Short Article
Septins Recognize and Entrap Dividing Bacterial
Cells for Delivery to Lysosomes
Graphical Abstract
Highlights
d Septins are recruited to micron-scale curvature of dividing
intracellular bacteria
d Cardiolipin promotes the recruitment of septins to curved
bacterial membranes
d Following recruitment, septins assemble into cages around
growing bacterial cells
d Septins inhibit bacterial division via recruitment of
autophagic and lysosomal machinery
Authors
Sina Krokowski,
Damia´ n Lobato-Ma´ rquez,
Arnaud Chastanet, ..., Elias T. Spiliotis,
Rut Carballido-Lo´ pez, Serge Mostowy
Correspondence
serge.mostowy@lshtm.ac.uk
In Brief
Septins are cytoskeleton components
widely recognized for their role in
eukaryotic cell division. Krokowski et al.
discover that septins recognize dividing
bacterial cells for entrapment and
delivery to lysosomes. These results
reveal a fundamental danger signal used
by the host cell to recognize intracellular
bacterial pathogens for cellular immunity.
Krokowski et al., 2018, Cell Host & Microbe 24, 866–874
December 12, 2018 ª 2018 The Author(s). Published by Elsevier Inc.
https://doi.org/10.1016/j.chom.2018.11.005

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Cell Host & Microbe
Short Article
Septins Recognize and Entrap Dividing
Bacterial Cells for Delivery to Lysosomes
Sina Krokowski,1,2 Damia´ n Lobato-Ma´ rquez,1,2 Arnaud Chastanet,3 Pedro Matos Pereira,4 Dimitrios Angelis,5
Dieter Galea,1 Gerald Larrouy-Maumus,6 Ricardo Henriques,4 Elias T. Spiliotis,5 Rut Carballido-Lo´ pez,3
and Serge Mostowy1,2,7,*
1Section of Microbiology, MRC Centre for Molecular Bacteriology and Infection, Imperial College London, London SW7 2AZ, UK
2Department of Immunology & Infection, London School of Hygiene & Tropical Medicine, London WC1E 7HT, UK
3MICALIS, INRA, AgroParisTech, Universite´ Paris-Saclay, Jouy-en-Josas 78350, France
4Quantitative Imaging and NanoBiophysics Group, MRC Laboratory for Molecular Cell Biology and Department of Cell and Developmental
Biology, University College London, London WC1E 6BT, UK
5Department of Biology, Drexel University, Philadelphia, PA 19104, USA
6Faculty of Natural Sciences, Department of Life Sciences, MRC Centre for Molecular Bacteriology and Infection, Imperial College London,
London SW7 2AZ, UK
7Lead Contact
*Correspondence: serge.mostowy@lshtm.ac.uk
https://doi.org/10.1016/j.chom.2018.11.005
SUMMARY
The cytoskeleton occupies a central role in cellular
immunity by promoting bacterial sensing and anti-
bacterial functions. Septins are cytoskeletal proteins
implicated in various cellular processes, including
cell division. Septins also assemble into cage-like
structures that entrap cytosolic Shigella, yet how
septins recognize bacteria is poorly understood.
Here, we discover that septins are recruited to re-
gions of micron-scale membrane curvature upon
invasion and division by a variety of bacterial spe-
cies. Cardiolipin, a curvature-specific phospholipid,
promotes septin recruitment to highly curved mem-
branes of Shigella, and bacterial mutants lacking
cardiolipin exhibit less septin cage entrapment.
Chemically inhibiting cell separation to prolong
membrane curvature or reducing Shigella cell growth
respectively increases and decreases septin cage
formation. Once formed, septin cages inhibit Shigella
cell division upon recruitment of autophagic and
lysosomal machinery. Thus, recognition of dividing
bacterial cells by the septin cytoskeleton is a power-
ful mechanism to restrict the proliferation of intracel-
lular bacterial pathogens.
INTRODUCTION
Septins are highly conserved filament-forming proteins that play
key roles in eukaryotic cell division (Mostowy and Cossart, 2012;
Saarikangas and Barral, 2011). Originally discovered for their role
in division of budding yeast (Hartwell, 1971), recent work has
shown that septins also play a role in division of mitochondria
(Pagliuso et al., 2016; Sirianni et al., 2016). In humans, the 13
septins are classified into four homology groups (SEPT2,
SEPT3, SEPT6, and SEPT7) where septins from different groups
form hetero-oligomers and assemble into non-polar filaments,
which can form higher-order structures including bundles and
rings (Mostowy and Cossart, 2012). Septins have recently
been shown to recognize areas of the plasma membrane pre-
senting micron-scale curvature, including the cytokinetic furrow
and phagocytic cup (Bridges et al., 2016). Although viewed as a
fundamental property of the septin cytoskeleton (Cannon et al.,
2017), signals responsible for septin recruitment to membrane,
and the precise role of septin-membrane interactions, remain
poorly understood.
Shigella
flexneri
is
taxonomically
indistinguishable
from
Escherichia coli, but possesses a virulence plasmid encoding a
type III secretion system (T3SS) that enables host cell invasion
(Parsot, 2009). Following invasion, Shigella escapes from the
phagosome to proliferate in the cytosol and polymerize actin tails
for cell-to-cell spread (Welch and Way, 2013). To defend against
Shigella invasion, host cells use a variety of mechanisms,
including autophagy (Ogawa et al., 2005), guanylate-binding
proteins (GBPs) (Li et al., 2017; Wandel et al., 2017), and sep-
tin-mediated cellular immunity (Mostowy et al., 2010). To prevent
bacterial dissemination, septins entrap actin-polymerizing bac-
teria in �1-mm (diameter) cage-like structures (Mostowy et al.,
2010). It has been shown that �50% of entrapped bacteria are
metabolically inactive (Sirianni et al., 2016), but their fate is
mostly unknown.
The eukaryotic cytoskeleton is well known to rearrange during
infection and play a crucial role in host-microbe interactions (Ha-
glund and Welch, 2011). Components of the cytoskeleton
mediate cellular immunity by enabling bacterial detection and
mobilizing antibacterial mechanisms (Mostowy and Shenoy,
2015). Despite the septin cage representing an important link
between the cytoskeleton and cellular immunity, we lack funda-
mental insights into how septins recognize bacteria for cage
entrapment. Here, we discover that septin recognition of mem-
brane curvature and growth during bacterial cell division is an
unsuspected mechanism used by the host cell to defend against
invasive pathogens.
866
Cell Host & Microbe 24, 866–874, December 12, 2018 ª 2018 The Author(s). Published by Elsevier Inc.
This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

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RESULTS
Septins Recognize Micron-Scale Bacterial Curvature
How do septins recognize bacteria for entrapment? Considering
that septins sense micron-scale curvature of eukaryotic mem-
brane (Bridges et al., 2016), we hypothesized that septins are
recruited to Shigella (cells �1 mm in diameter) in a curvature-
dependent manner. To test this, we examined the recruitment
of SEPT6-GFP to Shigella M90T mCherry using time-lapse mi-
croscopy. We observed that for 87.4% ± 1.9% of entrapped bac-
teria, septins are first recruited to the division site and/or the cell
poles (both displaying high curvature) before they assemble into
cage-like structures (Figures 1A and 1B; Video S1), suggesting a
role for bacterial curvature in septin recruitment.
Bacterial invagination at the division site is driven by the bacte-
rial tubulin homolog FtsZ, which forms the cytokinetic Z-ring. To
follow the division site of intracellular bacteria, we expressed an
inducible ftsZ-gfp fusion in S. flexneri (Figures S1A–S1E). Strik-
ingly, time-lapse microscopy of SEPT6-RFP HeLa cells infected
with Shigella FtsZ-GFP revealed that SEPT6-RFP can overlap
with the Z-ring for up to 36 min (Figures 1C and 1D). Fixed micro-
scopy of 147 Shigella-septin cages showed that SEPT7 overlaps
with FtsZ-GFP at the bacterial division site for 68.5% ± 3.7% of
Z-ring-positive bacteria (Figure 1E), and structural illumination
microscopy (SIM) confirmed that SEPT7 alignment to FtsZ-GFP
is highly conserved (Figures S1F and S1G). To test whether
septins align with the Z-ring due to membrane invagination, we
simultaneously labeled the Z-ring and bacterial membrane and
performed quantitative microscopy. Here, we observed that sep-
tinalignment to the Z-ring is significantly increased (3.0± 0.4-fold)
when membrane is invaginated, as compared with when mem-
brane is not invaginated (Figure 1F). These data strongly suggest
that bacterial curvature generated by Z-ring constriction pro-
motes septin localization to the bacterial division site.
We questioned whether septins can be recruited to other bac-
teria presenting micron-scale curvature. Shigella sonnei is closely
related to S. flexneri and similarly entrapped in septin cages.
Using time-lapse SIM of HeLa SEPT6-GFP cells infected with
S. sonnei mCherry, we observed initial septin recruitment to
bacterial division sites and/or cell poles (Figure S1H). We next
infected HeLa cells with invasive Pseudomonas aeruginosa
PAK-GFP and discovered by quantitative microscopy that
17.5% ± 1.4% of intracellular bacteria are entrapped in SEPT7
cage-like structures at 4 hr post infection (Figure 1G). Time-lapse
microscopy of SEPT6-RFP HeLa cells infected with P.aeruginosa
GFP showed initial septin recruitment to highly curved bacterial
membrane (Figure 1H; Video S2). To investigate whether septins
can also recognize Gram-positive bacteria, we infected SEPT6-
RFP HeLa cells with invasive Staphylococcus aureus RN6390
GFP, and time-lapse microscopy showed septin recruitment to
S. aureus division sites (Figure 1I; Video S3). Together, these re-
sults highlight septin recruitment to micron-scale curvature pre-
sented by a variety of invasive bacterial species.
Cardiolipin Promotes Septin Recruitment to Shigella
Membrane Curvature
Considering that septins bind anionic phospholipids of eukary-
otic membranes, we reasoned that septins might also bind
anionic phospholipids specific to bacterial curvature. In rod-
shaped bacteria, the lipid species cardiolipin (CL) and phospha-
tidylglycerol (PG) are enriched at the bacterial division site and
cell poles (Kawai et al., 2004; Oliver et al., 2014) (Figure S2A).
We purified SEPT2/6/7 and SEPT9 and tested for lipid binding
in vitro using membrane lipid strips containing 15 different
phospholipids (Figures 2A and S2B). SEPT2/6/7 and SEPT9
bound strongly to CL but not significantly to PG. We also tested
for CL binding of SEPT2, SEPT6, SEPT9, and SEPT6/7 using
dot-blot assays with purified CL from E. coli (Figure 2B).
Together, these results show that SEPT2 and SEPT6 do not
bind CL whereas SEPT2/6/7, SEPT6/7, and SEPT9 do.
To confirm that septins bind bacterial membrane, we per-
formed liposome flotation assays using purified SEPT2/6/7 and
total lipid extracts from S. flexneri. Septins clearly bound vesicles
made from bacterial total lipid extracts (Figure 2C). We then con-
structed a S. flexneri DclsDymdCDybhO (DCL) mutant strain void
of CL (Figure S2C) and tested for SEPT2/6/7 binding. In this case,
we found that SEPT2/6/7 binds significantly more (6.3 ± 3.5-fold)
to vesicles produced from wild-type (WT) Shigella than DCL
Shigella (Figure 2C). Consistent with this, quantitative micro-
scopy revealed that DCL Shigella are significantly less (1.4 ±
0.1-fold) entrapped in SEPT7 cages than WT Shigella (Figures
2D and S2D–S2F).
Is septin interaction with CL a recruitment mechanism or can it
additionally promote cage assembly? To address this, we per-
formed time-lapse microscopy of SEPT6-GFP HeLa cells
infected with WT or DCL Shigella mCherry. We observed that
septin recruitment to bacterial curvature lacking CL is signifi-
cantly decreased (2.9 ± 0.3-fold) compared with bacterial curva-
ture presenting CL (n = 276 WT versus n = 93 DCL total bacterial
cells). To further disentangle the role of curvature and CL in sep-
tin recruitment, we prepared supported bacterial lipid bilayers on
1- or 5-mm (diameter) beads, and compared septin recruitment
here with beads coated with S. flexneri lipids presenting CL or
not. We found that septins preferentially associate with 1-mm
beads and that CL promotes septin recruitment to both 1- and
5-mm beads (Figures 2E and 2F). From these results, we
conclude that CL can promote the recruitment of septins to
bacterial curvature.
Septin Cages Entrap Actively Dividing Bacteria
To gain insights into bacterial factors required for cage entrap-
ment to proceed after septin recruitment, we used antibiotics
targeting different processes of bacterial cell division. First, we
inhibited bacterial cell growth by treating infected cells with
erythromycin or trimethoprim, antibiotics that interfere with bac-
terial protein synthesis or DNA replication, respectively. Under
these conditions SEPT7 cages are rarely observed (Figure 3A),
despite bacteria being metabolically active and recruiting actin
similar to untreated bacteria (Figures S3A–S3C). Time-lapse
microscopy showed that septins are transiently recruited to the
poles of trimethoprim-treated bacteria, but mostly (i.e., for
79.3% ± 2.6% of bacteria) fail to assemble into cages (Figure 3C).
Together, these data support a model in which bacterial curva-
ture is required for septin recruitment and bacterial growth is
required for septin cage entrapment.
To further test our model, we treated infected cells with
cephalexin, an antibiotic that inhibits cell separation and thus
promotes filamentation (Pogliano et al., 1997). In this case, the
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percentage of Shigella entrapped in SEPT7 cage-like structures
is significantly increased (1.9 ± 0.1-fold) compared with un-
treated bacteria (Figures 3D and 3E). Similar results were
obtained when testing septin caging of filamentous bacteria
created by overproducing the FtsZ inhibitor SulA (Figures 3F
and S3D), which in contrast to cephalexin inhibits cell separation
before Z-ring formation. We hypothesized that septins may be
recruited to CL-rich curved cell poles of filamentous bacteria.
To test this, we infected SEPT6-GFP HeLa cells with Shigella
mCherry, treated them with cephalexin for 3 hr, and performed
time-lapse microscopy. However, we could rarely see initial
septin recruitment to filamentous bacteria, suggesting that
septin recruitment happens to membrane curvature prolonged
by cephalexin before it inhibits cell separation. To confirm this,
we treated infected cells with cephalexin but investigated septin
recruitment before the drug could fully act (45 min after drug
addition). Here, we clearly observed septin recruitment to
dividing bacteria before cells could grow into filaments (Fig-
ure S3E). Collectively, pharmacologic and genetic manipulation
of Shigella reveals that, following septin recruitment, bacterial
cell growth is required for septin cage entrapment.
Septin Cages Inhibit Bacterial Cell Division via
Autophagy and Lysosome Fusion
To address the impact of septin caging on bacterial cell division,
we tested whether septin cages inhibit the division of entrapped
Shigella. We used time-lapse microscopy to focus on the fate of
Z-ring-positive bacteria following septin cage recruitment. We
observed that 61.3% ± 4.0% of septin cage-entrapped Shigella
lose their Z-ring (Figures 4A and 4B), and that Z-ring disassembly
takes 27.8 ± 3.9 min following septin cage recruitment (Fig-
ure 4C). In agreement with a role for septin caging in the inhibition
of bacterial cell division, time-lapse microscopy showed that,
remarkably, 92.7% ± 2.5% of bacteria fail to divide following
septin cage entrapment.
To test the role of autophagy in the inhibition of bacterial cell
division by septin cages, we quantified Z-ring-positive Shigella
recruiting septins and p62 (early autophagy marker) or LC3B
(early and late autophagy marker). We found that Shigella recruit-
ing both septins and p62 are significantly less (1.9 ± 0.2-fold)
Z-ring positive, as compared with Shigella which recruit septins
but not p62 (Figures 4D and 4E). Moreover, Shigella are signifi-
cantly less (1.5 ± 0.1-fold) Z-ring positive when recruiting both
SEPT7 and p62, as compared with bacteria recruiting p62 alone.
Similar results are obtained using LC3B (Figures 4F and 4G).
Together, these data suggest that septins are necessary but
not sufficient for Shigella Z-ring disassembly, and highlight an
interdependence between septins and autophagy in the inhibi-
tion of bacterial cell division.
Considering that septins are implicated in the fusion of
lysosomes with endocytic membranes (Dolat and Spiliotis,
2016), we hypothesized that septin caging may promote the
fusion of lysosomes with entrapped Shigella. In line with this,
time-lapse microscopy captured 42.0% ± 5.8% of Shigella-
SEPT6 cages becoming LysoTracker positive within the imaging
period (Figure 4H). To test whether the antibacterial activity of
septin cages is dependent on lysosome fusion, we treated in-
fected cells with chloroquine to neutralize lysosomes and inhibit
autophagy (Figures S4A and S4B). When infected cells are
treated with chloroquine, entrapped Shigella fail to disassemble
their Z-ring (Figures 4I and 4J). Collectively, these results demon-
strate that septin cages entrap actively dividing bacteria and
prevent further division events by autophagy and lysosome
fusion.
DISCUSSION
How septins recognize intracellular bacteria for cage entrapment
has remained unknown. Using single-cell analysis we found that
septins are recruited to micron-scale curvature presented by
Shigella, Pseudomonas, and Staphylococcus. In the case of
Shigella, we show that septin recruitment is promoted by CL,
which is enriched at such regions of high membrane curvature.
Following recruitment, septins assemble into cages around
actively growing Shigella to inhibit cell division via autophagy
and lysosome fusion. These results uncover a mechanism
used by the host cell to sense and restrict bacterial cell division,
and have important implications for septin biology and cellular
immunity.
Investigation of the host cell cytoskeleton during bacterial
infection has enabled major discoveries in both infection and
cell biology (Haglund and Welch, 2011; Welch and Way, 2013).
Figure 1. Septins Recognize Micron-Scale Bacterial Curvature
(A) Time-lapse of S. flexneri mCherry-infected SEPT6-GFP HeLa at 2 hr 10 min post infection imaged every 2 min. White arrowheads indicate septin recruitment to
the bacterial division site. Scale bar, 1 mm. See also Video S1.
(B) Quantification of (A). The graph represents mean % ± SEM of septin recruitment to highly curved membrane areas (bacterial cell poles and/or bacterial
midcell). Values from n = 79 bacterial cells from 8 independent experiments.
(C) Time-lapse of S. flexneri FtsZ-GFP-infected SEPT6-RFP HeLa cells at 2 hr 10 min imaged every 2 min. White arrowheads indicate SEPT6-RFP overlap with
FtsZ-GFP at the bacterial division site. Dashed lines indicate bacterial contour. Scale bar, 1 mm.
(D) Quantification of (C). Graph shows individual times of SEPT6-FtsZ overlap from n = 26 bacterial cells including mean ± SEM from 6 independent experiments.
(E) Representative SEPT7 cage in S. flexneri FtsZ-GFP-infected HeLa cells at 3 hr 40 min post infection. Scale bars, 1 mm. Inset images highlight a septin ring at the
bacterial division site. Fluorescent intensity profile (FIP) was taken of the dotted line along the midline of the cell in the inset image and normalized from 0 to 1.
(F) HeLa cells were infected for 3 hr 40 min with S. flexneri FtsZ-GFP and bacterial membrane was labeled with FM4-64X. Graph represents mean % ± SEM of
SEPT7 aligning at midcell of entrapped S. flexneri when bacteria are either Z-ring negative and not invaginated (�, �), Z-ring positive and not invaginated (+, �),
Z-ring positive and invaginated (+, +), or Z-ring negative after cell separation (�, +). Values from n = 289 bacterial cells from 3 independent experiments. One-way
ANOVA; ns, p > 0.05; ***p < 0.001.
(G) P. aeruginosa GFP-infected HeLa cells at 4 hr post infection immunostained for SEPT7. Scale bars, 5 mm (main image) and 1 mm (inset).
(H) Time-lapse of P. aeruginosa GFP-infected SEPT6-RFP HeLa cells at 1 hr post infection imaged every 2 min. Scale bar, 1 mm. See also Video S2.
(I) Time-lapse of S. aureus GFP-infected SEPT6-RFP HeLa cells at 1 hr post infection imaged every 2 min. Scale bar, 1 mm. See also Video S3.
See also Figure S1.
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Although first identified in 1991 (Bi and Lutkenhaus, 1991) and
studied extensively for more than 15 years, FtsZ had never
been examined in pathogenic bacteria during infection of host
cells. For the complete understanding of infectious processes,
it will be crucial to study FtsZ and other components of the
bacterial cytoskeleton, including the actin homolog MreB and
septin-like proteins MinCD, during infection. Here, we visualize
FtsZ during infection and reveal that septins recognize actively
dividing bacterial cells. Considering this, one should expect
that septins are less efficient in recognition of non-dividing bac-
terial cells and sensitive to bacteria changing morphology during
infection. It will thus be of great interest to investigate a role for
septins in selection for bacterial pathogens that can escape
detection by cellular immunity and remain dormant in host cells.
CL has recently been linked to bacterial virulence. In the case
of Salmonella Typhimurium, CL delivery to the outer membrane
Figure 2. Cardiolipin Promotes Septin Recruitment to Shigella Membrane Curvature
(A) Membrane lipid strips were incubated with 200 nM SEPT2/6/7. TAG, triacylglycerol; DAG, diacylglycerol; PA, phosphatidic acid; PS, phosphatidylserine; PE,
phosphatidylethanolamine; PC, phosphatidylcholine; PG, phosphatidylglycerol; CL, cardiolipin; PI, phosphatidylinositol; PIP, phosphatidylinositol phosphate;
PI(4,5)P2, phosphatidylinositol bisphosphate; PI(3,4,5)P3, phosphatidylinositol trisphosphate; CHO, cholesterol; SM, sphingomyelin; SUL, sulfatide.
(B) Representative lipid dot blot in which 200 nM SEPT2, SEPT6 (negative control because no lipid interaction [Spiliotis, 2018]), SEPT6/7, or SEPT9 was incubated
with a nitrocellulose membrane containing water (CTRL) or 10 nmol purified CL from E. coli (E. coli CL).
(C) SEPT2/6/7 was incubated with liposomes made from S. flexneri wild-type (WT) or DCL and centrifuged on a sucrose gradient. Representative western blot
(top) shows equal volumes for the top fraction (B, liposome-bound SEPT2/6/7) and bottom fraction (U, unbound SEPT2/6/7). Bar graph shows mean ± SEM
of the amount of SEPT2/6/7 in the bound (B) and unbound (U) fraction relative to liposomes made from WT from 3 independent experiments. Student’s t test,
**p < 0.01,* p < 0.05.
(D) Graph represents mean % ± SEM of SEPT7 cage-entrapped S. flexneri WT or DCL at 3 hr 40 min post infection. Values from n = 4,945 bacterial cells from
3 independent experiments. Student’s t test, ***p < 0.001.
(E) Representative image of 50 nM SEPT2/6/7 labeled with NHS-Alexa Fluor 488 (green) recruitment to 1-mm or 5-mm silica beads coated in lipid bilayer from
S. flexneri WT or DCL containing RhPE (purple). Scale bar, 1 mm.
(F) Quantification of (E). Graph shows median and whiskers (min to max) from n R 243 beads for each condition from 3 independent experiments. Kruskal-Wallis
test, ***p < 0.001, **p < 0.01.
See also Figure S2.
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Figure 3. Septin Cages Entrap Actively Dividing Bacteria
(A) Diagrams illustrate that untreated bacteria (CTRL) assemble a Z-ring at bacterial midcell and erythromycin (EM) and trimethoprim (TMP) inhibit bacterial cell
division and Z-ring assembly. Untreated (CTRL), EM-treated, or TMP-treated S. flexneri x-light GFP-infected HeLa cells at 3 hr 40 min post infection. Scale bars,
5 mm (main image) and 1 mm (inset).
(B) Quantification of (A). Graph shows mean % ± SEM of S. flexneri entrapped in SEPT7 cages in CTRL, EM-treated, or TMP-treated cells. Values from n = 5,215
bacterial cells from 3 independent experiments. Student’s t test, ***p < 0.001.
(C) HeLa SEPT6-GFP cells were infected with Shigella mCherry, treated with TMP for 2 hr, and imaged every 2 min. Video frames (representative for
n = 76 bacterial cells from 3 independent experiments) show temporary septin recruitment to the pole but no assembly into septin cages. Scale bar, 1 mm.
(D) Diagram illustrates cephalexin-treated bacterium, which elongates and forms division sites (i.e., FtsZ positive). SIM image of SEPT7 cage around cephalexin-
treated S. flexneri GFP at 3 hr 40 min inside HeLa cell. Scale bar, 1 mm.
(E) Graph represents mean % ± SEM of S. flexneri entrapped in SEPT7 cage-like structures in untreated (CTRL) or cephalexin-treated (Ceph) cells. Values from
n = 2,487 bacterial cells for CTRL and n = 499 bacterial cells from Ceph samples from 3 independent experiments. Student’s t test, **p < 0.01.
(F) Diagram illustrates that overproduction of SulA inhibits Z-ring formation leading to cell filamentation. Graph shows mean % ± SEM of S. flexneri entrapped in
SEPT7 cage-like structures in untreated (CTRL) or SulA-overproduced (SulA) samples. Values from n = 3,693 bacterial cells from 3 independent experiments.
Student’s t test, ***p < 0.001.
See also Figure S3.
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can promote membrane barrier function and intracellular survival
(Dalebroux et al., 2015). In the case of S. flexneri, CL promotes
IcsA localization on the bacterial surface for actin-based motility
(Rossi et al., 2017). What is the precise role of CL in septin
recruitment? Our results suggest that septins bind CL for recruit-
ment to highly curved bacterial membrane. How phospholipids
and membrane curvature recruit septins in eukaryotic cells is
not fully known (Cannon et al., 2017). We thus propose that
Figure 4. Septin Cages Inhibit Bacterial Cell Division via Autophagy and Lysosome Fusion
(A) Time-lapse of S. flexneri FtsZ-GFP-infected SEPT6-RFP HeLa cells at 2 hr 10 min post infection imaged every 4 min showing late stages of septin cage.
Arrowheads point to the progressive disassembly of the Z-ring inside the bacterium (dashed outline). Scale bar, 1 mm.
(B) Quantification of (A). Graph shows mean % ± SEM of non-entrapped S. flexneri (-SEPT6 cage) or septin cage-entrapped S. flexneri (+SEPT6 cage) becoming
Z-ring negative during imaging. Values from n = 1,721 bacterial cells from 8 independent experiments. Only bacteria that were entrapped for at least 3
consecutive time frames were considered as SEPT6 cage entrapped. Student’s t test, ***p < 0.001.
(C) Quantification of (A). Graph shows the time from SEPT6 cage entrapment until Z-ring disassembly including mean ± SEM from n = 25 bacterial cells from
6 independent experiments. Only videos starting with septin recruitment and ending with Z-ring disassembly were considered for this quantification.
(D–G) S. flexneri FtsZ-GFP-infected HeLa cells at 3 hr 40 min post infection. Image shows two SEPT7 (D) or SEPT6 (F) cages positive for p62 (D) or LC3B (F)
entrapping Z ring negative bacteria. Scale bar, 1 mm. Graphs show mean % ± SEM of Z-ring-positive bacteria (E and G). Values from n = 3,292 (E) or n = 1,737 (G)
bacterial cells from 4 independent experiments Student’s t test, ns, p > 0.5; ***p < 0.001.
(H) Time-lapse of S. flexneri-infected, LysoTracker red-labeled SEPT6-GFP HeLa cells at 2 hr 10 min imaged every 3 min. Frames show late stages of septin
cage-entrapped Shigella (dashed outline). Scale bar, 1 mm.
(I) SEPT7 cages in S. flexneri FtsZ-GFP-infected untreated (CTRL) or chloroquine-treated (CQ) HeLa cells at 3 hr 40 min. Scale bar, 1 mm.
(J) Quantification of (I). Graph shows mean % ± SEM of Z-ring-positive S. flexneri outside septin cages (�SEPT7 cage) and inside septin cages (+SEPT7 cage) in
CTRL or CQ-treated cells. Values from n = 5,047 bacterial cells from 3 independent experiments. Student’s t test, ns, p > 0.5; *p < 0.05.
See also Figure S4.
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in-depth investigation of the Shigella-septin cage will help to
describe the coordination between lipids, membrane curvature,
and septin recruitment. Other factors besides CL binding and
curvature may contribute to the recruitment of septins to intra-
cellular Shigella. To discover this, future work will be required
to screen bacterial surface components that can influence septin
recruitment.
Cellular effector mechanisms that recognize invasive bacterial
pathogens are the subject of intense investigation (Kieser and
Kagan, 2017; Randow et al., 2013). It has recently become clear
that the cytoskeleton is a key component of cellular immunity
(Mostowy and Shenoy, 2015). However, the full breadth of cyto-
skeletal roles in host defense remains to be established. Our data
reveal that septins recognize bacterial cell division for host
defense. Here, we focus on S. flexneri, a World Health Organiza-
tion priority pathogen also used as a valuable tool to investigate
factors crucial for cellular immunity including autophagy, neutro-
phil
extracellular
traps,
nucleotide-binding
oligomerization
domain-like receptors, and GBPs. Considering that septin
recruitment has been described for a wide variety of bacterial
pathogens (reviewed in Torraca and Mostowy, 2016) and
vaccinia virus (Pfanzelter et al., 2018), it will next be important
to test how widespread is the role of cell shape and membrane
curvature in pathogen sensing.
Septinswerediscoveredfor their role inyeastcelldivision(Hart-
well, 1971). Recently, septins have received great attention for
their role in mitochondrial division (Pagliuso et al., 2016; Sirianni
et al., 2016). In this study, we discover that septins also recognize
bacterial cell division to restrict the proliferation of invasive path-
ogens. Having identified a link between cell division and cellular
immunity, our results reveal a fundamental danger signal used
by the host cell to recognize intracellular bacteria. Future work
will determine how septin biology can be harnessed for therapeu-
tic purposes, including control of antibiotic-resistant infections.
STAR+METHODS
Detailed methods are provided in the online version of this paper
and include the following:
d KEY RESOURCES TABLE
d CONTACT FOR REAGENT AND RESOURCE SHARING
d EXPERIMENTAL MODEL AND SUBJECT DETAILS
B Bacterial Strains
B Cell Lines
d METHOD DETAILS
B Bacterial Growth
B Construction of Deletion Mutants
B Plasmid Construction
B Cardiolipin Detection Using MALDI-TOF MS
B Protein-Lipid Overlay Assays
B Liposome Flotation Assay
B Septin Recruitment to Supported Lipid Bilayer Micro-
spheres
B Antibodies
B Bacterial Infection of Epithelial Cells
B Fluorescence Microscopy of Infected Cells
B Structured Illumination Microscopy
d QUANTIFICATION AND STATISTICAL ANALYSIS
SUPPLEMENTAL INFORMATION
Supplemental Information includes four figures, one table, and three videos
and can be found with this article online at https://doi.org/10.1016/j.chom.
2018.11.005.
ACKNOWLEDGMENTS
We thank S. Murdoch and T. Palmer for S. aureus RN6390-GFP and A. Filloux
for P. aeruginosa PAK::tn7gfp. We thank C. Parsot, A. Clements, C. Cornilleau,
and F. Caudron for helpful tools and discussion. We thank the Company of Bi-
ologists for Travel fellowship to S.K. D.L.-M. is funded by the European Union’s
Horizon 2020 research and innovation program under the Marie Sk1odowska-
Curie grant agreement no. H2020-MSCA-IF-2016-752022. P.M.P. and R.H.
are funded by grants from the UK Biotechnology and Biological Sciences
Research Council (BB/M022374/1; BB/P027431/1; BB/R000697/1), the UK
Medical Research Council (MR/K015826/1), and Wellcome Trust (203276/Z/
16/Z). D.A. and E.T.S. are funded by National Institutes of Health/National Insti-
tute of General Medical Sciences (GM097664). Work in the R.C.-L. laboratory
was supported by a starting grant from the European Research Council (ERC-
StG-311231) and an international grant from the French National Research
Agency (ANR-12-ISV3-0004-01). Work in the S.M. laboratory is supported
by a Wellcome Trust Senior Research Fellowship (206444/Z/17/Z), Wellcome
Trust Research Career Development Fellowship (WT097411MA), and the
Lister Institute of Preventive Medicine.
AUTHOR CONTRIBUTIONS
S.K., D.L.-M., A.C., P.M.P., D.A., D.G., and G.L.-M. conducted experiments.
S.K., D.L.-M., A.C., P.M.P., R.H., E.T.S., R.C.-L., and S.M. designed experi-
ments and analyzed results. S.K. and S.M. wrote the manuscript, and all au-
thors commented on the manuscript.
DECLARATION OF INTERESTS
The authors declare that they have no conflict of interest.
Received: February 1, 2018
Revised: August 14, 2018
Accepted: November 5, 2018
Published: December 12, 2018
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STAR+METHODS
KEY RESOURCES TABLE
REAGENT or RESOURCE
SOURCE
IDENTIFIER
Antibodies
Rabbit polyclonal anti-SEPT7
IBL
Cat#18991; RRID: AB_1630825
Rabbit polyclonal anti-LC3
Abcam
Cat#ab48394; RRID: AB_881433
Rabbit polyclonal anti-p62
MBL
Cat#PM045; RRID: AB_1279301
Mouse monoclonal anti-His
Thermo Fisher Scientific
Cat#MA1-21315; RRID: AB_557403
Mouse monoclonal anti-p62
BD Biosciences
Cat#610832; RRID: AB_398151
Mouse monoclonal anti-GAPDH
Abcam
Cat#ab8245; RRID: AB_2107448
Bacterial and Virus Strains
Escherichia coli DH5a
Thermo Fisher Scientific
Cat#18265017
Pseudomonas aeruginosa PAK::tn7gfp
(McCarthy et al., 2017)
N/A
Shigella flexneri M90T Serotype 5a
(Mostowy et al., 2010)
N/A
S. flexneri M90T Serotype 5a GFP
(Mostowy et al., 2010)
N/A
S. flexneri M90T Serotype 5a
ΔclsΔymdCΔybhO
This study
N/A
S. sonnei 53G
(Formal et al., 1966)
N/A
Staphylococcus aureus RN6390-GFP
Laboratory of Tracy Palmer
N/A
Chemicals, Peptides, and Recombinant Proteins
L-a-phosphatidylethanolamine-N-
(lissamine rhodamine B sulfonyl)
Sigma-Aldrich
Cat# 810146C
Nonfunctionalised silica
microspheres 1.05 mm
Bang Laboratories
Cat#SS04000
Nonfunctionalised silica
microspheres 4.89 mm
Bang Laboratories
Cat#SS05003
Experimental Models: Cell Lines
HeLa Human cervix carcinoma epithelial
cell line
ATCC
CCL-2
HeLa pLVX-puro SEPT6-GFP N-terminal
fusion
(Sirianni et al., 2016)
N/A
HeLa pLVX-puro SEPT6-RFP N-terminal
fusion
(Pfanzelter et al., 2018)
N/A
U-2 OS Human osteosarcoma epithelial
cell line
ATCC
HTB-96
Oligonucleotides
Sequences of oligonucleotides are listed
in Table S1.
This manuscript
N/A
Recombinant DNA
pBAD18
(Guzman et al., 1995)
N/A
pBAD18 FtsZ-GFP
This study
N/A
pBAD18 SulA
This study
N/A
pDHL584
(Landgraf et al., 2012)
N/A
pFPV25.2
(Valdivia and Falkow, 1996)
N/A
pKD3
(Datsenko and Wanner, 2000)
N/A
pKD4
(Datsenko and Wanner, 2000)
N/A
pKD46
(Datsenko and Wanner, 2000)
N/A
pCP20
(Datsenko and Wanner, 2000)
N/A
(Continued on next page)
Cell Host & Microbe 24, 866–874.e1–e4, December 12, 2018
e1

----!@#$NewPage!@#$----
CONTACT FOR REAGENT AND RESOURCE SHARING
Further information and requests for resources and reagents should be directed to and will be fulfilled by the Lead Contact, Serge
Mostowy (serge.mostowy@lshtm.ac.uk).
EXPERIMENTAL MODEL AND SUBJECT DETAILS
Bacterial Strains
Bacterial strains used in this study are listed in the Key Resources Table. E. coli DH5-a were grown in Lysogeny Broth (LB) broth and
plates. Shigella were grown on (Trypto-Casein-Soy) TCS plates containing 0.1% (w/v) Congo red dye or in TCS broth. Pseudomonas
aeruginosa GFP (kindly provided by A. Filloux; McCarthy et al., 2017) and Staphylococcus aureus GFP (kindly provided by T. Palmer)
were grown on TCS plates or in TCS broth. Selection markers were used at the indicated concentrations: carbenicillin (100 mg/ml);
kanamycin (50 mg/ml); chloramphenicol (30 mg/ml).
Cell Lines
HeLa (ATCC CCL, female), HeLa SEPT6-GFP, HeLa SEPT6-RFP (kindly provided by M. Way; Pfanzelter et al., 2018) or U-2 OS (ATCC
HTB-96, female) cells were cultured in DMEM (GIBCO) supplemented with 10 % fetal bovine serum (FBS) at 37�C and 5% CO2. For
selection, 1 mg/ml puromycin was added to the culturing media of HeLa SEPT6-GFP and HeLa SEPT6-RFP cells.
METHOD DETAILS
Bacterial Growth
Shigella were grown overnight and diluted to a starting OD600 of 0.01. Samples were prepared in triplicates in a 96-well plate. OD600
was measured every 30 min for 15 h at 37�C with shaking using a microplate reader (TECAN Infinite M200 Pro).
Construction of Deletion Mutants
Primers used in this study were designed using Benchling (https://benchling.com) and are listed in Table S1. S. flexneri mutants Dcls,
DymdC and DybhO were created using l-Red-mediated recombination (Datsenko and Wanner, 2000). For Dcls and DymdC, a PCR
product was generated by using pKD4 and primers SK-105 (fw) and SK-106 (rev) or SK-113 (fw) and SK-114 (rev), respectively. For
DybhO, a PCR product was generated using pKD3 and primers SK-107 (fw) and SK-108 (rev). PCR products were electroporated into
S. flexneri producing l-Red recombinase (Datsenko and Wanner, 2000) and recombinants were selected by kanamycin (Dcls::kan
and DymdC::kan) or chloramphenicol (DybhO::cat) resistance. Double and triple mutants were created by removing the kanamycin
cassette in Dcls using pCP20 (Cherepanov and Wackernagel, 1995), followed by subsequent bacteriophage P1 transduction of the
DymdC::kan and the DybhO::cat alleles. All strains were verified via PCR. The abbreviation DCL is used throughout the manuscript for
DclsDymdCDybhO.
Plasmid Construction
Constructed plasmids were confirmed by sequencing. Plasmid encoding sulA from pBAD18 was constructed by amplifying sulA from
S. flexneri chromosomal DNA using primers SK-101 (fw) and SK-102 (rev). The resulting PCR product was digested with SalI and
EcoRI restriction enzymes and introduced in the SalI/EcoRI site of plasmid pBAD18.
Plasmid encoding ftsZ-gfp from pSA10 was constructed by amplifying ftsZ from S. flexneri chromosomal DNA using primers SK-45
(fw) and SK-20 (rev) and by amplifying a monomeric superfolder gfp from plasmid pDHL584 (Landgraf et al., 2012) using primers
Continued
REAGENT or RESOURCE
SOURCE
IDENTIFIER
pSA10
(Schlosser-Silverman et al., 2000)
N/A
pSA10 FtsZ-GFP
This study
N/A
pSA11
(Schlosser-Silverman et al., 2000)
N/A
Software and Algorithms
Prism
Graphpad software
https://www.graphpad.com/
FIJI
NIH
https://imagej.net/ImageJ
ICY
Institut Pasteur
http://icy.bioimageanalysis.org/
Huygens Professional software
SVI
N/A
ZEN
Zeiss
N/A
Benchling
N/A
https://benchling.com
e2
Cell Host & Microbe 24, 866–874.e1–e4, December 12, 2018

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SK-19 (fw) and SK-54 (rev). The DNA fragment containing gfp gene was fused to the C-terminus of the ftsZ encoding DNA fragment
using Gibson assembly. The ftsZ-gfp DNA fragment was digested with SalI and EcoRI restriction enzymes and introduced into the
SalI/EcoRI restriction site of plasmid pBAD18 (Guzman et al., 1995).
Cardiolipin Detection Using MALDI-TOF MS
Bacteria were grown to stationary phase and heat killed at 90�C for 1 h. After three washes in water, bacteria were diluted to a final
concentration of 104-105 bacteria per ml. To ionize cardiolipin, 0.5 ml matrix [10 mg / ml 2,5-dihydroxybenzoic acid in 90:10 chloro-
form / methanol (v/v)] and 0.5 ml bacteria solution were applied on the target and dried gently under a stream of air. MALDI-TOF MS
analysis was performed using the reflectron mode on a 4800 Proteomics Analyzer (with TOF-TOF Optics Applied Biosystems). Sam-
ples were analysed in the negative ion mode operated at 20 kV with an extraction delay time of 20 ns. The negative mass spectrum
was scanned between m/z 1000 and 3000 and MS data were analysed using Data Explorer 4.9 (Applied Biosystems).
Protein-Lipid Overlay Assays
SEPT2/6/7 was purified as previously described in Mavrakis et al. (2014). Purification of SEPT2, SEPT6 or SEPT9 was performed
according to Bai et al. (2013). Membrane lipid-strips were purchased from Echelon Biosciences (Salt Lake City, Utah) and E. coli
cardiolipin was purchased from Avanti Polar Lipids (Alabaster, Alabama). Membrane lipid strips were used according to the manu-
facturer’s instructions with 50 mM Tris, pH 7.5, 150 mM NaCl, 0.1% Tween20, 3% Fatty-acid-free BSA used as blocking buffer.
Protein-lipid overlay assays were carried out according to Dowler et al. (2002) using 200 nM septins. The binding of His-SEPT2
and His-SEPT9 was visualised using primary antibodies against His and secondary 680-conjugates goat anti mouse antibodies.
The fluorescent signal was detected using the Odyssey imager (Licor Biosciences).
Liposome Flotation Assay
Stationary phase S. flexneri WT or DCL were centrifuged, washed and resuspended in chloroform/methanol (1:1, v/v) and lipids were
extracted three times. To generate small unilamellar vesicles (SUVs), lipids were dried completely under a light nitrogen stream and
rehydrated in liposome buffer (50 mM Tris pH 8.0, 50 mM KCl) for 60 min at 65�C and 700 rpm. Lipids were frozen and thawed five
times in liquid nitrogen and passed through a mini-extruder (Avanti Polar Lipids) at least 20 times using a 0.1 mm pore filter on a heat
block at 65�C. To test for septin binding, 8 mg/ml SUVs were mixed with 0.5 mM purified SEPT2/6/7 trimer in 150 ml liposome buffer
containing 1 mM MgCl2. Samples were incubated at 25�C and 500 rpm for 1 h, transferred into a polycarbonated ultracentrifuge tube
(Beckman Coulter) and mixed with 100 ml liposome buffer containing 75% sucrose. Samples were gently overlaid with liposome
buffer containing 25% sucrose and 50 ml liposome buffer and centrifuged at 48,000 rpm in a TLA-120.2 rotor for 1 h at 20�C. Equal
volumes of top and bottom fractions were taken, mixed with Laemmli buffer and run on a 12% SDS-PAGE gel. Samples were blotted
and incubated with anti-His antibody followed by peroxidase-conjugated goat anti-mouse (Dako). Membranes were scanned using
the ChemiDoc Touch Imaging System (Biorad).
Septin Recruitment to Supported Lipid Bilayer Microspheres
Septin recruitment to supported lipid bilayer microspheres was performed as described in Bridges et al. (2016). In brief, SUVs were
made from total bacterial lipid extracts adding <0.1% L-a-phosphatidylethanolamine-N-(lissamine rhodamine B sulfonyl) (Avanti
Polar Lipids). SUVs were adsorbed onto nonfunctionalised silica microspheres (1.05 or 4.89 mm mean diameter, rounded in text
for simplicity; Bang Laboratories) and 8 mg/ml lipids were mixed with 1 or 5 mm beads in 80 ml at 500 rpm and 25�C for 1h. Beads
were centrifuged for 30 s and washed 4x in liposome buffer containing 50 mM MgCl2. SEPT2/6/7 was fluorescently labelled using
Alexa Fluor 488 NHS Ester as previously described (Mavrakis et al., 2016). After labelling, septins were dialysed against storage buffer
(50 mM Tris, pH 8.0, 300 mM KCl, 5 mM MgCl2 and 5 mM DTT). Coated beads were mixed with labelled SEPT2/6/7 to gain a final
septin concentration of 50 nM. Beads were imaged on 2 % agarose pads using an Axiovert Z1 driven by ZEN software (Carl Zeiss
MicroImaging). ‘Septin recruitment’ was calculated according to Bridges et al. (2016) using ICY.
Antibodies
Rabbit polyclonal antibodies used were anti-SEPT7 (IBL 18991), anti-LC3 (ab48394) and anti-p62 (MBL PM045). Mouse monoclonal
antibodies used were His (Thermo Scientific MA1-21315), p62 (BD 610832) and GAPDH (ab8245). Secondary antibodies used were
Alexa Fluor 680-conjugated goat anti-mouse, Alexa 488-, 555- or 647-conjugated donkey anti-rabbit and Alexa Fluor 647-conju-
gated donkey anti-mouse (Molecular Probes). F-actin was labelled with Alexa 488- or 647-phalloidin (Molecular Probes).
For the immunoblots, total cellular extracts were prepared using Laemmli buffer and blotted with the primary antibodies
anti-GAPDH and anti-p62 followed by peroxidase-conjugated goat anti-mouse (Dako) and anti-rabbit secondary antibodies
(Dako). GAPDH was used as a loading control. Proteins were run on 10 % SDS polyacrylamide gels.
Bacterial Infection of Epithelial Cells
Cells for fixed microscopy were plated (1 - 5 x 105) on glass coverslips in 6-well plates (Thermo Scientific) and used for experiments
24 - 48 h later. HeLa cells for time-lapse microscopy were grown (5 x 105) on MatTek glass-bottom dishes (MatTek corporation) and
infected 24 h later.
Cell Host & Microbe 24, 866–874.e1–e4, December 12, 2018
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For Shigella infections, bacteria were grown to OD600 �0.6 and added to HeLa cells at an MOI of 100. Samples were centrifuged at
110 g for 10 min at 21�C and incubated for 30 min at 37�C and 5% CO2. Cells were washed with PBS and incubated in 50 mg/ml
gentamicin-containing media. Where indicated, arabinose or antibiotics were added at the same time as gentamicin (40 min after
infection to allow bacteria to invade host cells and escape to the cytosol). FtsZ-GFP or SulA production was induced with 0.2 %
or 1 % arabinose, respectively. Erythromycin was used at 14 mM, trimethoprim was used at 70 mM and cephalexin was used at
2 mg / ml. 3 mg / ml FM4-64X or 0.1 mM Isopropyl b-D-1-thiogalactopyranoside (IPTG) was added 30 min prior to fixation. 10 mM
chloroquine was added 15 h before infection. Drugs were kept in the media throughout the infection process. For gentamicin
protection assays, intracellular bacteria were extracted after 1 h and 4 h 40 min from infected HeLa cells using 0.1% Triton X-100
(Krokowski and Mostowy, 2016). Lysates were serially diluted and plated on LB agar.
For Pseudomonas infections, bacteria were grown to OD600 �2.5, diluted in DMEM to an MOI of 10 and added to HeLa cells.
Samples were centrifuged at 1000 rpm for 5 min and incubated for 30 min at 37�C and 5% CO2. Cells were washed with PBS
and incubated in 400 mg/ml gentamicin-containing media for 3 h 25 min for fixed and 1 h for time-lapse microscopy.
For Staphylococcus infections, bacteria were grown to OD600 �0.3, washed with PBS and diluted in DMEM to an MOI of 20. Bac-
teria were added to HeLa cells, centrifuged for 5 min at 1000 rpm and incubated for 30 min at 37�C and 5% CO2. Cells were washed
with PBS and incubated in DMEM containing 100 mg/ml gentamicin and 10 mg/ml lysostaphin for 20 min at 37�C. Infected cells were
washed with PBS and incubated for further 35 min in DMEM containing 100 mg/ml gentamicin for time-lapse microscopy.
Fluorescence Microscopy of Infected Cells
Infected HeLa cells were fixed in 4 % paraformaldehyde (PFA) for 15 min at room temperature (RT), washed with PBS and quenched
for 10 min in 0.05 M ammonium chloride at RT. Afterwards cells were permeabilised for 5 min with 0.1% Triton-X-100 at RT and
stained for fluorescence microscopy. For the LC3 antibody, cells were fixed and permeabilised in 100% ice-cold methanol. Incuba-
tion with primary antibodies was performed in PBS for 1 h 30 min at RT and incubation with secondary antibodies and Phalloidin was
performed in PBS for 45 min at RT. Cells were incubated for 10 min in 1 mg / ml DAPI and mounted in aqua polymount mounting me-
dium (Polyscience).
Fixed cells were imaged on a fluorescence-inverted microscope Axiovert 200M (Carl Zeiss) drivenby Volocity software (Parkin Elmer)
(Figures3AandS3B),confocal microscopeLSM710(CarlZeiss)drivenbyZEN2010software(Figure1A),ElyraPS.1 microscopedriven
by ZEN software (Carl Zeiss) (Figures S1F–S1H and 3D) or Axiovert Z1 driven by ZEN Blue 2.3 software (Carl Zeiss) (all remaining Fig-
ures). For time-lapse microscopy, samples were imaged in FluoroBrite medium (Life Technologies) supplied with 5% FCS, 4 mM
L-glutamine and 50 mg/ml gentamicin at the Axiovert Z1 at 37�C and 5% CO2 or at the confocal microscope LSM 710 at 37�C for 3 h.
For microscopy of Shigella FtsZ-GFP in broth, bacteria were grown to exponential phase and FtsZ-GFP production was induced
for further 2 h using 0.1 % L-arabinose. Where indicated, Shigella strains (WT, FtsZ-GFP) were treated with 3 mg / ml FM4-64X for
30 min and / or 1 mg / ml DAPI for 10 min before analysis.
Microscopy images were quantified using Z-stack image series taking 5 to 15 slides every 0.2 – 0.4 mm. Image processing was
performed using Fiji or Icy (http://icy.bioimageanalysis.org) and deconvolution was performed using Huygens deconvolution soft-
ware or ZEN software. Bacterial cell length and width were measured manually using the plugin ‘Coli-inspector’ for FIJI. ICY was
used to generate fluorescence profiles (FIP) using the plugin ‘Intensity Profile’ and to generate 3D images using the plugins ‘Stereo
3D Canvas (VTK)’ and ‘3D Rotation’.
Structured Illumination Microscopy
For fixed SIM, U-2 OS cells (1 x 105) were seeded on high precision glass coverslips (Carl Roth) in 6-well-plates (Thermo Scientific)
and used 48 h later for infection with S. flexneri FtsZ-GFP. After 3 h 40 min of infection, cells were fixed, quenched and immunola-
belled with primary or secondary antibodies in PBS containing 0.1% Triton-X-100 and 5% horse serum. After a second fixation in 4%
PFA for 15 min, cells were imaged in 100 mM beta-mercaptoethylamine pH 7.5. SIM imaging was performed using Plan-Apochromat
63x/1.4 oil DIC M27 objective, in an Elyra PS.1 microscope (Zeiss). Images were acquired using 5 phase shifts and 3 grid rotations
and processed using the ZEN software (2012, version 8.1.6.484, Carl Zeiss). For channel alignment, a multi-coloured bead slide was
imaged using the same image acquisition settings. For single particle analysis (Gray et al., 2016), the septal region and the long axis of
the bacterial cell were manually selected in the FtsZ channel. All bacterial cells were automatically aligned using these two references
and the resulting stacks were averaged to create population representative models.
QUANTIFICATION AND STATISTICAL ANALYSIS
Statistical analysis was performed in Excel (Microsoft) and GraphPad Prism (v6.0, La Jolla, USA). Host cells dying from bacterial load
were excluded from analysis. Unless otherwise indicated, data represent the mean ± standard error of the mean (SEM) from at least
3 independent experiments. Student’s t-test (unpaired, two-tailed), one-way ANOVA or Kruskal-Wallis were used to test for statistical
significance, with p < 0.05 considered as significant. Fold changes were calculated from each independent experiment and the
average ± SEM are given in the text. All statistical details including statistical tests, significance, exact value of n bacterial cells
and definition of centre and dispersion can be found in the figure legends.
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Cell Host & Microbe 24, 866–874.e1–e4, December 12, 2018