in Hot Springs. Front Bioeng Biotechnol 2020; 8:464. [PMID: 32548097 PMCID: PMC7271673 DOI: 10.3389/fbioe.2020.00464] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2019] [Accepted: 04/21/2020] [Indexed: 12/03/2022] Open
Abstract
Although the recognition of archaea as one of the three kingdoms in the tree of life has been nearly a half-century long, the comparative investigations on their ecological adaptations with bacteria have been limited. The mechanisms of their community assembly and diversity maintenance in hot springs have not been addressed. The mechanistic study is critical not only for understanding the hot-spring microbiome structure and dynamics, but also for shedding light on their evolutionary adaptations. We applied the neutral theory model and species sorting paradigm of metacommunity theory to investigate how hot-spring microbial communities were assembled, how their diversities were maintained, and how the temperature and pH influence these mechanisms. Through rigorous statistical tests based on the neutral theory and species sorting paradigm, we found (i) According to the neutral theory, archaeal and bacterial communities are assembled differently, with stochastic neutral force playing a more significant role in archaeal communities than in bacterial communities (neutrality-rate = 52.9 vs. 15.8%, p-value < 0.05). (ii) Temperature and pH account for rather limited (<10%) variations in hot-spring microbiomes based on the species sorting paradigm. The pH has more significant influences than temperature on archaeal communities, and both pH and temperature have similarly low influences on bacterial community structure. (iii) We postulate that the differences between archaea and bacteria are likely due to the longer evolutionary history and better adaptation of archaea to host spring environments.
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Affiliation(s)
- Lianwei Li
- Computational Biology and Medical Ecology Lab, State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China.,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China
| | - Zhanshan Sam Ma
- Computational Biology and Medical Ecology Lab, State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China.,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China.,Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China
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Ma Z(S. Estimating the Optimum Coverage and Quality of Amplicon Sequencing With Taylor's Power Law Extensions. Front Bioeng Biotechnol 2020; 8:372. [PMID: 32500062 PMCID: PMC7242763 DOI: 10.3389/fbioe.2020.00372] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2020] [Accepted: 04/03/2020] [Indexed: 11/13/2022] Open
Abstract
Theoretical analysis of DNA sequencing coverage problem has been investigated with complex mathematical models such as Lander-Waterman expectation theory and Stevens' theorem for randomly covering a domain. In the field of metagenomics sequencing, several approaches have been developed to estimate the coverage of whole-genome shotgun sequencing, but surprisingly few studies addressed the coverage problem for marker-gene amplicon sequencing, for which arguably the biggest challenge is the complexity or heterogeneity of microbial communities. Overall, much of the practice still relies variously on speculation, semi-empirical and ad hoc heuristic models. Conservatively raising coverage may ensure the success of sequencing project, but often with unduly cost. In this study, we borrow the principles and approaches of optimum sampling methodology originated in applied entomology, achieved equal success in plant pathology and parasitology, and plays a critical role in the decision-making for global crop and forest protection against economic pests since 1970s when the pesticide crisis and food safety concerns forced the reduction of pesticide usages, which in turn requires reliable sampling techniques for monitoring pest populations. We realized that sequencing coverage is essentially an optimum sampling problem. Perhaps the only essential difference between sampling insects and sampling microbiome is the "instrument" used. In traditional entomology, it is usually humans that visually count the numbers of insects, occasionally aided by binocular microscope. In the metagenomics research, it is the DNA sequencers that count the number of DNA reads. Furthermore, a key theoretical foundation for sampling insect pest populations, i.e., Taylor's power law, which achieved rare status of ecological law and captures the population aggregation, has been recently extended to the community level for describing community heterogeneity and stability, namely, Taylor's power law extensions (TPLEs). This theoretical advance enabled us to develop a novel approach to assessing the quality and determining optimum reads (coverage) of amplicon sequencing operations. Specifically, two applications were developed: one is, in hindsight, to assess the quality of amplicon sequencing operation in terms of the precision and confidence levels. Another is, prior to sequencing operation, to determine the minimum sequencing efforts for a sequencing project to achieve preset precision and confidence levels.
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Affiliation(s)
- Zhanshan (Sam) Ma
- Computational Biology and Medical Ecology Lab, State Key Lab of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China
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Ma Z(S, Taylor RAJ. Human reproductive system microbiomes exhibited significantly different heterogeneity scaling with gut microbiome, but the intra‐system scaling is invariant. OIKOS 2020. [DOI: 10.1111/oik.07116] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Affiliation(s)
- Zhanshan (Sam) Ma
- Computational Biology and Medical Ecology Lab, State Key Laboratory of Genetic Resources and Evolution, Kunming Inst. of Zoology, Chinese Academy of Sciences Kunming PR China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences Kunming PR China
| | - Robin A. J. Taylor
- Dept of Entomology, The Ohio State Univ., Ohio Agricultural Research and Development Center Wooster OH USA
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