Biology Reference
In-Depth Information
a set of molecules that characterize pathogens but not the
host. Multiple genes that were previously not known to
function in the immune system were discovered to play
a role in the immune response
[12]
. For example, Aderem
and colleagues found that the transcription factor ATF3,
which was previously implicated in the regulation of stress
response, cell cycle and apoptosis, but not in immunity, is
a regulator of the TLR response. More recently, Hacohen,
Regev, Amit and collaborators, discovered a host of cell-
cycle regulators that have been co-opted for antiviral tran-
scriptional responses in non-dividing dendritic cells
[5,8]
.
Thus, one insight that emerged from these studies is that the
set of 'immunologically important genes' is still poorly
defined. This is even reflected among already discovered
associations, as there is inconsistency between the existing
databases for immune-related genes
[15]
. Because new
immune genes are still being discovered, it is challenging to
test all genes and pre-filter them by known function or in
another unbiased fashion to reduce the number of hypoth-
eses to test further
[16]
. Studies of eukaryotic regulatory
networks are revealing network motifs
[17]
used by
eukaryotic cells to elicit specific regulatory functions (see
Chapter 4). For example, TLR-4, NF
k
B and ATF generate
a pulse response of downstream targets to lipopolysaccha-
ride stimulation through an incoherent feedforward loop
(TLR4 activates NF
k
B and ATF, with NF
k
B activating
downstream targets such as IL-6 and ATF repressing the
same targets)
[12,18]
. Similarly, Amit et al. discovered
a large number of coherent feed forward loops in a pathogen-
sensing network
[5]
, which at least in some cases appears to
protect the system from activating a complex regulatory
program in the face of a transient, rather than persistent
signal
[18]
. As additional layers of regulation are incorpo-
rated into the network reconstruction
[7,8]
new motifs
incorporating multiple layers of regulation and timescales
are likely to be discovered.
major leukocyte classes in blood based on cell shape and
size (automatic cell counters rely on cell size and isoelec-
tric focusing). First used in 1957, it is one of the tests most
commonly prescribed by physicians because it can be
indicative of a recent infection or disease. Yet, as the
number of immune cell subtypes discovered has grown
beyond those basic cell types assayed in the CBC, no
standard clinical test measuring cell-type subset abundance
followed (e.g., neither the loss of T (H)-17 cells or the
reduction in CD8
þ
na¨ve and memory cells, described
above, would have been identified by a CBC). Rather,
currently in the clinic, and at the risk of missing prognostic
disease-relevant information, the abundance of immune
cell subsets is either not tested, tested at a low resolution, or
tested for specific cell subsets based on other patient
phenotypic information for disease differential diagnosis.
As different cell types correspond to different functions,
an important question is how many different cell types there
are in the immune system, and by which markers they can
be identified. In many cases different cell subtypes have
vastly differing expression profiles, although the reusability
of the gene modules and regulatory programs in a different
cellular context is evident
[21]
. For example, the respective
gene expression and microRNA profile of 38 and 27 classic
hematopoiesis cell types were recently profiled in humans
[21,22]
, whereas the ImmGen project, a consortium effort
that aims to profile the gene expression pattern of every
known mouse immune cell type, has already profiled over
200 different cell type subsets
[23]
, though for the majority
of these cell type subsets their clinical effects are still not
sufficiently well known.
Perhaps an even more relevant question is, to what
degree do cells occupy discrete 'cell-states', as defined by
their gene expression, protein and functional responses? So
far, scientists have placed artificial 'cell-state' barriers,
although it is possible that there is a continuum of func-
tionality. Recent technological breakthroughs now enable
the measurement of immune cell subsets at the single-cell
level and at a high dimension, that is, measurement of
multiple proteins or genes on the same single cell (Boxes 1
and 2), and are beginning to shed light on this question.
For example, recently Nabel, S
´
kaly and colleagues
showed that immunization-specific gene expression signa-
tures were detectable at a single-cell CD8
þ
T-cell level
following vaccination, and define novel T-cell subsets whose
relative frequency in alternative vaccine strains is variable
[24]
. Thus, current 'standards' for cell-type subsetting are in
flux, which makes it more difficult to design and evaluate
CD8
þ
T cells vaccines, and more generally the relationship
between cell-type subset and the immune response.
Novel cytometry-based studies evaluate differences at
the single-cell level and at high dimensionality for thousands
of cells
[1,2,25]
: Bendall et al. used mass cytometry to
profile the entire hematopoietic lineage of an individual
Exploring Cellular Diversity
Each of the cell types of the immune system has specific,
highly specialized functions. For example, cytotoxic T cells
(also known as CD8
þ
T cells) can kill other cells, whereas T-
helper cells (also known as CD4
þ
T cells) generally provide
stimulatory signals to other cells to enable them to perform
their particular tasks. Many immune-related disorders are
directly associated with a malfunction of a specific cell type.
For instance, the inability to create T (H)-17 helper T-cells in
Job's syndrome patients is the causative agent for high
susceptibility to fungal infections
[19]
, whereas a reduction
in lifespan of CD8
þ
na¨ve and memory cells can lead to
severe cutaneous viral infections
[20]
.
Changes in cell type abundance and relative frequency
may have important clinical implications. The complete
blood count (CBC) is a clinical assay that enumerates five
