Tissue dual RNA-seq allows fast discovery ofinfection-specific functions and riboregulatorsshaping host–pathogen transcriptomesAaron M. Nussa,1, Michael Beckstettea,1, Maria Pimenovaa, Carina Schmühla, Wiebke Opitza, Fabio Pisanoa,Ann Kathrin Herovena, and Petra Derscha,2

aDepartment of Molecular Infection Biology, Helmholtz Centre for Infection Research, 38124 Braunschweig, Germany

Edited by Ralph R. Isberg, Howard Hughes Medical Institute/Tufts University School of Medicine, Boston, MA, and approved December 19, 2016 (received forreview August 14, 2016)

Pathogenic bacteria need to rapidly adjust their virulence and fitnessprogram to prevent eradication by the host. So far, underlyingadaptation processes that drive pathogenesis have mostly beenstudied in vitro, neglecting the true complexity of host-inducedstimuli acting on the invading pathogen. In this study, we developedan unbiased experimental approach that allows simultaneous mon-itoring of genome-wide infection-linked transcriptional alterations ofthe host and colonizing extracellular pathogens. Using this tool forYersinia pseudotuberculosis-infected lymphatic tissues, we revealednumerous alterations of host transcripts associated with inflamma-tory and acute-phase responses, coagulative activities, and transitionmetal ion sequestration, highlighting that the immune response isdominated by infiltrating neutrophils and elicits a mixed TH17/TH1response. In consequence, the pathogen’s response is mainly di-rected to prevent phagocytic attacks. Yersinia up-regulates the geneand expression dose of the antiphagocytic type III secretion system(T3SS) and induces functions counteracting neutrophil-induced iondeprivation, radical stress, and nutritional restraints. Several con-served bacterial riboregulators were identified that impacted thisresponse. The strongest influence on virulence was found for theloss of the carbon storage regulator (Csr) system, which is shownto be essential for the up-regulation of the T3SS on host cell contact.In summary, our established approach provides a powerful tool forthe discovery of infection-specific stimuli, induced host and pathogenresponses, and underlying regulatory processes.

tissue dual RNA-seq | host–pathogen interaction | host-adaptedmetabolism | noncoding RNAs | Yersinia

All bacterial pathogens encounter rapidly changing environ-mental conditions and adverse host reactions during the

course of infection. Accordingly, a dynamic cascade of events isinitiated that triggers a global alteration of gene expression pat-terns in both interacting organisms to adapt for survival. Moni-toring these infection-linked transcriptome alterations representsa powerful approach to identify virulence-related factors andregulatory processes that drive pathogenesis. Over the past years,RNA sequencing (RNA-seq) technologies have revolutionized theanalyses of transcriptomes by enabling a highly accurate andsensitive transcriptional profiling on single-nucleotide resolution.Moreover, RNA-seq has permitted the identification of sensoryRNA elements and numerous noncoding RNAs (ncRNAs) inpathogenic bacteria. A small subset of the few already character-ized riboregulators was found to contribute to pathogenesis (1–3).Most global gene expression studies of pathogens relied on

laboratory growth conditions, which mimic certain host environ-ments (4–6). Only a few RNA-seq studies have used cell culturesystems or fluids of infected animals to profile pathogen geneexpression in vivo, but they have commonly neglected the hostresponse (7–9). Consequently, our knowledge about the temporalevents and gene expression changes in both the pathogen and thehost that drive pathogenesis is still very limited.

The recent development of “dual RNA-seq” (using probe-in-dependent parallel cDNA sequencing) now offers the possibility tosimultaneously profile RNA expression in the pathogen and in-fected host cells (10). Taking advantage of this technology, high-resolution transcriptome profiles have lately been obtained fromHeLa cells invaded by Salmonella enterica serovar Typhimurium,primary human bronchial epithelial cells infected withHaemophilusinfluenza, and macrophages with intracellular Mycobacterium tu-berculosis (11–13). These studies not only revealed novel insightsinto pathogen–host cell cross-talk, but they also illustrated theimportance of ncRNAs for fine-tuned intracellular bacterial geneexpression and how it manipulates host cells.As a major drawback, this approach does not address patho-

gens that live and replicate in extracellular spaces either withintissues or on the surface of the epithelia that line body cavitiesduring the natural course of an infection. Moreover, although cellculture models are immensely useful for dissecting out pathwaysand the molecular details, they exclude the influence of the hostimmune response and cannot substitute for the whole-animal/tissue context. To overcome this limitation, we established a fast,generic tissue dual RNA-seq approach, which allows compre-hensive and simultaneous monitoring of infection-linked geneexpression changes of the infected host and the colonizing

Significance

Our knowledge of the functions required by extracellular bac-terial pathogens to grow in host tissues is still limited. Mostavailable information refers to studies conducted under labora-tory growth conditions that mimic host environments but ex-clude the influence of the host immune system. Tissue dual RNAsequencing allows simultaneous transcript profiling of a patho-gen and its infected host. This sensitive approach led to theidentification of host immune responses and virulence-relevantbacterial functions that were not previously reported in thecontext of a Yersinia infection. Application of this tool will allowtranscript profiling of other pathogens to unravel concealedgene functions that are crucial for survival in different hostniches and will improve identification of potential drug targets.

Author contributions: A.M.N., M.B., and P.D. designed research; A.M.N., M.B., M.P., C.S.,W.O., F.P., A.K.H., and P.D. performed research; A.M.N., M.B., M.P., C.S., W.O., A.K.H., andP.D. analyzed data; and A.M.N., M.B., and P.D. wrote the paper.

The authors declare no conflict of interest.

This article is a PNAS Direct Submission.

Data deposition: The raw high-throughput read data have been deposited as FASTQ filesin the European Nucleotide Archive (ENA; accession no. PRJEB14242). Split and processedFASTQ files as well as corresponding BAM files have been deposited in the ENA (accessionno. PRJEB17683).1A.M.N. and M.B. contributed equally to this work.2To whom correspondence should be addressed. Email: petra.dersch@helmholtz-hzi.de.

This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1613405114/-/DCSupplemental.

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pathogen. In contrast to traditional microarray-based studies, thisapproach is species-independent (i.e., it does not require the time-consuming design of pathogen- and host-specific custom chips)and can concurrently capture the full-transcript repertoire of thepathogen and the host. We successfully applied this method toinvestigate the global gene expression pattern of the enteropatho-genic bacterium Yersinia pseudotuberculosis growing extracellularlyin the gut-associated lymphoid follicles (Peyer’s patches) of in-fected mice. The obtained high-resolution transcriptomes con-firmed known host–pathogen interactions and revealed insightsinto infection-specific stimuli that induce host responses andprovoke bacterial gene expression driving pathogenesis. Collec-tively, our findings show that tissue dual RNA-seq is a fast andpowerful tool that can be applied to a broad range of bacteriaand host tissues/organs to discover virulence-related functionsand defense reactions of the host.

Results and DiscussionTissue Dual RNA-Seq of Y. pseudotuberculosis-Infected Peyer’s Patches.We established tissue dual RNA-seq using Y. pseudotuberculosisproliferating in the gut-associated lymphoid tissue (Peyer’s patches)of infected mice. The Peyer’s patch is the primary replication site ofenteropathogenic yersiniae after transcytosis of the intestinal epi-thelium. Inside the Peyer’s patches, the bacteria replicate extracel-lularly to high numbers (107–108 cfu/g tissue) (14). A striking featureof the pathology of an enteric Yersinia infection is inflammation ofthe intestinal tissue. The murine infection model, which mimics allaspects of the human disease, has been proven extremely valuablefor the characterization of host responses (e.g., cytokine signalingpathways) involved in infection control (15–17). The well-definedhost response associated with the colonization of the Peyer’spatches (mainly obtained with Yersinia enterocolitica) will allow us toprove the validity of our approach and helps to reveal different andhidden pathogen-triggered host reactions.In our tissue dual RNA-seq approach, we systematically cata-

loged (i) the transcriptome of Y. pseudotuberculosis strain IP32953grown in murine Peyer’s patches or under different laboratorygrowth conditions in vitro and (ii) the host transcriptome of un-infected and infected mice (Fig. 1A). To simultaneously capturepathogen and host transcripts, high-quality total RNA was isolatedfrom Peyer’s patches 3 d postinfection (SI Appendix, Fig. S1A).Mouse rRNA, which represents the major RNA species within invivo RNA pools, was depleted to increase coverage of informativemouse and bacterial transcripts (Fig. 1A). Commercially availableRNA spike-in mixes covering a 106-fold concentration range wereadded to RNA pools from infected and uninfected tissues to de-termine the dynamic range within a sample and test for accuratefold change responses between different biological treatments(Fig. 1A and SI Appendix, Fig. S1 B and C) (18). Subsequentstrand-specific Illumina-based deep sequencing (SI Appendix)generated ∼201 million cDNA reads from biological triplicatecDNA libraries of infected Peyer’s patches (Dataset S1). About148 million reads mapped to the mm10 genome, whereas morethan 8.5 million cDNA reads mapped to the Y. pseudotuberculosisgenome. From cDNA libraries of uninfected Peyer’s patches,∼114 million reads were generated, of which 87 million mapped totheMus musculusmm10 genome (Dataset S1). Between ∼230,000and 1.6 million uniquely mapped reads for the pathogen (grown invivo and in vitro) and between 19 and 68 million mapped reads forthe host were obtained from cDNA libraries, providing sufficientcoverage for robust RNA profiling (Fig. 1B and Dataset S1) (19,20). By using stringent filter criteria, we observed linearity betweenthe read density and RNA input over the entire detection range ofaround 12 log2 units concentration (SI Appendix, Fig. S1B). Thisspan was sufficient to reliably quantify and compare transcriptabundance across a wide dynamic range (19, 20). Highly accuratefold change estimates are visualized by the linear fit (SI Appendix,Fig. S1C). Host and pathogen global gene expression profiles were

distinct, and profiles of the three biological triplicates clusteredtogether (Fig. 1 C and D). Normalized read counts for all detectedmouse (SI Appendix, Fig. S2A) or Yersinia (SI Appendix, Fig. S2B)genes were plotted for the three biological replicates, and thePearson correlation coefficient (r) is indicated. All samples closelycorrelated with their respective replicates from the same biologicalsample group (r > 0.9). For Yersinia, 1,312 transcriptional startsites of mRNAs (mTSSs) were mapped (Dataset S2), and 129trans-encoded small ncRNAs, 45 antisense RNAs, and 233′-UTR–derived RNAs (Dataset S2) were identified. The 5′-UTRsize distribution of mRNAs, the transcriptional start site (TSS)nucleotide use, and the core promoter structure are highly similarto Y. pseudotuberculosis YPIII (SI Appendix, Fig. S3) (5) andconsistent with reports in Escherichia coli and Salmonella (21, 22).

Yersinia-Induced Host Responses. The host gene expression profilewas calculated by the differential expression analysis packageDESeq2 (23), and genes showing statistically significant changesin the expression level by at least fourfold were considered. Of19,993 profiled host transcripts, 1,336 were significantly alteredin abundance within infected Peyer’s patches (Fig. 2A andDataset S3). Although 448 transcripts were more abundant as aresponse to the bacterial infection, 888 were less abundant (re-ferred to as infection “induced” or “repressed” genes). As aconsequence of the Yersinia infection, significant alterations inthe host transcriptome were evident, with many of the highlyinduced genes being associated with (i) inflammatory responses,(ii) acute-phase responses, (iii) coagulative activities, and (iv)

Fig. 1. Tissue dual RNA-seq workflow and global reports. (A) For tissue dualRNA-seq, female BALB/c mice were orally infected with 2 × 108 cfu Y. pseu-dotuberculosis IP32953 (infected) or 1× PBS (uninfected). For in vitro RNA-seq,IP32953 was grown in LB to exponential or stationary phase at 25 °C or 37 °C.Total RNA was isolated from Peyer’s patches of mice or bacterial culturesprocessed for preparation of strand-specific barcoded cDNA libraries and se-quenced (SI Appendix). cDNA reads were separated in silico by mapping to themm10 and the IP32953 genomes. TAP, tobacco acid pyrophosphatase. (B)Circos plot visualizing reads per kilobase transcript length per million mappedreads-normalized expression values of in vitro and in vivo RNA-seq datafor the IP32953 chromosome (NC_006155.1) and pYV virulence plasmid(NC_006153.2). E25, exponential phase 25 °C; E37, exponential phase 37 °C; invivo, infected Peyer’s patches; S25, stationary phase 25 °C; S37, stationaryphase 37 °C. (C) Heat map of Euclidian sample distances of rlog-transformedread counts for triplicate mouse RNA-seq data from RNA pools of uninfectedand infected Peyer’s patches. (D) Principal component (PC) analysis of meancentered and scaled rlog-transformed read count values of bacterial in vitroand in vivo RNA-seq data for the Y. pseudotuberculosis IP32953 core genomeand the pYV virulence plasmid.

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transition metal ion sequestration, which are among the topenriched pathways (Fig. 2B and Dataset S3). Detected changes inthe abundance of host transcripts reflect expression changes butalso, variations in the cell composition of the infected tissues (e.g.,because of infiltrating immune cells). DESeq2 estimated foldchange responses of selected host transcripts were confirmed byquantitative RT-PCR (qRT-PCR) (SI Appendix, Fig. S4A).Inflammatory responses. Because inflammation is a hallmark ofYersinia infection, it was expected that various transcripts forhost immunomodulatory proteins would be strongly enriched ininfected Peyer’s patches (Fig. 2B and Dataset S3). The pattern ofup-regulated inflammatory cytokines/chemokine receptors andstrong enrichment of neutrophil-specific transcripts (e.g., stefinA/cystatin A, prokineticin 2, Schlafen 4, Fpr1, and Clec4e) in-volved in neutrophil mobilization, neutrophil-mediated phago-cytosis, and neutrophil extracellular traps formation (24–26)highlight that the host immune response is dominated by in-filtrating neutrophils (Dataset S3). This finding is consistent withprevious observations that the number of neutrophils withinmurine Peyer’s patches increases ∼100-fold (14). Among thehighest infection-induced immunomodulatory genes were thoseof the major proinflammatory cytokines (IL-1α, IL-1β, IL-6, IL-17F, and IFN-γ) and the chemokines (CCL2, CXCL1, CXCL2,

CXCL3, CXCL5, and CXCL10). They were previously shownto be strongly up-regulated in Peyer’s patches infected with Y.enterocolitica and/or lymph nodes infected with Yersinia pestis andcontribute to the pathology of Yersiniosis and plague (16, 17, 27–29). However, many up-regulated chemokine/lymphokine recep-tors and immune cell signaling molecules have not yet been de-scribed in the context of a Yersinia infection (Dataset S3). Of thoselisted, IL-22 and IL-23a are known to enhance innate and adaptiveimmune responses (30, 31). Others (e.g., IL-19 and IL-27) quenchthe inflammatory effects, similar to IL-10, IL-11, the IL-1 receptorantagonist IL-1Ra, and the decoy receptor IL-1R2, which se-quester and inhibit IL-1 (32, 33). Overall, high induction of TH17-type cytokines (IL-17, IL-6, IL-1, and IL-23) and enrichment ofthe TH1-type cytokine IFN-γ suggest that Y. pseudotuberculosistriggers adaptive immunity toward a mixed TH17/TH1 response.Acute-phase response. Another specific cluster of enriched tran-scripts is part of the acute-phase response—a complex systemicreaction activated by trauma, infection, and inflammation withthe goal of clearing potential pathogens, reestablishing homeo-stasis, and promoting healing (34). This cluster encompassesmainly the serum amyloids A2, A3, A4, and P (Fig. 2B andDataset S3), which contribute to intestinal immunity. Serumamyloids are up-regulated by proinflammatory signals (e.g., IL-1,

Fig. 2. The host’s transcriptional response to Y. pseudotuberculosis. (A) Volcano plot obtained from DESeq2 analysis of uninfected and infected Peyer’spatches RNA pools. (B) Heat map of the top 50 enriched and depleted host transcripts. Color-coding is based on rlog-transformed read count values.(C) Infection-mediated activation of extrinsic tissue factor-dependent coagulation cascade genes. On IP32953 colonization, extrinsic coagulation cascadetranscripts are highly enriched in infected Peyer’s patches. Fibrin clotting is typically induced by bacterial antigens, such as LPS, to trap the invading bacteriaand prevent further dissemination. In addition, stimulation of the extrinsic coagulation pathway is triggered by the neutrophil-specific collagenase MMP8,which activates the tissue factor via cleavage of TFPI.

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TNF-α, and IL-6), which are increased during Yersinia infection.They participate in the systemic modulation of innate and adaptiveimmune responses (e.g., TH17 responses and migration/activationof monocytes, neutrophils, and T cells) (35–38). Moreover, they haveantimicrobial activity and induce expression of matrix metal-loproteases, chitinase-like proteins, and collagenases that arepivotal for tissue remodeling after injury (39). Transcripts of themetalloproteases MMP3 and MMP8 and the chitinase-like proteinsCHIL1 and CHIL3 were especially significantly enriched in Yersinia-infected Peyer’s patches (Fig. 2 and Dataset S3). A recent studyfurther showed that serum amyloid A binds and transports retinoids,which are induced in response to the infection (Dataset S3). Reti-noids promote maturation of immune cells, elicit TH17 responses,and facilitate the regeneration of damaged epithelial barriers (40, 41).Coagulative activities. Transcripts related to the coagulation cascadewere among the most enriched host messengers, encoding the co-agulation factors VII, X, XIIIa1, and FII; the α-, β-, and γ-subunitsof the acute-phase reactant fibrinogen (Fga, Fgb, and Fgg); andplasminogen (Plg) (Fig. 2 B and C and Dataset S3). In particular,factor VII, factor X, and fibrinogen transcripts were highlyenriched, suggesting that a Yersinia infection triggers activation ofthe tissue factor-dependent extrinsic coagulation cascade (Fig. 2C).Enhanced fibrin deposition was shown to physically trap invadingpathogens and limit their spread (42). Activation of the extrinsiccoagulation pathway by Y. pseudotuberculosis is further supported bythe vast accumulation of neutrophil-specific Mmp8 transcripts (Fig.2 and Dataset S3). MMP8 is stored in specific granules and releasedby neutrophils at sites of acute inflammation (43, 44). It contributesto activation of the extrinsic coagulation pathway because of itscapacity to cleave the tissue factor pathway inhibitor (TFPI), whichwas shown to obtain antibacterial activity on proteolytic processing(45, 46). Similarly, many other coagulation factors, including factorX and prothrombin, contain a catalytic domain at their C terminuswith antimicrobial activity after proteolytic processing (47). To date,it is unknown whether coagulation plays a protective role against aY. pseudotuberculosis infection. However, both plasminogen andfibrinogen have been identified as critical determinants of the in-flammatory response and survival after Y. pestis infection. Y. pestisinfections normally lead to formation of widespread foci containinglarge numbers of scattered bacteria with low numbers of infiltratedinflammatory cells and reduced fibrin deposition because of thepresence of the plasminogen activator gene pla (48–50). Thispathology is contrary to infections caused by Y. pseudotuberculosis,which lead to foci of densely packed bacterial microcolonies withmany surrounding inflammatory cells, primarily neutrophils (51,52). Formation of fibrin-rich matrices at the early stage of microbialinvasion seems to support recruitment and attachment of phago-cytizing cells as well as T cell-mediated responses that may help tocounteract a Yersinia infection (48–50). Impediment of the in-flammatory response, neutrophil recruitment, and reduced survivalof fibrin(ogen)-deficient mice after a Y. pestis infection underminethe role of fibrin(ogen) as a critical amplifier of the inflammatoryresponse and crucial determinant of the host defense againstpathogenic yersiniae (48, 53).Metal ion sequestration. Among the strongest induced host factors inthe infected lymphatic tissue are metal ion sequestration systems(Fig. 2 A and B and Dataset S3). Vertebrates sequester metalions from invading pathogens as a first line of defense against bac-terial infections, an antimicrobial strategy termed “nutritional im-munity” (54). Genes encoding the heme and iron-loadedsiderophore sequestration systems haptoglobin and lipocalin 2(LCN2) are >100-fold induced on infection; transcripts of lacto-transferrin and hemopexin were 7- and 14-fold enriched (Fig. 2 Aand B and Dataset S3). LCN2 is expressed and secreted in a Toll-likereceptor 4-dependent manner in response to TH17 cell-specificproinflammatory cytokines, such as IL-17 and IL-22 (55), whichare also up-regulated during the infection (Dataset S3). LCN2stimulates the secretion of neutrophil-attracting CXC chemokines

(55). Moreover, transcripts for the heterodimeric S100A8/S100A9complex were among the top 10 enriched messengers (83- to 190-fold) (Fig. 2B and Dataset S3). The S100A8/S100A9 complex, alsoknown as calprotectin, sequesters the essential trace elements zincand manganese (56, 57) and was found to be released from intestinalepithelial cells and infiltrating neutrophils during acute inflammation(55, 58, 59).In addition, expression of the immunoresponsive gene 1 (Irg1) and

the histidine decarboxylase gene (Hdc) was highly induced in re-sponse to a Y. pseudotuberculosis infection (Fig. 2B and Dataset S3).HDC is exclusively responsible for production of the biogenic aminehistamine. Histamine signaling via the histamine receptor 2 has beenpreviously reported to be important for controlling Y. enterocoliticacolonization in the Peyer’s patches, possibly through altering of cy-tokine production and disruption of the TH1–TH2 balance (60). TheIrg1 gene encodes an enzyme synthesizing the metabolite itaconatefrom the TCA cycle intermediate cis-aconitate. Its production isspecifically induced and highly expressed by macrophages on LPSactivation, and it is a potent inhibitor of isocitrate lyase, a key enzymeof the glyoxylate shunt, which is required for assimilation of fattyacids (61). Notably, Y. pestis and Y. pseudotuberculosis encode itaco-nate-degrading enzymes within the ripCBA operon (62), indicatingthat these bacteria evolved detoxification pathways to prevent itaco-nate-mediated growth inhibition. However, itaconate degradationand metabolism seem less relevant for Y. pseudotuberculosis duringPeyer’s patch colonization, because ripCBA transcripts (YPTB1926-1924) were barely detectable by RNA-seq (Dataset S4).Other than the identified up-regulated functions, 888 host

transcripts were strongly decreased during infection. A largenumber of down-regulated transcripts encode metabolic enzymes.Among them are several monooxygenases, in particular cyto-chrome P450 enzymes, solute carriers, and UDP-glucuronosyl-transferase systems, which convert lipophilic molecules intoexcretable compounds (Dataset S3). The infection-induced de-crease of these transcripts may simply reflect an overall shutdownof pivotal cellular functions in response to the infection. A down-regulation of monooxygenases was also observed in Y. enter-ocolitica-infected Peyer’s patches, which led to the assumption thatthey may reduce oxidative stress and minimize detrimental effects(63). Among the depleted transcripts are several that relate totransport and hydrolytic genes of dietary mono-/disaccharides (e.g.,glucose transporters: Slc5a4a, Slc5a11, Slc5a4b, Slc5a1, lactase,trehalase, and sucrose isomaltase) (Fig. 2B and Dataset S3), in-dicating Yersinia-mediated malnutrition. Based on the fact thatunabsorbed carbohydrates increase the flow of water and electro-lytes into the lumen (64), it is possible that a decrease of these

Fig. 3. Temperature as a major stimulus for virulence plasmid expression invivo. (A) Principal component (PC) analysis of reads per kilobase transcriptlength per million mapped reads-normalized expression values of in vitroand in vivo RNA-seq data for the IP32953 pYV virulence plasmid(NC_006153.2). (B) Percentage of pYV cDNA read counts obtained from invitro and in vivo RNA-seq data relative to the read counts obtained for thebacterial chromosome. Unpaired t test (n = 3). E25, exponential phase 25 °C;E37, exponential phase 37 °C; in vivo, infected Peyer’s patches; S25, sta-tionary phase 25 °C; S37, stationary phase 37 °C. **P ≤ 0.01; ***P ≤ 0.001.

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enzyme activities contributes to the intestinal disorders (diarrhea)associated with a Yersinia infection. Additional analysis of Yersinia-mediated alteration of individual transport functions in the brushborder and association with the intestinal disorders is required toconfirm this hypothesis.

The Host-Responsive mRNA Repertoire of Yersinia. To identify in-fection-specific gene expression alterations, which consequentlylead to the precise adjustment of virulence and fitness programs ofthe pathogen, we simultaneously profiled the entire transcriptionallandscape of Y. pseudotuberculosis during growth under laboratoryconditions (in vitro) and Peyer’s patch colonization (in vivo) (Fig.1A). The bacterial in vivo expression profile of chromosomalgenes was very distinct from all in vitro profiles (Fig. 1D), whereasprofiles of the virulence plasmid pYV from in vivo- and in vitro-grown bacteria at 37 °C were more alike (Fig. 3 and SI Appendix,Fig. S5 A and B). The Yersinia virulence plasmid pYV encodes theadhesin YadA, the Ysc type III secretion system (T3SS) and theeffectors called Yops, which are translocated by the T3SS mainlyinto neutrophils and macrophages on cell contact. The Yopsmodulate eukaryotic signaling pathways to counteract phagocy-

tosis and other immune responses, and they induce apoptosis ofthe infected host cell (65, 66).Expression of virulence factors. Similar mRNA profiles of the pYV-encoded virulence genes at 37 °C suggest that the thermal upshifton host entry is the primary signal triggering pYV gene expression.The overall ysc/yop mRNA level is further increased during colo-nization of Peyer’s patches (Fig. 3B and Dataset S4), showing thatadditional temperature-independent signals enhance pYV geneexpression (e.g., via host cell contact) (67). Notably, the levels of thecopB mRNA, encoding a negative regulator of the pYV replicasegene repA (68), were significantly decreased during infection(Dataset S4 and SI Appendix, Fig. S5 B and C). The ratio of repAtranscripts to its antisense RNA copA was strongly increased com-pared with bacteria grown at 37 °C. This transcriptional profile in-dicated that the replication of pYV is increased during Peyer’spatch colonization and supported a recent observation showing thatYersinia up-regulates the pYV copy number during infection (69).To explicitly unravel other transcriptional responses that allow

the bacteria to resist host defenses and replicate within extra-cellular lymphatic tissue compartments, we screened for tran-scripts that differed significantly in their abundance between

Fig. 4. Bacterial global gene expression analysis uncovers infection-specific metabolic adaptations. (A) Four-way Venn diagram illustrating Yersinia tran-scripts, which are significantly altered (log2fc ≥ 1; log2fc ≤ −1; adjusted P value ≤ 0.05) during Peyer’s patch colonization (in vivo); 283 transcripts were alteredin abundance in vivo compared with all four tested in vitro conditions, including those that were enriched under one condition and depleted under anothercondition. From those 283 transcripts, 116 were consistently enriched, and 62 were consistently depleted in vivo. E25, exponential phase 25 °C; E37, expo-nential phase 37 °C; in vivo, infected Peyer’s patches; S25, stationary phase 25 °C; S37, stationary phase 37 °C. (B) Heat map of selected bacterial transcriptsrelated to metabolic functions that are strictly enriched (red) or depleted (blue) during infection. Values represent the log2 fold change between indicatedconditions. (C) Central carbon metabolism of Y. pseudotuberculosis. Significant changes of the transcriptomic pattern between the in vitro- and in vivo-grownbacteria are indicated. Enriched transcripts during infection are given in red, and decreased transcripts are indicated in blue.

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in vitro and infection conditions (Fig. 4A, Datasets S4 and S5,and SI Appendix, Fig. S6). During Peyer’s patch colonization,97 mRNAs were consistently enriched, whereas 60 mRNAs wereconsistently depleted. Similar to host gene expression profiles,DESeq2-estimated fold change responses for selected bacterialmessenger and small ncRNAs were confirmed by qRT-PCR (SIAppendix, Fig. S4 B and C).Most of the differentially regulated transcripts encode stress

responses and host-adapted metabolic functions but not classicalvirulence factors (e.g., ail). Evidently, their expression is mainlytriggered by temperature and not triggered by infection-specificstimuli (Datasets S4 and S5).Host-induced bacterial stress responses. The bacterial in vivotranscriptome revealed that Yersinia is exposed to severe stressesduring Peyer’s patch colonization. The overall transcript abun-dance of important stress resistance genes (e.g., groEL/ES, dnaK,grpE, rpoS, and cspA/B/C/D) was high (Dataset S4). Moreover,several genes involved in detoxification of nitric oxide and otherreactive nitrogen species (e.g., nitric oxide dioxygenase: hmp;glutaredoxin: nrdH) were strongly up-regulated. This upregulationcounteracts induction of nitric oxide synthase 2 in the infectedtissue (Dataset S3). In contrast, classical oxidative stress-relatedtranscripts were not enriched (Datasets S4 and S5). This expres-sion profile suggests that Y. pseudotuberculosis is not exposed toreactive oxygen species produced by neutrophils and other innateimmune cells. However, a recent study showed that the produc-tion of multiple Yersinia catalases, superoxide dismutases, andthioredoxin (katA, sodB, sodC, and trxA) is controlled on theposttranscriptional level by thermoresponsive RNA structures(RNA thermometers) (70). They act as translational repressorelements at lower temperature but not at 37 °C, and they are thusnot detectable by conventional RNA-seq.The most strongly enriched bacterial transcripts in response to

host defense strategies are those implicated in metal ion acquisition(Fig. 4B and Datasets S4 and S5). The great majority encodes up-take systems for iron (e.g., heme uptake system: hmuPRSTUV;ferric/ferrous transporters: yfeABCDE; siderophore systems: fecCD,alcABC, fyuA-ybtUTE-irp1/2-ybtA-ybtPQXS, fcuA, rhbC, sfuB, tonB,and exbBD). Some also or specifically sequester zinc (znuA-znuCBand ybtPQXS) or manganese (mntH and yfeABCDE) (71), most ofwhich are well-known members of the Fur and Zur regulon. Thestrong increase of multiple redundant systems suggests that espe-cially the availability of iron and zinc is very limited within the in-fected tissue because of the induction of metal ion sequestrationand intracellular retention systems by the host (Fig. 2 A and B andDataset S3) (72).Another strategy to overcome metal ion scarcity in the bacteria

is the substitution of ion-containing proteins against nonion-con-taining homologs. The most striking example is the rpmE2J tran-script encoding the ribosomal subunits RpmE2 and RpmJ, one oftwo alternative L31 and L36 proteins, which showed the highestinduction (>300-fold) during infection (Datasets S4 and S5). Bothproteins lack zinc-binding sites in contrast to their paralogsencoded by YPTB0102 (RpmE) and YPTB3677 (RpmJ). Recentstudies in E. coli and Bacillus subtilis suggested that the zinc-containing RpmE protein is replaced by the highly overexpressednonzinc-containing paralog to mobilize zinc from ribosomes underzinc-limiting conditions (73, 74). A highly conserved Zur box wasidentified in the Y. pseudotuberculosis rpmE2 regulatory upstreamregion overlapping the rpmE2 TSS (mRNA mTSS_0385) (DatasetS2 and SI Appendix, Fig. S7A). We could show Zur-dependentexpression of the rpmE2J operon (SI Appendix, Fig. S7B). Thisfinding implies that a switch to RpmE2J-containing ribosomescontributes to the survival of the pathogen in low-zinc in vivoenvironments. However, despite the strong induction during in-fection, mouse survival and tissue colonization efficiency of thebacteria were not affected by a loss of both alternative ribosomalproteins (SI Appendix, Fig. S7 C and D). This observation illus-

trates that loss of a single-ion substitution system is insufficient toreduce pathogenesis. Most likely, it is compensated by the up-regulation of other alternative metal ion-independent metabolicfunctions and scavenging systems (Datasets S4 and S5).Host-adapted metabolism. Another prerequisite for the survival ofmany bacterial pathogens is the adaptation of their metabolism tothe nutrients available within the host tissue. We found thatyersiniae colonizing the Peyer’s patches use carbohydrates as theirprimary carbon source. Particularly, transcripts encoding the glu-cose, mannose (ptsGI/crr and manXYZ), fructose (fruBKA), andglucuronate (uxaABC) uptake systems as well as the upper part ofglycolysis (gapA, gmpA, eno, and pykF) were highly abundant orstrongly enriched during infection (Fig. 4B, Datasets S4 and S5,and SI Appendix, Fig. S8A). In agreement, an fruBKA deletionmutant was significantly impaired, and a pykF mutant was com-pletely outcompeted in Peyer’s patch colonization (SI Appendix,Fig. S8B) (75). A strong down-regulation of TCA cycle compo-nents (acnB, fumA, sdhCDAB, icdA, andmdh), fatty acid oxidationenzymes (fadBA, fadJ, and fadL), and cytochrome o ubiquinoloxidase (cyoABCDE), the terminal complex of the respiratorychain, coupled with a high and/or strongly enhanced in vivo ex-pression of fermentation genes (adhE, focA-pflB, and ldhA) sug-gest that pyruvate originating from glycolysis is reduced to ethanol,formate, and lactate (Fig. 4 B and C and Datasets S4 and S5).Parallel use of different fermentation pathways and expressionof rescuing alternative enzymes (YPTB0382, YPTB1517, andYPTB3387) seem to account for the fact that inactivation of thehighest induced adhE gene was insufficient to affect the outcomeof the infection (SI Appendix, Fig. S8B).Overall, the Y. pseudotuberculosis metabolism in Peyer’s patches

resembles that of Y. pestis during rat bubo colonization (76–78),indicating that the different lymphatic tissues constitute a similarnutritional environment, which requires comparable metabolicadaptations. Likewise to Y. pseudotuberculosis, Y. pestis was foundto strongly up-regulate homologous metal ion acquisition andnitrosative stress systems within bubos (76, 77). Similarly, simplecarbohydrates constitute the main carbon source that is metabolizedto pyruvate and then, redirected to anaerobic energy productionpathways because of the down-regulation of the TCA cycle. How-ever, in contrast to Y. pseudotuberculosis, fructose and mannose arenot important carbon sources for Y. pestis (76, 78). Moreover,Y. pestis seems to metabolize its energy sources mainly by anaerobicrespiration (e.g., by the dimethyl sulfoxide reductase DmsABC)(76). The dmsABC transcript was not detected at a significant levelin our study, indicating that these genes are not required forY. pseudotuberculosis during Peyer’s patch colonization.

Growth in Lymphatic Tissues Alters the Abundance of ConservedMetabolic ncRNAs. Previous in vitro studies identified numerousncRNAs in Y. pseudotuberculosis (5, 6). Many of them respond totemperature, but whether they contribute to virulence remainedlargely unknown. Our in vivo transcriptome analysis revealedthat the transcript of the general RNA chaperone Hfq as well asthat of the global regulator Crp, which controls large subsets ofncRNAs in Y. pseudotuberculosis (5, 6), changed significantlyduring infection compared with in vitro growth at 37 °C (DatasetS5). This result indicated that growth in lymphatic tissues altersthe abundance of regulatory RNAs. In fact, of 197 identifiedncRNAs (Dataset S2), 9 trans-encoded ncRNAs (Fig. 5A) wereat least twofold enriched in vivo compared with all in vitroconditions. Some Yersinia-specific in vivo-induced trans-encodedRNAs were identified [Ysr189(NU), Ysr206(NU), and Ysr310(NU)],but their overall expression level was rather low. In contrast, severalof the conserved ncRNAs (SgrS, RyhB1, and RyhB2), which werenot or were marginally expressed in vitro, were strongly up-regu-lated (20- to 250-fold) and highly abundant during infection (Fig. 5A and B).

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The sibling RNAs RyhB1/RyhB2 are both activated after ironscarcity by inactivation of the ferric uptake regulator Fur (79).Both ncRNAs are functionally redundant, but RyhB1 seemsslightly more sensitive to alterations of degradosome factors (79,80). They both regulate iron homeostasis by up-regulation ofiron-scavenging systems and repression of nonessential iron-containing proteins to liberate iron (79, 81). Notably, in E. coliand Salmonella, the RyhB RNAs were found to repress expres-sion of iron-containing TCA cycle enzymes, such as succinatedehydrogenase and fumarate reductase (sdhCDAB and frdABCD),fumerase (fumA), and aconitase (acnA and acnB), as well asthe respiratory-chain components (nuo and fdo) (81, 82). This

finding strongly suggests that they contribute to the down-regulation of the TCA cycle and respiration of Y. pseudotuber-culosis during infection.SgrS RNA homologs are found in several γ-proteobacteria,

including E. coli and Salmonella (83). SgrS production in thesebacteria is induced during accumulation of phosphosugars in thecytoplasm, a harmful growth-restricting condition referred to asglucose-phosphate stress (84, 85). The regulatory function ofSgrS involves translational repression and enhanced degradationof mRNAs encoding sugar transporters (ptsG, fruBKA, andmanXYZ), which are highly abundant in Yersinia during Peyer’spatch colonization (83, 86, 87). A deletion of sgrS restrictedgrowth of Y. pseudotuberculosis at 37 °C in the presence of theglucose-phosphate stress-inducing agent methyl α-D-glucoside(αMG) (Fig. 5C). This result showed that SgrS fulfills a similarfunction in Y. pseudotuberculosis, and its up-regulation in vivosupports our data identifying glucose and fructose as dominantcarbon sources during Peyer’s patch colonization.Another abundant in vivo–up-regulated ncRNA, GlmY, is in-

volved in cell wall synthesis. Together with its sibling ncRNAGlmZ, they regulate expression of the glucosamine-6-phosphatesynthase GlmS. Transcription of glmY is activated from a σ54-dependent promoter and controlled by the GlrR/GlrK two-component system, which plays a role in virulence (88, 89).High abundance and strong in vivo induction of the important

metabolic ncRNAs SgrS, RyhB1/RyhB2, and GlmY prompted us totest their role for virulence. The lack of GlmY, SgrS, or RyhB1/2 did

Fig. 5. Highly conserved bacterial ncRNAs contribute to pathogenesis. (A) Heatmap of in vivo-enriched (red) and -depleted (blue) trans-encoded bacterialncRNAs. Values represent the log2 fold change of indicated conditions (ad-justed P value ≤ 0.05). (B) Read coverage of the RNA-seq analysis of the sgrS,ryhB1, ryhB2, and glmY loci is illustrated in the Integrated Genome Browser(99). The data were normalized according to the number of uniquely mappedreads. E25, exponential phase 25 °C; E37, exponential phase 37 °C; in vivo, in-fected Peyer’s patches; S25, stationary phase 25 °C; S37, stationary phase 37 °C.(C) Y. pseudotuberculosis WT strain IP32953 and the isogenic ΔsgrS strain weregrown in LB at 37 °C in the presence or absence of 1% αMG, a glucose-phos-phate stress-inducing agent. (D) Two independent groups of BALB/c mice(2 × n = 5 per group) were orally infected with an equal mixture of 107 cfuIP32953 (WT) and the isogenic mutant YPIP56 (ΔsgrS/ryhB1/ryhB2/glmY). Dataare graphed as competitive index values for tissue samples from one mouse inPeyer’s patches (PPs), mesenteric lymph nodes (MLNs), and organs after 3 days.A competitive index score of one denotes no difference in virulence comparedwith the WT. The statistical significance between the WT and the mutant wasdetermined by a Wilcoxon signed rank test. **P ≤ 0.01; ***P ≤ 0.001. Fig. 6. CsrA is crucial for virulence and mediates expression of T3SS. (A) Mice

were orally infected with 2 × 108 cfu Y. pseudotuberculosis WT strain YPIII orthe isogenic ΔcsrA strain. Survival of mice was monitored for 12 d in two in-dependent experiments with 2 × 10 mice per group for each genotype. ***P ≤0.001; log rank (Mantel–Cox) test. (B) BALB/c mice were orally infected with107 cfu Y. pseudotuberculosis YPIII WT or the isogenic ΔcsrA strain. Mice werekilled 3 d postinfection, and the numbers of bacteria in homogenized Peyer’spatches (PPs), mesenteric lymph nodes (MLNs), liver, and spleen was determined.Data from two independent experiments (2 × 5 mice per group) are presented.Statistical significances between the WT and mutants were determined by aMann–Whitney test. The detection limit is indicated by the dotted line. *P ≤0.05; **P ≤ 0.01; ***P ≤ 0.001. (C) TCA-precipitated supernatants or (D) Westernblots of whole-cell extracts of Y. pseudotuberculosis YPIII WT and the isogenicΔcsrA strain with and without the complementing csrA+ plasmid pAKH56grown at 37 °C in the absence of Ca2+ are shown. Yops, LcrF, and YadA iden-tified by (C) Coomassie blue staining or (D) Western blotting are indicated. Thenucleoid-associated protein H-NS was used as loading control.

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not have an effect or had only a very mild effect on host colonization(SI Appendix, Fig. S8C). This finding illustrates that the network ofcellular functions controlled by the ncRNAs is very robust, becausetheir individual loss can be easily compensated. In contrast, a dele-tion of all four ncRNA genes significantly impaired colonization ofthe Peyer’s patches and mesenteric lymph nodes (Fig. 5D), showingthat pathogenicity is reduced when their functions are eliminated.Within the entire ncRNA pool, only a set of five trans-encoded

RNAs was depleted in in vivo compared with in vitro growth (Fig.5A and Dataset S4). The most abundant ncRNAs are carbon storageregulator B (CsrB) and CsrC, of which CsrB showed the strongestdecrease under infection conditions (Fig. 5A and Dataset S4). De-crease of CsrB and CsrC levels is likely induced by the down-regu-lation of Crp and up-regulation of CsrD (Datasets S4 and S5). Crp isa known activator of csrB transcription, and CsrD is involved in theRNase E-mediated decay of CsrB and CsrC (90, 91). CsrB, CsrC,and the RNA-binding protein CsrA form the conserved Csr system,in which both Csr RNAs bind multiple CsrA molecules and preventCsrA interaction with other target mRNAs. The CsrA regulon ofEnterobacteriaceae is very complex and includes colonization factors,infection-linked metabolic processes, and physiological traits (92,93), indicating that an increase of active CsrA is important underinfection conditions. We tested a Y. pseudotuberculosis YPIII csrAmutant in the oral mouse model and found that mice infected with acsrA mutant did not develop any disease symptoms and remainedalive 14 d postinfection (Fig. 6A); 10- to 100-fold fewer bacteria wererecovered from the Peyer’s patches and mesenteric lymph nodes atday 3 postinfection, and no bacteria could be isolated from the liverand spleen (Fig. 6B), showing that CsrA is crucial for virulence.

Important Genes for Peyer’s Patch Colonization Are Part of the CsrARegulon. A comparison of genes that were differentially expressedduring infection with the previously defined CsrA regulon (75)revealed that CsrA governs numerous metabolic genes implicatedin the adaptation of Yersinia to the lymphatic environment. Wedetected a strongly reduced transcript abundance of pyruvate–TCA cycle genes (acs, sdhCDAB, icdA, fumA, and acnB) andfatty acid oxidation genes (fadAB, fadJ, and fadL) in vivo, whichare repressed by CsrA, and a high abundance of the adhEmRNA, which is activated by CsrA (Datasets S4 and S5) (75).This finding suggests that adjustment of the CsrABC levelsduring infection plays a crucial role for the adaptation of thebiological fitness during host tissue colonization.The strong attenuation of a csrA mutant also indicated that

essential virulence functions (e.g., T3SS/yop genes) are abolishedin the absence of CsrA. To test this hypothesis, we investigated the

influence of CsrA on Yop secretion using Ca2+ limitation as asubstitute for cell contact. Ca2+ depletion stimulated secretion ofYops (Fig. 6C) by the Y. pseudotuberculosis WT strain YPIII butnot by the isogenic csrAmutant. Moreover, levels of the T3SS/Yopregulator LcrF and the adhesin YadA were not increased or onlyslightly increased in the absence of CsrA on Ca2+ depletion (Fig.6D). The WT phenotype could be restored by csrA expression intrans, indicating that Yop/YadA expression indeed requires CsrA,which promotes induction of LcrF synthesis on host cell contact.This observation provides evidence that CsrA not only affects thebacterial metabolic fitness but also, is crucial for type III secretionand pathogenesis during colonization of the Peyer’s patches.

ConclusionsOne key feature of this work is the ability to simultaneously cap-ture the RNA expression profile of the extracellular pathogenYersinia and its mammalian host during infection. The establishedtissue dual RNA-seq approach generated a comprehensive, high-resolution transcriptomic dataset that (i) enabled us to identifyimmune reactions directed against the pathogen and opposedresponses of Yersinia at one time point of the infection that drivepathogenesis with high statistical confidence and (ii) allowed us todiscover infection-specific stimuli and bacterial riboregulatorsshaping host–pathogen interactions. Future studies includingearlier and later stages of the infection will provide valuable in-formation about the dynamics of gene expression changes in thepathogen and its host during the course of an infection. Thebacterial load within infected tissues is the most limiting factor fortissue dual RNA-seq, and transcripts with very low abundancemight have been missed. However, ongoing improvements insampling, library preparation, and high-throughput sequencingtechnologies will very likely allow a more sensitive detection andanalysis of expression changes in less colonized host tissues in thenear future. Moreover, single-cell RNA-seq (94, 95) will enable usto elucidate the transcriptional response of individual host celltypes or different bacterial species (e.g., other enteric pathogensand intestinal microbiota) and dissect heterogeneity of bacterialand host cell subpopulations during the infection.Our data on Y. pseudotuberculosis revealed many similarities

but also marked differences in the host response to infection withits close relatives Y. enterocolitica and Y. pestis (29, 63). Specifi-cally, integration of the strong enrichment of neutrophil-specifictranscripts for antimicrobial defense and immune cell dynamicsduring infection illustrates that the immune response directedagainst Y. pseudotuberculosis is dominated by the massive re-cruitment and activation of neutrophils and steers adaptive

Fig. 7. Infection-specific changes of the Yersinia–host transcriptomes. Schematic overview of the complex transcript-based adaptations of Y. pseudotu-berculosis and the host during colonization of Peyer’s patches. The most strongly affected inflammatory and acute-phase responses, metabolic and virulenceadaptations, and identified differentially regulated bacterial riboregulators with impact on pathogenesis are illustrated. DC, dendritic cell; NK, natural killercell; NO, nitric oxide; PMN, polymorphonuclear leukocyte.

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immunity primarily to TH1 and TH17 responses (Fig. 7). Thisresponse coincides with an induction of the extrinsic coagulationcascade, shown to form fibrin-rich matrices that encase thebacteria to hamper dissemination and enhance bacterial clear-ance (42, 51). Consequently, the most important defensemechanism of the bacteria is to adjust to the stressful conditionsand counteract neutrophil attack within fibrin clots.Accordingly, the pathogen’s transcriptional response is charac-

terized by a marked up-regulation of the antiphagocytic T3SS/Yopmachinery in response to temperature and an increase of the vir-ulence plasmid copy number, which is likely triggered by host cellcontact (69, 96). This defense strategy is supported by the inductionof radical detoxifying genes, such as hmp (Fig. 7).In addition to the immune defense mechanisms, in vivo growth

of Yersinia is also accompanied by a strong up-regulation of Fe/Zn/Mn sequestration/uptake systems and a readjustment of metabolicfunctions that allows the pathogen to overcome host-imposed ionand nutrient constraints (Fig. 7). The plethora of up-regulatedredundant ion acquisition systems reflects the high importance ofthis process to prevent pertinent host measures to restrict bacterialgrowth. It also illustrates the difficulties that interfere with thisprocess by target-directed antimicrobial therapies.Our data further suggest that Yersinia assesses and uses a number

of diverse nutrients, especially simple sugars, which likely originatefrom dying cells in the infected tissue (97) and remain available be-cause of the overall reduction of host cell sugar carriers (Fig. 7). Theyare metabolized to pyruvate and converted by anaerobic fermenta-tion into a variable mixture of short-chain fatty acids. This metabolicdiversity relieves Yersinia dependence on a particular energy sourceand improves survival when individual nutrients are scarce or fluc-tuating during the infection process. It further explains the remark-able robustness of the pathogen’s metabolism against internalperturbations but pinpoints limited possibilities for antimicrobialtargets (e.g., the phosphoenolpyruvate/pyruvate-acetyl-CoA node).Furthermore, our data provide an overall view of the ncRNA

expression profile within lymphatic tissue, which offers a uniqueresource for the identification of important riboregulators duringinfection. We show that a successful host infection by Y. pseu-

dotuberculosis relies on the combined action of several highlyexpressed, conserved ncRNAs, with abundance that is adjustedin response to ion/nutrient availability under infection conditionsand/or by the global ncRNA regulators Hfq and Crp. In partic-ular, adjustment of the activity of the global RNA regulator CsrAvia the ncRNAs CsrB and CsrC is crucial for virulence. Otherthan its vital role in the regulation of carbon metabolism (75)and invasin gene expression (98), we show that CsrA is essentialfor Yop synthesis and secretion to defend against attacks ofsurrounding phagocytic cells during later stages of the infection.In summary, these findings argue for the usefulness of the

established tissue dual RNA-seq approach to derive meaningfulconclusions related to pathogen biology and host response that af-fect the outcome of an infection. The integration of obtained RNAprofile information with data of immune cell migration and bacte-rial pathogenesis offers insights into the complex host–pathogeninteraction network and developing disease. It further createspossibilities to identify critical processes that govern pathogencolonization and increase the potential to identify targets forantimicrobial therapies.

Materials and MethodsDetails on methodologies are provided in SI Appendix and include bacterialgrowth conditions, DNA cloning procedures and mutant constructions,analysis of reporter gene expression, Yop synthesis and secretion assays,animal experiments, RNA isolation, qRT-PCR, cDNA library preparation, readmapping, bioinformatics, and statistics. The custom annotation file includingidentified ncRNAs is given in Dataset S6. The animal protocols wereapproved by the Niedersächsisches Landesamt für Verbraucherschutz undLebensmittelsicherheit: permission no. 33.9.42502-04-12/1010.

ACKNOWLEDGMENTS. We thank M. Fenner for discussions and W. Weigelfor critical reading of the manuscript. We also thank R. Steinmann, M. Kroll,M. Schoof, W. Heine, O. Goldmann, and J. Reinkensmeier for tools andexperimental and bioinformatics support and K. Paduch and T. Krause fortechnical assistance. This work was supported from German Research Foun-dation Grants DE616/4 (to A.M.N.), DE616/6 (to A.M.N.), and SPP1617–YoungInvestigator Start Up Funding (to A.M.N.). M.P. and W.O. received fellow-ships from the Helmholtz Centre for Infection Research Graduate School.P.D. is supported by the German Center of Infection Research.

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