Abstract
Coxiella burnetii is an obligate Gram-negative intracellular pathogen
and the etiological agent of Q fever. Successful infection requires a
functional Type IV secretion system, which translocates more than 100
effector proteins into the host cytosol to establish the infection,
restructure the intracellular host environment, and create a
parasitophorous vacuole where the replicating bacteria reside. We used
yeast two-hybrid (Y2H) screening of 33 selected C. burnetii effectors
against whole genome human and murine proteome libraries to generate a
map of potential host-pathogen protein-protein interactions (PPIs). We
detected 273 unique interactions between 20 pathogen and 247 human
proteins, and 157 between 17 pathogen and 137 murine proteins. We used
orthology to combine the data and create a single host-pathogen
interaction network containing 415 unique interactions between 25 C.
burnetii and 363 human proteins. We further performed complementary
pairwise Y2H testing of 43 out of 91 C. burnetii-human interactions
involving five pathogen proteins. We used the combined data to 1)
perform enrichment analyses of target host cellular processes and
pathways, 2) examine effectors with known infection phenotypes, and 3)
infer potential mechanisms of action for four effectors with
uncharacterized functions. The host-pathogen interaction profiles
supported known Coxiella phenotypes, such as adapting cell morphology
through cytoskeletal re-arrangements, protein processing and
trafficking, organelle generation, cholesterol processing, innate
immune modulation, and interactions with the ubiquitin and proteasome
pathways. The generated dataset of PPIs—the largest collection of
unbiased Coxiella host-pathogen interactions to date—represents a rich
source of information with respect to secreted pathogen effector
proteins and their interactions with human host proteins.
Introduction
Coxiella burnetii is a Gram-negative intracellular bacterium,
classified by the Centers for Disease Control and Prevention as a
Category B biothreat agent [[39]1–[40]4]. It is the causative agent of
Q fever, where “Q” is short for “Query” and refers to its initially
unknown etiological origin. The bacterium is widespread in the United
States (U.S.) and highly infectious [[41]5,[42]6], causing disease
manifestations that range from asymptomatic, acute, and chronic, and
have the ability to induce long-term sequelae [[43]7]. Most naturally
occurring infections are transmitted to humans from infected livestock,
resulting in occasional localized outbreaks [[44]8] that represent a
threat to military personnel deployed to areas of endemic infection
[[45]9]. The infection is treatable with antibiotics. However, its high
infection rate makes it a potential bio-warfare agent because no
U.S.-licensed vaccine or specific prophylactic treatment is available.
C. burnetii belongs to the phylum Proteobacteria, which contains a
number of highly pathogenic intracellular bacteria. Although it shares
some features with these species, it creates a uniquely adapted
intracellular environment in the host cell. C. burnetii primarily
infects human alveolar macrophages [[46]10, [47]11], although it can
infect other cell types as well [[48]12].
The infecting bacteria use a series of mechanisms to establish
themselves in the host cell, of which the most characteristic is the
formation of a Coxiella-containing vacuole (CCV) capable of occupying
the bulk of the host cell [[49]13]. The CCV environment is unique in
that it retains the characteristically low pH of a lysosome, an
apparently essential component for optimal C. burnetii growth and
metabolism. The ability to modulate the host response and cellular
environment is a key adaptive aspect of this intracellular lifestyle.
One essential component of this process is the secretion of bacterial
proteins though the CCV membrane into the cytosol of the host cell.
Although C. burnetii has components of Type I and Type II secretion
systems [[50]14,[51]15], the most important secretory pathway is
through the Dot/Icm (defect in organelle trafficking/intracellular
multiplication) Type IV Secretion System (T4SS), which is known to
mediate the translocation of more than 100 bacterial “effector”
proteins [[52]2,[53]16]. The functions of these effectors include
enzymatic activity and regulation of host processes, such as apoptosis
[[54]17], autophagy [[55]18, [56]19], immune responses [[57]20], and
vesicular/protein trafficking [[58]21, [59]22], through host-pathogen
protein-protein interactions (PPIs). Less well understood is the exact
nature of how these effector proteins—either as individual proteins,
protein complexes, or sets of proteins, or in combination with host
proteins—exert their function to establish the infection.
We have previously used pairwise host-pathogen protein interactions
between a select set of putative effector proteins and whole genome
human/murine protein libraries, as determined through yeast two-hybrid
(Y2H) studies, to both identify virulence factors and map out the role
of host-pathogen interactions in Burkholderia mallei and Francisella
tularensis [[60]23–[61]27]. Here, we examined a select set of 33
secreted C. burnetii proteins to identify the putative host protein
targets with which they interact, and used them to shed light on their
possible roles in establishing and maintaining Coxiella infection.
The interaction data identified targeted host pathways involved in
diverse sets of cellular functions, such as protein processing in the
endoplasmic reticulum (ER), the innate immune response, and vacuole or
organelle trafficking. We also linked individual effector-host
interactions to host proteins involved in specific cellular tasks, such
as cholesterol processing and cell cycle propagation at the centromere.
The bulk of the interaction data was compatible with the notion that
the bacteria interfere with host cell physiology at multiple
intervention points, broadly corresponding to the known cellular
phenotypes associated with the intracellular life-style of Coxiella.
Materials and methods
Selection of C. burnetii effector proteins for screening
We searched the literature to select C. burnetii effectors for Y2H
screening according to the following criteria: 1) the presence of the
gene in the pathogenic strains Nine Mile I RSA493, Heinzerling RSA331,
Dugway 5J108-111, G Q212, and K Q154; 2) evidence that the gene is
controlled by the PmrA-regulated C. burnetii T4SS stress response
[[62]28]; and 3) evidence that the protein is secreted
[[63]16,[64]29–[65]31]. We obtained all Coxiella genomic information
from the Pathosystems Resource Integration Center database [[66]32].
High-throughput Y2H screens to identify host-C. burnetii PPIs
Cloning of C. burnetii effector genes
We first cloned the C. burnetii genes into Gateway entry clones, and
then the Y2H expression vectors to perform high-throughput Y2H
screening against the human and mouse proteomes. To amplify the C.
burnetii genes by PCR, we used gene-specific primers that incorporated
forward and reverse Gateway recombination cloning sequences attB1
(5’-GGGGACAAGTTTGTACAAAAAAGCAGGCTTC-3’) and attB2
(5’-GGGGACCACTTTGTACAAGAAAGCTGGGTC-3’), respectively. We used the
genomic DNA of C. burnetii RSA331 to amplify the target genes. The
PCR-amplified open reading frames (ORFs) were subsequently cloned into
a gateway entry vector (pDONR/zeo™), as recommended by the BP Clonase™
II enzyme provider (Thermo Fisher Scientific, Waltham, MA). We used
Sanger sequencing to validate the cloned ORFs in the entry vectors. We
sub-cloned the ORFs from the entry vector into yeast Y2H DNA-binding
domain vectors (bait clones), pGBGT7g (as N-terminal fusion) and pGBACg
(C-terminal fusion) [[67]33], using Gateway LR reactions (Thermo Fisher
Scientific). Subsequently, we transferred the Y2H bait clones into the
haploid yeast strain AH109 (MAT-α), as previously described [[68]34].
Auto-activation test
Before Y2H library screening, we examined the C. burnetii Y2H bait
clones for auto-activation, i.e., detectable bait-dependent reporter
gene activation in the absence of any interacting protein. Because the
yeast strains used in this study contained the HIS3 reporter gene,
auto-activation could be titrated by varying the concentration of
3-amino-1,2,4-triazole (3-AT), a competitive inhibitor of HIS3. We
inspected the C. burnetii bait clones for auto-activation on synthetic
yeast medium plates containing different concentrations of 3-AT. We
used the lowest concentration of 3-AT that suppressed growth for
auto-activation of the bait because it avoided background growth while
still detecting true interactions.
Y2H library screening
We used a haploid yeast strain expressing each C. burnetii protein as
bait for the interaction screening with human and murine normalized
universal cDNA libraries (catalog nos. 630480 and 630482, respectively;
Clontech Laboratories, Mountain View, CA). The bait and prey yeast
culture was grown and mixed at a 1:1 ratio and plated on yeast extract,
peptone, dextrose, and adenine (YEPDA) agar plates. We incubated the
YEPDA agar plates at 30°C for 6 h or overnight at room temperature.
During this process, both prey and bait plasmids were combined in
diploid yeast cells by yeast mating. Yeast cells from the mating plates
(YEPDA agar) were collected and transferred onto interaction-selection
plates with yeast-synthetic medium (lacking tryptophan, leucine, and
histidine) containing predefined concentrations of 3-AT, and the plates
were incubated at 30°C for 4 to 6 days. We identified samples that
showed colony growth on the interaction-selection plates but not on the
control plates (bait mated to empty prey vector) as two-hybrid positive
yeast clones. We manually selected positive yeast colonies and
subjected them to yeast colony PCR followed by DNA sequencing to
determine the interacting proteins [[69]34]. We performed the Y2H
screens twice for each effector and combined the data from both
screens. However, we discarded single hits, i.e., interactions based on
only one positive yeast colony.
All bait proteins were mapped to their corresponding C. burnetii locus
tags, and all prey proteins were mapped to their official gene symbols
as defined in the HUGO Gene Nomenclature Committee database [[70]35] or
Mouse Genome Informatics database [[71]36]. When identified prey
proteins could not be mapped to protein-coding sequences, we removed
the interactions involving them. Moreover, we removed protein
interactions between C. burnetii and “sticky” host proteins known to be
indiscriminate binders as listed in [72]S1 Table.
Complementary pairwise Y2H testing of human-C. burnetii high-throughput
protein interactions
To test C. burnetii–human protein interactions identified by the Y2H
library screening, we selected 94 pairs (involving 82 human proteins)
for pairwise Y2H assay testing. We randomly selected these
effector-host interactions among four relatively uncharacterized C.
burnetii effector proteins (CBU0794, CBU0881, CBU1724, and CBU2078) and
the plasmid protein CBUA0014 based on their large number of observed
interactions in the high-throughput screens. We constructed the human
prey Y2H clones by sub-cloning the ORFs from the Human ORFeome
collection [[73]37] into pGADT7g and pGADCg Y2H prey vectors. We
successfully cloned 79 of the 82 human ORFs into Y2H prey vectors. We
transferred the Y2H prey clones into yeast strain Y187 (MAT-a), and
tested 81 of the 94 selected protein interactions, using the same
procedure as outlined above to identify two-hybrid positive
interactions in this screen.
Creation of expanded human-C. burnetii protein interaction network
We extracted human-murine orthologs from the NCBI HomoloGene database
of homologs ([74]www.ncbi.nlm.nih.gov/homologene) [[75]38] and used
them to identify orthology-based human-C. burnetii protein interactions
[[76]24]. We added the predicted orthology-based protein interactions
to the human-C. burnetii Y2H data to create an expanded set of C.
burnetii-human protein interactions. We used both human and murine
libraries to provide better coverage of interactions with pooling of
data allowing us to do a more robust statistical analysis. The data at
hand do not support a statistical analysis of either species alone as
meaningful. The provided data in the Supplementary Materials provide
the species-distinct human and murine interactions.
Gene Ontology and pathway enrichment analysis of host genes
We performed standard enrichment analyses for C. burnetii-interacting
host proteins as described previously [[77]26]. Briefly, the enrichment
of Gene Ontology (GO) [[78]39] and Kyoto Encyclopedia of Genes and
Genomes (KEGG) [[79]40] pathways was calculated in R by using the
Bioconductor packages BioMart [[80]41] and KEGGgraph [[81]42]. The
background set of proteins for the GO analysis involved all constituent
proteins from the human PPI network, and we used the complete GO tree
annotation, excluding the root and the top two levels of GO terms. The
background set of proteins for the KEGG enrichment analysis involved
human proteins available in KEGGgraph that participated in at least one
KEGG pathway. We used the Benjamini-Hochberg method [[82]43] to correct
all obtained p-values (p[raw]) to adjusted p-values (p[adj]).
Results
High-throughput Y2H screening of host-pathogen interactions
We successfully cloned and prepared 33 C. burnetii effectors, and
tested them in Y2H assays against both human and murine whole proteome
libraries. [83]Table 1 summarizes the available effector information,
number of interacting host-pathogen proteins of each effector protein
with either human or murine proteins, and protein interactions common
to the two libraries. Of the tested pathogen proteins, 25 (76%) tested
positive for interactions with either human or murine proteins, 12
(36%) showed interactions with both hosts, and eight failed to show any
positive hits in our screens. The protein interaction data consisted of
273 unique interactions between 20 C. burnetii and 247 human proteins,
and 157 between 17 C. burnetii and 137 murine proteins. The majority of
C. burnetii proteins interacted with unique host proteins, i.e., 228
(92%) human proteins and 123 (90%) murine proteins interacted with a
single C. burnetii protein. C. burnetii proteins that interacted with
multiple proteins from either host also tended to interact with the
other host. Of the nine pathogen effectors with more than 10
interacting host proteins, seven interacted with both hosts (7/9 or
78%). Of the remaining 16 that interacted with 10 or fewer host
proteins, only five interacted with both hosts (5/16 or 31%). We
observed far fewer instances of individual host-pathogen PPIs in both
libraries; the Y2H screens identified five conserved PPIs between the
human and murine data sets, i.e., interactions in which human proteins
interacted with the same C. burnetii proteins as their murine
orthologs. These differences could be due to low quantities of a prey
gene in one of the two cDNA libraries or to non-exhaustive sampling of
host-prey and pathogen-bait protein interactions.
Table 1. List of proteins evaluated in high-throughput yeast two-hybrid assay
and number of host protein-protein interactions.
Locus ID Name Description and Notes PmrA/ Secreted Protein-protein
interactions
Human Murine Shared
CBU0041 coxCC1, cirA - y/- 3 6 -
CBU0077 - Hypothetical membrane spanning protein; late expression y/y 3
3 -
CBU0175 coxK1 Ser/Thr protein kinase protein -/y 9 - -
CBU0295 - Uncharacterized -/y 1 3 -
CBU0388 cetCb2 Uncharacterized -/y 1 - -
CBU0410 coxCC3 Hypothetical membrane spanning protein y/y - - -
CBU0425 cirB Uncharacterized; no intracellular replication defect y/- -
- -
CBU0447 ankF Ankyrin repeat protein; requires chaperone icmS -/y 1 - -
CBU0626 cetCb3 Uncharacterized -/y - - -
CBU0781 ankG Putative ankyrin repeat protein; confirmed anti-apoptotic,
requires chaperone icmS -/- 33 7 -
CBU0794 coxCC4 Uncharacterized; trafficking to host-cell nucleus -/y 17
5 -
CBU0881 coxCC5 Hypothetical cytosolic protein; RSA493, Q212, and
Hentzerling only -/y 59 16 -
CBU0885 - Hypothetical cytosolic protein -/y 2 - -
CBU0937 coxDFB1, cirC UPF0422 protein; no intracellular replication
defect -/y 26 - -
CBU1217 coxU2 Hypothetical membrane spanning protein -/y - - -
CBU1314 coxCC6 Hypothetical cytosolic protein; trafficking to host-cell
nucleus -/y 3 2 -
CBU1379a coxK2 Uncharacterized -/y 7 - -
CBU1425 coxDFb4 17 kDa common-antigen; surface antigen -/y - - -
CBU1457 coxTPR1 Tetratricopeptide repeat family protein -/y 9 24 -
CBU1460 coxCC7, cig44 Uncharacterized y/y - 5 -
CBU1524 caeA Anti-apoptotic -/- 35 - -
CBU1543 coxCC10, cig49 Uncharacterized y/y - 1 -
CBU1556 coxCC11, cvpC Hypothetical membrane spanning protein; no
intracellular replication defect -/y 1 3 -
CBU1569 coxCC12 Hypothetical cytosolic protein; no intracellular
replication defect -/y - - -
CBU1686 cetCb5 Uncharacterized -/y - - -
CBU1724 cetCb6 Uncharacterized -/y 17 37 2
CBU1751 coxDFB5, cig57 Vesicular trafficking y/y - 2 -
CBU1769 coxH3 Alpha/beta hydrolase -/y 5 - -
CBU1823 coxH4, cig61, icaA Uncharacterized y/y - - -
CBU1825 coxDFB6 Uncharacterized -/y - 5 -
CBU2056 - Uncharacterized -/y - 4 -
CBU2078 coxFIC1 Fic family protein -/y 15 27 1
CBUA0014 coxU3 Uncharacterized; Hentzerling and RSA493 only y/y 26 7 1
[84]Open in a new tab
The binary interactions for all human and orthologous murine proteins
are detailed in [85]S2 Table.
Although Weber et al. reported that CBU0041 and CBU0885 were toxic to
yeast when their expression was strongly induced in yeast [[86]16],
these proteins were not toxic in our Y2H screening using Saccharomyces
cerevisiae AH109 and Y187 strains. The yeast Y2H vectors we used have a
“2-micron” (2μ) origin where an endogenous (ADH1) promoter–resulting in
a low-level expression of the recombinant protein–drives the protein
expression and, hence, resulting in a lack of toxicity in our
experiments.
The Y2H screens failed to capture the previously identified interaction
between AnkG (CBU0881) and p32 [[87]17]. A Y2H failure to detect (false
negative) may have multiple origins, such as lack of exhaustive
screening, true absence under the current set of experimental
conditions, or deficiency of the target protein in the library (p32 was
not detected in any other interaction in our screens). Currently, we
are not able to determine the definitive cause of this absence.
In the following sections, we used the generated data to broadly
characterize possible host-pathogen interaction phenotypes by
performing overall analyses that take into account sets of observed and
pooled interactions. These analyses do not allow us to individually
account for each protein interaction, because individual
protein-protein interactions range from strong binding events to more
ephemeral signaling events and, as such, are not fully characterized or
distinguishable by the deployed Y2H technique.
Orthology-derived high-throughput human-C. burnetii protein interaction
network
The set of 25 interacting proteins represents a large fraction of
potentially important effectors with a role in establishing the
Coxiella infection. The total set of all interactions represents an
interaction profile of multiple pathogen-targeted processes used to
establish and maintain the bacterial infection. To characterize this
interaction profile, we merged the human-C. burnetii experimental and
orthologous data sets to create an expanded set of human-C. burnetii
pairwise PPIs consisting of 415 unique interactions between 25 C.
burnetii and 363 human proteins. [88]Fig 1 graphically shows the
resulting host-pathogen protein interaction network, with all
interactions provided in [89]S2 Table.
Fig 1. Yeast two-hybrid (Y2H) host-pathogen protein-protein interactions.
[90]Fig 1
[91]Open in a new tab
Using Y2H screens against whole human and murine proteome libraries, we
detected 273 unique interactions between 20 Coxiella burnetii and 247
human proteins and 157 unique interactions between 17 C. burnetii and
137 murine proteins. We used these data to construct a single
host-pathogen protein interaction network, based on murine/human
orthology, containing 415 unique interactions between 25 C. burnetii
and 363 human proteins. Green nodes represent C. burnetii proteins,
whereas pink and red nodes represent host proteins. Twelve C. burnetii
proteins interacted with both hosts, three of which participated in
conserved interactions (i.e., they interacted with both human proteins
and their murine orthologs; shown as red nodes and connected with thick
grey edges).
Protein domain analysis of targeted host proteins
We investigated the presence of conserved protein domains in host genes
for nine C. burnetii effectors that interacted with 10 or more host
proteins. Overall, 19 statistically over-represented conserved domains
were identified among the effector-interacting host proteins. [92]Table
2 shows that each effector has at least one statistically significant
domain over-represented in the protein set compared to all host
proteins, with over-represented host-domains typically present in 15%
or less of the targeted host proteins for each effector. This indicated
that no single domain dominated the effector-host protein binding. The
major exception to this was the calcium-binding EGF-like domain
(EGF_CA), which appeared in 26 host proteins targeted by CBUA0014 and
in 12 targeted by CBU0781. This domain is present in a large number of
membrane-bound proteins as well as extracellular proteins and is
essential for numerous protein-protein interactions [[93]44].
Furthermore, CBUA0014 also targeted two host domains—the PDZ_signaling
domain among 10 host proteins, and the TGF-beta binding (TB) domain
among nine host proteins. These domains are commonly identified as
being part of multiple host protein-protein interaction events in
organizing signaling complexes at cellular membranes that regulate cell
proliferation, differentiation, and growth.
Table 2. Conserved domains among the Coxiella burnetii-interacting host
genes.
Gene ID Domain ID[94]^1 Domain Summary Description N[d][95]^2
N[h][96]^3 N[db][97]^4 p[raw][98]^5 p[adj][99]^6
CBU0781 zf-BED Zinc finger DNA-binding domain in
chromatin-boundary-element-binding proteins and transposases 4 40 5 3.0
10^−9 1.3 10^−8
TB TGF-beta binding (TB) domain; cysteine-rich repeat found in
TGF-binding protein and fibrillin 3 40 38 1.1 10^−4 1.3 10^−4
EGF_CA Calcium-binding EGF-like domain; present in a large number of
membrane-bound proteins, important in protein-protein interactions 12
40 514 9.6 10^−9 3.1 10^−8
CBU0794 zf-H2C2_2 Zinc-finger double domain 3 22 490 2.4 10^−2 2.6
10^−2
zf-C2H2 Classic zinc-finger domain, associated with DNA- or protein-
binding structural motifs, such as in eukaryotic transcription factors
3 22 234 3.4 10^−3 3.9 10^−3
CBU0881 BRCT Breast cancer suppression protein (BRAC1) carboxy-terminal
domain found predominantly in proteins involved in cell cycle
checkpoint functions responsive to DNA damage 6 75 29 7.0 10^−9 2.6
10^−8
zf-FCS Zinc-finger domain that can function as a transcriptional
trans-activator 8 75 26 1.5 10^−12 9.5 10^−12
WEPRS_RNA Domain involved in both protein-RNA interactions (by binding
tRNA) and protein-protein interactions 3 75 4 2.3 10^−6 3.2 10^−6
TSP_3 Thrombospondin type 3 repeat, containing short aspartate-rich
repeats, which binds to calcium ions 3 75 14 4.3 10^−5 5.5 10^−6
Cupredoxin Domains that contain type I copper centers and are involved
in inter-molecular electron transfer reactions 3 75 7 7.7 10^−6 1.1
10^−5
CBU0937 Calpain_inhib Domain found in protein inhibitors of calpains,
i.e., [100]calcium-dependent, non-[101]lysosomal [102]cysteine
[103]proteases 3 26 3 6.3 10^−8 1.8 10^−7
CBU1457 Peptidase_M14NE-CP-C_like C-terminal domain of M14 N/E
carboxypeptidase; putative folding, regulation, or interaction domain 3
33 12 2.8 10^−6 4.5 10^−6
Int_alpha Integrin alpha (beta-propeller repeats); found in adhesion
molecules that mediate cell-extracellular matrix and cell-cell
interactions 5 33 74 4.7 10^−7 1.1 10^−6
Collagen Collagen triple helix repeat; found in structural proteins
involved in formation of connective tissue structure 6 33 234 8.0 10^−7
1.1 10^−6
RyR Ryanodine receptor domain with unknown function 4 54 12 1.3 10^−7
3.5 10^−7
CBU2078 Int_alpha Integrin alpha (beta-propeller repeats); found in
adhesion molecules that mediate cell-extracellular matrix and cell-cell
interactions 5 42 74 1.4 10^−6 2.8 10^−7
CBUA0014 vWFA von Willebrand factor type A (vWA) domain, involved in
basal membrane formation, cell migration, cell differentiation,
adhesion, hemostasis, signaling, chromosomal stability, malignant
transformation, and immune defenses 4 33 50 3.5 10^−6 5.4 10^−6
PDZ_signaling PDZ domain responsible for specific protein-protein
interactions 10 33 197 2.3 10^−11 1.0 10^−10
TB TGF-beta binding (TB) domain; cysteine-rich repeat found in
TGF-binding protein and fibrillin 9 33 38 6.1 10^−16 7.9 10^−15
PDZ PDZ domain that may play a role in scaffolding supramolecular
complexes and in diverse signaling proteins 3 33 68 3.2 10^−4 3.8 10^−3
FF Involved in protein-protein interactions and in the regulation of
actin cytoskeleton dynamics 3 33 10 1.7 10^−6 3.2 10^−6
EGF_CA Calcium-binding EGF-like domain; present in a large number of
membrane-bound proteins, important in protein-protein interactions 26
33 514 2.6 10^−25 6.7 10^−24
[104]Open in a new tab
^1We performed domain identification, using NCBI CD Search
([105]https://www.ncbi.nlm.nih.gov/Structure/bwrpsb/bwrpsb.cgi?) with
default parameter settings for nine Coxiella burnetii (CB) genes that
interacted with at least 10 host genes.
^2N[d]: number of occurrences of the domain among the targeted
proteins; only domains that occurred at least three times in the host
genes were analyzed.
^3N[h]: number of host genes that have the domain.
^4N[db]: number of occurrences of the domain in the background set. All
representative human proteins that have been manually reviewed were
downloaded from UniProt ([106]http://www.uniprot.org/). Among the
20,201 genes, we used the 19,036 genes containing domains (NCBI CD
Search) as the background set for the statistical analyses.
^5Original p-value from Fisher’s exact test.
^6Adjusted p-value using the Benjamini–Hochberg correction procedure.
Enrichment analysis of high-throughput Y2H host-pathogen interactions
The relatively large number of known effectors studied and host-protein
interactions retrieved allowed us to analyze the combined interaction
data as an “effector profile” of coordinated interactions to identify a
potential repertoire of host functions targeted by C. burnetii. This
approach was intended to generate broad hypotheses on common underlying
effector mechanisms. Hence, we used all available high-throughput Y2H
data to identify pathways, biological processes, and cellular locations
associated with the targeted host proteins.
[107]Table 3 shows the enriched KEGG pathways targeted by the
effectors, using the orthology-derived high-throughput human-C.
burnetii protein interaction network. This analysis indicates that the
bacterial effectors have a preferential association with protein
processing in the endoplasmic reticulum (ER), focal adhesion, and
interference with protein degradation via the ubiquitin-proteasome
pathway. The targeted host proteins affect glycolipid metabolism by
interacting with host metabolism pathways involving small-branched
hydrophobic amino acids. Finally, the effectors targeted host proteins
involved in signaling via kinase regulation in the TGF-β and PI3K-AKT
pathways.
Table 3. Enrichment of KEGG terms for human proteins interacting with C.
burnetii.
Pathway description Cb-targeted host proteins KEGG proteins p[raw]
p[adj]
Protein processing in endoplasmic reticulum 11 85 2.8 10^−6 3.3 10^−4
TGF-β signaling pathway 7 43 4.6 10^−5 3.5 10^−3
Focal adhesion 7 60 4.0 10^−4 0.02
Proteasome 6 43 4.0 10^−4 0.02
Valine, leucine, and isoleucine degradation 5 29 4.6 10^−4 0.02
Glycerolipid metabolism 6 16 2.6 10^−4 0.02
PI3K-AKT signaling pathway 8 82 5.3 10^−4 0.02
[108]Open in a new tab
Cb, Coxiella burnetii; KEGG, Kyoto Encyclopedia of Genes and Genomes;
p[raw], original p-value; p[adj], p-value adjusted according to the
Benjamini-Hochberg multiple test correction [[109]43].
[110]Table 4 shows the enriched GO Biological Process terms associated
with the host proteins identified by the Y2H screen of the 25
interacting bacterial proteins. These terms are largely compatible with
the KEGG analysis in [111]Table 3, and highlight specific processes
associated with metabolism and ubiquitin processing. The GO analysis
also highlights immune response modulation processes involving immune
receptor signaling and antigen presentation processes. Additionally
targeted host functionalities include posttranscriptional regulation of
gene expression.
Table 4. Enrichment of GO Biological Process terms for human proteins
interacting with C. burnetii.
Term description Cb-targeted host proteins GO proteins p[raw] p[adj]
Metabolism
Nitrogen compound metabolic process 141 5759 4.2 10^−4 0.10
Regulation of cellular amide metabolic process 16 311 4.5 10^−4 0.10
Immune response modulation
Fc-ε receptor signaling pathway 11 118 2.1 10^−5 0.06
Stimulatory C-type lectin receptor signaling pathway 9 92 8.1 10^−5
0.09
Antigen processing and presentation of exogenous antigen 11 156 2.6
10^−4 0.10
Ubiquitin processing
Positive regulation of ubiquitin-protease ligase activity 7 67 3.3
10^−4 0.10
Regulation of protein ubiquitination 13 229 6.2 10^−4 0.11
Other
Posttranscriptional regulation of gene expression 21 392 3.3 10^−5 0.06
Regulation of translation 15 283 5.0 10^−4 0.11
[112]Open in a new tab
Cb, Coxiella burnetii; GO, Gene Ontology; p[raw], original p-value;
p[adj], adjusted p-value according to the Benjamini-Hochberg multiple
test correction [[113]43].
[114]Table 5 shows the cellular localization of the host proteins.
Overall, they were located in multiple cellular compartments in the
cytoplasm, membrane-bound organelles, and nucleus. We could not
identify any specific sub-nuclear location or particular intracellular
vesicle for the host-targeted proteins, suggesting that they are
present at multiple sites and potentially involved in multiple
processes. The large number of host targets associated with
extracellular exosomes points to processes associated with vesicles in
general, as well as those with the potential to interact with the
content of the exosomes as a means to influence the host immune
response [[115]45]. The locations associated with focal adhesions,
adherence junctions, and microtubule cytoskeletons point to a
preference for influencing cell signaling and vacuolar re-arrangements
associated with the infection. The association of targeted proteins
with the ribonucleoprotein complex is consistent with a potential role
for effectors in interfering with host protein processing in the ER.
Additionally, a number of targeted proteins were located in the
mitochondrial matrix.
Table 5. Enrichment of GO Cellular Component terms for human proteins
interacting with C. burnetii.
Term description Cb-targeted host proteins GO proteins p[raw] p[adj]
Overall location
Cytoplasm 221 9158 4.3∙10^−10 3.0∙10^−8
Membrane-bound organelle 238 10322 2.1∙10^−9 1.1∙10^−7
Nucleus 147 5873 6.1∙10^−6 2.0∙10^−4
Specific location
Extracellular exosome 88 2427 2.0∙10^−10 1.8∙10^−8
Vesicle 106 3245 5.8∙10^−10 3.6∙10^−8
Ribonucleoprotein complex 24 603 4.5∙10^−4 8.2∙10^−3
Focal adhesion 15 334 1.6∙10^−3 0.02
Mitochondrial matrix 15 346 2.3∙10^−3 0.03
Adherence junction 16 400 3.8∙10^−4 0.05
ESCRT complex 11 218 4.2∙10^−4 0.06
Microtubule organizing center 19 534 5.9∙10^−3 0.06
ER-Golgi compartment 5 82 0.02 0.13
[116]Open in a new tab
Cb, Coxiella burnetii; ER, endoplasmic reticulum; ESCRT, endosomal
sorting complexes required for transport; GO, Gene Ontology; p[raw],
original p-value; p[adj], adjusted p-value according to the
Benjamini-Hochberg multiple test correction [[117]43].
Emerging interaction patterns from patterns of host interactions
Coxiella has the capability to successfully infect different eukaryotic
hosts and cell types by using sets of translocated T4SS effector
proteins. This implies that the interactions may be non-specific yet
concerted to establish the biological host phenotype amenable to
pathogen survival. The mechanisms by which Coxiella manipulates host
cell processes are largely unknown, but effector-targeted host proteins
can provide a mechanistic understanding of pathogenesis.
Our pathway analysis identified a number of metabolic host target
proteins involved in small hydrophobic amino acid degradation and
glycerolipid metabolism ([118]Table 3). Given that metabolism has not
been considered as a host target process of T4SS effectors before
[[119]46], this suggests novel mechanisms involving energy metabolism
(triglycerides are primarily used for energy storage) and essential
amino acids (valine, leucine, and isoleucine), which may be related to
preventing host cell autophagy by blocking a host-defensive starvation
response [[120]47].
The ability of C. burnetii to orchestrate physiological processes of
host-cell organelles and interfere with host protein processing was
evident from the large number of protein binding events that
preferentially could take place in the ER and Golgi (Tables
[121]3–[122]5). [123]Fig 2 shows the intervention points of nine
screened Coxiella effectors affecting human-host protein processing in
the ER. Previous studies have noted the importance and occurrence of
pathogen interactions with the ER as a critical component of lipid
metabolism, protein synthesis, protein trafficking, and cellular stress
responses [[124]48, [125]49]. [126]Fig 2 illustrates how both a single
effector (CBU0794) interacted with multiple host proteins as well as
multiple pathogen proteins targeting individual host proteins (Hsp40
and ERManI). The coordinated interactions affected processes, such as
protein export, COPII-mediated vesicle formation, initiation of
apoptosis, and ER-assisted degradation, via the ubiquitin-proteasome
system. The recently noted interactions between the CCV and the ER,
which involve the host protein oxysterol-binding protein homologue
ORP1L and RAS oncogene RAB7A [[127]49], were partly captured in our
data with CBU0794 interacting with the oxysterol binding protein
OSBPL1A.
Fig 2. Coxiella interactions in the endoplasmic reticulum protein-processing
pathway.
[128]Fig 2
[129]Open in a new tab
The interacting host proteins are highlighted in red text and the
pathogen proteins are superimposed as named yellow circles and located
close to their interacting host partners. Overlaying the interacting C.
burnetii proteins onto their human partners in Kyoto Encyclopedia of
Genes and Genomes (KEGG) pathways illustrates intervention points of
nine screened Coxiella effectors that could affect human-host protein
processing in the endoplasmic reticulum (ER). Pathogen proteins can
multiply their effect by interacting with multiple host proteins or
focus their effect by using different pathogen proteins to target the
same host protein. The potential effect of these interactions could
influence multiple processes, such as protein export, COPII-mediated
vesicle formation, initiation of apoptosis, and ER-assisted protein
degradation. In this pathway representation, CBUA0014 interacts with
Hsp40 and Skp1; CBU1379a with BiP; CirA with PERK; CirC with ERManI;
CBU0794 with Calpain and Sec23/24; CBU1724 with Cul1; and CBU1457 with
Cul1. The underlying network graph is reprinted from KEGG [[130]40]
under a CC BY license, with permission from the Kanehisa Laboratories,
original copyright 2016.
The summaries of host protein interactions in Tables [131]3–[132]5
implicated multiple coupled host pathways involving focal adhesion,
immune signaling and response (primarily via ubiquitin-proteasome
degradation), and changes in cell morphology. The main host targets in
the focal adhesion pathway involve MAPK signaling pathways regulating
cell survival and the ability to modulate the actin cytoskeleton and
cell morphology [[133]50–[134]54]. Kinase interactions involved CBU1724
binding with MAPK10 to modulate cellular stress responses. The
remaining effectors targeting the focal adhesion pathway were linked to
proteins that regulate actin cytoskeletal remodeling of cell morphology
and cell-cell or cell-matrix interactions. The ability to regulate or
modulate actin cytoskeleton remodeling in altering cell morphology is
also linked to interference in the transitions between phases of the
cell cycle, with the polarization state of alveolar macrophages
influencing the susceptibility of the host cells to infection
[[135]55]. C. burnetii interactions at centrosome microtubules could
serve to regulate cell cycle progression by interfering with or
altering spindle assembly and, thereby, changing cell polarity. The
host targets for these interactions include both regulatory elements,
such as ROCK1 and RBL2, as well as the actin-binding protein ANLN.
Pathogen-host interactions that interfered with different components of
the immune system involved both a signaling component directly
targeting the Fc receptor (FCER1G). Although antibody-mediated immunity
to C. burnetii is thought to be Fc receptor independent [[136]56], the
ability to directly bind to the receptor may have cascading effects
interfering with phagocytosis and cytokine generation. The
ubiquitin-proteasome system was affected by both ubiquitin-ligase
complex interactions as well as by numerous proteasome sub-unit
interactions involving multiple C. burnetii proteins. Modulation of the
ubiquitin-proteasome pathway is a feature of the strategy utilized by
the closely related pathogen Legionella pneumophila [[137]57, [138]58],
which co-opts the host protein degradation system to temporally
regulate bacterial effectors in the host cell.
The preferential cellular locations of targeted host proteins
([139]Table 5) also point to important bacterial mechanisms related to
endosomal trafficking, vacuole creation, and exosome function
[[140]45,[141]59,[142]60]. They indicated that a large number of
pathogen targets associated with extracellular host exosomes form a
broad group of C. burnetii-targeted proteins; almost 30% of all protein
interactions could be linked to exosomes. Although the targeted host
proteins are involved in numerous physiological functions, their main
roles are in proteolysis via proteasome interactions, cytoskeletal
arrangement via actin regulation, chaperone activity through heat-shock
proteins, and oxidative stress responses via thioredoxin interactions.
The main function of extracellular exosomes is to enable intercellular
host communication, primarily as carriers of immune signals during
pathogen infections. For example, Salmonella-infected host cells
secrete exosomes enriched in bacterial lipopolysaccharides [[143]61].
The potential ability of C. burnetii to interfere with this process is
a novel aspect of the immune evasion by this pathogen.
Proteins linked to endosomal sorting complexes required for transport
(ESCRT) also function in vesicle budding, a process used by the
uninfected host cell to control membrane abscission during cytokinesis.
Intracellular vacuolar pathogens, such as Salmonella, Legionella, and
Coxiella, must be able to influence these key host processes to
establish their specialized intracellular environments. The interaction
set targeting the ESCRT involved 7 pathogen proteins and 11 host
proteins associated with 17 total host-pathogen interactions. Of
special note is the ER to Golgi protein trafficking host protein
TRAPPC8 [[144]62], which potentially interacts with four different C.
burnetii effectors; ubiquitin peptidase USP8, which regulates endosome
morphology and protein transport [[145]63], and NPC2, which is involved
in cholesterol trafficking [[146]64].
The identification of the mitochondrial matrix as a host location
targeted by C. burnetii effectors implicated multiple processes that
may lead to a more complex mitochondrial phenotype than just inhibition
of apoptosis [[147]65–[148]67]. Of the 16 host-pathogen protein
interactions among 14 host proteins and 11 C. burnetii proteins, 31%
were linked to protein synthesis within mitochondria, 19% to fatty acid
beta-oxidation, with the rest involving different enzymatic catabolic
functions.
The presence of multiple host targets in different pathways points to a
possible higher biological or casual organization of bacterial effector
interactions. [149]Fig 3 shows the interconnected nature of
Coxiella-targeted host pathways according to the number of
pathogen-interacting host proteins present in human KEGG pathways. We
have broadly arranged and grouped these pathways to highlight RNA
processing, protein handling, macromolecular degradation, cellular
signaling (including immune-related signaling), and metabolism. Pathway
intersections (crosstalk) are indicated by arrows and highlight the
potential of effector proteins to affect multiple cellular processes of
the host. Although pathway enrichment analysis highlights the presence
of multiple targets, each individual interaction could also be critical
to the function of the pathway or have physiologically important
downstream effects. The biological assumption underlying pathway
enrichment analysis is that by affecting multiple targets in a pathway,
there is a higher chance that the function of a pathway may be altered.
Hence, a bacterium that has become successful at infecting hosts is
assumed to have developed a higher propensity to affect multiple
proteins in that pathway. Because this may not always be the case, the
interpretation of the interaction data should also consider the overall
broader set of potentially affected pathways as well as individual sets
of effector host-pathogen interactions. The pathway mapping in [150]Fig
3 links major immune and stress signaling pathways to 1) cellular
remodeling pathways, 2) different lytic vesicles, proteolysis, and
programmed cell death, and 3) metabolic pathways involved in amino acid
degradation and energy production.
Fig 3. Host pathways targeted by Coxiella.
[151]Fig 3
[152]Open in a new tab
C. burnetii-interacting host proteins are present in interconnected
Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways with the
potential to affect multiple cellular processes of the host. The
pathways are grouped into five major categories: RNA processing,
protein processing, degradation pathways, signaling (including
signaling events related to the immune response), and metabolism. The
size of a star indicates the number of targeted host proteins in each
pathway. ECM, extracellular matrix; ER, endoplasmic reticulum; ErbB,
erythroblastic leukemia viral oncogene; ESCRT, endosomal sorting
complexes required for transport; MAPK, mitogen-activated protein
kinase; NOD, nucleotide-binding oligomerization domain; PIK3,
phosphatidylinositol-3-kinases; TCA, tricarboxylic acid; TGF,
transforming growth factor.
The aggregate information derived from all host-pathogen interactions
represents a spatial and temporal average of these interactions that do
not capture infection progression or maintenance per se. What emerges
from the interaction profile is a broad pattern of host process
interference, which is commensurate with known Coxiella/Legionella
infections and strongly emphasizes the ability to affect host organelle
creation, endosomal trafficking, and organelle interactions with the
parasitophorous vacuole [[153]68–[154]72].
Using Y2H interactions to characterize individual C. burnetii effector
function
We used the high-throughput Y2H interactions to identify processes and
pathways with a high probability of being affected during the
infection. The underlying assumption of this analysis—that multiple
protein interactions exert a coordinated effect to re-direct host
processes—is based partly on the observation that the bacterium is able
to non-specifically infect multiple hosts and cell types and partly on
the finding that a large number of effectors are secreted into the host
cell. Thus, although some individual interactions may be incorrect, the
broader integration patterns of coordinated action should still be
evident in these analyses. Conversely, we also used these interactions
in conjunction with a smaller pairwise test set to better characterize
a set of four effectors for which evidence on their functional
significance is lacking.
Complementary pairwise Y2H testing
We carried out high-throughput pathogen-host protein interaction
screening using C. burnetii ORFs and human and murine random cDNA
libraries. In order to assess the feasibility of using the
well-characterized human ORFeome resources to validate the
high-throughput Y2H interaction, we selected as subset of C.
burnetii-human PPIs and tested them using pairwise Y2H screening.
Herein, the Y2H prey clones were generated by cloning the human ORFeome
clones to pGADT7g [[155]37], a modified Gateway technology-compatible
Y2H prey vector. This prey vector differs in the linker amino acid
sequences encoded between the activation domain and the ORFs.
Furthermore, the human ORFeome clones do not contain an endogenous stop
codon; hence, they encode additional peptide sequences at the
C-terminal ends of the ORFs, which may affect their interaction
patterns. Previous studies have shown that such differences in either
bait or prey vectors produce significantly different interaction data
[[156]33, [157]73]. Our expectation was to reproduce approximately 50%
of interactions in the pairwise Y2H screening, as minor variations in
two-hybrid vectors detect markedly different subsets of interactions in
the same interactome space [[158]74].
In this pairwise low-throughput Y2H screen, we individually tested
selected interactions involving four relatively uncharacterized C.
burnetii effector proteins plus interactions associated with the
plasmid CBUA0014 effector examined in the high-throughput screens.
Thus, the pairwise testing encompassed 91 host-protein interactions
from five C. burnetii proteins—CBU0794, CBU0881, CBU1724, CBU2078, and
CBUA0014—which involved 22, 75, 54, 42, and 33 total interactions in
the high-throughput screen, respectively. Briefly, of the 226
individual interactions found in the high-throughput screen for these
effectors, we constructed Y2H clones and tested 91 or 40% in a pairwise
Y2H assay. Of these, 43 (47%) tested positive. There was no correlation
between the fraction of interactions that tested positive and the
number of interactions in the high-throughput screen, which further
suggests that interactions not seen in the pairwise Y2H screening could
be due to the intrinsic variation in the vectors and cDNA clone used.
The average interaction reproducibility per effector of 47% with a
sample standard deviation of 19% was better than, or on par, with other
experimental studies [[159]34, [160]75–[161]77]. All individual results
are included in [162]S2 Table.
Individual C. burnetii effector host-pathogen interactions
[163]Table 6 lists known effectors, with known mechanistic
associations, which we tested in our high-throughput Y2H screens. Given
their importance as pathogen proteins critical for C. burnetii
infections, we used the Y2H data to examine both location and
functional annotations associated with the targeted host proteins.
[164]Table 6 provides their common names, keywords from published
literature data, and a summary of the interaction analyses—the number
of host interactions, top four candidate cellular locations of
interacting host proteins, direct functional evidence from individual
host protein interactions, and enriched pathways/locations (Tables
[165]3–[166]5), including host-pathogen interactions where the effector
took part. Note that the sum of the fractions of protein locations can
exceed one, due to the possible presence of proteins in multiple
locations, e.g., if all targeted proteins were present both in the
nucleus and in mitochondria, both location fractions would be 100%.
Table 6. Functional characterization based on host-protein interaction data.
Locus Name Keywords Y2H protein interaction data
N[host] Top locations (%) Individual interactions Pathways
CBU0781 ankG anti-apoptotic; enters nucleus
[MATH: 40{ :MATH]
Nucleus Exosome Vesicle Mito apoptotic control; cell cycle Fc receptor
pathway; mitochondrial matrix
(50) (33) (32) (10)
CBU0937 cirC central for intracellular replication
[MATH: 26{ :MATH]
Nucleus Exosome Mito Memb stress response, solute transport Fc receptor
pathway; mitochondrial matrix
(38) (23) (15) (15)
CBU1314 - nuclear effector; modulation of host transcriptome
[MATH: 4{ :MATH]
Nucleus Exosome - - proteasome complex focal adhesion; NF-κB
immune-response
(75) (75)
CBU1524 caeA anti-apoptotic; enters nucleus
[MATH: 35{ :MATH]
Nucleus Exosome ER/Golg Memb spliceosome; ER-assisted protein
degradation endosomal sorting; NF-κB immune-response; cell cycle phase
transition
(65) (46) (17) (6)
CBUA0014 cepC E3 ubiquitin ligase binding
[MATH: 32{ :MATH]
Nucleus Exosome Memb ER/Golg pleiotropic, ubiquitination, vacuolar
sorting endosomal sorting; Fc receptor pathway; focal adhesion;
mitochondrial matrix; NF-κB immune-response
(41) (25) (18) (12)
[167]Open in a new tab
ER/Golg, endoplasmic reticulum/Golgi apparatus; Memb, plasma membrane;
Mito, mitochondria; N[host], number of host-pathogen protein
interactions; Y2H, yeast two-hybrid.
The T4SS effector CBU0781 (ankG) is linked to modulation/prevention of
intrinsic host cell apoptosis, located in mitochondria, and
subsequently translocated to the nucleus [[168]17,
[169]77,[170]78,[171]79]. Of the 40 identified host targets, the four
proteins localized to mitochondria (BBOX1, DLAT, ECH1, and OCIAD21) are
involved in metabolism. Most (50%) of the targeted host proteins are
located in the nucleus, with the remainder primarily located at sites
associated with the plasma membrane or different membrane-bound
cellular organelles. Of note is the observed Y2H interaction between
ankG and KPNA3, the importin subunit α3 of the nuclear pore complex,
which is required for the localization of ankG to the nucleus
[[172]17]. The ankG-host protein interactions in the nucleus are
associated with apoptotic processes involving ABCA1 [[173]80], PARP4
[[174]81], and PGRMC2 [[175]82], as well as interference in cell
cycle/mitotic progression via CDK14 [[176]83], STAG3 [[177]84], RFX5
[[178]85], and BAZ2B [[179]86].
The CBU0937 (cirC) effector was determined to be an immunoreactive Q
fever-specific protein [[180]87] and important for intracellular
replication. Examination of the host protein targets did not
unequivocally identify a virulence mechanism associated with this
effector. The primary locations of the host proteins indicated multiple
potential sites and mechanisms. Protein targets in the plasma membrane
may be related to solute transport and calcium and cationic exchange,
whereas those located in mitochondria could be linked to mitochondrial
protein synthesis. Targets in the nucleus could be related to stress
responses (MAP2K4, PPM1G, and RGS2) and RNA processing (PA2G4 and
PAPOLA).
The nuclear effector CBU1314 modulates the host transcription response
[[181]88], but with scant Y2H interaction data we could only identify
nuclear host protein interactions related to focal adhesion (the Rho
GTPase activating ARHGAP5 gene) and proteasome subunit interactions
involved in the NF-κB immune-response pathway.
CBU1524 (caeA) is linked to intranuclear interactions that prevent or
delay apoptosis of the host cell [[182]66,[183]67,[184]89]. Most (65%)
targeted host proteins were located in the nucleus, consistent with the
finding that caeA is preferentially located in the nucleus [[185]89].
However, substantial fractions were also observed in the plasma
membrane (25%) and in the ER/Golgi apparatus (17%). The roles of the
targeted nuclear proteins related to different aspects of gene
translation, such as splicing (e.g., spliceosome-associated proteins
DHX15, SAP18, and SNRPA1), RNA transport, and RNA transcription, as
well as ubiquitin-proteasome regulation. Those of the host proteins
localized to ER sites were associated with specific ER-associated
protein degradation (ERLIN2) and apoptosis (PKD2 [[186]90] and RTN4
[[187]91,[188]92]).
We also investigated the potential interactions of CBU0077, which
accumulates at vacuolar membranes and abnormal ER extensions,
suggesting that it interferes with vesicular traffic [[189]89]. Recent
research tag CBU0077 as a complex-forming effector at the mitochondrial
outer membrane during Coxiella infection [[190]93]. Six host proteins
interacted with CBU0077, three of which directly related to the
reported phenotype (i.e., the junction adhesion molecule AMICA1
[[191]94], the transmembrane-trafficking protein TMED10, and ACADM as
part of the mitochondrial fatty acid beta-oxidation pathway. None of
these host proteins were located in lysosomes, which are the preferred
sites in HeLa cells [[192]30], indicating that the roles of these
proteins may vary in different cell types [[193]69].
The presence of effectors on the conserved Coxiella plasmid indicates
the importance of their roles. The plasmid effector CBUA0014 (cpeC), an
F-box homology protein, localizes to ubiquitin-rich compartments and is
hypothesized to play an important role in establishing host infections
[[194]95]. [195]Table 6 shows a range of cellular sites where potential
host target proteins are preferentially located (nucleus, ER/Golgi
apparatus, and plasma membrane), as well as several specific pathways
that may be impacted by this effector, including components of the
ubiquitin-proteasome system and vacuolar sorting pathway (retromer
complexes). Of note are the protein interactions we verified in the
complementary pairwise Y2H testing experiment. Thus, cpeC could bind to
the ubiquitin-ligase complex component SKP1, which is part of the
SKP1-CUL1-F-box protein complex, as corroborated by the observation
that ubiquitin co-localizes with this effector [[196]95]. The potential
pleiotropic role of cpeC is indicated by the verified Y2H interactions
with VPS26A, which is involved in protein sorting of vacuolar pathogens
and TMX2 [[197]96] as part of the ESCRT endosomal sorting complex.
Inferring mechanisms of action for relatively uncharacterized effectors
We further selected four additional effectors (CBU0794, CBU0881,
CBU1724, and CBU2078) with little or no information on their role
during infections for analysis and complementary pairwise Y2H testing,
in an attempt to characterize their potential functions. [198]Table 7
provides an overview of these protein interaction analyses, including
alternate gene symbols, the success of the complementary testing effort
for these proteins, the number of host interactions, the top four
cellular locations where interacting host proteins may be located,
direct functional evidence from individual host protein interactions,
and a list of enriched pathways/locations from Tables [199]3–[200]5
involving the effector.
Table 7. Unknown secreted effector characterization based on host-protein
interaction data.
Locus Name Keywords Y2H protein interaction data
N[host] Top locations (%) Individual interactions Pathways
CBU0781 ankG anti-apoptotic; enters nucleus
[MATH: 40{ :MATH]
Nucleus Exosome Vesicle Mito apoptotic control; cell cycle Fc receptor
pathway; mitochondrial matrix
(50) (33) (32) (10)
CBU0937 cirC central for intracellular replication
[MATH: 26{ :MATH]
Nucleus Exosome Mito Memb stress response, solute transport Fc receptor
pathway; mitochondrial matrix
(38) (23) (15) (15)
CBU1314 - nuclear effector; modulation of host transcriptome
[MATH: 4{ :MATH]
Nucleus Exosome - - proteasome complex focal adhesion; NF-κB
immune-response
(75) (75)
CBU1524 caeA anti-apoptotic; enters nucleus
[MATH: 35{ :MATH]
Nucleus Exosome ER/Golg Memb spliceosome; ER-assisted protein
degradation endosomal sorting; NF-κB immune-response; cell cycle phase
transition
(65) (46) (17) (6)
CBUA0014 cepC E3 ubiquitin ligase binding
[MATH: 32{ :MATH]
Nucleus Exosome Memb ER/Golg pleiotropic, ubiquitination, vacuolar
sorting endosomal sorting; Fc receptor pathway; focal adhesion;
mitochondrial matrix; NF-κB immune-response
(41) (25) (18) (12)
[201]Open in a new tab
Centro, centrosome; ER/Golg, endoplasmic reticulum/Golgi apparatus;
ESCRT, endosomal sorting complexes required for transport; Memb, plasma
membrane; Mito, mitochondria; N[host], number of host-pathogen protein
interactions; Y2H, yeast two-hybrid.
The hypothetical protein CBU0794 exhibited interactions with host
proteins in the focal adhesion pathway (CAPN2) and with the proteasome
(PSMC1), but the relatively low number of interactions and the low
number of overall successfully pairwise tested Y2H interactions did not
allow us to define a more precise role for this effector.
The potential effector CBU0881 exhibited the second largest number of
host-pathogen interactions in our data set involving host
pathways/processes, such as endosomal sorting, focal adhesion, the
NF-κB immune-response, and protein processing in mitochondria.
Complementary Y2H testing confirmed two interactions in mitochondria
involving the peptidase PITRM1, which is responsible for degrading
transit peptide after their cleavage, and the tRNA-synthetase IARS2,
which is involved in mitochondrial protein synthesis. The interaction
data also point to extensive interactions of CBU0881 with IST1,
ATP6V1E2, CAPN7, and USP8 in the endosomal ESCRT pathway, with only the
last interaction retested but not confirmed.
The complementary Y2H testing data confirmed several interactions
associated with the centrosome, pointing to a heretofore unrecognized
Coxiella-targeted organelle. The high-throughput screens identified a
total of 14 host targets located in the centrosome, eight of which
interacted with CBU0881. Of five tested interactions, we confirmed
three in the pairwise Y2H screen: DCTN6, EFHC, and NEK2. The
corresponding functional relationships associated with their centrosome
location relate to protein organelle/vesicle transport and spindle
morphogenesis (DCTN6 [[202]97]), microtubule-regulation of cell
division (EFHC1 [[203]98]), and centrosome separation control and
bipolar spindle formation (NEK2 [[204]99,[205]100]). Further
indications of the potential pleiotropic role of this effector came
from the confirmed interactions associated with nucleus-located host
proteins involved in transcription via FAM60A in translational
repression and the peptidylprolyl isomerase PPIE in the spliceosome.
CBU1724 interacted with 17 human and 37 mouse proteins with two
overlapping interactions ([206]Table 1). The pathway analyses indicated
multiple roles in multiple pathways with selected interactions tested
and all confirmed in these pathways (MAPK10, ANLN, AK3, and NPC2).
Further evidence of a pleiotropic role for this protein was revealed by
the interactions with proteins involved in ubiquitin handling and
processing, such as CUL1, MYCBP2, OTUB1, and UBE2V2, with the
interaction between CBU1724 and the ubiquitin thioesterase OTUB1
confirmed in the complementary testing.
In addition to the high-throughput screening identification of
transthyretin (TTR) as a potential C. burnetii target involved in
cholesterol processing [[207]101], complementary testing confirmed two
additional host proteins involved in cholesterol handling: the
apolipoprotein APOA1BP [[208]102] and the intracellular cholesterol
transporter NPC2 [[209]103]. Although C. burnetii infections require
cholesterol from the host [[210]64,[211]104], pathogen mechanisms that
influence cholesterol uptake and processing in the host are not well
characterized. The use of T4SS effectors as potential mediators of this
process would thus be critical for maintaining and propagating the
infection.
For the final effector, the high-throughput screening pathway analysis
and accompanying Y2H pairwise testing data revealed that CBU2078
interacts with host proteins involved in focal adhesion and endosomal
sorting. Analysis of the complementary testing data confirmed
interactions for four of seven proteins involved in the
ubiquitin-proteasome system: RBBP6, RNF38, USP47, and WDR48. These
proteins included ubiquitin ligase/proteases (RBBP6, RNF38, and USP47)
as well as a protein that stimulates the activity of ubiquitin-specific
proteases (WDR48) [[212]105,[213]106].
Discussion
Y2H characterization of bacterial effector proteins
Large-scale high-throughput Y2H protein interaction screens can yield
large amounts of novel and unbiased data. Here, we used this technology
to focus on a select set of secreted bacterial effectors in an effort
to characterize C. burnetii host-pathogen interactions. We conducted
the largest human and murine genome-scale Y2H screening to date, using
33 C. burnetii T4SS effectors to identify and characterize
host-pathogen PPIs among this set. The aim of this study was thus to
derive general hypotheses on the mechanisms of effector actions
mediated by protein interactions. These screens provided partial host
interaction data for 25 bacterial effectors distributed among 415
unique pairwise interactions.
Our analyses of these data and the hypotheses derived from studying
individual and multiple interactions rely on the underlying protein
interactions having biological significance. The nature of protein
interactions is complex; high-affinity interactions are not necessarily
more biologically relevant than low-affinity interactions because
transient interactions with signaling proteins may have important
downstream effects not directly captured by PPI data. Many of these
low-affinity and transient interactions are strongly dependent on the
physiological state of the cell and may vary with the intracellular
environment. Similarly, host and pathogen proteins must be
simultaneously present in the same cellular compartment and of
sufficient quantity for the predicted interaction to be biologically
relevant. Thus, although all T4SS effectors are initially released into
the cytoplasm of the host cell, their primary targets may be host-cell
compartment/organelle specific, and their effects may depend on the
ability to efficiently translocate to the correct site of action at the
appropriate time.
C. burnetii is capable of colonizing multiple eukaryotic hosts,
including different mammalian species and many different cell types.
Consequently, the basic infection program executed by the pathogen must
exhibit both the generalized and specific features of host-pathway
interactions. A corollary of this assumption is that the likelihood of
each host-pathogen protein interaction being highly specific, involving
strong binary interactions, or being essential for establishing the
intracellular infection is small. Thus, we used the high-throughput
screening data to identify the biological processes or pathways and
cellular locations to which the targeted host proteins belong, in order
to characterize aspects of the general impact on the host cell of the
tested effectors.
Pathways and processes targeted by C. burnetii
The pathway enrichment analysis of the interactions detected in the Y2H
high-throughput screens identified host cellular processes known to
occur in Coxiella infections and broadly compatible with both
Legionella and Salmonella infection phenotypes. Not surprisingly, many
of these related to cellular processes in which direct protein
interactions are expected to play a critical role, such as in adapting
cell morphology through cytoskeletal re-arrangements, protein
processing and trafficking, and vacuolar generation. Similarly, direct
protein interactions could strongly affect the frequently observed
interactions with components of the ubiquitin-proteasome pathways. The
enrichment analyses also indicated targeted host processes involved in
amino acid metabolism and cholesterol processing, indicating a
potential nutritional component associated with the infection phenotype
and T4SS effectors. The interaction data also revealed the exosome to
be a preferred location for many of the targeted host proteins. If C.
burnetii effectors interfere with the intracellular trafficking of
immature exosomes or interact with proteins in exosomes, they would be
expected to dampen the immune signaling that occurs between host cells
and prevent the host from mounting a more robust immune response.
We also examined the host proteins targeted by specific effectors
previously found to alter Coxiella infection phenotypes in transposon
mutant studies. We used the interaction data to characterize potential
mechanisms of action and identify specific host targets for effectors
that could be associated with the observed mutant phenotypes for ankG,
cirC, and caeA. In the case of ankG and caeA, we used their nuclear
locations in the host cell to focus the analysis on apoptotic control
and interference with host gene transcription. In contrast, for other
proteins such as CBU1314, the interaction data were limited, suggesting
that protein interactions are not involved in their mode of operation.
Finally, we considered the interaction data to derive hypotheses on the
potential mechanisms of action of four individual effectors for which
phenotypic information is sparse. In three cases, the joint interaction
data supported mechanisms that were broadly similar to those of the
other effectors, such as involvement in ESCRT processes, ubiquitin
handling, and transcriptional control; at the same time, they also
pointed to specific processes not previously associated with T4SS
effectors, such as cholesterol transport (CBU1724) and centrosome
interactions (CBU0881). As characterizing novel effectors is often
referred to as “the hard part” [[214]2], careful in vitro and in vivo
phenotypic studies of deletion mutants will be needed to acquire more
precise information on their specific roles.
The present study delineates the largest collection thus far of C.
burnetii effector protein interactions derived from whole-genome human
and murine host protein libraries. This data set represents a rich
source of information on secreted pathogen effector proteins and their
interactions with host proteins. As such, these interactions contain
critical information on how the pathogen establishes and maintains a
successful intracellular infection.
Supporting information
S1 Table. Excluded host proteins.
The table provides host proteins known to be indiscriminate binders and
eliminated from our yeast two-hybrid high-throughput screen.
(XLSX)
[215]Click here for additional data file.^ (10.6KB, xlsx)
S2 Table. Host-pathogen interaction data.
The table provides all pairwise interactions detected in the yeast
two-hybrid (Y2H) high-throughput screen from the human libraries and
the corresponding murine orthologous interactions as well as the
pairwise interactions from the complementary pairwise Y2H testing.
(DOCX)
[216]Click here for additional data file.^ (43KB, docx)
Acknowledgments