High-content imaging screen of an arrayed M. tuberculosis transposon mutant library for growth in macrophages

To perform high-throughput monitoring of intracellular growth of a library of Mtb transposon mutants (S1 Table), we significantly modified our previously developed high-content imaging assay designed for high-throughput chemical screening [17] in order to accommodate heterogeneous bacterial growth among arrayed mutants and the need for external bacterial fluorescent staining by auramine-rhodamine for visualization (full details of assay and imaging pipeline development in S1 Text). Using rifampin in dose response to inhibit Mtb growth in macrophages, we developed a training set of images that represented a range of intracellular growth inhibition as defined by colony forming units (CFU). Based on correlation with CFU, we selected three readily-interpretable features as imaging metrics: percent of total macrophages infected with Mtb (“Percent infected”), normalized and integrated bacterial fluorescence intensity (“Mtb FI”), and macrophage cell count (“Macrophage count”) (S1A Fig). Of note, very similar metrics were used in a previous high-content imaging assay of Mtb growth in macrophages applied to small molecule screening [18]. A pilot screen of 190 mutants was then performed to assess assay performance (S1B Fig). The pilot screen data was additionally used to determine a linear combination of all three imaging metrics that would best identify true positives as determined by CFU retesting of predicted hits in comparison with wild-type control. The first principal component (PC1) from a principal component analysis computed on the data was observed to outperform all other metrics (S1C and S1D Fig).

Using our optimized assay and analysis (Fig 1A), we then screened the remainder of the arrayed, non-redundant Mtb 2660 transposon mutant library (Fig 1B, S1E and S2 Figs). Because Mtb mutant growth in macrophages is a graded rather than binary phenotype, we defined a threshold for calling hits for targeted follow-up studies. For each mutant, we calculated a weighted average of the 3 imaging outputs (PC1), and the 361 mutants (13.4% of the mutants screened) with the lowest PC1 scores were selected for additional study as our defined set of growth-impaired mutants (S2 Table, Fig 1C). In addition to 15 mutants identified in our screen that had already been confirmed to be growth-impaired in macrophages in the literature, we retested 73 of the top mutants by enumerating surviving bacteria by plating for CFU in comparison with wild-type Mtb. Although the biology captured by CFU measurements is limited in comparison with complex imaging phenotypes, CFU is considered the gold-standard measurement of comparative bacterial growth, and was thus used as a metric by which our imaging output was optimized and against which we tested hits. Combining the 47 CFU-confirmed and 15 literature-confirmed hits, a true positive rate of 72% was obtained for identifying mutants defective for intracellular growth (S3 Table). Several hits from previous screens [2–4] were among the identified mutants, thereby providing biological validation of our results (S2 Table).

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Fig 1. Identification of M. tuberculosis mutants defective for intracellular growth using a high-content imaging screen.

(A) Protocol for the high-content imaging assay for the transposon mutant library growth in macrophages. Wild-type Mtb at MOIs varying two-fold from 2:1 to 0.25:1 was included in each plate to allow both accurate normalization between plates and validation of a cutoff for hits based on control population behavior. Because the transposon mutant library does not express a fluorescent protein, Mtb was externally stained with auramine-rhodamine after fixation to permit visualization. (B) Correlation of PC1 score of technical replicates in the full screen. (C) Density function of PC1 values for mutants and controls. While hits were selected based on comparison with OD-matched mutants, the distribution of hit mutants falls almost entirely below the wild-type control distribution as well, confirming that hit mutants also behave differently than wild-type.

https://doi.org/10.1371/journal.ppat.1006363.g001

Several of the identified mutants fit well into the broader context of pathways and functions known to be important for Mtb survival in the host (S4 Table). Our screen identified genes in the ESX-1 type VII protein secretion system, perhaps the best-characterized mycobacterial virulence factor [5–7,19,20]. We identified mutants in loci that produce known virulence lipids, including PDIM [11,12]. We additionally identified multiple PE and PPE family genes [21], genes required for synthesis of molybdopterin cofactor [22], the two-component regulator senX3 [23], and regulators of Mtb metal content [24]. Host cholesterol is an important carbon source for intracellular Mtb [25,26]; we identified multiple enzymes in the cholesterol catabolic pathway. Finally, we identified several genes involved in nitrogen acquisition or metabolism, supporting the recent recognition of the importance of Mtb nitrogen metabolism in infection [27].

Multiparametric analysis of mutants impaired for intracellular growth identifies clusters of mutants predicted to be functionally related

A more comprehensive knowledge of the Mtb factors required for growth in macrophages is an important step in identifying the bacterium’s strategies for success. However, understanding the contribution of each gene to overall virulence and induced host responses as well as the networks that coordinate their functions would offer significant breadth and depth to our current understanding of the complex dynamic between pathogen and host. We thus sought to characterize the mutants identified in the screen both by the phenotype of bacterial growth restriction and by elicited host response. By combining these orthogonal phenotypes in a multiparametric analysis, we hoped to identify, through unbiased cluster analysis, genes that might be functionally related or act in a coordinated manner during infection.

While mutants of interest were initially selected based on an analysis pipeline trained to identify mutants with decreased CFU, in fact the biology of mutants captured in images is richer and more complex than a simple CFU measurement. To fully capitalize on the phenotypic complexity of bacterial growth restriction afforded by imaging, we sought to analyze the mutants based on individual imaging metrics that allow us to distinguish different mutants and the roles of the corresponding genes in infection. We ranked all screened mutants into deciles by score for each of the three individual imaging metrics used in the primary screen PCA and then grouped the mutants based on the similarities of their scores across all three. The majority of hits behaved as one might intuitively expect: higher macrophage survival, lower percent macrophages infected, and lower bacterial fluorescence intensity than the vast majority of screened mutants. However, some mutants behaved differently, eliciting more macrophage cell death or higher percent macrophage infection than the majority of mutants.

To characterize the host response elicited by each mutant, we then used a multiplexed Luminex assay to quantify macrophage production of cytokines in response to infection with each of the 361 mutants identified in the primary screen. Twelve cytokines were accurately quantifiable and differed significantly between wild-type-infected and subsets of mutant-infected cells (S3 Fig). These cytokines reflect processes known to be important for Mtb macrophage infection, including the type I IFN response (e.g. CCL5) and pro-inflammatory response (e.g. MMP9, TNF-α). As reflected in these 12 cytokines, macrophage responses to infection with the mutants were in fact quite varied (S4 Fig); this variability did not reflect either the input ratio of bacteria to macrophage or relative degree of intracellular growth impairment (S4B Fig), suggesting that the cytokine response to each mutant is independent of relative attenuation in macrophages. We hypothesized that combining imaging and cytokine phenotypes for each mutant would yield the most information about how those mutants might work together in networks interacting with aspects of the host response to infection (Fig 2A).

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Fig 2. Multiparametric analysis of mutants impaired for intracellular growth identified subsets with shared complex phenotypes.

(A) Schematic diagram of the approach to analyzing the mutants. Bacterial attenuation was analyzed based on three imaging parameters (Mtb fluorescence intensity, percent infected, and macrophage count) and host response was analyzed based on multiplexed cytokine analysis for each mutant. The phenotypes for each mutant were then combined into a multiparametric analysis as described in B. (B) Unsupervised 2-D clustering of mutants based on a multiparametric representation of their phenotypes. This analysis combines the four host response clusters (top 4 rows) and three bacterial imaging clusters (bottom 3 rows). Each column represents one of the 113 mutants included in the analysis. Colors indicate low (blue) to high (red) normalized values for each phenotype. Mutants cluster into five groups (Clusters I-V). Mutants in the PDIM locus (labels in orange) and ESX-1 locus (labels in green) group together in Cluster V. (C) Contribution of each bacterial imaging phenotype (bacterial replication, host survival, and % infected: orange vectors) and clustered cytokine response phenotype (cyt-1, cyt-2, cyt-3, and cyt-4: black vectors) to principal component 1 (PC1) and principal component 2 (PC2) of the principal component analysis. PC1 is comprised almost entirely of cytokine phenotypes while PC2 is comprised almost entirely of bacterial imaging features, suggesting that the two sets of features represent orthogonal and complementary information. (D) The 113 mutants included in the multiparametric analysis separate when plotted by PC1 and PC2. Included mutants were those that induced macrophage responses most distinct from the response to wild-type Mtb. Coloring of mutant clusters reflects mapping of the analysis performed in 2D back to the PC1/PC2 graph.

https://doi.org/10.1371/journal.ppat.1006363.g002

To cluster mutants based on both the imaging phenotype, which we considered to reflect primarily bacterial outcomes, and cytokine phenotype, which we considered to reflect primarily host response, we thus sought to combine the two phenotypes in a multiplexed analysis. For this clustering analysis, we had to explicitly balance the contribution of the imaging and cytokine features to avoid either source dominating the analysis. A straightforward approach to doing this is to select the same or similar number of measurements from both sources. To reduce the number of cytokine features, we grouped the features using hierarchical clustering and found that they fell into four groups (cyt-1 (CXCL10 and CCL5), cyt-2 (TNF-α, CXCL2, MMP9, and Lipocalin), cyt-3 (CCL2, CCL4, IGF-1, and BAFF), and cyt-4 (CCL3 and osteopontin) S4C and S4D Fig). Validating the biological relevance of these groupings, cytokines reflecting the type I IFN response clustered together, and pro-inflammatory cytokines clustered together in a distinct group. The features in each group were combined by averaging; we used this grouping for further analysis.

To maximize our ability to distinguish phenotypically unique sets of mutants, we limited analysis from this point to the 113 mutants impaired for intracellular growth with macrophage responses most distinct from wild-type infected cells. Of note, confirmed true positives (by CFU) were represented in both this set of 113 mutants and mutants that induced macrophages responses more similar to wild-type Mtb, supporting the idea that the induced macrophage response is a distinct phenotypic readout. Given that the bacterial imaging and host response phenotypes provide distinct information about the mutants, we hypothesized that mutants similar in both metrics would be the most closely functionally related. To identify such phenotypically similar groups of mutants, we then performed a two dimensional unsupervised clustering based on the combined host response features and bacterial imaging features (Fig 2B). This clustering identified five groups of mutants (S5 Table).

To determine objectively whether cytokine and imaging features contributed overlapping or distinct information to the analysis of each mutant, we next performed a principal component analysis to determine how features were related to one another. Interestingly, the first principal component (PC1) was comprised almost entirely of host response features (cyt-1, cyt-2, cyt-3, and cyt-4), while the second principal component (PC2) was comprised almost entirely of bacterial imaging phenotype features (Fig 2C). These results suggest that the bacterial imaging phenotypes and host response phenotypes are in fact nearly orthogonal, and provide complementary information about the tested mutants. Plotting the mutants by PC1 and PC2, we then determined that the mutants indeed segregate in two-dimensional space, indicating that the multiparametric analysis can provide insights into points of divergence in the host-pathogen interaction (Fig 2D). Given the unique phenotypic signature of each cluster in this combined analysis, we hypothesized the mutants within each cluster may be functionally related.

Synthesis and export of virulence lipid PDIM is required for induction of the macrophage type I IFN response

Notably, mutants in pathways for two well-known virulence factors, ESX-1 and PDIM, clustered together by this multiparametric analysis combining imaging and induced cytokine phenotypes. The ESX-1 protein secretion system has been proposed to permeabilize the phagosomal membrane, facilitating recognition of Mtb by the macrophage cytosolic surveillance program (CSP) and triggering a type I IFN response [7–10]. On balance, accumulating evidence suggests that this response benefits the bacterium. As expected, we found that ESX-1 mutants failed to induce a type I IFN response (Fig 3A). Surprisingly, PDIM mutants similarly failed to induce a type I IFN response (Fig 3A). Previously, ESX-1 secretion was the only Mtb function linked to the macrophage type I IFN response. Although the ESX-1 ATPase EccCa1 has been proposed to bind to a variety of enzymes required for M. marinum lipid biosynthesis, including some of the enzymes required for PDIM biosynthesis [28], a functional link has not previously been proposed between ESX-1 and PDIM. Our results suggest that PDIM functionally interacts with ESX-1, as it also plays a role in the intracellular events that culminate in induction of type I IFNs.

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Fig 3. PDIM production and export is required for induction of the macrophage type I IFN response.

(A) Measurement of macrophage CCL5 production after infection with Mtb strains. J774.A1 cells were infected with wild-type Mtb strains or transposon mutants at an MOI of 1:1. Supernatants were harvested at 48 or 72 hours after infection for cytokine quantitation using Luminex. Mean +/- SD of three biological replicates. (B-D) The type I IFN response was measured by quantitation of expression of the type I IFN-responsive gene ifit2 expression after macrophage infection with Mtb. Bone marrow-derived macrophages were infected with the indicated Mtb strains at an MOI of 2:1 and RNA was harvested at 24 hours for gene expression analysis by qRT-PCR. (B) Transposon mutants across the PDIM locus, including synthetic function mutants (ppsC, ppsD, mas), transport mutants (drrA, drrB, drrC, mmpL7), and acyl activating mutants (fadD28) failed to induce expression of type I IFN-responsive gene ifit2. P-value by two-tailed t-test for comparisons of Rv with Tn mutants in eccCb1, eccCa1, ppsC, ppsD, drrA, drrB, drrC, papA5, mas, fadD28, and fadD22 were < 0.05, for the comparison of Rv and mmpL7 was 0.05, and for the comparison of Rv with lppX, pks15, Rv2949c, and mutT4 were non-significant. (C) A drrC transposon mutant was complemented with tetracycline-inducible, chromosomally-integrated drrC; drrC expression was induced with 50ng/ml or 100ng/ml aTc. While in the absence of inducer ifit2 expression was substantially decreased relative to wild-type-infected macrophages, induction of drrC expression with aTc restored ifit2 expression. Two-tailed t-test p-value for the comparison of Rv with Tn::drrC and Tn::drrC::ptet-drrC 0 ng/ml aTc was < 0.01. (D) Infection with wild-type H37Rv, ppsD point mutant ppsD(G44C) that fails to produce PDIM, or complemented mutants ppsD(G44C)rev and ppsD(G44C)::pMVppsD. While loss of functional ppsD in the mutant resulted in loss of ifit2 expression, restoring ppsD function restored ifit2 production. Two-tailed t-test p-value for the comparison of Rv with ppsDmut was < 0.05. (B-D) Mean +/- SD of biological duplicates. (E) Microscopy of macrophages infected with PDIM mutant and complemented strains demonstrates that complementation restores wild-type image analysis phenotypes. J774A.1 macrophages were infected with wild-type, PDIM mutant, or complemented strains. After 3 days of infection, cells were washed, fixed, and stained with DAPI to visualize macrophage nuclei and auramine-rhodamine to visualize Mtb. Cells were imaged and CellProfiler automated image analysis was used [29] to quantitate bacterial fluorescent intensity, percent macrophages infected, and macrophage cell count. Mean +/- SD of six biological replicates.

https://doi.org/10.1371/journal.ppat.1006363.g003

Critical for Mtb growth in the host [11,12], PDIM is a large Mtb cell-surface lipid. The chromosomal locus responsible for producing and exporting PDIM encodes machinery for acyl chain production, acyl activation, post-production modification, and transport. Specific functions for PDIM have only recently been proposed, including mediating interactions between the bacterial cell and host plasma membrane [13] and masking MYD88-dependent detection of pathogen-associated molecular patterns (PAMPs) on the mycobacterial surface [14]. Our results indicate that PDIM is additionally required for intracellular processes leading to induction of the macrophage type I IFN response.

We hypothesized that either a distinct PDIM locus gene function (such as function of a single transporter) or fully intact, properly localized PDIM could be required to induce a type I IFN response. To systematically identify the PDIM locus functions required, we profiled expression of type I IFN-induced genes following macrophage infection with mutants that contained disruptions in many genes across the entire PDIM locus (Fig 3B). Mutants defective in each of the functions of the PDIM locus including acyl chain production (ppsD, ppsD, mas), acyl chain activation (fadD28), and transport (drrABC, mmpL7) failed to induce a type I IFN response. The only PDIM locus mutant that induced wild-type levels of type I IFN was lppX. Although proposed to be required for PDIM transport [30], lppX is in a different operon with pks1/15 genes [31]. Our results suggest that transporters drrABC and mmpL7 have functions distinct from lppX in lipid localization and ultimate function. The loss of a type I IFN response following macrophage infection with all other available mutants in the locus suggest that intact and properly localized PDIM is necessary for induction of type I IFNs.

To confirm that loss of the type I IFN response was in fact attributable to individual genes within the PDIM operons and provide additional confirmation of roles for both PDIM biosynthetic and transport genes, we used two mutant complementation strategies. First, we introduced an integrating, inducible allele of transporter drrC to complement drrC disruption in the corresponding transposon mutant. Loss of PDIM export was confirmed to be commensurate with what has previously been described for a comparable drrC transposon mutant [32] (S5 Fig). Second, we used a published mutant with a single loss-of-function point mutation in biosynthetic gene ppsD (ppsD(G44C)) and complemented mutant strains with either a chromosomal reversion of the mutation or episomal expression of the wild-type allele [33]; the published loss and restoration of PDIM in the mutant and revertant were confirmed using LC-MS (S6A Fig). Infection with either Tn::drrC or ppsDmut failed to induce the type I IFN response; in both cases, complementation restored the response (Fig 3C and 3D). As expected, the imaging phenotypes of the mutants in infected macrophages also reverted to wild-type by complementation, confirming that PDIM production and transport genes are required for full virulence (Fig 3E). Bulk secretion of IFN-β was more modest than the induced transcriptional response but followed a similar trend for each mutant (S7 Fig).

PDIM contributes to the type I IFN response by facilitating phagosomal permeabilization

We next investigated how PDIM might facilitate induction of the type I IFN response. To explore whether PDIM is a PAMP recognized by the macrophage CSP after ESX-1 permeabilizes the phagosomal membrane, we treated macrophages with a liposomal formulation of PDIM. No type I IFN response was elicited even at high concentrations of PDIM (S8 Fig), consistent with recent work suggesting that bacterial genomic DNA is instead the relevant CSP-detected PAMP triggering type I IFNs [8–10]. One step previously described as critical for induction of the macrophage type I IFN response to Mtb infection is disruption of the phagosomal membrane, which allows mixing of cytosolic and phagosomal contents and detection of bacterial products by the CSP [7]. To test whether PDIM facilitates phagosomal permeabilization, we sought to determine whether permeabilizing the phagosome by an alternative mechanism would render PDIM dispensable for induction of the type I IFN response. Using a previously described method for creating pores in the phagosomal membrane [7,34], we used listeriolysin O (hly) to permeabilize the phagosome in an ESX-1-independent manner. A ppsD clean deletion mutant (S6B Fig) was transformed with an integrating plasmid expressing hly (S9 Fig). Expression of listeriolysin O in PDIM mutant bacteria indeed restored the type I IFN response (Fig 4A), suggesting that PDIMs contribution to this response is at the level of phagosomal permeabilization. Two other groups have recently reported similar observations using flow cytometry to quantitate phagosomal permeabilization [35,36].

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Fig 4. PDIM facilitates phagosome permeabilization and is required for coordinated ESX-1-mediated secretion.

(A) Bone marrow-derived macrophages were infected with wild-type Mtb, a ppsD clean deletion strain (ΔppsD), ΔppsD complemented with ppsD, or the ΔppsD expressing listeriolysin O (hly) at an MOI of 2:1. RNA was harvested at 24 hours for gene expression analysis by qRT-PCR. Hly-mediated mediated phagosomal permeabilization restores the type I IFN response in the PDIM mutant. Mean +/- SD of biological duplicates. Two-tailed t-test p-value for the comparison of Rv with ΔppsD was < 0.001 and for the comparison of Rv with ΔppsD::hly was non-significant. (B) Western blot analysis of ESAT-6 and CFP-10 secretion in PDIM mutants. Supernatants from wild-type, ESX-1 mutant (Tn::eccCa1), or PDIM mutants and complements were harvested, concentrated, and probed for ESAT-6, CFP-10, antigen 85 (Sec-secreted control), and GroEL (lysis control). Corresponding pellets were simultaneously lysed and probed for ESAT- or CFP-10 (production control) and GroEL (loading control). Disruption of drrC results in loss of ESAT-6 and CFP-10 secretion; inducibly restoring drrC expression with 50ng/ml aTc restores ESAT-6 and CFP-10 secretion. Loss of ppsD function due to a point mutation in the active site (ppsD(G44C)) similarly results in loss of ESAT-6 secretion, but results in enhanced CFP-10 secretion. Reversion of the mutation back to wild-type ppsD(G44C)rev restores the wild-type phenotype. (C) Western blot analysis of ESX-5 secretion of EsxN and PPE41 in the ppsD point mutant and drrC transposon mutant. Supernatants from phosphate-starved wild-type or PDIM mutant and complement were harvested, concentrated, and probed for ESX-5 substrates EsxN or PPE41 and GroEL (lysis control). Supernatant from an ESX-5 hypersecreter strain (ΔpstA1) was used for definitive band identification [40]. Loss of ppsD function due to the G44C active site point mutation or loss of drrC function in the transposon mutant leads to significant loss of secretion of ESX-5 substrates PPE41 and EsxN. In both cases, secretion of EsxN and PPE41 is restored with complementation. Pellets below demonstrate that the ppsD mutant and drrC transposon mutant do not have a defect in EsxN or PPE41 production.

https://doi.org/10.1371/journal.ppat.1006363.g004

PDIM is required for coordinated secretion of ESX-1 and ESX-5 type VII secretion system substrates

ESX-1 protein secretion is the only other Mtb factor described to be required for phagosomal permeabilization. To determine whether PDIM is required for ESX-1 function itself, we tested whether mutants in PDIM biosynthesis and export were able to secrete the ESX-1 effector ESAT-6, which until very recently had been implicated as the likely pore-forming secreted effector of the ESX-1 system. Using Western blot analysis of bacterial supernatants and pellets, we found that ESAT-6 secretion was indeed impaired in both the ppsDmut biosynthesis mutant and the Tn::drrC export mutant (Fig 4B). ESAT-6 secretion was similarly impaired in strains with clean deletions of ppsD and the PDIM biosynthetic enzyme mas (S6B and S10 Figs). We then tested whether secretion of the heterodimeric partner of ESAT-6, CFP-10, was similarly impaired in PDIM mutants. Distinct from the phenotype observed for ESAT-6 where its secretion was impaired in all PDIM mutants, CFP-10 secretion was impaired in the drrC mutant and mas clean deletion, but was enhanced in the ppsD mutants (Fig 4B; S10 Fig). Wild-type phenotypes were restored by complementation of the mutations in all cases. Of note, simultaneous analysis of the lysed bacterial pellets indicated that total ESAT-6 and CFP-10 protein production was not affected by the absence of PDIM and, secretion of the Sec substrate antigen 85 was not impacted by the absence of PDIM, suggesting that PDIM does not globally impact secretion.

To determine whether PDIM’s disruption of ESX-1-mediated secretion was generalizable to other ESX secretion systems implicated in virulence [37,38], we next tested whether loss of PDIM disrupts secretion of ESX-3 and ESX-5 substrates. ESX-3 secretion was elicited by iron starvation [39]; ESX-5 was elicited by phosphate starvation [40]. While PDIM mutants did not show impaired secretion of ESX-3 substrates EsxG and EsxH (S11 Fig), the ppsD point mutant and drrC transposon mutant did demonstrate impaired secretion of ESX-5 substrates PPE41 and EsxN (Fig 4C). Simultaneous detection from bacterial pellet lysates indicated that production of ESX-5 substrates was not changed in either mutant. Thus, while the dependence of secretion on PDIM is not restricted solely to ESX-1 substrates but also impacts the secretion of ESX-5 substrates, it does demonstrate some specificity as it is not generalizable to all ESX secretion systems.

Two genes that cluster with the ESX-1 and PDIM are required for PDIM production

To further test whether mutant clustering by multiparametric analysis can predict novel functional relationships between genes, we next investigated the relationship between the functions of other genes represented in Cluster V and the functions of PDIM and ESX-1. We first sought to confirm that the observed, shared phenotype could be truly accounted for by the transposon-disrupted gene in each mutant by complementing several of the additional 8 mutants that appear in Cluster V with episomal copies of the respective wild-type genes, and tested for reversion to wild-type production of the type I IFN response. Single-gene complementation of two Cluster V mutants, Tn::Rv0712 and Tn::hrp1 (hypoxic response protein 1, Rv2626c), restored the type I IFN response (Fig 5A and 5B), suggesting that each of these genes is required for induction of type I IFNs. Rv0712 is a formylglycine-generating enzyme (FGE), required for activation of type I sulfatase enzymes [41]; however, the physiologic substrates and role of sulfatases in infection is unknown [42]. Rv0712 has been predicted to be essential in mice based on Tn-Seq experiments [43]. hrp1 is part of the DosR regulon, which is highly expressed upon exposure to nitric oxide or hypoxic conditions, and proposed to play a role in dormancy [44–46]. Hrp1 is a secreted protein with two cystathionine beta synthase (CBS) domains [47] but its biological function and role in infection is also unknown. Neither gene has previously been linked to mycobacterial lipids, ESX-mediated secretion, or the macrophage type I IFN response.

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Fig 5. Two additional genes that cluster with PDIM and ESX-1 are required for PDIM production and downstream induction of the type I IFN response.

(A-B) The type I IFN response to infection was measured by quantitation of expression of the type I IFN response-representative gene IFIT2. Bone-marrow derived macrophages were infected with wild-type Mtb, the Rv0712 transposon mutant and complemented mutant (A) or hrp1 transposon mutant and complemented mutant (B). RNA was harvested at 24 hours for gene expression analysis by qRT-PCR. IFIT2 was quantitated relative to control expression of GAPDH. Loss of type I IFN response to infection seen with disruption of Tn0712 or hrp1 in each mutant is restored with expression of the respective gene in the complemented strains. (A-B) Mean +/- SD of biological duplicates. Two-tailed t-test p-value for the comparison of Rv with Tn::hrp1 and Tn::Rv0712 was < 0.001. (C) PDIM was quantitated using LC-MS analysis of total cell wall lipid extracts. The indicated strains were grown in tween-free medium; total cell wall lipids were extracted from the bacterial cells. Loss of PDIM production seen in Rv0712 and hrp1 transposon mutants was restored with expression of the respective genes in the complemented strains. Mean +/- SD of biological triplicates. Fragmentation patterns for each quantitated species is listed in S1 Text. (D) Western blot analysis of ESAT-6 and CFP-10 secretion in Rv0712 and hrp1 mutants. Supernatants from each indicated strain including H37Rv wild-type control and Tn::ecca1 (ESX-1 mutant positive control) were harvested, concentrated, and probed for ESAT-6 or CFP-10, and GroEL (lysis control). Corresponding pellets were simultaneously lysed and probed for ESAT- or CFP-10 (production control) and GroEL (loading control). Disruption of Rv0712 resulted in diminished secretion of both ESAT-6 and CFP10; loss of secretion was reversed with complementation. Disruption of hrp1 resulted in diminished ESAT-6 secretion but no change in CFP-10 secretion. Diminished ESAT-6 secretion in the hrp1 mutant was restored with complementation.

https://doi.org/10.1371/journal.ppat.1006363.g005

Based on its phenotypic clustering, we hypothesized that Rv0712 and hrp1 could be required for PDIM biosynthesis thereby facilitating ESX-1 secretion and phagosomal permeabilization, for ESX-1 secretion independent of PDIM, or for an altogether independent function influencing the type I IFN response, such as the production or exposure of a bacterial PAMP or a role in host CSP signaling. Using quantitative mass spectrometric analysis of total cell wall mycobacterial lipids [48], we determined that in fact, both Tn::Rv0712 and Tn::hrp1 produced significantly less PDIM than wild-type H37Rv (Fig 5C; S12A and S12B Fig). PDIM production in the mutants was restored with complementation. We then tested whether the observed loss of PDIM in the mutants would correlate with changes in secretion of ESX-1 substrates. Secretion of ESAT-6 was diminished in both the hrp1 and Rv0712 mutants and restored in the complemented strains (Fig 5D); secretion of CFP-10 was diminished in the Rv0712 mutant but unchanged in the hrp1 mutant. Thus this multiparametric clustering successfully predicted that these two genes would functionally interact with PDIM and ESX-1 in their induction of the macrophage type I IFN response.

Bacterial strains and growth conditions

The transposon mutant library was made in Mtb strain H37Rv. For genetic manipulations, Mtb was growth in Middlebrook 7H9 broth (Difco) supplemented with Middlebrook OADC (BD), glycerol 0.2%, and tween-80 0.05%. Mtb strains ppsD(G44C), ppsD(G44C)revert and ppsD(G44C)pMV::ppsD were previously published strains [33]. The inducible drrC construct was generated by cloning the drrC gene into pMC1S [58]. The hly-expressing plasmid was generated by cloning Listeria hly into pMC1S. The ppsD and mas clean deletion strains were generated using mycobacterial recombineering to replace the entire ppsD or mas gene with a hygromycin cassette [59]. Tn::Rv0712 and Tn::hrp1 were selected from the arrayed, annotated transposon library and complemented with each individual gene in the episomal, constitutively expressing vector JP118 [39]. Gene-specific primers are listed in S1 Text.

Construction of an arrayed, annotated transposon mutant library

Mtb strain H37Rv was transposon mutagenized using a Himar-based transposon according to the protocol described in Sassetti et al [60]. Following selection on kanamycin-containing plates, approximately 26,000 individual colonies were selected and arrayed as glycerol stocks in 96-well plates. Colony PCR was then performed, using a two-step process with one primer internal to the transposon and one random primer for each PCR step to identify each insertion site. Each PCR product was then subjected to Sanger sequencing. Arrayed library mutants were selected after processing the data with a BLAST alignment-based script that incorporates a number of criteria, including Sanger read sequence quality, the uniqueness of genome sequence match, location of alignment within the sequence read and e-value of the BLAST match. In cases of genes demonstrating multiple insertion sites, priority was assigned to insertion sites greater than 10 nucleotides into an ORF or more than 50 nucleotides upstream of the stop. Ultimately 2660 transposon mutants, each with insertion in a different gene, were selected and arrayed in 28 96-well plates.

Characterization of library growth in vitro

The Tn mutant library was inoculated into 96-well plates containing 100μL Middlebrook 7H9 broth supplemented with Middlebrook OADC, glycerol 0.2%, and tween-80 0.05%. Plates were then incubated at 37°C. Every 2–3 days, wells were resuspended by pipetting and OD600 was determined using a SpectraMax plate-reader (Molecular Devices). Growth rates (υ) were calculated for each mutant by fitting a sigmoid function to the growth curve (OD600 over time) and estimating the slope. Most mutants in the library grew similarly in 96-well plates, and attenuated mutants did not grow differently than all mutants (S13A and S13B Fig).

High-content assay protocol

Full assay development details are in S1 Text. Briefly, transposon mutants were grown in 96-well plates in 7H9 media with OADC, glycerol, and tween-80 supplementation. On the day of infection, plates were centrifuged to pellet bacteria and media was removed. Pellets were resuspended in an equal volume of PBS, and plates were again centrifuged to pellet bacteria. Supernatants were removed, and cells were resuspended thoroughly in PBS. A low-speed spin was performed to pellet cell clumps. The supernatant was moved to another 96-well plate, and OD600 for each well was recorded. The average bacterial number per ml across the plate was calculated, and bacteria were added to DMEM with 20% heat-inactivated horse serum (HS) to give an average number of CFU/ml of 62,500 (averaged across all wells on the plate). The bacteria in DMEM/HS were then added to J774A.1 macrophages in 96-well plates to give an average MOI of 1:1. Control bacteria were prepared in parallel, and added to macrophages at an MOI of 2:1, 1:1, 1:2, and 1:4. After 4 hours for phagocytosis, media was aspirated, infected cells were washed once with PBS, and media was added back. Cells were incubated for 3 days, then media was aspirated off. Cells were again washed with PBS to remove extracellular bacteria, then fixed with 4% paraformaldehyde. Wells were then stained with auramine-rhodamine to visualize bacteria and DAPI (Sigma) to visualize macrophage nuclei. Plates were imaged on an ImageXpress high-content microscope (Molecular Devices). Images were then analyzed using CellProfiler automated image analysis [29].

CellProfiler automated image analysis pipeline

The basic operation of the image analysis workflow is similar to that used previously [17]. Briefly, a pre-processing CellProfiler pipeline was used to determine the illumination correction of each fluorescent channel. A second pipeline then used the results of the first pipeline to correct each channel for uneven illumination, followed by detection and exclusion of fluorescent debris, and collection of whole-image features from the corrected images including the green fluorescent pixel intensity and area integrated across the field of view, the macrophage number per field of view and the percentage of macrophages that are infected. This pipeline additionally collected a variety of image-based features for each auramine-rhodamine-labeled mycobacterial clump and the associated macrophage DNA-labeled nuclei, in order to produce rich, quantitative profiles in an unbiased manner. These features included mycobacterial and nuclear size and shape, intensity, and texture statistics. All pipelines used for this paper are publically available at http://www.cellprofiler.org/published_pipelines.shtml.

Statistical analysis of screening data

The features extracted from the image analysis pipeline were used to select hits as well as identify phenotypically distinct groups of mutants within the hits. By analyzing the features in the pilot screen, we identified three features (macrophage count, Mtb fluorescence intensity, percentage of infected macrophages) to be best predictive of CFU (S1 Text). To account for the small differences in MOI across replicates, the residues of the feature values regressed against the MOI were used in all further analyses. We combined the three features into a single readout by computing a linear combination for which the variance in the data was maximized (i.e. the first principal component “PC1” of the data). We found that PC1 was a better predictor of CFU compared to the individual features (S1C Fig, S1 Text) or a combination of all measured features (S1D Fig) and therefore used it to select mutants for follow up experiments.

Cytokine profiling of supernatants from macrophages infected with 361 screen hits

The 361 attenuated Mtb Tn mutants were grown in 4 96-well plates to mid-log phase. J774A.1 macrophages were seeded in 96-well plates overnight. Cells were then infected with the attenuated mutants or controls in a 96-well format, prepared as described above. The average MOI across the plate was 1:1. Infection was allowed to progress for 3 days (or 48 or 72 hours for the timecourse), then supernatants were harvested and used in a Luminex assay for detection of 34 multiplexed cytokines according to the manufacturer’s protocol.

Multiparametric analysis for mutant clustering

All mutants included in the primary screen were ranked in deciles for each of the three imaging features: bacterial fluorescence intensity, macrophage cell count, and percent macrophages infected. Host cytokine were clustered in an unsupervised manner into four groups based on behavior across all hit mutants. The 113 mutants eliciting cytokine responses most distinct from wild-type infection were then clustered using hierarchical clustering with Pearson correlation as the similarity metric. For the clustering, each mutant was represented by a 7-dimensional feature vector representing, both, imaging (3 features) and cytokine response (4 feature groups).

Western blotting for ESX secretion assays

Mtb strains were grown in Middlebrook 7H9 broth (Difco) supplemented with Middlebrook OADC (BD), glycerol 0.2%, and tween-80 0.05% to mid log-phase. For ESX-1 blotting, an equal number of cells from each culture were pelleted by centrifugation and resuspended in Sauton’s media supplemented with OADC and glycerol for 24 hours. For ESX-3 blotting, an equal number of cells from each culture were pelleted by centrifugation, washed three times in chelated Sauton’s medium [61], and resuspended in chelated Sauton’s medium for 48 hours. For ESX-5 blotting, an equal number of cells from each culture were pelleted by centrifugation, washed and resuspended in medium phosphate Sauton’s medium (250μM phosphate) with tween for 48 hours, then washed and resuspended in low phosphate Sauton’s medium (25μM phosphate) without tween for 48 hours (modified from [40]). Supernatants were then harvested and proteins were concentrated 500-fold. Concentrated supernatants were run on an Tris-glycine gel and probed with antibodies to ESAT-6 (Abcam), CFP-10 (Abcam), Antigen 85 (Abcam), GroEL (Abcam), EsxGH [61], a kind gift of Dr. Jennifer Philips, Washington University, EsxN, or PPE41. Blots were stained with Ponceau prior to antibody detection to ensure equal protein loading of all lanes. Pellets were lysed by bead beating in protein extraction buffer (50mM TrisCl, pH 7.5, 5mM EDTA, 1mM 2-mercaptoethanol, protease inhibitor (Amresco)) prior to use for Western blotting.

Production of EsxN and PPE41 antisera

Full-length esxN was amplified from M. tuberculosis Erdman genomic DNA by PCR with primers esxNHisF2 (5’gcattcatgacgattaattaccagttcgggga3’) and esxNHisR2 (5’ gcatctcgagggcccagctggagccga3’), digested with BspHI and XhoI and cloned in pET28b+ (Novagen) between the NcoI and XhoI restriction enzyme sites to generate pET28-EsxNHis₆ encoding EsxN with a C-terminal His₆ tag. A plasmid for co-expression of PPE41-His₆ and PE25 was described previously [62]. Recombinant proteins were produced in E. coli BL21(DE3) and purified by Ni²⁺-NTA affinity chromatography (Qiagen). PPE41-His₆ was bound to the column under native conditions in 20 mM HEPES buffer, 300 mM NaCl, pH 7.8 and eluted in 20 mM HEPES buffer, 500 mM NaCl, pH 7.8 containing 50–150 mM imidazole. EsxN-His₆ was purified under denaturing conditions; protein was bound to the column in 20 mM sodium phosphate buffer, 500 mM NaCl, 6 M guanidine hydrochloride, pH 7.8 and eluted in 20 mM sodium phosphate buffer, 500 mM NaCl, 8 M urea, pH 4. Contaminant proteins that co-purified with EsxN-His₆ were removed by passing eluted fractions through a 50 kDa cut-off Amicon Ultra centrifugal filtration unit (Millipore). Polyclonal antisera against purified EsxN-His₆ and PPE41-His₆ proteins were generated in rabbits by Pierce Custom Antibodies (Thermo Scientific) using TiterMax Gold adjuvant (Sigma).

Macrophage infections for RNA isolation and qPCR

Murine bone marrow-derived macrophages (BMDM) were prepared as previously described [17] from C57BL6 mice (Jackson Laboratories). BMDM were seeded in 24 well plates overnight in DMEM with 20% FBS and 25ng/ml rmM-CSF (R and D Systems). Mtb strains were grown to mid-log phase, then used to infect BMDM at an MOI of 2:1. After 4 hours of phagocytosis, cells were washed once with PBS and media was added back. RNA was harvested 24 hours after infection with TRIzol (ThermoFisher Scientific) and prepared according to the manufacturer’s protocol. cDNA was prepared using SuperScript III (ThermoFisher Scientific) according to the manufacturer’s protocol. qPCR was performed using primers specific to the indicated genes.

Total cell wall PDIM quantitation

Liquid chromatography-mass spectrometric quantitation of PDIM was performed on total cell wall extracts of Mtb according to published protocols [48]. In brief, Mtb strains were grown in 7H9 supplemented with Middlebrook OADC (BD) and glycerol 0.2%. Cells were then pelleted and extracted in chloroform:methanol and an equal quantity of total lipids were run through an established LC-MS protocol using an Agilent Technologies 6520 Accurate-Mass Q-Tof and a 1200 series HPLC system with a Monochrom diol column [48]. PDIM species were identified using positive mode MS based on predicted retention time [48], highly accurate mass matching to known PDIM species as listed in the figures, and confirmed based on collision-induced dissociation mass spectrometry with major fragments as listed in S1 Text.

Ethics statement

Protocols for care and use of mice for bone marrow macrophage preparation were approved by the Massachusetts General Hospital Institutional Animal Care and Use Committee. The approved protocol number is 2007N000048. The procedure for euthanasia approved as part of this protocol is in accordance with American Veterinary Medical Association Guidelines for the Euthanasia of Animals.