DR AMBER SMITH
Simultaneous infection
Trained as a mathematician, Dr Amber Smith is applying her knowledge of complex
mathematics to study the coinfection of a virus and bacterium. She describes the benefits and
challenges of blending theory and experiment
Can you explain why coinfection with
influenza A and Streptococcus pneumoniae
has been the emphasis of your research?
Influenza infections – which are viral
infections – are often complicated by
bacterial pathogens like S. pneumoniae. A
mild influenza infection becomes severe
when compounded by a secondary bacterial
infection, so understanding the mechanisms
that drive this lethal synergy is critical. In
our laboratory model, the virus rebounds
following bacterial invasion, the bacteria
grow rapidly (even for low doses that would
be cleared in the absence of the virus) and
host responses become dysfunctional.
It was these interesting dynamics that
attracted me, especially because influenza
is very important for public health. I saw an
opportunity to improve understanding using
mathematical methods, since they provide a
robust means of unravelling complex hostpathogen relationships.
Your work is at the forefront of experimental
and theoretical microbiology. How has your
background prepared you for this study?
My education and training have been primarily
in applied mathematics. I was first introduced
to mathematical biology as an undergraduate
at the Colorado School of Mines, USA, but
it wasn’t until I joined the University of Utah
that I started learning about microbiology. The
mathbio graduate programme emphasised
learning fundamental mathematical
techniques in addition to gaining experience in
the laboratory.
During my summers, and eventually as a
postdoctoral researcher, I worked at the
Los Alamos National Laboratory and began
collaborating with Dr Jon McCullers at St Jude
Children’s Research Hospital in Memphis,
Tennessee. He let me visit his lab to begin
learning the ins and outs of his coinfection
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INTERNATIONAL INNOVATION
experiments and even generate some of my
own data. This was an incredibly valuable
experience, during which I noticed both a gap
in communication between the fields and
a lack of data that is needed for modelling
studies. I subsequently began working in
this lab. I spent two years here as part of my
National Institutes of Health (NIH) K25 Career
Development Award to further my wet lab
skills so that I could effectively operate at the
intersection of biology and mathematics. It’s
been quite the journey getting to this point,
and I am incredibly fortunate to work with
leading scientists in both fields.
What are the benefits of a study that is
both theoretical and experimental?
Using theoretical methods allows us to
examine multiple aspects of a complex
system simultaneously in detail. We can
determine if our cartoon version of the biology
is correct, identify the dynamics that best
explain a particular set of data and quickly
simulate thousands of scenarios rather than
testing each in the laboratory. Doing so yields
information that isn’t always obvious and
narrows the experiments needed. However,
it is important to return to the lab to test
predictions experimentally in order to validate
the model and gain additional insight into the
biology. It is through this methodology that we
are able to identify the mechanisms driving
bacterial establishment during influenza and
improve our understanding of coinfection.
How do you balance the demands of
mathematical modelling and bench work?
The balance is actually quite difficult. I tend
to work in waves, where I focus on one aspect
until I have enough information to return
to the other. However, both areas require a
significant amount of work and are full-time
jobs in themselves. It has helped tremendously
to have a talented technician, Amanda Smith,
to assist with laboratory duties. Without
that support, the balance would be even
more challenging.
Can you provide an insight into the challenges
that such a combined approach raises?
How have you overcome these obstacles?
The biggest challenge I face is needing to be
an expert in multiple fields. It takes time to
develop the skills and intuition needed for
this approach to succeed. Another challenge
is convincing biologists that mathematical
models actually make useful predictions. My
goal is to talk about my work and teach the
concepts at seminars and conferences, so that
people will become more receptive.
What contributions do you aim to make to the
field in the next five to 10 years?
My greatest desire is that I will improve
understanding of coinfection biology and make
significant advances towards the prevention
and treatment of influenza-associated
bacterial infections. I also intend to shift the
current paradigm of microbiological research
to incorporate theoretical methods, and that
the tools and methodology I develop will aid
scientific advancement.
A lethal synergy
Researchers at St Jude Children’s Research Hospital are using
a unique blend of microbiology and mathematical modelling to
understand the interaction between influenza and a bacterial
pathogen – a major cause of influenza-associated death
INFLUENZA A VIRUS, more commonly
known as bird flu or avian flu, is an important
respiratory pathogen. Every year, it causes
seasonal epidemics, and when it is transmitted
from wild aquatic birds to domestic poultry like
chicken, it has the potential to cause a human
pandemic, just as it did in the infamous H1N1
pandemic of 2009. As such, the virus poses a
considerable public health threat.
Smith, who first developed mathematical
models of coinfection during her PhD, aims to
understand how the influenza virus interacts
with its bacterial copathogens and discover how
the immune system responds to the interaction.
She works at the interface of experimental
and theoretical microbiology, applying a
combination of mathematical models and
animal experiments.
The bacterium Streptococcus pneumoniae is
similarly dangerous. There are 90 strains of this
pathogen, causing pneumococcal infections
of varying severity. It was recognised as the
major cause of pneumonia in the late 19th
Century, and it is now also known to cause
meningitis and septicaemia, particularly in
immunocompromised individuals.
THE COMPLEXITIES OF COINFECTION
The theoretical models Smith develops can
characterise the kinetics of infection – or, in
other words, the rates of the reactions involved
in an infection’s growth and replication. These
models can also predict the time course of
infection and even the mechanisms involved in
pathogenesis. “Subsequently, these predictions
are tested through experimentation,”
Smith states.
Individually, these pathogens are harmful
enough, but together, they can be lethal. When
individuals are infected with the flu, their
immune systems are weakened; in this context,
an S. pneumoniae infection can occur, develop
into pneumonia and render a mild influenza
infection severe or even fatal. In fact, secondary
bacterial infection is thought to be the cause
of many deaths attributed to influenza. Indeed,
in many past pandemics, including the 2009
H1N1 pandemic, S. pneumoniae accounted
for a significant proportion of influenzaassociated deaths.
These coinfections are serious and
extremely complex. Their occurrence and
pathogenicity are multifactorial processes
involving various virulence factors and host
responses. Dr Amber Smith, Research
Associate at the Department of Infectious
Diseases at Memphis’ St Jude Children’s
Research Hospital, is using mathematical
models to tease apart these notoriously
complex mechanisms.
Using this innovative, model-driven
experimentation approach, she aims to identify
the factors that make these pathogens so
virulent, as well as the elements of the immune
system that respond to their attack. “An
improved understanding of the mechanisms
involved in causing and controlling infection
should result in new treatment strategies for
secondary pneumococcal infections following
influenza,” she enthuses.
Specifically, Smith is working to identify the
precise bacterial factors that contribute to the
development of virus-associated pneumonia
and to determine the relative contributions of
different S. pneumoniae genes to influenzaassociated infections.
THE HUNT FOR GENES
Both laboratory and clinical studies
suggest that particular strains of bacteria
can be ‘preferentially promoted’ to cause
disease in an influenza-infected individual,
indicating that genetic factors contribute
to the development of secondary bacterial
pneumonia. However, the majority of past
coinfection studies have focused on how the
virus affects host immunity, with bacterial
virulence factors being comparatively
neglected. This is an important knowledge
gap, as there is considerable genetic diversity
between the 90 strains of S. pneumoniae likely
to impact disease.
Pneumococcal pneumonia is developing in this mouse via increased virus production and decreased phagocytosis
of pneumococci.
www.internationalinnovation.com
15
INTELLIGENCE
INCIDENCE AND PATHOGENICITY OF
INFLUENZA-BACTERIAL COINFECTIONS
OBJECTIVES
• To determine the relative contributions of
pneumococcal genes to pathogenesis of
influenza infections through experimental and
theoretical methods
• To develop mathematical models that quantify
specific immune responses to influenza
virus infection
KEY COLLABORATORS
Dr Fred Adler, University of Utah, USA • Dr Alan
Perelson; Dr Ruy Ribiero, Los Alamos National
Laboratory, USA • Dr Jon McCullers, University of
Tennessee Health Science Center, USA • Dr Jason
Rosch, St Jude Children’s Research Hospital, USA
PARTNERS
University of Utah
Los Alamos National Laboratory
Pathosystems Resource Integration Center (PATRIC),
Virginia Bioinformatics Institute
FUNDING
National Institutes of Health (NIH)
American Lebanese Syrian Associated Charities
CONTACT
Dr Amber Smith
Research Associate
Infectious Diseases
MS 320, Room E8007
St Jude Children’s Research Hospital
262 Danny Thomas Place
Memphis, Tennessee 38105-3678
USA
T +1 901 595 5599
E amber.smith@stjude.org
www.math.utah.edu/~smith
www.stjude.org/smith
www.researchgate.net/profile/Amber_Smith6
www.linkedin.com/in/ambersmith3
AMBER SMITH received her PhD in
Mathematics from the University of
Utah in 2009, where she developed
novel mathematical models of
influenza and pneumococcal
infections and coinfections. She continued this work as
a postdoc at the Los Alamos National Laboratory until
2012. She was then awarded a K25 Career Development
Award to enhance the experimental aspects of this
research. In 2012, she moved to St Jude Children’s
Research Hospital and joined the faculty in 2014.
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INTERNATIONAL INNOVATION
Smith thus put forward a novel approach to
identify how S. pneumoniae virulence factors
contribute to disease in individuals already
infected with influenza. Her work represents
humanity’s first attempt to model the
complex relationships between a virus, host
and superinfecting bacteria.
To achieve this unique investigation, she and
her colleagues will employ a combination
of standard microbiological and animal
models, a bacterial genomics dataset
larger than any currently published, a novel
genetic screening technique and original
mathematical models. “By mathematically
modelling the infection process, we can
establish the dynamic feedbacks between the
pathogen and host responses, and learn how
changes in individual processes affect overall
dynamics and thus identify the virulence
factors involved in infection,” she expands.
By comparing the effects of pathogens in
situations where only one gene is different,
it is possible to quantify the contribution of
individual genes to pathogenicity.
Already, Smith has identified a subset of
bacterial genes, some of which have never
before been identified. “We are currently
investigating the relative contributions of each
to pathogen growth and host responses,”
she adds. Ultimately, she aims to elucidate
the genes that contribute to pneumonia
pathogenesis in influenza-infected patients.
Not only will this improve fundamental
biological understanding of viral-bacterial
interactions, it could also lead to the
identification of novel targets for vaccines
and antimicrobials.
DEADLY SYMBIOSIS
Another avenue of Smith’s research focuses
more on the influenza A virus. She is aiming
to develop mathematical models to quantify
immune responses to the virus, and in turn
reveal the regulatory networks that enable
the innate immune system to control it.
In a seminal 2013 paper, published in PLOS
Pathogens, Smith, alongside collaborators
from the US, Portugal and Australia,
revealed unprecedented detail on coinfection
with influenza A virus and S. pneumoniae.
Using data from infected mice alongside
mathematical modelling and quantitative
analyses, the researchers were able to better
understand how each pathogen influences
the other.
Experiments revealed that the severity of
the influenza infection increased when the
bacterial strain was present, and likewise
that the bacteria were able to establish
and grow rapidly when influenza was
present. The modelling results suggested
mechanisms for both, and the latter has
since been experimentally tested and
confirmed. The results indicated that
infection with influenza reduces the ability of
macrophages (a type of white blood cell that
engulfs pathogens) in the air sacs (alveoli)
of the lungs to clear bacteria. Further
experiments in mouse models of coinfection
confirmed this theory, concluding that
influenza primes the lungs for a secondary
bacterial infection by depleting alveolar
macrophages, a central component of
innate immunity.
This work represents humanity’s
first attempt to model the
complex relationships
between a virus, host and
superinfecting bacteria
These groundbreaking findings shed new
light on the mechanisms of influenza
coinfection. While the synergy is complex
and multifactorial, by identifying important
factors in protection against and susceptibility
to secondary infections, this study will
pave the way for the development of
effective therapies.
But this is really only the beginning for Smith,
as she expounds: “Now that we know alveolar
macrophages are the key component driving
coinfection, we can begin investigating this
process in more detail. The next step is to
build upon previous models to examine the
downstream responses”. And with each piece
of the puzzle, they get closer to a treatment.
THERAPEUTIC TARGETING
Smith has taken an innovative approach to
studying the medically important problem
of coinfection, blending theoretical and
experimental techniques and showing
remarkable skill in doing both herself. Her
models of pneumococcal and coinfection
kinetics were both the first of their kind, and
using the latter, she was able to predict a
major coinfection mechanism, which she then
validated through experimentation.
Looking ahead, this work could have major
clinical impact. Smith has already made
progress towards finding new therapeutic
targets, identifying a process that can prevent
secondary bacterial infections following
influenza – alveolar macrophage depletion.
The next step is to inhibit this process during
influenza infection, which should slow – or
even stop – bacterial growth, greatly reducing
influenza’s public health impact. “We are
currently investigating which part of this
process is most amenable to therapeutic
targeting,” Smith concludes.