INSIGHTS | PERSPECTIVES
By Julija Krupic
The ability to learn and remember new experiences lies at the heart of our existence. After all, we are our memo- ries. It has been widely accepted that memories are formed and stored via strengthening of neural connections
due to the correlated activities of neurons,
where presumably one neuron is causing
or at least contributing to the activity of
another connecting neuron and hence becomes associated with it. This principle is
known as the Hebbian learning rule (1):
i.e., if interconnected neurons become active very close in time during a particular
event, their connection strengthens and
“a memory” of this event is formed (1). In
other words, “neurons wire together, if they
fire together” (2). Thus, neural connection
must show some sort of plasticity—i.e., an
ability to be modified based on the mutual
firing patterns of interconnected neurons—
in order to form memories and associations. Indeed, it has been shown that brief
(hundreds of milliseconds) stimulations
of interconnected neurons significantly
improve signal transmission between the
two, a phenomenon known as long-term
potentiation (LTP). On page 1033 of this
issue, Bittner et al. (3) describe a different learning mechanism called behavioral time scale synaptic plasticity (BTSP),
which spans a considerably longer time
course of several seconds, implying that no
A. fumigatus infection causes >200,000 cases
of invasive aspergillosis annually, which is
associated with mortality rates of up to 90%
in some patients with impaired immunity
(6). Shlezinger et al. report a mechanism
of mammalian innate immunity to inhaled
A. fumigatus conidia. They show how neutrophils (a type of innate immune cell) kill
A. fumigatus conidia and, conversely, how
the fungus resists this process. They did
this using fluorescent Aspergillus reporter
(FLARE)—A. fumigatus conidia that “
report” through fluorescence viability on contact with leukocytes in vivo (7). Neutrophils
induce caspase-dependent programmed cell
death (PCD) in the conidia, triggered by host
oxygen-dependent signals—e.g., reduced
form of nicotinamide adenine dinucleotide
phosphate (NADPH) in neutrophils (see the
figure). Conversely, to counteract PCD, A. fumigatus conidia use AfBir1, a gene homologous to human survivin, which encodes a
BIR domain and suppresses PCD. Targeting
AfBir1 with a chemical inhibitor augments
fungal PCD and host survival. Thus, AfBir1
may be an appealing drug target.
Control of PCD is central to all types of
host-pathogen interactions. For example,
PCD occurs in plant fungal pathogens (8).
PCD is a response to noxious stimuli (9);
fungitoxic plant-defense products also trigger fungal PCD (8, 9). Thus, while interacting
with host cells, fungi are exposed to host-de-rived PCD-inducing molecules. Genetic manipulation of the fungal anti-PCD response
by ablating Bir1 reduces fungal virulence (10).
Thus, fungal PCD is triggered and regulated
by Bir1 during interaction with plants and
mammals. Because human (and mouse) neutrophils trigger PCD in A. fumigatus conidia,
targeting AfBir1 could be used to bolster innate immunity or undermine fungal immune
evasion. The arsenal of antifungal drugs is
small and dwindling. Multidrug resistance is
now a global threat, so new drugs are needed.
Although neutrophils are potent killers of
fungi, this cell type exemplifies the two sides
of leukocyte function. An example is their
pathological role in a severe form of allergic
inflammation, neutrophilic asthma. Asthma
afflicts hundreds of millions of people globally. In 2007, medical expenses from asthma
cost the United States $50.1 billion (11).
Asthma often originates from the inhala-
tion of innocuous substances or mild irritants
that elicit a disproportionately potent im-
mune response in the lungs. This allergic re-
sponse is often characterized by an excessive
influx of eosinophils (granulocytic immune
cells) into the lungs. Whereas neutrophilic
asthma results from the accumulation of
neutrophils, also a granulocytic immune cell.
Interestingly, these dichotomous granulocyte
immune cell responses are reciprocally regu-
lated by discrete populations of T helper cells
(12). DCs are central mediators of immunity
and inflammation. Although lymphocytes
(e.g., T cells) are directly responsible for po-
sitioning granulocytes at sites of insult, T
helper cells first require interaction with
DCs. Drawing from environmental cues, DCs
imprint T helper cells with defined functions.
For example, this can promote differentiation
of T helper cells that recruit neutrophils or
eosinophils to the lungs. How do DCs regu-
late an eosinophil-inducing versus a neutro-
phil-inducing T helper cell response?
Sinclair et al. offer a compelling model
whereby cell-intrinsic metabolism regulates
the tissue distribution of DCs and controls
T helper cell fate determination. Using a
mouse model of allergic asthma, the authors
found that mice with a conditional deletion
of mechanistic target of rapamycin (Mtor, a
central regulator of metabolism) in DCs no
longer experienced eosinophilic asthma upon
allergen inhalation. Rather, large numbers of
neutrophils were recruited to the lungs. These
striking findings may help resolve several disjointed clinical and epidemiologic observations. Individuals with metabolic syndrome,
denoted by obesity and deficits in fasting glucose metabolism, experience increased rates
of asthma (13). Moreover, asthma associated
with obesity is typically neutrophilic (14). It
is possible that the irregularities in glucose
metabolism that are evident in obese individuals lead to reduced m TOR activation and the
skewing of neutrophil-inducing T helper cells
in response to aeroallergens. Thus, therapies
that restore glucose metabolism in pulmonary DCs could provide new treatment options for neutrophilic asthma.
These findings underline the balance between helpful lung immunity and harmful inflammation. They disclose new mechanisms
as well as host and pathogen targets that offer prospective arrows in the quiver of our
therapeutic arsenal. j
1. N. Shlezingeretal .,Science357, 1037 (2017).
2. C. Sinclair et al ., Science 357, 1014 (2017).
3. J. Frohlich-No woisky et al., Proc. Natl. Acad. Sci. U.S. A.
106, 12814 (2009).
4. The Burden of Fungal Disease (Leading International
Fungal Education, 2017); http://go.nature.com/2sMKpuN.
5. D.L.Hawksworth, Mycol. Res. 105,1422(2001).
6. G. D. Brown et al ., Sci. Transl. Med. 4 , 165rv13
7. A. Jhingran et al., Cell Rep.2, 1762 (2012).
8. A. Sharon, A. Finkelshtein, in The Mycota , K. Esser, H.
Deising, Eds. (Springer, Heidelberg, 2009).
9. A.Sharon et al., FEMS Microbiol. Rev.33,833(2009).
10. N. Shlezinger et al ., PLOS Pathog. 7, e1002185 (2011).
11. CDC Asthma Facts, CDC’s National Asthma Control
Program Grantees (U.S. Department of Health and Human
Services, Centers for Disease Control and Prevention,
12. D. F. Choy etal ., Sci. Transl.Med. 7, 301ra129 (2015).
13. D. A. Beuther, E. R. Sutherland, Am. J. Respir. Crit. Care
Med. 175, 661 (2007).
14. H. A. Scott et al ., Eur. Respir. J. 38, 594 (2011).
New learning rule aligns
behavioral and synaptic
time scales in place cells
Cell and Developmental Biology, University College London,
London, UK. Email: firstname.lastname@example.org
“The authors speculate
that such a long time scale
plasticity window in
principle allows for the
storage of an entire sequence