Where we came from, who we are, and where we are going have been explored since the existence of recorded history. Although most of us ignore various doomsday predictions about our planet and species, plus nature mother is often benign, it is an undisputed fact that nature can be a horrific enemy occasionally (McGuire, 2002). Humans have been fighting somewhat recurring battles against the results of its capriciousness—severe floods and storms, devastating earthquakes, cataclysmic volcanic eruptions (McGuire, 2002), and disease pandemics such as Justinian plague in year 541, which was estimated to have killed then half of world population (Morens and Fauci, 2020). The extinction of dinosaurs and 2/3 extant species at the Cretaceous period 65 million years ago reminds us that human race may exist and thrive only by geological accident and may be within a hair’s breadth of extinction, if the hypothesis of asteroid struck turns out to be true (McGuire, 2002). A recent report by Hyndman et al. (2018) suggests the protection obtained through the integration of bornaviruses into the genomes of Cretaceous-era mammals may have given them an advantage over reptiles as the predominant terrestrial vertebrates after dinosaurs went extinct. The integrated bornavirus genes, known as “endogenous bornaviral-like elements” (EBLs), which was lacking in birds and reptiles, granted mammals a level of protection against bornaviruses. As a side note, this advantage granted by EBLs is somewhat similar to the work principle of mRNA vaccine (against the COVID-19 infections). Of course, there is a fundamental difference between mRNA vaccine and EBLs. In the case of mRNA vaccine, the mRNA is not inserted into the human genome and is not inheritable. Enard and Petrov (2020), through reanalysis of the 1,000-genomes project data, detected approximately 4,500 host loci that may have preserved the footprints left by ancient viral epidemics in the past 50,000 years. Their findings suggest that RNA viruses have exerted significantly stronger selective pressures than DNA viruses across diverse human populations, also highlighting the more important zoonotic potential of RNA viruses.

SARS-CoV-2 is the gravest microbial threats to humans in the 21st century to date. The COVID-19 pandemic is obviously a stunning wakeup call that forces us to adapt, react, and reconsider the nature of our relationship with the natural world, and emerging and re-emerging infectious diseases such as COVID-19 are epiphenomena of human existence and our interactions with each other, and with natural world (Morens and Fauci, 2020). In the Anthropocene epoch, human activities have been frequently aggressive, damaging, and unbalanced interactions with nature, which creates an endless variety of opportunities for genetically unstable infectious agents (such as corona-viruses that are extremely easy to mutate) to spillover to the “unfilled” ecologic niches such as those created by biodiversity loss and climate changes (Cardinale et al., 2012; Faust et al., 2018; Johnson et al., 2020; Morens and Fauci, 2020). Without enacting essential adaptations, humans may increasingly trigger new disease emergences and remain at risk for the foreseeable future (Morens and Fauci, 2020).

Bernardo-Cravo et al. (2020) presented a pyramid model (diagram) for illustrating the manifold interactions among host, host microbiome, pathogens and the environment, which has one more component, human microbiome, than Morens and Fauci (2020) model. Figure 1 exhibited a slightly revised version of Fauci-Morens-Bernardo-Cravo model (termed FMB model hereafter) that highlights the key threads of medicine, ecology and environment. Bernardo-Cravo et al. (2020) argued that the tendency of host-disease risk or susceptibility is generally determined by his or her resistance and tolerance to pathogens, pathogen permeability of the host microbiome, pathogenicity (as determined by pathogen infectivity and virulence), as well as by environment (Figure 1). The severity of a disease may range from asymptomatic to fatality. The far-reaching influences of environmental factors, including various anthropogenic impacts such as pollution, climate change, and land use (i.e., deforestation, urbanization, and agricultural intensification) on our health and diseases have been receiving public attentions increasingly (Patz et al., 2005; Schmeller et al., 2020). We argue that most of the environmental factors, especially those caused by human activities, can lead to biodiversity loss that in turn may have significant influences on the risks of emerging diseases, particularly the spillover of zoonoses to humans, and on our susceptibility to diseases. In other words, pandemic disease emergence is likely determined by dynamic equilibriums of complex globally distributed ecosystems consisting of animals, pathogens, humans, and the environment (Cardinale et al., 2012; Newbold et al., 2015, 2018; Plowright et al., 2017; Rohr et al., 2020). Biodiversity conservation, which can be defined as “preserving functioning ecosystems with predominantly native species” (Rohr et al., 2020), is therefore of critical importance for us to fight against the emerging pandemics such as ongoing COVID-19.

Broadly speaking, medical enterprises humans involve are not limited to the diseases of humans and animals that are briefly touched previously. One obvious missing block is the diseases of plants, particularly of crops and forests, from which humans get food and major ecosystem services such as timbers, habitats for wildlife, conservation of soil erosion, prevention of desertification and watershed preservation and stable rainfall and climate. Figure 2 summarizes the major components of medical enterprises we discuss in this article, from disease and/or insect pests of plants (crops and forests), animals (livestock and wildlife), and humans. Obviously, the medical enterprises span many facets of science, technology, socioeconomics, and humanity (e.g., Dobson et al., 2020). In the present article, our focus is exclusively on ecological facet, the justifications of which are briefly explained below.

The ecological perspective of “One Health” is a strategy for tackling diseases, which takes into accounts all components and factors that may cause or raise risk of disease, and in which properties of human, environmental, and animal health are assessed in a unified manner to detect, understand, and solve public health problems (Ellwanger et al., 2020). Those components/factors may include environmental and ecological/wildlife, as well as domestic animal and human. The human factors also cover behavioral and medical issues, such as cultural, political and other socio-economic drivers that can influence disease spread and epidemics (Lloyd-Smith et al., 2005, 2009; Luis et al., 2015, 2018; Cunningham et al., 2017; Ellwanger et al., 2020). The devastating impacts of zoonoses on human health and wellbeing have been vividly demonstrating by the current COVID-19 pandemic, which is currently classified as emerging infectious disease (EID) with probable animal origin. Identifying the possible zoonotic emergence and the exact mechanisms responsible for its initial transmission can play a critical role in designing and implementing suitable preventive barriers against the further transmission of SARS-CoV-2. In consideration of the strong interrelatedness among animals, humans, and environment, prioritized research focus on one-health approach is likely to identify critical intervention steps in the transmission of zoonotic viruses (Gibb et al., 2020a,b; Latinne et al., 2020; Rahman et al., 2020; Tiwari et al., 2020).

The “One Health” strategy has been playing a critical role in investigating and dealing with emerging and reemerging infectious diseases, and it is undoubtedly one of the most successful ecological frameworks for dealing with emerging and reemerging infectious diseases. Since there are already many excellent reviews on “One Health” strategy, we are not going to further discuss it in this article. Different from the One Health strategy, in this article, we further broaden the scope of our discussion to virtually all major medical enterprises aimed to protect human well-beings from diseases of plants, livestock, wildlife, and ourselves. Furthermore, we focus on theoretical ecology foundations for diseases and supporting fields such as genomics, metagenomics, bioinformatics, and computational biology.

Ecology is not only relevant but also critical to virtually all major aspects of medical enterprises (sciences and technologies) illustrated in Figure 2. This is because pathogen, the causing agent of disease, is not an isolated entity; instead, pathogen interacts with its host and constitutes an ecosystem, not to mention that both pathogen and host are influenced by their environment. Ecosystem and environment are the very entities that ecology investigates. In fact, pathogen and host, and possible vector organism that introduces pathogen to host, frequently constitute the core of the host-pathogen ecosystem. As shown in Figure 2, at least three ecological subjects: disease ecology, IPM and medical ecology, are associated with medical enterprises of human well beings. The remainder of this reviewer is organized as four sections: (i) disease ecology of plants; (ii) disease ecology of animals; (iii) cancer ecology; (iv) ecology of human microbiome associated diseases; and (v) proposal toward a unified medical ecology of human diseases.

Before discussing the emerging/reemerging infectious diseases of animals and humans, we first discuss the diseases of plants. A simplified view of diseases is the diseased states of hosts caused by pathogens, which are usually microbes (bacteria, fungal, viruses, etc.) but insect pests, nematodes, mites as “pathogen” for plants (crops and forests) are obviously the largest exception. Here, we first discuss the disease ecology of plants, i.e., the integrated pest management (IPM).

The disease ecology can be defined as “the ecological study of host-pathogen interactions within the context of their environment and evolution” (Kilpatrick and Altizer, 2010). Broadly speaking, the origin of disease ecology can be traced back to the 1930s when entomologists studied the insect-parasitoid dynamics, known as Nicholson–Bailey model, which can be considered as difference equation version of the classic Lotka–Volterra differential equations for modeling species interactions (predator-prey, competition, etc.). The latter was proposed by mathematician and physicist Alfred Lotka and Vito Volterra during 1910s–1920s and their work set the foundation for theoretical (mathematical) ecology (Kingsland, 1995). Therefore, it can be seen that from the very beginning, theoretical (mathematical) ecology has been closely associated with the study of disease pathogen, although initially it was about the disease of animals and plants. The field took off in the 1950s and 1960s when population ecologists, entomologists, and plant pathologists were engaged in hot debates on the mechanisms of population regulation in nature. Theoretically, the debates helped to expand the breadth of theoretical ecology, and somewhat “ironically” shifted the focus of ecology away from population ecology, because the debates pushed ecologists and mathematicians to recognize that the mechanisms of population regulation and closely related themes such as population (ecosystem) stability, species extinctions could hardly be understood without looking into beyond species interactions. Those debates culminated at annual Cold Spring Harbor symposiums on population ecology in the 1960s but, as many ecologists believe, generated little consensus until today, other than shifting the focus of ecology from population ecology to community ecology, and directly catalyzed the emergence of ecosystem ecology from 1960s to 1980s. Although population ecology has never regained its glory since then, the methodology of using mathematical models pioneered by population ecologists has been firmly established as a tradition in whole ecological sciences, including landscape ecology and global change ecology (or planetary ecology). Practically, those debates had far reaching impacts on the strategies for humans to fight against diseases and insect pests of crop and forest plants.

By the 1960s, a consensus has been written into the textbook, and the consensus was that it is generally neither wise nor feasible to eradicate insect pests and/or plant diseases (Kogan and Jepson, 2007). The so-termed IPM is both the strategy and philosophy for humans to deal with the pest (insect pest and plant diseases) problem (Figure 3). Philosophically, we human usually have to coexist with pests, and indeed, we should tolerate their damages as long as the damages are below the so-termed economic tolerance level (ETL) (Kogan and Jepson, 2007). The reason we have to tolerate pests is certainly not because we do not wish to eradicate them, simply because we usually cannot destroy them or the eradication is too costly to bear. In fact, during the approximately two decades after World War II, the wide availability and usage of the pesticide DDT, once convinced people that the insect pest problem was solved forever. DDT was first developed in 1939 and was first used during World War II to clear South Pacific islands of malaria-causing insects for United States troops while being used as an effective delousing powder in Europe. It was believed to be the most powerful pesticide human had ever invented given it could virtually kill all kinds of insects tested from lice, mosquitoes, to caterpillars, and the inventor was awarded Nobel chemical prize.

When DDT was first introduced for civilian use in 1945, few expressed doubts. One was nature writer Edwin Way Teale (The Pulitzer Prize Winner of 1966), who warned, “A spray as indiscriminate as DDT can upset the economy of nature as much as a revolution upsets social economy. Ninety percent of all insects are good, and if they are killed, things go out of kilter right away.” Another was Rachel Carlson, the author of “Silent Spring” (1962) (NRDC, 2015), which spawned the environment movement since 1960s and the establishment of EPA (Environmental Protection Agency) in the United States. It was already known that in the 1960s, DDT was found in the ocean’s deepest and most inaccessible reaches such as fishes, mollusks and seabirds, and in penguin of the South Arctic. When the pesticides such as DDT was banned from usages due its potential healthy implications, entomologists and plant pathologists began to adopt a more ecological and environmental friendly approach, that is, the IPM (e.g., Kogan and Jepson, 2007). With the IPM philosophy, besides backing off from the eradication to tolerating (co-existence) strategy, and an integrated approach (rather than relying on a single tactic in particular pesticide, which should be minimized or avoided as much as possible) with multiple tactics such as quarantine, biological control with natural enemies, crop rotation, mixed plantation, biodiversity augmentation, etc. should be adopted. With the IPM, complex system analysis and mathematical modeling of pest-crop (forest) ecosystem should be used to quantify the ETL and economic threshold (ET), to predict the pest population dynamics, and to devise decision-making rules. By the 1990s, decision support systems (DSSs) using expert system and AI technologies had already been advocated to implement and guide the practice of IPM (Ma et al., 1992; Kogan and Jepson, 2007). Of course, constrained by then state-of-the-art in AI, the application of AI in IPM was rather primitive in today’s standards. Nevertheless, the ideas to use mathematical modeling and AI technology still certainly make sense not only in today’s IPM, but also in biomedicine of humans, especially as future trends (He et al., 2019; Zeng et al., 2021).

In retrospect of the history of IPM and in perspective of bio- and clinical medicines, we may draw the following four analogical principles:

The disease ecology, of course, is not limited to the ecology for plant diseases as briefly introduced previously, where the IPM has been established as the philosophy and strategy for managing insect pests and diseases of plants (crop, vegetables, fruits, and forests), and the biological control (bio-control with natural enemies) is well regarded as the most appropriate measure because of its ecological and environmental friendly nature. In addition, biodiversity augmentation such as mixed plantation of tree plants (mixed forests) has been demonstrated to be effective in managing forest diseases and insect pests. Nevertheless, the role of biodiversity augmentation in control plant diseases and pests is limited, perhaps because manipulating plant diversity is often economically unworthy or infeasible. Of course, increasing natural enemies may also be considered as increasing biodiversity, but it is usually categorized as bio-control. As it is briefly discussed below, in the disease ecology of wildlife, biodiversity or the so-termed diversity–disease relationship (DDR) has been a focus from early days of zoonotic research. Indeed, the importance of DDR of wildlife zoonoses cannot be overly emphasized because it is highly relevant to the spillover risk of zoonoses to humans!

Strictly speaking, the previous discussed IPM is traditionally not investigated in the context of disease ecology; instead it belongs to the domain of applied entomology (agricultural entomology, forest entomology, and horticulture entomology) and plant pathology. The reason we put the IPM into the context of disease ecology is to draw the common and essential principles underlying the diseases of plants, animals, and humans as shown later. The strict usage of disease ecology is usually limited to the diseases of the wildlife. Obviously, pathogens of wildlife are not only a common and integral part of natural ecosystems, but they are also linked to dynamics of wildlife populations. Their actions may drive their hosts to the extinctions occasionally; consequently pose deadly challenges to conservation efforts of endangered species. In the long run, they are also drivers of evolution and play pervasive ecological and evolutionary roles in the ecology and evolution of wildlife. At the foundational level, the mission of disease ecology includes the efforts to deepen our understanding on the pathogen transmission and spreading over space and time as well as their impact on host populations. These efforts also set foundation for epidemiology, which aims to identify risk factors for infectious and non-infectious diseases. Box 1 summarized some key concepts and aspects of disease ecology.

In our opinion, the field of zoonoses and EID are severely fragmented, possibly due to its highly cross-disciplinary nature. The fragmentation is highly undesirable because an inadvertent knowledge gap may leave the door open for an unwelcome black swan to enter. Therefore, sufficient coverage from cross-disciplinary perspectives is crucial for the healthy development of the field. The field traditionally involves epidemiology, public health, clinical medicine, veterinary medicine, medical microbiology and virology, immunology, ecology and evolution, environmental science, etc. In the 21st century, some emerging novel sciences and technologies joined in, notably molecular biology, bioinformatics, disease ecology, medical ecology, AI, and big data science and technology. The focus of this article is disease- and medical-ecology perspectives.

Arguably the most important mission in studying disease ecology of wildlife or zoonoses is to do with the emerging/reemerging infectious diseases (EID), which are frequently caused by pathogens originating from animal hosts, especially wildlife animals (Guégan et al., 2020). EID events are dominated by zoonoses (60.3% of EIDs): the majority of which (71.8%) originate in wildlife (e.g., SARS and Ebola virus), and are increasing significantly over time (Jones et al., 2008). Zoonoses are infectious diseases that are naturally transmittable from vertebrate animals to humans. Zoonotic viruses are not only the most frequently (constituting over 65% of pathogens discovered since 1980) newly emerging human pathogens, but also include some of the most heinous infectious diseases such as Ebola and Marburg virus, HIV-1 and HIV-2, Sin Nombre virus, Nipah, Hendra and Menangle virus, West Nile virus, Borrelia burgdorferi, and more recently (after 2000), SARS, Middle East respiratory syndrome (MERS) and several subtypes of avian influenza, as well as most recently and likely COVID-19. Some zoonoses requires intermediate vectors (also known as vector-borne pathogens: VBPs), including important human diseases such as malaria and dengue, as well as zoonotic diseases for which people are dead-end hosts, such as Lyme disease and West Nile virus (Taylor et al., 2001; Woolhouse et al., 2001; Woolhouse, 2002; Woolhouse and Gowtage-Sequeria, 2005; Kilpatrick, 2011; Kilpatrick and Randolph, 2012; Johnson et al., 2015a). Johnson et al. (2015a) survey suggested that wild animals were the major source (91% or 86 out of 95) transmission of zoonotic viruses, while only 34% (32 out of 95) transmitted by domestic animals, and 25% by both wild and domestic animals. For example, the Nipah virus (NIV) was introduced into pigs from wild animals, time after time, such as bats, leading to persistent enzootic infection in pigs. Eventually, spillover of NIV to livestock workers occurred (Walsh, 2015).

It was found that the majority (94%) (N = 162) of zoonotic viruses discovered before 2015 were RNA viruses, far more than the number of zoonotic DNA viruses. RNA viruses, such as influenza viruses, flaviviruses, enteroviruses, and coronaviruses, have inherently deficient or absent polymerase error-correction mechanisms and are transmitted as quasi-species or swarms of many, often hundreds or thousands of, genetic variants. Their genetic instability is particularly high, which allows for rapid microbial evolution in an extremely diverse population under natural selection (Morens and Fauci, 2020).

Wild rodents were identified as a spillover source of some zoonotic viruses, such as zoonotic arenaviruses and zoonotic bunyaviruses (Han et al., 2015). Bats belong to oldest mammals and contribute about 20% to mammalian diversity (Zhang et al., 1992; Johnson et al., 2020). Their vast diversity and long co-evolutionary relationships with pathogens maximize the opportunity for cross-species mixing and maintenance of quasi-species pools of viruses that may infect a range of hosts (Menachery et al., 2017). Bats appear to be the most active transmitters given they were more implicated for zoonotic paramyxoviruses and most zoonotic rhabdoviruses (Brook and Dobson, 2015), while primates were implicated as a transmission source of zoonotic retroviruses (Johnson et al., 2015a). Bats are also among the most abundant source for novel viral sequences (Anthony et al., 2013), which have been identified mainly from enteric samples (i.e., bat guano). The huge pools of viruses in bat guano may play a critical role in the bat microbiome to prime their immunity (Menachery et al., 2017).

Despite harboring exceptionally diverse kinds of viruses, surveyed bats rarely display signs of disease, a phenomenon similarly discovered in humans with herpes viruses (Barton et al., 2007). Understanding why bats seem to possess exceptional immunity against viruses is of obvious importance. One important reason may be that virus tropism differences between species and tissues may contribute to limiting disease in bats. Enteric infection can be a significantly different tissue than the respiratory tract in terms of disease and adaptive immunity. The enteric location may generate a dampened adaptive response that permits viral maintenance, while elements of adaptive immunity in bat species keep functional, similar to the members of the microbiome in human guts (Menachery et al., 2017).

The unique host environment of bats is also responsible for the broad diversity in corona-virus (CoV) quasi-species pools. During flight, bats can accumulate reactive oxygen species (ROS) for short periods of time, which may have mutagenic effects, possibly overwhelming CoV proofreading repair and/or altering viral polymerase fidelity and increasing species diversity. The mutagenic effects may also be critical for cross-species or spillover transmission (Seronello et al., 2011). Similarly, Zhou et al. (2016) found that the constitutive expression of type-I IFN (interferon or IFN-α) in bat hosts may select for advantageous viral mutations that enhance resistance to innate immune antiviral defense pathways and provide a replication advantage, especially after cross species transmission. That is, constitutively expressed IFN-α may result in the induction of a subset of IFN-stimulated genes associated with antiviral activity and resistance to DNA damage, suggesting a unique IFN system of bats that promotes their capacity to coexist with viruses (Zhou et al., 2016).

It should be noted that, in spite of previous discussed multiple suspicions bats are implicated, those animals should not be automatically labeled as “bad guys” in spillover events. It is a fact that bats harbor more viruses than many animals, and several studies already pointed important features of bat immune system as involved in both resistance to disease and viruses maintenance in bat populations (Zhou et al., 2016). In other words, bats may possess special mechanisms to “neutralize” disease risks from viruses they host. Actually, few data is available concerning other wildlife species eventually similarly or even more “spillover prone” than bats.

Phylogenetic analyses based on sequence similarity have been playing an important role in studies of the origin and cross-species transmission (spillover) of coronaviruses (e.g., Latinne et al., 2020). Munnink et al. (2020) conducted an in-depth investigation of SARS-CoV-2 infections in animals and humans working or living in 16 mink farms in the Netherlands. SARS-CoV-2 infections were detected in 68% (66 out of 97) of the owners, workers, and their close contacts. Their study provided evidence of SARS-CoV-2 spillover back and forth between animals and humans within mink farms given some people were infected with viral strains with an animal sequence signature. Theoretically, an animal species of sufficiently high population density to allow natural selection and a competent ACE2 protein for SARS-CoV-2 to “hook,” such as mink, would be a possible host of the direct progenitor of SARS-CoV-2 (Zhou and Shi, 2021). However, whether bats or pangolins, which carry coronaviruses with genomes that are ∼90 to 96% similar to human SARS-CoV-2, were the animal source of the first human outbreak, are still in hot debates because there is not certain evidence other than the previously mentioned genome similarity (Hu et al., 2020). Phylogenetic analyses of viral genomes from bats and pangolins revealed that further adaptations, either in animal hosts or in humans, must have occurred before the virus caused the COVID-19 pandemic, if SARS-CoV-2 was indeed spillover from bats or pangolins. SARS-CoV-2 antibodies were detected in human serum samples taken outside of China before the COVID-19 outbreak was detected, which indicates that SARS-CoV-2 had existed for some time before the first cases were described in Wuhan (Andersen et al., 2020). Therefore, it is possible that spillover of SARS-CoV-2 had occurred long before humans discovered its infections.

The zooanthroponosis of SARS-CoV-2 (COVID-19) has been confirmed by its successful detections in animals including domesticated cats, dogs, and ferrets, as well as captive-managed mink, lions, tigers, deer, and mice. Other than circumstantial evidence of zoonotic cases in mink farms in the Netherlands (Zhou and Shi, 2021), no cases of natural transmission from wild or domesticated animals to humans have been confirmed; therefore the zoonotic status of COVID-19 is still a conjecture (e.g., Dhama et al., 2020). Currently nearly 1/4 billion human COVID-19 infections documented seem to be exclusively via human–human transmissions. That is, SARS-CoV-2 virus and COVID-19 do not seems to satisfy the WHO (World Health Organization) definition for zoonoses. For this reason, Haider et al. (2020) suggested to classify SARS-CoV-2 (COVID-19) as an EID of probable animal origin. Compared with other emerging viruses, such as Ebola, avian H7N9, SARS-CoV, and MERS-CoV, SARS-CoV-2 is of relatively low pathogenicity and moderate transmissibility.

Arguably, few other human diseases have been investigated more extensively from ecological and evolutionary perspectives than cancers. Perhaps, the only exceptional category has been the epidemiological studies of infectious diseases, and more recently the microbiome-associated diseases. Ecological concepts and principles have been extensively applied to study cancer and so does the evolutionary theory. Box 2 summarized 20 such concepts, principles, and theories that originated from ecological and evolutionary sciences and found applications in cancer research. Two particular points are worthy of special mentions here, as explained below:

One is that ecology and evolution are innately interwoven for cancer studies: using Hutchinson (1965) classic monograph titled “The Ecological Theatre and Evolutionary Play,” cancer evolution is played out in the ecological setting (the “theater”) of constraining and changing environments (Hall, 2017). The cancer cell environment includes other host cells, microbiomes, and the biochemical and physiological environments. Obviously, virtually everything in cancer environment is dynamic, and for this reason, cancer evolution, which is played out at ultra- micro-, micro-, macro-, and global scales as explained in Box 2. Environment also supplies the energy and materials that allows cancer cells to survive and evolve, until they evolve to their maximal fitness, which kills its host but ironically themselves too, or they are suppressed and/or eradicated by competitions from other somatic cells, predation by immune cells, and/or various medical treatments. For the interwoven nature between cancer ecology and evolution, evo-eco (or eco-evo) paradigm for cancer research has been suggested to play a similar role as the popular evo-devo in evolutionary developmental biology.

Another point to note is the somewhat mismatch between theoretical studies and clinic applications. Although the recognition of cancer as an evolutionary process occurred more than a half-century ago and the recognition of ecological theories have also occurred since the new century, and evo-eco thinking has indeed generated tremendous impacts on cancer research, we must admit that much of the research remain are at the stage of discussions on their parallels. Indeed, much of the ecological and evolutionary concepts in cancer ecology are analogies (parallels) drawn from ecology and evolution. For this reason, evo-eco thinking has not achieved tangible clinic success. As indicated by Korolev et al. (2014), it is crucial to pursue the identified parallels further by making them quantitative, testable, and eventually useful insights for devising therapy strategies and methods (Plutynski, 2021). DNA sequencing technologies, and experiments with microbes and animal models have created unprecedented opportunities to revolutionize the eco-evolutionary studies on cancers.

Cancer is so closely related to genes that it is considered to be a disease of human genome; recent findings suggest that human metagenome is also involved in cancer development (Poore et al., 2020). For this reason, beyond the points summarized in Box 2, in the remainder of this sub-section, we briefly discuss a more recent topic in cancer ecology, the relationship between cancer and human microbiomes. Human microbiomes are distributed not only within and on human bodies, but also within the tumor tissues. They can be neighbors of cancer cells as well as “insiders” within cancer cells. Therefore, microbiomes should have far reaching impacts on the cancers. Nevertheless, the field is still in its infancy stage with a history of slightly longer than a decade.

Bacteria and virus within tumors are localized within both cancer cells and immune cells. However, exact diagnostic implications of microbial contributions to different types of cancer were largely unknown until Nejman et al. (2020) and Poore et al. (2020). Poore et al. (2020) reanalyzed microbial reads from 18,116 samples from 10,481 patients belonging to 33 cancer types deposited in TCGA databases by utilizing machine learning algorithms. They found that there are unique microbial signatures in tissue and blood within and between most cancer types. In some cases, microbiome signature can be more sensitive than human genomic signature. Nejman et al. (2020) took largely experimental approaches to investigating the 1,526 tumor and adjacent normal tissues across seven cancer types covering breast, lung, ovary, pancreas, melanoma, bone, and brain tumors. Their findings are similar to those obtained from the bioinformatics (machine-learning) approaches by Poore et al. (2020). For example, Nejman et al. (2020) demonstrated from their 1,526 tumor microbiome samples that the beta-diversity within a given tumor type is smaller than the beta-diversity between tumor types, i.e., the within cancer type similarity (between tumor tissue and adjacent normal tissue) is larger than between cancer types.

Although bacteria were first detected in human tumors more than a century ago (Nejman et al., 2020), the studies on the relationship between microbiome and cancer is still in its early infancy, and answers to many of the fundamental questions are still open. The most intensively studied microbiome-cancer relationship has been focused on gut microbiome, but in recent years, attentions have been increasingly paid to tissue microbiome such as lung-tissue microbiome and lung cancer relationship. Understanding how microbes in the respiratory tract might influence lung carcinoma development and treatment efficacy may be instrumental for forecasting the risk of cancer development and to improve treatment efficacy and safety (Ramiìrez-Labrada et al., 2020). Cooperative interactions between microbiome and host might lead to microbial participation in host functions such as defense and metabolism. Furthermore, the same microbes that promote human health, under one circumstance, might induce disease and cancer development in another circumstance. In some other circumstances, the change of microbiome composition may cause disease.

In the case of lung cancer, it has been postulated that altered lung microbiome and chronic inflammation in lung tissue contribute to carcinogenesis (e.g., Clavel et al., 2017). The lung microbiome dysbiosis may modulate the risk of malignancy at multiple levels including chronic inflammation and oncogenes (e.g., Tsay et al., 2021). The correlation between repeated antibiotic exposure and increased risk of lung cancer has been investigated. Several bacteria including Mycobacterium tuberculosis have been found to relate with lung cancer.

The coevolution of the host immunity-microbiome interaction may have led to the development of regulatory pathways that modulate self-tolerance and tolerance against non-cancerous agents vs. elimination of pathogens and tumor cells. The delicate balance between tolerance and lung immune activation may be interrupted by changes in immunity-microbiome cooperation due to the antibiotic overuse, changes in diet, or chronic infections, and the loss of balance might raise the risk of lung cancer (e.g., Woodhams et al., 2020).

YPZ and ZSM conceived and outlined the review topics. ZSM wrote the draft. Both authors revised the draft and approved the submission.

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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