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Opinion
SARS-CoV-2: Cross-scale Insights from
Ecology and Evolution
Celine E. Snedden,
1,5
Sara K. Makanani,
1,5
Shawn T. Schwartz,
1
Amandine Gamble,
1
Rachel V. Blakey,
1,2
Benny Borremans,
1,3,4
Sarah K. Helman,
1
Luisa Espericueta,
1
Alondra Valencia,
1
Andrew Endo,
1
Michael E. Alfaro,
1,∗
and James O. Lloyd-Smith
1,∗
Ecological and evolutionary processes govern the fitness, propagation, and interac-
tions of organisms through space and time, and viruses are no exception. While
coronavirus disease 2019 (COVID-19) research has primarily emphasized virologi-
cal, clinical, and epidemiological perspectives, crucial aspects of the pandemic
are fundamentally ecological or evolutionary. Here, we highlight five conceptual
domains of ecology and evolution –invasion, consumer-resource interactions, spa-
tial ecology, diversity, and adaptation –that illuminate (sometimes unexpectedly)
the emergence and spread of severe acute respiratory syndrome coronavirus 2
(SARS-CoV-2). We describe the applications of these concepts across levels of
biological organization and spatial scales, including within individual hosts, host
populations, and multispecies communities. Together, these perspectives illustrate
the integrative power of ecological and evolutionary ideas and highlight the benefits
of interdisciplinary thinking for understanding emerging viruses.
The Integrative Power of Ecological and Evolutionary Concepts for
Understanding Emerging Viruses
Zoonotic pathogens, namely those transmitted from vertebrate animals into humans, comprise
a majority of the infectious diseases that plague humankind. Examples range from pathogens
that infect humans exclusively via spillover (see Glossary)fromanimalreservoir hosts
(e.g., rabies virus, Leptospira interrogans, West Nile virus) to those that spread among humans
for decades after a successful spillover event (e.g., HIV-1, influenza A virus) [1]. Most recently,
the emergence of SARS-CoV-2 triggered the COVID-19 pandemic, up-ended global society,
and stimulated an unprecedented burst of research spanning multiple disciplines. Much of
this research addresses the growth and change of SARS-CoV-2, which are population
processes that are deeply rooted in ecology and evolutionary biology [2,3]. These disciplines
have proven their utility for combating infectious diseases by informing public policy [4,5],
identifying potential reservoir hosts [6], and directing vaccine research [7,8]. Yet despite their
inherent power to integrate findings from other disciplines, ecological and evolutionary ideas
have not been fully appreciated in the current SARS-CoV-2 literature. Vast opportunity remains
to explore their fruitful applications across levels of biological organization (henceforth referred
to as scales), namely within individual hosts, host populations, and multispecies communities.
By recognizing parallels in the patterns and processes governing viral dynamics at these
different scales, the scientific community can harness existing knowledge in ecology and
evolutionary biology to drive progress in understanding, mitigating, and preventing the
emergence of infectious diseases.
To advance this aim, here we illustrate how five conceptual domains of ecology and evolutionary
biology can shed light on the emergence of novel viruses, including SARS-CoV-2, across the
Highlights
Foundational concepts from ecology
and evolution can elucidate the
emergence and spread of severe
acute respiratory syndrome coronavi-
rus 2 (SARS-CoV-2), and all viruses,
across multiple scales.
Ecological and evolutionary methods
that characterize population dynamics
of organisms are potent tools to
investigate viral growth and spread within
individual hosts, or epidemic growth in
host populations.
The field of macroevolution classically
studies the diversification and adaptation
of multicellular organisms, but major op-
portunities exist to apply macroevolution-
ary concepts to the evolution of viruses.
Concepts from spatial ecology, from
source-sink dynamics to synchrony,
can help us to understand patterns and
processes in the emergence of viruses.
Interdisciplinary research across the life
sciences can reveal otherwise unattain-
able insights into emerging infectious
diseases, posing new hypotheses and
refining existing knowledge in traditional
disciplines.
1
Department of Ecology and
Evolutionary Biology, University of
California, Los Angeles, CA, USA
2
La Kretz Center for California
Conservation Science, Institute of the
Environment and Sustainability,
University of California, La Kretz Hall,
Los Angeles, CA, USA
3
I-BioStat, Data Science Institute,
Hasselt University, Hasselt, Belgium
4
Evolutionary Ecology Group, University
of Antwerp, Antwerp, Belgium
5
These authors contributed equally to
this work
Trends in Microbiology, Month 2021, Vol. xx, No. xx https://doi.org/10.1016/j.tim.2021.03.013 1
© 2021 Elsevier Ltd. All rights reserved.
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within-host, population, and multispecies community scales (Figure 1, Key Figure). Though these
conceptual domains (hereafter, concepts) are inextricably linked, we present them separately
(each partitioned into discrete paragraphs by scale) and provide graphical representation of
their connections (Figure 2). In parallel, we emphasize tools and methods developed in ecology
and evolutionary biology that can unlock insights for understanding this, or any, pandemic
(Boxes 1 and 2). Our goal is not to provide an exhaustive review of the ballooning COVID-19
literature but instead to translate and apply relevant ideas from ecology and evolutionary biology
in a manner accessible to a wide audience. In particular, we aim to: (i) demonstrate the integra-
tive power of ecological and evolutionary ideas for scientists from different disciplines
(e.g., microbiology, mathematics, public health), (ii) excite students about the broad applica-
tions of ecology and evolution across the life sciences, and (iii) prompt established ecologists
Key Figure
Cross-scale Applications of Ecological and Evolutionary Concepts to Viruses, with Examples from
Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2)
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Figure 1. A series of descriptions highlighting five core ecological and evolutionary principles at multiple scales, including within host (individual; blue), within po pulations (population;
purple), and across species (community; pink). Bolded content reflects the general applications of each concept to viruses. Italicized content reflects specific examples relevant to
SARS-CoV-2 and SARS-like coronaviruses (CoVs). The references for each concept and example can be found in the corresponding paragraph of the text.
*Correspondence:
michaelalfaro@ucla.edu (M.E. Alfaro)
and jlloydsmith@ucla.edu
(J.O. Lloyd-Smith).
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and evolutionary biologists to recognize novel opportunities to apply their expertise across
disciplines and scales to fight this and future pandemics.
Ecological Dimensions of Viral Emergence
The field of ecology focuses on the distribution, abundance, and interactions of organisms across
space and time, and is traditionally subdivided by levels of organization, which include the popu-
lation scale (i.e., the study of one species in a given region) and the community scale (i.e., the
study of multiple species). Less conventionally, an individual organism can be viewed as its
own within-host ecosystem, where host cells and microorganisms interact in a landscape of
host tissues. In the context of infectious diseases, ecological principles govern the population
dynamics of many relevant entities (including viruses, cells, and host individuals), and these
population processes can naturally be delineated at different scales [9]. Below, we introduce
each concept at the population scale, as it provides the most intuitive platform for discussion,
followed by applications at the within-host and within-community scales.
Invasion Processes and Emerging Viruses
The success of a virus in a new target population is governed by processes of ecological invasion,
which manifest in phases of introduction, establishment, and spread [10–12]. For example, when
the COVID-19 pandemic began, infected travelers from China transported SARS-CoV-2 to coun-
tries across the globe, including Germany, Italy, and the USA [13]. Once introduced, successful
establishment of a virus requires local transmission, which depends on viral shedding, host con-
tact patterns, and host population susceptibility [10,14]. The likelihood of establishment
increases if multiple introduction events occur or if many individuals arrive simultaneously, as
described by the propagule pressure hypothesis [15]. In the event of sustained community
transmission, the virus can be considered an invasive species in this local host population. Sub-
sequent dispersal propagates the virus further by initiating similar invasion processes in other
connected regions [10]. SARS-CoV-2 showcases that these invasion waves can ultimately trigger
a global pandemic.
The infection of an individual host can also be viewed as an invasion process, wherein exposure
introduces a founder population of potentially invasive viruses (i.e., the inoculum). The route of
this exposure determines the inoculation site, where receptor expression, immune activation, and
other factors determine tissue susceptibility [16], just as resource availability and the presence of
competitors, predators, and pathogens impact landscape suitability for introduced plant and
animal species [10,17]. These host factors vary across tissues and affect the probability of estab-
lishing local infection for a given site of deposition [16,18]. Once established, onward spread is
governed by tissue susceptibility, physical connectivity, and transport mechanisms. For instance,
SARS-CoV-2 infection typically begins in the respiratory tract, where the cellular receptor
angiotensin-converting enzyme 2 (ACE2) is highly expressed, and it has been proposed that
subsequent neuroinvasion can occur via the olfactory nerve or via the bloodstream paired with
damage to the blood–brain barrier [19]. While the effect of a single high-dose exposure versus
multiple low-dose exposures remains largely unresolved [15,18,20], invasion theory predicts
that, for a given dose, infection is more likely when viruses deposit at different sites across a
heterogeneous tissue landscape [21].
At the community scale, the invasion analogy applies to viral host jumps, where a virus must
overcome sequential barriers to invade a novel host species [10–12,22]. Given some type of
cross-species contact, viral shedding from reservoir or intermediate hosts can introduce the
virus to an individual from a recipient host species [11,22]. A variety of virological and evolutionary
factors (dictated by the within-host invasion process) influence establishment of the virus in this
Glossary
Adaptive radiation: the rapid
diversification of organisms in response
to available environmental niches.
Bottleneck: a reduction in genetic
variation resulting from a change in
populationsize that occurs for at least
one generation.
Convergent evolution:similarity in trait
or genotype that is acquired
independently in two or more lineages,
often interpreted as evidence of
adaptation.
Dispersal: movement of individuals
across a landscape.
Ecological opportunity: the
environmental potential available to a
newly colonizing lineage for
diversification into divergent niches.
Ecological trap: a low-quality habitat
patch, where mortalities exceed births,
that decreases overall population fitness
because individuals settle in these
habitats instead of other available high-
quality habitats.
Enemy release hypothesis: this
hypothesis posits that the absence of
enemies (e.g., predators) within an
invasive species’exotic range leads to
successful invasion.
Exaptation: a trait that evolved by
natural selection to perform a specific
function that later performs another
unrelated function.
Founder population: agroupof
individuals from a larger population that
migrate, settle, and establish a new
population in a new, uninhabited
environment.
Functional response: the relationship
between consumption rate of a
consumer (e.g., predator) and
abundance of the target resource
(e.g., prey).
Gene flow: exchange of genetic
material between connected
populations through migration.
Genetic drift: changes in allele
frequency within a population due to
random chance.
Intermediate host: a host species that
acts as a bridge to facilitate pathogen
transmission between a reservoir
species and a focal host species.
Invasive species: aspecies
introduced to an area outside its normal
range, often by human means, where it
reproduces and spreads beyond the
area in which it was released and
negatively impacts the new ecosystem.
Landscape immunity: defined in [22]
as the ecological conditions that control
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host, including immune defenses and the availability of suitable cellular receptors. Even if the virus
successfully infects this individual, other barriers can limit further spread within this novel host
population (dictated by the population invasion process) [10,11]. For SARS-CoV-2, the path to
zoonotic spillover remains unknown, though the progenitor virus likely originated in bats. The di-
versity of bat viruses, if paired with contact among humans and bats, potentially via intermediate
hosts, can provide multiple opportunities for successful cross-species invasion to occur, as de-
scribed by the propagule pressure hypothesis [15,22,23]. Several groups of bat-borne viruses,
including the Henipaviruses and Ebolaviruses, are well known to have caused numerous out-
breaks via independent zoonotic transmissions [23]. Given evidence of multiple spillover events
of SARS-like coronaviruses [24], further investigation is warranted into whether SARS-CoV-2
could have been introduced to humans more than once. Once introduced, the
contrast between the robust antiviral defenses in bats and humans, combined with the immuno-
logical naïveté of the human population, may have facilitated the successful invasion of SARS-
CoV-2 as suggested by the enemy release hypothesis [17,25].
Consumer–Resource Interactions between Viruses, Hosts, and Intervention Strategies
The population dynamics of a virus invariably depend on consumer–resource interactions in
which consumers rely on, and directly impact, resource availability. These interactions are a
critical component of ecological community structure and provide the foundation for classical
epidemiological models, where populations of infected hosts grow by 'consuming' susceptible
individuals (i.e., the resource). In fact, the simplest epidemic models and predator–prey models
are mathematically equivalent (Box 1)[26] and thus share fundamental features such as the
tendency to cycle. Vaccination reduces susceptible availability and hence lowers infection preva-
lence [4,27], just as a loss of prey reduces predator abundance. Less obviously, nonpharmaceutical
interventions can be analyzed in the consumer–resource framework where contact tracers can be
viewed as hyperpredators that remove (i.e., consume) infected individuals from a population, and
physical distancing alters how the infection rate depends on susceptible abundance (i.e., the
functional response). Such epidemiological models can provide prompt insights into the popula-
tion dynamics of an emerging virus under various assumptions (e.g., quarantine compliance, vacci-
nation rates), as evidenced in the SARS-CoV-2 literature (e.g., [27]). While obtaining accurate
predictions from these models requires reliable parameter estimates from high-quality datasets,
strategies developed in ecology can account for and leverage imperfect data (Box 1).
The interactions between viruses and cells within an individual host can also be treated as a
network of consumer–resource interactions [28]. In the simplest case, viruses (i.e., the consumer)
infect susceptible cells (i.e., the resource), thus decreasing susceptible cell population size while
increasing viral population size (Box 1)[29]. This conceptual framework can also incorporate the
immune system, which can consume viral particles and infected cells [30] or block viral consump-
tion of susceptible cells by stimulating an antiviral state [25]. Models that incorporate these inter-
actions improve our understanding of the immune system and our ability to control disease
progression [29]. For instance, they can explore the impacts of target cell depletion on viral
load and within-host spread [28].
Consumer–resource interactions influence community-level dynamics of virus emergence by
providing opportunities for spillover events and potential pandemics [2]. For instance, the hunting,
handling, and consumption of livestock and wildlife can expose humans to zoonotic viruses
through contact with infected tissues [11,31]. Three familiar examples include SARS-CoV, HIV-1,
and 2009 H1N1 pandemic influenza virus (H1N1pdm), which are linked to palm civets in Chinese
wildlife markets, hunted chimpanzees in Central Africa, and pig farms in Mexico, respectively
[31,32]. Though the precise origin of SARS-CoV-2 remains unclear, the trade and consumption
pathogen populations while
strengthening the immune functions of
wild animals in an ecosystem.
Population dynamics: the study of
how and why population size and
structure change over time.
Propagule pressure hypothesis: this
hypothesis posits that a greater number
of individuals in a single release event or
a higher frequency of release eventsover
time increases the likelihood of invasion
success.
Reassortment: atypeof
recombination exclusive to segmented
viruses in which coinfection of a host cell
results in the exchange of gene
segments between similar virus strains.
Recombination: the process by which
segments of genomic material are
broken and exchanged during genome
replication, creating new combinations
of alleles.
Reservoir host: ahostspeciesin
which a pathogen circulates
continuously without reintroduction and
which can transmit the pathogen to
other hosts.
Spillover: the transmission of a
pathogen from one host species to
another; zoonotic spillover specifies
transmission from a vertebrate animal to
ahuman.
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of exotic animals in Chinese wildlife markets have been suspected to be involved [33]. Interactions
with farmed animals can also facilitate human-to-animal transmission of viruses, as most recently
evidenced by SARS-CoV-2 outbreaks in mink farms [34]. Many countries have also reported
human-to-pig H1N1pdm transmission, where further reassortment could generate another virus
capable of infecting humans [35]. These examples highlight the inherent health risks (for both
humans and animals) associated with animal products, and they emphasize the importance of
developing, implementing, and managing more responsible biosecurity regulations for livestock
and wildlife trade [36].
Ecological Principles Governing Virus Spatial Dynamics
Spatial ecology describes the spread, persistence, and interactions of individuals across land-
scapes consisting of habitat patches connected by dispersal. Individuals moving from source
habitats, where birth rates exceed mortality rates, can colonize new habitats or sustain popula-
tions in sink habitats, where mortalities exceed births [37]. This source–sink framework directly
applies to spatial spread of disease, where epidemiologists call sources 'supercritical' and
sinks 'subcritical' for pathogen transmission. For example, during the early COVID-19 epidemic
in China, infected travelers from Wuhan (i.e., the source, with positive epidemic growth) sparked
outbreaks in many other Chinese cities (i.e., the new habitats). However, prompt implementation
of local control measures in these cities reduced growth rates to become negative (i.e., they
became sinks), so those outbreaks died out once the source outbreak was controlled [38]. In
such heterogeneous landscapes, synchronous dynamics, wherein populations rise and fall
concurrently, increase the likelihood of population-wide extinction. Such synchrony can arise
from correlated exogenous factors (e.g., climate conditions) and/or sufficient dispersal [39]. For
viruses, if prevalence declines simultaneously in connected patches, the absence of high-
prevalence sources prevents dispersing hosts from recolonizing locally extinct patches [39,40].
Public health officials can leverage this principle to limit the spread of emerging infectious diseases
if control policies are coordinated across cities and regions to promote synchronous declines in
prevalence. Unfortunately, the lack of coordination plaguing the COVID-19 response has allowed
reseeding of outbreaks in locales that had previously contained SARS-CoV-2, leading to more
cases and more interventions needed [5].
These spatial ecology concepts can also illuminate viral spread within the spatially structured
organs and tissues of an infected host. Because viral replication depends on many factors,
including temperature, immune response, and cellular receptor and protease expression, dif-
ferent tissues act as sources or sinks [41]. For example, to enter a cell, the SARS-CoV-2
spike protein must bind to the ACE2 receptor and be primed by the protease TMPRSS2, al-
though other receptors and proteases may also be involved [42]. Tissues with sufficient
coexpression of ACE2 and TMPRSS2 (e.g., nasal cavity) may act as sources that seed infection
of surrounding areas with lower expression levels (e.g., bronchioles) [16,43]. When ACE2 is
expressed without TMPRSS2 (e.g., the heart), a tissue may function as an ecological trap,
where virions bind target cells but cannot enter or replicate [3,41,43]. Interestingly, this concept
can be leveraged to design therapeutics (e.g., [44]). Physical transport mechanisms can also
create ecological traps: for instance, SARS-CoV-2 may infect the central nervous system
[19], but the viral particles produced in these tissues cannot readily transmit between hosts.
Additionally, SARS-CoV-2 largely infects the human upper respiratory tract, from which pro-
duced virions are readily expired, whereas Middle East respiratory syndrome coronavirus
(MERS-CoV) and SARS-CoV infections predominantly reside in the lower respiratory tract,
from which viral particles cannot readily be expelled from the host [45]. This difference in tissue
tropism affects the transmissibility of these coronaviruses, and likely their pandemic potential.
These examples demonstrate that models designed in spatial ecology can integrate knowledge
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Box 1. Ecological Methods for Modeling Viral Dynamics and Addressing Data Limitations
Classically, ecologists study population dynamics by using mechanistic models that classify entities (e.g., individuals) into
compartments according to their states and quantify transition rates between them. Most models of disease transmission
are based on the classification of individuals into susceptible (S), infectious (I), and recovered/immune (R) states (Figure I),
though additional states are frequently included [26,27]. Other applications include within-host models of virus replication
(classified by target cells, infected cells, and free-living virus) [29] and between-farm models of infected livestock (e.g., foot-
and-mouth disease, classified by susceptible, noninfectious, infectious, and slaughtered farms) [83]. Various mathematical
frameworks can capture these dynamics and advance a wide range of scientific aims, including estimating epidemiological
parameters, assessing the effectiveness of public health strategies, and directing optimal data collection [84].
Statistical ecologists deploy another suite of tools. Bayesian joint-likelihood models are well suited to integrating multiple
datasets with different units and temporal/spatial scales and can be designed to account for mechanism (e.g., [85]) or
discover statistical patterns (e.g., [86]). Species distribution models classify and predict habitat suitability for a given
species on the basis of environmental factors and known species occurrence [87]. These methods can be used to
estimate the regional and global distribution of viruses [88], with important exceptions [89], but their application to studying
tissue tropism across the within-host landscape remains largely unexplored.
Parameterizing ecological models relies on accurate quantification of state variables (e.g., prevalence) from field and
laboratory data. However, data are never perfect due tofactors that include sparse or irregular sampling, diagnostics with
imperfect sensitivity or specificity, human error, flawed experimental design, or missing data. The possibility of false-
positive and false-negative test results is particularly important for epidemiological models (Figure I). While all of these
issues can introduce bias or other problems, ecologists have developed strategies and tools to account for them, including
occupancy models and state-space models [90,91]. Occupancy models use repeated observations (e.g., multiple swabs
per individual per day) to jointly estimate detection probability and the occupancy of a species in a landscape (or
analogously, infection prevalence) (Figure I)[92]. State-space models account for imperfect observations in time series
data by separating the dynamics of the biological process (e.g., infection dynamics) from noise or bias in the observation
process (e.g., false negatives) [91]. Extensions of these two methods can incorporate multiple infection states [93],
estimate transmission and recovery rates [86], and include multiple host or virus species [94].
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Figure I. The SIR Model of Infection Dynamics and the Occupancy Modeling Approach to Determine
Infection State. The SIR model is a fundamental mechanistic model of infection dynamics. Colored boxes represent
entities (e.g., cell, tissue, organ, person, or population) that are classified by their infection state: susceptible (S, green),
infectious (I, purple), and recovered (R, blue). The biological system (i.e., the virus, host population, and environment)
determines the transition rates between each state (represented by arrows) and whether a recovered host can become
susceptible again (broken arrow). In parallel, the occupancy modeling approach uses sampling techniques to infer an
entity’s infection state at various time points. Here, we present two sample types (Observation 1 and 2) that are measured
per sampling event (marked by a red X). In this figure, we depict measurements of immune markers (e.g., antibodies) and
viral material (e.g., viral RNA), though the framework is applicable to any other observation relevant for the considered
system. Three tests are conducted per sample type per sample time, and each vial represents an individual test per
time point. Vial color denotes the test result (green, positive; purple, negative), which can correctly or incorrectly classify
infection state [T.P. (true positive); T.N. (true negative)]. The frequency of false-negative or false-positive test results
depends on the diagnostic, the sampling time, and inherent variability in infection dynamics.
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from molecular biology (e.g., receptor affinity), multiomics (e.g., receptor expression), and physiol-
ogy (e.g., tissue connectivity) to uncover patterns that underlie varying transmission characteristics
and pathogenicity of different viruses.
Concepts and tools from spatial ecology allow us to identify and predict landscapes at high risk
of experiencing cross-species spillover [46]. In particular, anthropogenic landscape changes
increase spillover risk by: (i) altering the abundance and distribution of wildlife hosts, with highly
modified areas potentially attracting a greater abundance of known reservoir hosts of zoonoses
(e.g., rodents and some bat species), (ii) promoting stress-induced shedding and host suscep-
tibility, and (iii) increasing contact rates among domestic animals, wildlife, and humans
[1,2,11,22,47]. While interspecificcontactsaredifficult to quantify in the wild, advances in an-
imal tracking [48], data sharing platforms (e.g., Movebank), and quantitative methods [49]can
refine our predictions of animal encounters, so additional monitoring can be directed to high-
risk locations. However, given the difficulty of identifying and tracking the multitude of potential
hosts, future applications of spatial ecology to understanding and preventing cross-species
transmission may focus increasingly on resilience, rather than risk, within landscapes. Scien-
tists have called for ecological countermeasures to prevent future pandemics, including foster-
ing landscape immunity. Interdisciplinary collaborations (among disease ecologists,
conservation practitioners, immunologists, and many more) are necessary to understand
and maintain landscape immunity across diverse ecosystems and to formulate clear guidance
for policy-makers [22].
Evolutionary Dimensions of Emerging Viruses
The evolution of organisms hinges on the accumulation of heritable mutations over successive
generations, which can generate phenotypic variation. When studying virus evolution, it is essen-
tial to note that virus populations can be defined simultaneously at several nested scales (within
their hosts, within host populations, and across host species communities). Evolutionary forces
(e.g., mutation, selection) affect viral diversity and fitness concurrently at all of these scales, always
mediated by the common currency of viral genomes. Due to the inherently intertwined nature of
evolutionary processes at these different scales, we explore each concept first at the within-host
scale, where viral factors (e.g., mutation rates) and host pressures (e.g., immune responses) act
proximately to generate viral diversity and perhaps drive adaptation [2]. Then, we discuss how
processes functioning within host populations and across host species further shape the evolu-
tionary trajectory of an emerging virus.
Evolutionary Controls of Viral Diversity
Genetic diversity accumulates over many generations through mutation and recombination,
and the frequency of these processes varies across viral lineages. Most RNA viruses have re-
markably high mutation rates due to a low-fidelity RNA polymerase that increases the frequency
of spontaneous mutations [50,51]. However, SARS-CoV and SARS-CoV-2 utilize a high-fidelity,
RNA-dependent RNA proofreading mechanism, which reduces the occurrence of mutations and
helps the virus to maintain a functional genome [51,52]. For other coronaviruses (e.g., HCoV-
OC43), recombination is essential for generating diversity, which suggests that this process
may also be important for SARS-CoV-2 [52,53]. Concrete evidence of recombination seemed
conspicuously absent in SARS-CoV-2 genomes sampled during early 2020, while point muta-
tions and deletions were common [54]. However, new evidence that SARS-CoV-2 recombines
readily in vitro [53] emphasizes that diversity may initially have been insufficient to yield detectable
recombination, and further study is needed to investigate recombination in field isolates. Addition-
ally, in vivo studies of within-host viral diversity could better characterize the relative frequencies of
mutation and recombination. Such research has been limited so far; however, two notable case
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studies of immunocompromised patients reported nonsynonymous and synonymous mutations
and deletions across 15 sites arising over 150 days [55] and 30 sites over 152 days [56] but did
not appear to screen for recombination.
Just as for multicellular organisms, population genetic mechanisms (e.g., gene flow,genetic
drift) modulate the genetic diversity of viruses in a host population. The occurrence of bottle-
neck events eliminates viral variants, while high gene flow promotes homogeneity [57]. Despite
the vast ecological opportunity posed by its recent zoonotic jump and the sheer number of
COVID-19 cases worldwide, the global diversity of SARS-CoV-2 measured in late July 2020
was remarkably low, with 46 723 sequenced genomes from 99 countries diverging maximally
by 32 SNPs, all of which were considered descendants of a single lineage [54]. However, as of
January 2021, global diversity has increased enormously [58], including three novel lineages
each characterized by 17 (B.1.1.7), nine (B.1.351), and 16 (P.1) nonsynonymous mutations,
of which 38 are distinct [59,60]. Two explanations for this surge of diversity include sufficient
time elapsed since emergence for the accumulation of viral diversity and/or transmission of di-
verse variants that arose in long-term COVID-19 patients [55,59]. In principle, the diversity of
endemic human coronaviruses could provide a preview of the future evolutionary trajectory
of SARS-CoV-2, but sparse sampling (e.g., 36 HCoV-OC43 genomes examined from four
countries over 30 years [61]) makes quantitative comparisons difficult. By contrast, the massive
sequencing efforts of SARS-CoV-2 provide an exciting opportunity to detect new variants in
real time and, by utilizing techniques from macroevolution, investigate the controls on global
coronavirus diversity (Box 2).
Phylogenetic perspectives on diversification can identify genetic relationships among viruses and
provide pivotal insights into evolutionary trajectories of host jumps. Such analyses showed that
reassortment of human, avian, and porcine influenza viruses gave rise to the 2009 H1N1 pan-
demic strain [35]. Early phylogenetic studies suggested that SARS-CoV-2 emergence involved
recombination between bat and pangolin coronaviruses, but subsequent results showed that
the lineage that gave rise to SARS-CoV-2 has been present in bats for many years [62]. However,
the detection of coronaviruses in many host species (e.g., raccoon dogs, minks), coupled with
their propensity to recombine, emphasizes that coinfection could facilitate recombination be-
tween various, potentially distinct, coronaviruses and thus generate novel viruses with pandemic
potential [34,63,64]. Further analyses of genetic diversity can shed light on the multihost epidemi-
ology of coronaviruses, distinguishing reservoir, intermediate, and dead-end hosts. For instance,
the high and stable diversity of SARS-like coronaviruses in bats supports their role as a reservoir,
while rapid growth of viral diversity in humans and civets was a hallmark of recent spillover of
SARS-CoV in 2002–2004 [64]. Continuing transmission between host species can further con-
tribute to viral diversity as evidenced by repeated transmission of SARS-CoV-2 between minks
and humans, with novel variants arising in minks sometimes transmitted back to humans,
which echoes observations for influenza A [34,35].
Adaptation and Viral Evolutionary Success
The evolutionary process of viral adaptation reflects selective pressures operating across multiple
scales [65]. Inside an infected host, purifying selection purges viral variants with disadvantageous
traits (e.g., structural instability), and positive selection favors those that confer an adaptive ad-
vantage (e.g., evasion of immune responses) [3,54,66]. Selection can act strongly on viral attach-
ment proteins, which mediate cellular entry and are an accessible target for the immune system
[67]. For SARS-CoV-2, mutations in the spike protein can alter viral fitness by enhancing ACE2
receptor binding or facilitating immune escape. Notably, the variant lineages that arose in late
2020 shared several substitutions in the spike protein, including K417N (found in the B.1.351
Trends in Microbiology
8Trends in Microbiology, Month 2021, Vol. xx, No. xx
and P.1 lineages), E484K (B.1.1.7, B.1.351, P.1), N501Y (B.1.1.7, B.1.351, P.1), and D614G
(B.1.1.7, B.1.351, P.1) [60,66,68–70]. In vitro assays suggest that both D614G and N501Y pro-
mote an up-conformation of the spike protein subunits, which increases the likelihood of binding
ACE2, exposes the cleavage site, and increases overall infectivity of a cell [69,70]. K417N exhibits
diminished neutralization by monoclonal antibodies, but only moderately increases ACE2 binding
affinity. E484K exhibits increased binding affinity to ACE2 and reduced neutralizing activity of
monoclonal antibodies [71].
In host populations, selection favors viral variants that can transmit between hosts and propagate
through the population; thus, rising frequency of particular variants suggests a selective advan-
tage. However, similar patterns could arise due to founder effects or stochasticity [72], so cau-
tious interpretation is warranted. For SARS-CoV-2, D614G rose to high frequency in separate
global outbreaks and became dominant worldwide by March 2020 [68,73], and phylogenetic
analysis in the UK suggests that D614G approached fixation after introduction into a region dom-
inated by the wild-type [73]. These findings are consistent with an adaptive role for D614G, which
is further supported by evidence that it promotes increased transmissibility compared to the wild
type: (i) more efficient transmission in hamsters, (ii) increased replication in the upper respiratory
tract of humans and hamsters in vitro and in vivo, and (iii) the spike conformational mechanism
described above [68,69,74,75]. Similarly, B.1.1.7 became the dominant lineage in the UK within
3 months of its emergence in late September 2020, while B.1.351 and P.1 rose rapidly in fre-
quency in South Africa and Brazil, respectively [59,76]. Although these lineages appear to have
emerged independently in different countries, they share several key substitutions in the spike
Box 2. Macroevolutionary Theory: An Underused Toolbox for Studying Viral Diversity
Macroevolution is the study of processes that govern the origin, persistence, and extinction of species. Despite a well-
developed set of conceptual tools for understanding diversity dynamics, including models of lineage origination and
extinction that vary with time, traits, and environmental conditions, macroevolutionary approaches have scarcely been
applied in virological studies. Macroevolutionary ideas may apply fruitfully to viral diversity across scales, and even
within a single viral species. Potential examples include:
●Macroevolution has revealed surprising ways that species persistence and diversification can be decoupled from
forces governing individual fitness [e.g., selection has repeatedly favored traits associated with mammalian
hypercarnivory (e.g., bone-cracking) at the individual level, but these lineages are more vulnerable to extinction than
generalist clades [95]] [96,97], and may offer new perspectives on cross-scale phenomena in viruses such as the
evolution of virulence.
●The concept of ecological adaptive radiation links ecological opportunity (e.g., absence of competitors when novel
habitats are colonized) to the rapid proliferation of new species adapted to distinct niches. Host jumps leading to
epidemics or pandemics could provide viruses with vast ecological opportunity to differentiate (e.g., the global popu-
lation of susceptible humans for SARS-CoV-2, as well as other new host species infected by humans), yet host
population movement and viral gene flow will work against differentiation. Adaptive radiation theory may help to predict
evolutionary trajectories of novel viruses in humans or other hosts.
●Macroevolutionar y theory around adaptive radiation and clade comp etition [98] may provide new insightsinto patterns in
infectious disease emergence events, including impacts of competition with endemic viruses and the factors controlling
the total diversity of viruses that can infect humans.
●Substantial challenges exist for delineating the significant evolutionary differences between variants, strains, species, and
lineages. Macroevolutionary principlescombined with species delimitation frameworkscould help to integrate genotypic
data with phenotypic data (e.g., conserved protein domains, receptor specificity) to create a rigorous system for virus
species delineation which might offer insights into the properties of an emerging virus (e.g., potential host range, trans-
mission route) [99].
Some of these questions have been approached within emerging fields such as phylodynamics [100], but macroevolution
may help to develop much-needed frameworks for understanding the vastness of viral diversity, especially at deeper
phylogenetic and temporal scales. Furthermore, since viruses diversify much more rapidly than plant and animal species,
engagement with virology might provide macroevolutionists with heretofore nonexistent opportunities to directly observe
hypothesized processes for the assembly of biodiversity.
Trends in Microbiology
Trends in Microbiology, Month 2021, Vol. xx, No. xx 9
protein (D614G, N501Y, E484K) associated with within-host advantages and, putatively, in-
creased transmissibility [59,71,77]. Such convergent evolution is a classic sign of adaptation
[58,78], and viruses may provide an unexpected opportunity to investigate the relationship be-
tween convergence in function (e.g., transmissibility) and convergence of the underlying genetic
and/or structural components of the trait [79].
At the scale of cross-species emergence, the role of virus adaptation is the subject of
longstanding debate: when (if ever) is adaptation required, and where does it occur [78]?
Natural selection can drive the evolution of a trait that is later commandeered for a new func-
tion, and such exaptation of viruses in animal reservoirs can facilitate host jumps. Genetic
analysis has revealed a furin-recognition motif in the SARS-CoV-2 spike protein which facili-
tates binding of human ACE2 and enables cleavage by the furin protease [6]. This motif is
present in a coronavirus found in Malayan pangolins (Manis javanica) but is absent in the co-
ronavirus (RaTG13) most genetically similar to SARS-CoV-2 (found in horseshoe bats;
Rhinolophus affinis)[6]. The acquisition of this motif (via an unclear pathway) may have
functioned as an exaptation that mediated transfer of the SARS-CoV-2 progenitor from wildlife
into humans. Since cellular entry is a key determinant of viral host range, the use of highly con-
served receptors (and hence a generalist life history) may function as an alternative typeof exapta-
tion that provides more opportunities for spillover events [80,81]. For example, ACE2 is highly
conserved among humans, various bat species, and potential intermediate hosts [23]. Indeed,
many host species have proved susceptible to SARS-CoV-2, including ferrets and cats [82]; in
silico analysis identifies many other potentially susceptible species, providing insights into the
current or future host range of the virus [80].
Concluding Remarks
Given the increasing frequency of zoonotic emergence events and their potential societal im-
pacts, it is imperative to leverage all applicable tools to better understand, predict, and prevent
the spillover and subsequent spread of novel infectious diseases. Ecological and evolutionary
concepts, which have been crafted and tested for decades, provide key insights into the origin
of emerging viruses, the trajectory of an outbreak or pandemic, and the risk of future spillover.
These concepts, which are already inherently intertwined (Figure 2), prove even more powerful
when integrated with other fields, including microbiology, epidemiology, and medicine. Such in-
terdisciplinary approaches can uncover key insights that are otherwise unattainable, and, in par-
ticular, could answer many unresolved questions about SARS-CoV-2 (see Outstanding
Questions). The insights gained, and new avenues for investigation developed from these ques-
tions, will drive progress in further refining ecological and evolutionary theory, directing future in-
terdisciplinary research, and improving general understanding of the mechanisms that drive the
emergence of infectious diseases.
Acknowledgments
We thank allparticipants of the seminar where theideas for this manuscriptwere formulated.We apologize to the manyauthors
whose work we were unable to include because of space limitations. All figures were created using BioRender.com.B.B.was
supported by the European Commission Horizon 2020 Marie Skłodowská-Curie Actions (grant no. 707840). C.E.S was
supported by the National Institutes of Health (grant 5T32 GM008185-33). R.V.B. was supported by the La Kretz Center for
CaliforniaConservation Science at the Universityof California Los Angeles.J.O.L.-S. and A.G. were supported by the Defense
Advanced Research Projects Agency DARPA PREEMPT #D18AC00031, the National Science Foundation (DEB-1557022),
and the UCLA AIDSInstitute and Charity Treks. The content of the article does not necessarily reflect the position or the policy
of the US government, and no official endorsement should be inferred.
Declaration of Interests
There are no interests to declare.
Outstanding Questions
Can insights from invasion ecology
be harnessed to formulate a new
generation of mechanistic dose–
response models? Can we leverage
biomedical findings to model a viral
exposure event as a population
growth process on a heterogeneous
landscape?
Does pre-existing immunity to SARS-
CoV-2 arise from prior exposure to
endemic coronaviruses? If so, do
differences in these virus community
interactions explain geographic varia-
tion in pandemic intensity? Can con-
sumer–resource models be combined
with patient data to investigate the
impacts of pre-existing immunity on
disease course?
Can animal tracking technologies
reveal the interactions of potential
reservoir and intermediate hosts of
SARS-CoV-2? Does overlaying this
information with human population
data reveal regions and species that
mayhavebeeninvolvedinSARS-
CoV-2 spillover? Can these techniques
identify high-risk areas for future
emerging viruses?
How is SARS-CoV-2 tissue tropism
influenced by features of the within-host
landscape (e.g., temperature, pH, pro-
tein expression)? Can species distribu-
tion models incorporate this information
to clarify the apparent disparities
between ACE2 expression and SARS-
CoV-2 tissue tropism?
The up versus down conformation in the
spike protein may favor reproduction (via
better receptor binding) versus survival
(via hiding epitopes from antibodies),
respectively. Can the optimal balance of
these states be understood using the
evolutionary theory of life history trade-
offs?
How will the virulence of SARS-CoV-2 in
humans change over time, and will this
be governed chiefly by population immu-
nity or viral evolution, or both? Did other
endemic human coronaviruses begin as
catastrophic pandemics and evolve into
'common cold' viruses?
How many endemic coronaviruses can
the human population sustain, and
what forces govern this limit? Is there
competition among coronaviruses for
Trends in Microbiology
10 Trends in Microbiology, Month 2021, Vol. xx, No. xx
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