Host cyclophilin-mediated maturation of an obligate intracellular bacterial surface virulence factor

Host cyclophilin-mediated maturation of an obligate intracellular bacterial surface virulence factor | bioRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-M677548'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search New Results Host cyclophilin-mediated maturation of an obligate intracellular bacterial surface virulence factor View ORCID Profile Brandon Sit , View ORCID Profile Allen G. Sanderlin , View ORCID Profile Clara Y. Zhu , View ORCID Profile Lauren E. Bird , View ORCID Profile John G. Doench , View ORCID Profile Rebecca L. Lamason doi: https://doi.org/10.1101/2025.10.28.684717 Brandon Sit 1 Department of Biology, Massachusetts Institute of Technology , Cambridge, MA, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Brandon Sit For correspondence: sitb{at}mit.edu rlamason{at}mit.edu Allen G. Sanderlin 1 Department of Biology, Massachusetts Institute of Technology , Cambridge, MA, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Allen G. Sanderlin Clara Y. Zhu 1 Department of Biology, Massachusetts Institute of Technology , Cambridge, MA, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Clara Y. Zhu Lauren E. Bird 1 Department of Biology, Massachusetts Institute of Technology , Cambridge, MA, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Lauren E. Bird John G. Doench 2 Genetic Perturbation Platform, Broad Institute , Cambridge, MA, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for John G. Doench Rebecca L. Lamason 1 Department of Biology, Massachusetts Institute of Technology , Cambridge, MA, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Rebecca L. Lamason For correspondence: sitb{at}mit.edu rlamason{at}mit.edu Abstract Full Text Info/History Metrics Supplementary material Preview PDF Abstract Obligate intracellular bacterial pathogens cannot grow extracellularly, a trait that renders them highly understudied, but also endows them with unexpected host dependencies. Here, using the emerging obligate intracellular tickborne pathogen Rickettsia parkeri, we conducted a genome-scale CRISPR/Cas12a knockout infection screen to identify human cell determinants of rickettsial intracellular fitness. We discovered that the host peptidylprolyl isomerase cyclophilin A (PPIA/CypA), was essential for the formation of the R. parkeri actin tails that enable pathogen motility. PPIA localized to actin-associated bacterial poles and directly interacted with Sca2, the R. parkeri surface-exposed autotransporter chiefly responsible for actin tail nucleation. Sca2 bound PPIA through a domain implicated in surface translocation, and Sca2 failed to reach the R. parkeri surface in PPIA-deficient host cells. We propose that host PPIA enables Sca2 surface exposure during R. parkeri infection through a direct interkingdom protein maturation event, which represents an unexplored axis of the intracellular host-bacterial interface. Introduction Intracellular bacterial pathogens rely on numerous interactions with host factors to facilitate infection. These dependencies are particularly salient for obligate intracellular bacterial pathogens, which lack the ability to replicate extracellularly, leaving them entirely reliant on successful manipulation of the host cell for survival 1 . The concomitant loss of factors needed to thrive extracellularly and adaptation to the cytosolic niche has driven evolution of unique infection mechanisms and bacterial biology in obligate intracellular species. However, our understanding of these highly specialized bacteria lags well behind that of facultative intracellular species, primarily because of the lack of axenic culture systems and robust genetic perturbation tools that empower pathogen-directed investigations 2 . Extensive genomic fragmentation, gene loss, and sequence divergence in obligate intracellular species additionally impede in silico approaches to predict pathogen biology and host interactions 3 . Many obligate intracellular pathogens relevant to human health belong to Rickettsia , a Gram-negative genus responsible for a range of arthropod-borne vascular endothelial diseases with drastically increasing global burden 4 ( e.g. , Rocky Mountain spotted fever). Among the phylogenetically distinct subgroups of Rickettsia, the tick-borne spotted fever group (SFG) is increasingly recognized as an excellent model to probe how bacteria adapt to and infect the host cytosolic niche 5 . SFG rickettsial pathogens undergo an intracellular lifecycle that begins with host cell invasion followed by escape from the initial vacuole into the cytosol ( Fig. 1A ). There, SFG rickettsiae replicate and assemble tails of host actin that enable pathogen cytosolic motility, ultimately driving cell-to-cell spread and dissemination. Although the rickettsial lifecycle resembles that of other intracellular pathogens like Listeria monocytogenes , SFG Rickettsia spp. exhibit divergent underlying mechanisms of host interaction, likely due to their highly minimized genomes and specialized evolutionary trajectory 5 . This includes unique interactions with host receptors during invasion 6 , innate defense pathways 7 , and host cytoskeletal components that support actin-based motility and intercellular spread 8,9 . Despite recent progress in rickettsial genetic tools 10,11 , the traditional constraints of studying obligate intracellular pathogens still greatly limit our ability to probe how these species interact with and depend on their host cells. Download figure Open in new tab Figure 1. Genome-scale CRISPR/Cas12a screen for host determinants of R. parkeri infection. ( A ): Intracellular lifecycle of R. parkeri in mammalian cells. ( B ): Screen design and workflow. The top and bottom 10% fluorescence bins were sorted from infected libraries to identify human genes impacting Rp AausFP1 burden. ( C ): Waterfall plot of screen results. Mean log2 fold change (LFC) for gRNAs targeting each gene between screen replicates is plotted. Dashed lines correspond to LFC values with false discovery rates (FDR) <0.05. ( D ): Network analysis of hits with FDR 0.9 to another hit (solid lines) were not visualized. Colors correspond to DBSCAN-identified clusters, and dotted lines additionally denote cluster edges. The NCOA4 / CCDC6 cluster did not have a clear functional annotation. ( E ): Selected functionally related hits from cluster analysis and manual curation of screen results. All listed hits had LFC > 0.5 in the indicated direction. LCUFA: long-chain unsaturated fatty acids. ( F ): Hit validation with targeted enAsCas12a gene knockouts in A549s at 48 hpi with Rp AausFP1. Note RALA/B is a double knockout construct. Each point represents the relative geometric mean GFP intensity of a biological replicate compared to a matched non-target (NT) well processed on the same day. Given their intricate connections with host cell biology, intracellular microbial pathogens are ideal for studies that perturb the host to study the pathogen. High-throughput genetic perturbation technologies, chiefly CRISPR/Cas9, have accelerated the adoption of host genetic screens to study intracellular pathogens including viruses, bacteria, and parasites 12 . These approaches have been immensely fruitful in revealing both shared and unique aspects of microbial pathogenesis. For example, viral screens have enabled identification of shared and specialized host receptors for a wide range of viruses 13 . Since host-directed approaches circumvent the need for extensive pathogen genetic manipulation, they are particularly well-suited for studies of obligate intracellular bacterial pathogenesis. However, host-directed genetic screens have very rarely been used with obligate intracellular bacteria 14 , potentially due to technical barriers to infecting large host cell libraries, inadequate screening-compatible functional readouts, and a lack of defined methods for downstream mechanistic investigation of hits. Recent advances such as newer Cas enzymes like enAsCas12a aid the development of challenging screens by enabling multiplex gene targeting and reduced whole-genome library sizes 15 , ameliorating some of the obstacles associated with host-directed genetic screens for obligate intracellular bacteria. Here, we designed a Cas12a-based functional genomic screen to investigate SFG rickettsial infection at scale by genetically perturbing their host environment. Using the model SFG pathogen Rickettsia parkeri, we revealed the suite of host processes underlying infection in human cells. Validated hits comprised diverse host pathways such as lipid metabolism and histone modification, unveiling numerous novel host regulators of rickettsial infection for future investigation. We report that a host proline isomerase, PPIA (cyclophilin A), directly interacts with the R. parkeri actin-based motility factor Sca2 and enables its surface exposure, an unprecedented type of host-bacterial interaction and insight into prokaryotic outer membrane protein maturation. Our results emphasize the utility of using host genetics as a lens through which to perturb and explore the biology of obligate intracellular bacterial pathogens. Results Genome-scale identification of host determinants of R. parkeri fitness To identify human genes that influence pathogen fitness across the complex intracellular R. parkeri lifecycle ( Fig. 1A ), we designed a flow cytometry-based functional genetic screen to use fluorescence as a readout of bacterial burden in a pooled host knockout setting. We first screened R. parkeri strains expressing various fluorescent proteins to identify a suitable challenge strain. We found that R. parkeri expressing either TagBFP ( Rp BFP) or the bright GFP variant AausFP1 16 ( Rp AausFP1) had superior fluorescence compared to traditional GFPuv-expressing R. parkeri strains ( Fig. S1A ). However, the fluorescence of Rp BFP, but not Rp AausFP1, was completely quenched by methanol fixation, which can be preferrable to crosslinking fixation methods for sequencing-based screens ( Fig. S1B ). Rp AausFP1 was indistinguishable from WT R. parkeri in plaque assays and the fluorescence of infected host cells closely matched the signal from staining with an α- Rickettsia antibody ( Fig. S1C-E ). These data demonstrate that AausFP1 provides a faithful readout of R. parkeri burden and led us to select Rp AausFP1 as the challenge for the screen. We next used Rp AausFP1 to infect a genome-scale knockout library of A549 human epithelial cells stably expressing enAsCas12a ( Fig. 1B ). We reasoned that gRNAs enriched in the high or low fluorescence bins would represent host genes that normally restrain or promote R. parkeri fitness, respectively. We selected a Cas12a-based platform with tandem guide constructs that lower screen coverage requirements by ∼50% compared to Cas9 15 , substantially reducing the sorted bin sizes necessary for flow cytometry-based screens. At 48 hours post-infection (hpi), a timepoint where >95% of the host cell population was infected ( Fig. S1F-G and S2A ), host cells were fixed and the top and bottom 10% of infected cells were isolated by FACS and sequenced to identify host loci impacting R. parkeri burden. There was strong depletion of known essential genes in the input library, demonstrating Cas12a-based editing was robust in our system ( Fig. S2B ). In sorted samples, we also noted a low overall correlation between gRNA construct fold changes between the low and high fluorescence bins, a key expected characteristic of positive selection screens because of the lack of selective pressure on most gRNAs in the library 17 ( Fig. S2C ). By comparing gRNA fold changes in the high versus the low bins across two screen replicates, we identified 96 high and 113 low bin hits with corrected FDR < 0.05 ( Fig. 1C and Table S1 ). Cluster and manual analyses highlighted a wide range of hit functions, underscoring the breadth of host processes required for optimal R. parkeri infection ( Fig. 1D-E and Table S2 ). These included core host cell processes ( e.g ., chromatin regulation through the SAGA complex), metabolic pathways and intracellular trafficking mechanisms ( e.g. , exocytosis). Importantly, three components of the Arp2/3 actin nucleation complex ( ARPC2, ARPC4, and ACTR3 ) were identified as required for optimal R. parkeri infection. Prior work evaluating host cytoskeletal factor contributions to infection uncovered a role for Arp2/3 in promoting R. parkeri invasion, validating our untargeted screening approach 18 . Concordant sets of positive and negative hits in ceramide and triglyceride biosynthesis were particularly evident, as were genes specifically involved in long-chain unsaturated fatty acid biosynthesis ( Fig. 1E ), suggesting that the balance between competing arms of host lipid metabolism is a key regulator of intracellular R. parkeri fitness. This concept is consistent with prior lipid-targeted work in other cell types 19 and highlights the ability of the screen to identify functionally consistent hits. We next validated selected positive and negative hits by generating single gene knockout A549 pools with enAsCas12a and infecting them with Rp AausFP1. We focused on hits that were not already strongly selected in the input libraries, in order to enrich for host loci that directly regulate R. parkeri as opposed to exerting general effects on host cell fitness that would indirectly impact pathogen burden ( Fig. S2D ) As expected, knockout lines for hits in the low infection bin ( i.e. , required for infection) exhibited lower levels of Rp AausFP1 than non-target (NT) controls, and vice versa ( Fig. 1F ). Within the validated hits are numerous host loci that have not previously been described to contribute to rickettsial infection but have known roles in intracellular bacterial pathogenesis ( e.g. , EXOC7/8 20 and NHLRC2 21 ). We also validated hits that have not been associated with any other mammalian bacterial or microbial infection ( e.g., NF2 and CHP1 ). Surprisingly, one of the top hits from the screen, PPIA , validated in the opposite direction of its original bin ( Fig. 1F , rightmost). This unexpected observation prioritized PPIA for further investigation. PPIA is essential for R. parkeri intercellular spread and actin-based motility PPIA, also known as cyclophilin A or CypA, is a widely conserved peptidyl-prolyl isomerase that catalyzes cis-trans proline isomerization with numerous reported roles in host cell signaling and biology 22 . PPIA has been repeatedly implicated in host susceptibility to viral infections, particularly HIV-1, but its role in bacterial pathogenesis is not well understood 23 . No other members of the cyclophilin family were identified as hits, indicating PPIA has a specific contribution to R. parkeri infection. In flow cytometry of infected PPIA ko host cells, we noted a seemingly bimodal phenotype with a distinct infected subpopulation of hyper-infected cells, contrasting with the uniformly right-shifted phenotype of prototypical “high” bin hits ( e.g. , CHP1 ) ( Fig. 2A-B ). We hypothesized this phenotype could be explained by a reduction in pathogen intercellular spread, leading to buildup of R. parkeri in a small number of cells. This would explain why PPIA was a high bin hit in the screen, since selective accumulation of R. parkeri in PPIA ko cells would move this population into the high fluorescence population relative to cells with unrelated edits. Indeed, we observed a near-complete loss of pathogen spread between host cells in fluorescence microscopy of host cell monolayers sparsely infected with R. parkeri ( Fig. 2C-D ). Importantly, the bacterial number per cluster of infected host cells was unaltered, indicating PPIA is not required for R. parkeri replication ( Fig. 2E ). Re-expression of WT PPIA, but not a mutant lacking the key catalytic and substrate binding pocket residue 24 Arg55 (PPIA R55A ), completely rescued the spread phenotype ( Fig. 2C-D ), indicating that PPIA’s effect on R. parkeri infection requires its capacity to bind and isomerize substrates. Download figure Open in new tab Figure 2. Host PPIA is required for R. parkeri spread and actin-based motility. ( A ): Western blot confirming loss of PPIA in pools (KO) and clonal cell lines with rescue constructs. Data are representaive of two independent blots with cells from different passages. ( B ): Flow cytometry curves of CHP1 ko and PPIA ko cells infected with Rp AausFP1 at 48 hpi. Grey curves represent matched NT samples (same between knockouts). Curves are representative of n=3 biological replicates. Arrow indicates hyper-infected population in PPIA ko cells. ( C ): Spread assay of WT R. parkeri in NT and PPIA ko cell lines. Dashed lines outline representative infection foci. ( D and E ): Quantification of spread assays for number of host cells (D) and bacteria per focus (E). Means and s.d. from n=3 biological replicates are plotted. Means were used to calculate p-values (one-way ANOVA with Holm-Šídák multiple comparisons test). ( F ): Actin tails at 48 hpi in NT and PPIA ko cells infected with WT or sca2 ::Tn R. parkeri . Expected strain phenotypes are diagrammed on the right for reference. ( G ): Quantification of data from Panel F. Means and s.d. from n=3 biological replicates (>2000 bacteria counted per replicate) are plotted. Means were used to calculate p-values (Welch’s t-test). ( H ): Actin tails at 48 hpi in cells treated with varying concentrations of cyclosporin A (CsA) for 24 h, beginning at 24 hpi. Arrowheads highlight bacteria with actin tails. Images are representative of at least 3 biological replicates. The lack of R. parkeri spread in PPIA ko host cells resembles known phenotypes for R. parkeri lacking Sca2 ( sca2 ::Tn), the pathogen surface protein primarily responsible for actin tail nucleation and cytosolic motility 25,26 . Indeed, actin tails were completely absent in R. parkeri- infected PPIA ko host cells, phenocopying the loss of actin tails seen with sca2 ::Tn infections ( Fig. 2F-G ). Treatment of infected cells with known chemical inhibitors of PPIA (cyclosporin A (CsA) and NIM811) also blocked actin tail formation, orthogonally supporting a role for PPIA in this stage of infection ( Fig. 2H ). Importantly, inhibitors of the other two known families of proline isomerase, FK506 (FKBPs) and juglone (parvulins), did not affect actin tails ( Fig. S2A ), indicating that proline isomerization in general is not required for R. parkeri actin-based motility. We also observed actin tail loss in infected PPIA ko or CsA-treated human vascular endothelial-like cells (EA.hy926) ( Fig. S3B-D ), demonstrating this phenotype is conserved in the physiological target cell type of R. parkeri 27,28 . From these data, we concluded that host PPIA is essential for R. parkeri actin tail formation and subsequent cell-to-cell spread. PPIA localizes at the R. parkeri actin-associated pole To further understand the role of PPIA in actin-based motility, we asked where PPIA was localized during infection. For this question, we adopted a previously established approach from studies of PPIA localization to the HIV-1 capsid using PPIA fused to the tetrameric RFP derivative dsRed 29,30 . We modified this construct by replacing dsRed with dsRed-Express2 (dRE2), a variant with lower toxicity 31 . Strikingly, during R. parkeri infection of WT A549 cells harboring the fusion construct, we observed polar localization of PPIA-dRE2 in approximately 12% of bacteria at 48 hpi ( Fig. 3A-B ). Polar PPIA-dRE2 signal was associated with R. parkeri with and without actin tails, indicating PPIA does not require actin to localize to the bacterium. There was also no apparent PPIA-dRE2 enrichment along the actin tail itself or along stress fibers. Interestingly, in the subset of R. parkeri that had both polar PPIA-dRE2 signal and an actin tail, dRE2 signal localized to the actin-associated pole of the bacterium 97% of the time (88 out of 91 scored bacteria). Polar PPIA-dRE2 localization was lost in infected cells expressing PPIA R55A -dRE2 ( Fig. 3A-B ) or treated with CsA ( Fig. 3C-D ), suggesting that localization is dependent on PPIA activity and/or substrate binding. PPIA’s polar localization raised the possibility that it targets a substrate at the bacterial pole that contributes to actin-based motility. Based on prior evidence that the R. parkeri actin-nucleating factor Sca2 is heavily enriched at the actin-associated pole 25 , we hypothesized Sca2 may be the target of PPIA. Indeed, PPIA-dRE2 failed to localize to R. parkeri when cells were infected with sca2 ::Tn bacteria ( Fig. 3F-G ), implicating Sca2 as the mediator of PPIA recruitment to the R. parkeri pole. Download figure Open in new tab Figure 3. PPIA localizes to the R. parkeri actin-associated pole in a Sca2-dependent manner. ( A ): Localization of dsRed-Express2 (dRE2) constructs in clonal stably transduced A549s infected with WT R. parkeri at 48 hpi. Arrowheads highlight bacteria with polar PPIA-dRE2 signal. ( B ): Quantification of polar dRE2 signal frequencies from experiments in Panel A. ( C ): PPIA-dRE2 localization in infected A549s treated with 10μM CsA for 24 h at 24 hpi. ( D ): Quantification of data in Panel C. ( E ): PPIA-dRE2 localization in infections with sca2 ::Tn R. parkeri . ( F ): Quantification of data in Panel E. In B, D and F, means and s.d. from n=3 biological replicates are plotted (>1000 bacteria counted per replicate). Means were used to calculate p-values (one-way ANOVA with Holm-Šídák multiple comparisons test (B) or a Welch’s t-test (D and F)). Images are representative of n=3 biological replicates. PPIA interacts directly with the Sca2 passenger domain C-terminus Noting that Sca2 is required for PPIA localization and they co-occur at the actin-associated pole, we next hypothesized that the two proteins directly interact. Sca2 belongs to the autotransporter family of bacterial outer membrane proteins, which consist of an N-terminal passenger domain that is extruded to the surface by transit through a C-terminal β-barrel 32 ( Fig. 4A ). The Sca2 passenger domain has an atypical globular α-helical structure, rather than the β-solenoids that characterize model autotransporters ( Fig. S4A ). The domain comprises N-terminal sequences that mediate actin nucleation and a C-terminal region containing a C-repeat domain (CRD) that lacks a clearly defined function 33–36 . AlphaFold3 modeling of a PPIA-Sca2 interaction using the full R. parkeri Sca2 sequence revealed a high-confidence predicted interaction localized to the C-terminal region near the CRD (iPTM=0.73) ( Fig. 4B-C ). To test this prediction, we purified GST-tagged truncation constructs of R. parkeri Sca2 and used them for in vitro pulldowns with purified PPIA ( Fig. 4D ). As predicted, Sca2(34-1544, PD) containing the entire passenger domain pulled down PPIA. Sca2(34-1086, PDΔ), which lacks the C-terminal region, did not pull down PPIA, whereas a construct containing only this stretch of sequence did (Sca2(1086-1544), CRD) ( Fig. 4D ). These results demonstrate the necessity and sufficiency of the CRD-containing region for PPIA binding. Download figure Open in new tab Figure 4. PPIA interacts directly with the C-terminal passenger region of R. parkeri Sca2. ( A ): Domain diagram of R. parkeri Sca2. ( B ): Position-adjusted error (PAE) plot of the AlphaFold3 model of the full-length Sca2 and PPIA interaction. The region where the two proteins are predicted to interact is boxed in red. ( C ): Simplified diagram of Sca2 topology and predicted PPIA binding location. ( D-F ): Glutathione pulldowns of PPIA with GST-tagged Sca2, D - Sca2 domain constructs indicated in panel A, E - WT Sca2 and mutant PPIA, F - addition of 10-100μM cyclosporin A (CsA) to binding reaction. ( G ): Top: predicted PPIA-Sca2 (1086-1544) interaction. The two Gly-Pro sites are indicated in orange and PPIA is surface shaded. Bottom: schematic of C-terminal region and locations of the two Gly-Pro sites. ( H ): Glutathione pulldown with WT PPIA and fine-scale Sca2 CRD truncations indicated in panel G. * = non-specific band or possible spontaneous GST cleavage product. All images shown are Coomassie blue stained SDS-PAGE gels representative of at least 2 independent pulldowns. Canonical PPIA binding occurs via its main catalytic pocket, which contains several well-characterized residues that mediate both substrate binding and isomerase activity 37 . Of these, Arg55 is the most often targeted in loss-of-function studies, and we earlier demonstrated that this residue is required for PPIA’s control of R. parkeri spread ( Fig. 2C-D ). Using the glutathione pulldown assay, we found that purified PPIA R55A could not be pulled down by Sca2(1086-1544) ( Fig. 4E ). Furthermore, addition of the competitive PPIA inhibitor CsA, which binds the catalytic pocket, also blocked pulldown of WT PPIA ( Fig. 4F ). We concluded from these data that PPIA binds Sca2 through its primary binding pocket, suggesting that Sca2 may be an isomerization substrate of PPIA. None of the known proline-rich sequences in the N-terminal region 33 appear important for the predicted interaction or pulldown ( Fig. 4D ), indicating there is sequence-specific binding between PPIA and Sca2. PPIA binds a wide range of substrates with reported preference for sequences containing Gly-Pro dipeptides 38 . Sca2(1086-1544) harbors two Gly-Pro sequences in the CRD (residues 1192-1193 or 1284-1285), which are largely conserved in SFG Rickettsia spp. as well as other species in other Rickettsia subgroups ( Fig. S4B ). When only the CRD was used as the input for interaction prediction, PPIA was predicted to interact with the second Gly-Pro position at amino acids 1284-1285 (iPTM=0.85) ( Fig. 4G , S4C ). In the modelled structure, the Pro1285-containing loop extrudes into the PPIA catalytic pocket, where it makes contacts with critical PPIA residues including Arg55 24 ( Fig. S4D-E ). This interaction closely resembles the experimentally determined structure of PPIA’s long-known interaction with the HIV-1 capsid protein 39,40 ( Fig. S4E ). To investigate this prediction, we generated an additional series of CRD truncation constructs retaining one or neither of the two Gly-Pro sequences and indeed found that truncations lacking Gly1284-Pro1285 did not pull down PPIA as efficiently ( Fig. 4H ). Surprisingly, however, mutation of Gly or Pro in either or both Gly-Pro sequences within the Sca2 CRD did not block binding ( Fig. S4F-G ). Collectively, these data suggest that the PPIA-Sca2 CRD interaction may involve compensatory binding, a non-canonical PPIA binding site, or may depend on precise sequence context surrounding the putative Gly-Pro binding sites. Sca2 surface exposure requires host cell PPIA In model autotransporters, the passenger domain C-terminus is thought to exit the β-barrel first as a hairpin and undergo an early extracellular folding event critical for translocation of the remainder of the passenger domain 41–45 . Our finding that PPIA directly binds the Sca2 passenger C-terminal region therefore suggests that PPIA acts at the level of Sca2 surface exposure, explaining its requirement for actin tail formation. To test this idea, we leveraged our standard immunofluorescence staining protocol, which does not permeabilize R. parkeri and is thus a surface-selective procedure 46 . Using a validated α-Sca2 antibody raised against the first 500aa of the passenger domain 33 , we found that surface Sca2 was lost in R. parkeri -infected PPIA ko cells at 48 hpi ( Fig. 5A , left and Fig. 5B ). Importantly, bacteria lacking surface Sca2 staining still retained Sca2 protein, as subsequent permeabilization of R. parkeri with lysozyme revealed comparable total frequency and levels of Sca2 between PPIA ko and NT infections ( Fig. 5A , right, and Fig. 5B-C ). Total Sca2 levels were also unaltered in immunoblots of infected cells ( Fig. S5A ), suggesting PPIA specifically acts at the level of Sca2 surface exposure and not alternate mechanisms like transcriptional regulation or protein stability. Treatment of WT A549 cells with CsA or NIM811 blocked Sca2 surface exposure ( Fig. 5D ), orthogonally confirming the role of PPIA. To assess the dynamic nature of this process, we performed a washout experiment where we removed CsA at different times during infection. As little as 2 h of CsA washout enabled recovery of Sca2 surface exposure and actin tails ( Fig. S5B-C ), suggesting that the effects of the drug are transient and that Sca2 translocation can resume or is continually produced during infection. Together, these findings support a model where PPIA binds the Sca2 C-terminal passenger region during surface translocation, promoting its stabilization or folding and thus enabling passenger domain surface exposure ( Fig. 5E ). Download figure Open in new tab Figure 5. PPIA is required for surface exposure of Sca2. ( A ): Sca2 staining in lysozyme-treated or untreated NT or PPIA ko A549 cells infected with WT R. parkeri at 48 hpi. Left: non-permeabilized (surface staining only) samples. Right: permeabilized (total staining) samples. ( B ): Quantification of Sca2-positive bacteria in lysozyme-treated or untreated samples. ( C ): Quantification of Sca2 intensity in lysozyme-treated samples. Samples were normalized by dividing by the area of each bacterium. ( D ): Effect of 10μM CsA or NIM811 treatment on Sca2 surface levels during infection of WT A549 cells at 48 hpi. Arrowheads highlight bacteria with actin tails. Means and s.d. from n=3 biological replicates are plotted (>2000 bacteria counted per replicate). Means were used to calculate p-values (Welch’s t-test). Images are representative of n=3 biological replicates. ( E ): Proposed model of PPIA-enabled Sca2 surface translocation. PPIA binds the Sca2 CRD as it is exposed to the extracellular space, stabilizing or folding it and enabling extrusion of the remainder of the passenger domain, ultimately allowing actin tail nucleation. In the absence of PPIA, this process likely stalls at hairpin formation and the passenger domain is never exposed. Obligate intracellular pathogens lack endogenous PPIA homologues Cyclophilin proline isomerases are conserved across all domains of life. Most Gram-negative bacteria, such as E. coli , encode two cyclophilins (PpiA and PpiB) which respectively reside in the periplasm and cytosol 47 . Our observation that Sca2 surface exposure depends on the host cyclophilin PPIA suggested that species like R. parkeri may lack endogenous cyclophilin activity, instead relying on host-supplied factors like PPIA to participate in surface protein maturation. Through PFAM annotation searches with Annotree 48 , we indeed found that the cyclophilin family (cyclophilin type peptidyl-prolyl cis-trans isomerase/CLD, PF00160) is completely absent from not only R. parkeri , but all Rickettsia spp., despite broad conservation across Alphaproteobacteria ( Fig. 6 , Table S4 ). Striking, we also found that CLD-type isomerases also appear to be absent in every other known obligate intracellular bacterial pathogen, including those closely related to Rickettsia ( Orientia, Anaplasma, Ehrlichia ) and those from other bacterial phyla, including Gammaproteobacteria ( Coxiella burnetii ). In contrast, CLD-type isomerases were only absent from one genus of facultative intracellular pathogens ( Francisella ), and present in all others queried ( Listeria, Salmonella, Shigella, Mycobacterium ). This conservation pattern was restricted to cyclophilin-like domains and not proline isomerases in general, as predicted FKBP-type (PF00254) and parvulin-type (PF13145) isomerases are present and have been biochemically characterized in Rickettsia spp. 49 . Therefore, the absence of cyclophilin-type proline isomerases may be associated with obligate intracellular bacterial lifestyles. Download figure Open in new tab Figure 6. Cyclophilins are absent in obligate intracellular bacterial pathogens. Cladogram depicts relative evolutionary position between selected bacterial species representative of extracellular and facultative or obligate intracellular lifestyles. Species not known to be pathogenic to humans are marked with *. Species shaded in pink are obligate intracellular microbes. Branch lengths do not represent distances. Open and filled squares indicate the absence or presence, respectively, of each proline isomerase family. Strains included in the analysis are listed in Table S3. Discussion Obligate intracellular bacterial pathogens like R. parkeri continue to defy traditional bacteriological methods of investigation, constraining our knowledge of how these bacteria interface with host factors during infection. Using a host-directed functional genetic screen, we provided the first large-scale functional insight into host-pathogen interactions underlying SFG rickettsial infection. From the screen, we also identified a direct interaction between the host proline isomerase PPIA and the R. parkeri actin-nucleating factor Sca2. We found that Sca2 requires host PPIA for surface exposure, suggesting a new concept in host-bacterial interaction where host factors directly participate in pathogen surface protein maturation. Together, our data establishes a functional genetic platform for understanding obligate intracellular bacterial infection and emphasizes the utility of emerging model organisms like R. parkeri for understanding basic bacterial biology in the cytosolic niche. PPIA bidirectionally influences infection by viruses including HIV-1, HBV, and influenza by binding to viral proteins and shaping their function(s) 23 . However, its role in bacterial infection had remained enigmatic. Prior reports examining actin-targeting pathogens like enterohemorrhagic E. coli and L. monocytogenes have described varying effects on infection that all appear to be host-acting, without PPIA recruitment to the pathogen 50,51 . The only known direct intracellular interactions between host cyclophilins and bacterial factors involve secreted bacterial toxins 52,53 or effector proteins 54–56 . The PPIA-Sca2 interaction we discovered here is the first example of a host cyclophilin targeting the bacterial surface, which adds a key piece of evidence to an emerging model of PPIA as a central mediator of microbial infection outcome across plant and animal hosts 23 . Its surface-targeting mechanism also raises conceptual parallels between obligate intracellular bacteria and viruses, which are both completely dependent on the host cell to survive. The dependence of Sca2 surface exposure on PPIA indicates that actin tail formation and polymerization require pathogen-extrinsic factors. The broader idea that host proteins shape actin-based motility is not new, as organisms like L. monocytogenes and Shigella flexneri typically rely on host components and regulators of the actin cytoskeleton 57,58 or host-mediated phosphorylation of the bacterial factors in each species that target actin 59 . Our findings add to those strategies by demonstrating a distinct mechanism whereby the host directly controls maturation of the pathogen’s actin assembly factor. Sca2 is a key SFG Rickettsia spp. in vivo virulence determinant 60,61 , but little is known about how this protein reaches the bacterial surface or is regulated during infection. Furthermore, Sca2 levels do not appreciably shift over the course of R. parkeri infection 25 , hinting that regulation of this critical surface factor may have been partially outsourced to a host element like PPIA. Determining the contribution of the PPIA-Sca2 interaction to R. parkeri fitness in vivo and across different cell types and environments will reveal crucial context into host-dependent regulation of rickettsial actin-based motility during infection. Trans -acting extracellular folding or isomerization events like the action PPIA likely exerts on Sca2 have not been described for any other known autotransporters, which are often bacterial virulence determinants. The prevailing model of autotransporter biogenesis involves the canonical β-solenoid passenger domain structure templating its own surface translocation 32 . While >90% of known autotransporters are β-solenoidal 62 , key autotransporters in species like Pseudomonas aeruginosa ( e.g. , EstA 63 ) adopt α-helical passenger domain folds ( Fig. S4A ). It is unknown whether a similar templating mechanism enables surface translocation in these non-canonical passenger domains. The Sca2 C-terminal domain likely contains an α-helical bundle, but there is no experimental evidence to support the notion that it is self-templating 34 . Our data favors a model where α-helical autotransporters, including Sca2, follow a similar pathway to the surface as their β-solenoidal counterparts, but with evolved dependencies on external factors, specifically cyclophilins. Although autotransporters in intracellular pathogens would naturally have access to host cyclophilins for this purpose, for this model to apply to free-living bacteria, the cyclophilin would need to be surface-exposed. This is a known phenomenon in Gram-positive species 64 but has yet to be demonstrated in Gram-negatives. However, there is evidence for secretion of the normally periplasmic cyclophilin PpiB in Legionella pneumophila , suggesting that endogenous Gram-negative cyclophilins can be externalized 65 . Passenger domain C-termini are enriched for proline residues 66 and FKBPs and parvulins can interact with passenger domains in the periplasm 67,68 , reinforcing the broader idea that proline isomerases, now including cyclophilins, can play crucial and specialized roles in autotransporter biogenesis. Sca2 is an excellent model to continue exploring this idea, as it is one of the few α-helical autotransporters with a known molecular function. The precise folding, stabilization and/or isomerization events that PPIA exerts on Sca2 remain an open question, with implications for understanding the biogenesis and maturation of autotransporters with atypical passenger domains. Human PPIA has a somewhat permissive binding capacity beyond a preference for Gly-Pro-containing sequences 38 , and our data showed that mutation of the Gly-Pro residues was not sufficient to abolish the interaction between Sca2 and PPIA. Future work will require precise determination of this sequence to expand our understanding of how PPIA recognizes and binds interaction partners. PPIA could also plausibly target other surface proteins on R. parkeri or other intracellular bacteria. Indeed, we observed that cyclophilins have been specifically lost across obligate intracellular bacterial pathogens, suggesting that these broadly expressed host factors may be common elements of the cytoplasm that are recognized and hijacked by obligate intracellular microbes. Our study establishes the utility of Cas12a-based platforms for host-pathogen infection screens and underscores the idea that obligate intracellular bacteria fitness is deeply intertwined with host cell processes. Screen hits likely contribute to infection through a variety of mechanisms determined by whether the hits act indirectly or directly on R. parkeri , where in the cell they act, and whether they shape pathogen fitness at only one stage of the R. parkeri lifecycle or throughout infection. Continued investigation of host gene roles in R. parkeri infection may also reveal insights into basic host biology, a common outcome of studies of intracellular pathogenesis 69 . For example, dissecting opposing infection phenotypes for ceramide and triglyceride metabolism from the screen may reveal intrinsic host control mechanisms for balancing competing lipid biosynthetic pathways. It remains to be seen whether a similar or divergent set of genes support R. parkeri infection across the cell types the pathogen encounters during infection ( e.g., vascular endothelial cells), a question that may be resolved by further genome-scale screening efforts in different infection contexts. Finally, large-scale host-directed perturbations across other Rickettsia spp. and other currently genetically intractable or poorly tractable bacterial pathogens may be instrumental to mine untapped bacterial diversity, revealing shared and unique traits associated with bacterial adaptation to the intracellular space. Methods Eukaryotic cell lines Human A549 lung epithelial cells, HEK293T human embryonic kidney, and African green monkey Vero kidney epithelial cell lines were obtained from the UC Berkeley Cell Culture Facility (Berkeley, CA, USA). Human EA.hy926 vascular endothelial cells were a gift from Daniel Swale (University of Florida, USA). Cells were maintained in Dulbecco’s modified Eagle’s medium supplemented with 10% (A549, HEK293T, EA.hy926, Gibco) or 5% (Vero, Atlas Biologicals) fetal bovine serum (FBS). Where necessary, cells were selected with puromycin (2 µg/mL) or blasticidin (8 µg/mL). Propagation and transformation of R. parkeri All strains used in this study are wild-type (WT) or transformed derivatives of R. parkeri Portsmouth generously provided by Christopher Paddock (Centers for Disease Control, USA). General procedures for routine propagation of R. parkeri have been described previously 9 . Briefly, R. parkeri stocks were expanded for use by rocking infection of Vero cell monolayers in T25-T175 flasks, followed by incubation for ∼72 h at 37°C in DMEM + 2% FBS until the host cell monolayer was >90% rounded by light microscopy. R. parkeri were then isolated by bead beating, further purified by passage through a 2 µm glass microfiber filter (Cytiva), and stocks were resuspended in brain-heart infusion (BHI) media (BD Difco) and stored as 50-300 µL aliquots at -80°C. Aliquots were tittered by plaque assays as previously described 46 , and limited to a maximum of six freeze-thaw cycles for use in experimental infections. For transformation of R. parkeri , bacterial were freshly isolated from an infected T25 flask (for pRAM18dRA (empty vector) and pRAM18dRGA (one copy of GFPuv)) or T75 flask (pEG03 (one copy of AausFP1 70 ), gift of Erin Goley (Johns Hopkins University, USA)) and electroporated with 1 µg or 6 µg, respectively, of the indicated plasmids as previously described 8 . Electroporated bacteria were recovered by immediate re-infection of fresh Vero monolayers and monitoring for plaque formation under rifampicin (200 ng/mL) selection. Bacteria from successfully recovered wells were plaque-purified as previously described to isolate clonal transformants for expansion. R. parkeri expressing TagBFP or tandem copies of GFPuv and the isolation of sca2 ::Tn R. parkeri transposon mutant have been previously reported 9,25 . Molecular cloning A list of vectors used in this study is provided in Table S5 . All vectors were sequenced-confirmed by whole-plasmid sequencing (Plasmidsaurus). For pRDA_550 knockout vectors, synthesized gRNA cassettes (Millipore) harboring tandem gRNAs against each gene of insert from the Humagne C+D gRNA library were inserted into BsmBI-digested pRDA_550 by standard Golden Gate cloning procedures. Guide sequences used in this study are listed in Table S4. For pFUW2IB-based lentiviral rescue constructs, an ORF containing H. sapiens PPIA C-terminally fused to dsRed-Express2 with the previously reported linker GSGGSGGSGGQSTVPRARDPPVAT 29 was synthesized (Twist Biosciences) and cloned into NheI/EcoRI-digested pFUW2IB by standard restriction cloning. The PPIA R55A -dRE2 construct was constructed by round-the-horn PCR followed by DpnI digestion, ligation and transformation into DH5α E. coli . For R. parkeri Sca2 protein purification constructs, sca2 regions were amplified from R. parkeri Portsmouth gDNA and cloned by Gibson assembly into the pGEX-6P3 backbone. Truncations and point mutations, including the pET3A-OSF-PPIA(R55A) construct, were constructed by round-the-horn PCR followed by DpnI digestion, ligation and transformation into DH5α E. coli . Flow cytometry of R. parkeri -infected cells A549 parental or knockout cells were seeded in 12 well plates at 2x10 5 cells/well 2 days before infection. On the day of infection, cells were spinfected with the indicated strains of R. parkeri at an MOI ∼3 (0.1-10 for MOI titration experiments) at 200 rcf for 5 min at RT. Cells were incubated at 33°C to allow infection to proceed. At the indicated timepoints, cells were trypsinized and pelleted in 1.5 mL tubes at 1200 rcf for 5 min at RT. Media was aspirated from pelleted cells, which were then resuspended in 500 µL fixative (4% PFA in PBS or 100% ice-cold methanol), vortexed briefly, and incubated on ice for 15 min. For methanol fixation, tubes were briefly dragged along a rack to avoid subsequent clumping upon methanol addition. After fixation, 500 µL sterile FACS buffer (1xPBS + 1% BSA + 0.02% sodium azide) was added, and cells were pelleted at 300 rcf for 5 min. Cells were washed once with FACS buffer and transferred to filter cap round bottom tubes (BD) for flow cytometry. For antibody staining of PFA-fixed infected cells, after washing with FACS buffer, cells were re-pelleted and permeabilized with 0.5% Triton-X 100 in FACS buffer on ice for 10 min. Permeabilized cells were washed with FACS buffer and then stained with primary antibody mouse 14-13 anti- Rickettsia (gift of Ted Hackstadt) diluted in FACS buffer on ice for 30 min. Cells were washed twice with FACS buffer and then stained with goat anti-mouse Alexa Fluor 647 (Invitrogen #A-21236) diluted in FACS buffer on ice for 30 min. Cells were washed twice with FACS buffer and transferred to a filter cap 5 mL round bottom tube for flow cytometry. All flow cytometry analysis was performed on a FACSCanto II instrument (BD). For all GFP derivatives, a 488 nm laser was used with an LP 502 and BP 530/30 configuration. For TagBFP, a 405 nm laser was used with a BP 450/50 configuration. For Alexa Fluor 647, a 633 nm laser was used with a BP 660/20 configuration. All samples were gated for acquisition on single cells using SSC-A, FSC-A and FSC-H. For gating fluorescence, samples were compared to uninfected control wells from the same plate. Data analysis was performed with FlowJo 10 (BD). Genome-wide CRISPR/Cas12a screen and data analysis The A549-enAsCas12a stable cell line was generated by transducing parental A549 cells with pRDA_174 lentivirus, followed by blasticidin selection for 14 d. enAsCas12a expression was verified by Western blot against the HA epitope tag on enAsCas12a and activity was verified by subsequent transduction with pRDA_221 harboring a GFP expression cassette and a GFP-targeting gRNA, followed by assessment of GFP fluorescence reduction relative to parental A549 cells by flow cytometry. To generate the knockout library, 9x10 7 A549-enAsCas12a cells were transduced with lentivirus carrying the Humagne C+D (CP1882) human genome-wide knockout library (500x representation at 30% predicted transduction efficiency). The calculated transduction efficiency was 35%. Transduced cells were selected with puromycin for 7 d, maintaining a minimum population size of 6x10 7 to avoid bottlenecks. After 1 week, the minimum population size was lowered to 2x10 7 cells. For the first replicate of the screen, 10 T175 flasks of the library were seeded at 6x10 6 cells in 35 mL total media per flask. 72 h after seeding, flasks were infected with Rp AausFP1. At 48 hpi, infected cells were harvested by trypsinization followed by centrifugation at 1200 rcf for 5 min. Cell pellets were pooled and fixed by resuspension in 100% ice-cold methanol by drop-by-drop addition with continuous vortexing. Resuspended cells were incubated on ice for 15 min and then washed in FACS buffer. Cells were diluted to 1x10 7 /mL in FACS buffer and sorted on a FACSAria II (BD) to isolate the top and bottom 10% GFP fluorescence bins relative to a fixed, uninfected sample of the library. At least 6x10 6 cells were isolated in each bin and used for gDNA isolation (Machery-Nagel Nucleospin) alongside an equivalent sample of unsorted cells. All isolated gDNA (>10 µg/sample) was used for PCR amplification of the gRNA cassette and sequencing, performed by the Broad Institute Genetic Perturbation Platform. The second replicate of the screen was performed with a later passage of the same library. The screen was conducted identically to the first replicate, with the only modification being a higher cell concentration (1.5x10 7 /mL) used for FACS. Screen analysis was performed with Apron (Broad Institute) (see “Bioinformatic Analyses” section for further details). Generation of knockout cell line pools, clones and rescue lines For all knockout lines, the enAsCas12a-based all-in-one lentiviral knockout vector pRDA_052 was used. The lentiviral expression vector pFUW2IB was used to express specific constructs under the control of the UbC promoter. To generate lentivirus, HEK293Ts were transfected with 280 ng pRDA_052 or pFUW2IB vector and 140 ng each of the pMDLg/pRRE, pRSV-REV and pCMV-VSV-G packaging vectors with LT-1 transfection reagent (Mirus Bio #2304) according to standard protocols and lentivirus was collected in media supplemented with 1% BSA. Lentiviral supernatants were collected 48 h post-transfection and filtered through 0.45µm PES filters (Genesee Scientific #25-246) before transduction. A549s transduced with the indicated pRDA_052 derivative harboring a gRNA from the Humagne C+D library were selected with puromycin for at least 7 d before knockout validation (via immunoblot) and/or phenotypic validation. For single-cell cloning of PPIA ko lines, clones were isolated by limiting dilution in 96-well plates followed by growth for 14 d in media containing puromycin. Wells containing single colonies were trypsinized and transferred to larger culture plates for phenotyping by immunoblot for PPIA. Clones with obviously altered cell morphology or growth kinetics were not propagated. To generate PPIA ko rescue lines or parental A549 lines expressing dRE2-tagged proteins, cells were transduced with pFUW2IB derivatives and selected with blasticidin for 14 d. dRE2-tagged protein-expressing lines were single-cell cloned as described for the PPIA ko clones. For PPIA ko rescue lines, lentiviral PPIA ORFs were altered with at least 3 silent mutations within the first 10 nt of the seed sequence to render them enAsCas12a-resistant (listed in Table S6 ). Confocal immunofluorescence (IF) microscopy All IF assays used the same standard fixation and staining protocol, with variations noted below for each specific assay. Host cells were seeded in 24-well tissue culture-treated plastic plates (Genclone) on sterile glass #1.5 coverslips (Fisherbrand) and allowed to attach for at least 24 h. At the indicated infection endpoint, cells were fixed with 4% PFA for 15 min at RT and then washed three times with 1xPBS. Fixed coverslips were quenched with 0.1 mM glycine for 10 min and then washed three times with 1xPBS. Cells were then permeabilized with 0.5% Triton-X 100 in PBS for 5 min, after which cells were washed with 1xPBS and blocked for 30 min with 2% BSA/PBS. Blocking solution was then replaced with primary antibodies diluted in 2% BSA/PBS for 1 h at RT. Cells were washed by soaking three times for 5 min with 1xPBS and secondary antibodies diluted in 2% BSA/PBS added for 1 h at RT. Coverslips were washed and mounted on glass slides using ProLong Gold antifade mountant (Invitrogen). Mounted slides were dried overnight in the dark and sealed with nail polish for imaging. Images were acquired on an Olympus IXplore Spin microscope system with a Yokogawa CSU-W1 spinning disk unit and an ORCA-Flash4.0 sCMOS camera using either 60x UPlanSApo (1.30 NA) (spread assays) or 100x UPlanSApo (1.35 NA) (all other assays) objectives. At least 10 fields of view per coverslip were acquired by scanning the R. parkeri channel to image solely based on bacterial density. Image analysis was performed in ImageJ. Infectious focus (spread) assay A549 cells were seeded at 2x10 5 cells/well in 24 well plates 2 d prior to infection. Cells were spinfected with MOI ∼0.001 WT R. parkeri and incubated at 33°C for 1 h, after which media was aspirated, wells washed three times with sterile 1xPBS, and fresh media containing 10 µg/mL gentamicin was added to each well. Plates were incubated for an additional 27 h at 33°C before fixation. Primary antibodies used were: rabbit chimeric 14-13 anti- Rickettsia 71 (gift of Ted Hackstadt (Rocky Mountain Laboratories/NIAID, USA)), mouse anti-β-catenin (CST #2677S). Secondary antibodies and stains used were: Hoescht (Invitrogen H3570), goat anti-rabbit Alexa Fluor 488 (Invitrogen A-11001), and goat-anti mouse Fcγ Alexa Fluor 568 (Jackson ImmunoResearch #115-605-071). At least 20 infection foci per coverslip were imaged for quantification. Actin tail assay A549 cells were seeded at 2x10 5 cells/well in 24 well plates 2 d prior to infection. Cells were spinfected with MOI ∼0.5 WT R. parkeri and incubated at 33°C for 48 h before PFA fixation as described above. Cells were stained as for the infectious focus assay with the addition of phalloidin Alexa Fluor 647 (Invitrogen #A22287). Tails were counted by first segmenting single R. parkeri with MicrobeJ as described below, then scoring for actin tails. Tails were only counted if they exceeded the length of the associated bacterium. Drug treatment and washout assays For single timepoint drug treatments, A549 cells were seeded at 2x10 5 cells/well in 24-well plates 2 d prior to infection. Cells were spinfected with MOI ∼0.5 WT R. parkeri and incubated at 33°C for 24 h, at which point media was removed, cells washed once in 1xPBS and fresh media containing the indicated drugs at the indicated concentrations was added. Cells were returned to 33C and incubated for an additional 24 h. Cells were fixed at 48 hpi. Assays assessing the effect of drugs on actin tails were stained identically to the actin tail assay. Assays assessing the effect of drugs on Sca2 surface exposure used the following primary antibodies: mouse 14-13 anti- Rickettsia and rabbit anti- R. parkeri Sca2 (in-house). Secondary antibodies and stains used were: Hoescht, goat anti-mouse Alexa Fluor 488, goat anti-rabbit Alexa Fluor 568 (Invitrogen #A-11004), and phalloidin Alexa Fluor 647. For CsA washouts, at 1 hpi cells were washed with 1xPBS and then media containing 10 µM CsA was added. At varying washout timepoints, media was removed, cells were washed three times with 1xPBS, and CsA-free media was added. At 48 hpi, cells were fixed and stained as described above. PPIA-dRE2 localization assays A549 cells were seeded at 4x10 4 cells/well in 24-well plates 2 d prior to infection. Cells were spinfected with MOI ∼2.5 WT R. parkeri and incubated at 33°C. For treatment with CsA, 10 µM CsA or DMSO was added to cells as described above at 24 hpi. At 48 hpi, cells were fixed with 4% PFA for 1 h in the dark at RT before washing and staining by the standard protocol described above. The following primary antibodies were used: mouse 14-13 anti- Rickettsia and rabbit anti- R. parkeri Sca2. The following secondary antibodies were used: goat anti-mouse Alexa Fluor 405 and phalloidin Alexa Fluor 488. Lysozyme permeabilization immunofluorescence assay for Sca2 The differential permeabilization assay was performed as previously described 46 . Briefly, A549 cells were seeded, infected and fixed as described for the actin tail assay with duplicate coverslips seeded per condition for staining with and without lysozyme permeabilization. All coverslips were first stained with the standard IF protocol using the primary antibody mouse 14-13 anti- Rickettsia and the secondary antibody goat anti-mouse Alexa Fluor 488, Hoechst, and phalloidin 647. For non-permeabilized coverslips, this also included the rabbit anti- R. parkeri Sca2 primary and goat anti-rabbit Alexa Fluor 568 antibodies, after which staining was complete. For permeabilized coverslips, after the first round of staining, samples were re-fixed with 4% PFA for 5 min at RT and stored in 1xPBS overnight at 4°C. Samples were re-quenched with 100 mM glycine as described above, then permeabilized by incubation in lysozyme reaction buffer (0.8×PBS, 50 mM glucose, 5 mM EDTA, 0.1% Triton X-100, 5mg/mL lysozyme (Sigma #L6876)) for 20 m at 37°C. Permeabilized samples were washed three times with 1xPBS and then stained as described above with the rabbit anti- R. parkeri Sca2 primary and goat anti-rabbit Alexa Fluor 568 secondary antibodies. Image analysis was performed with MicrobeJ 72 version 5.13(l). Single bacteria were detected using the 14-13 anti- Rickettsia signal with custom settings: smoothed morphology, area 0.4-3.5, length 0.5-3.5, width 0.4-1, circularity 0.5-1, angularity 0-0.5 (all µm). Clumps of bacteria, bacteria in the nucleus (which have abnormally high rates of actin-based motility 73 ), as well as any cells along the edge of the image were excluded. Segmented bacterial outlines were used to manually score Sca2-positive R. parkeri . For measuring total levels of Sca2 in permeabilized bacteria, MicrobeJ was used to calculate the sum intensity of the Sca2 channel in segmented R. parkeri . This total was then normalized by bacterial area. Immunoblotting Uninfected samples for verifying PPIA knockout were harvested during routine passaging. For samples from infected cells, A549s were at 2e5/well in 12 well plates 2 d prior to infection. Cells were infected with WT or sca2 ::Tn R. parkeri at MOI ∼3-5 by spinfection and incubated at 33°C until harvesting at 48 hpi. Samples from uninfected or infected plates were processed identically for Western blotting. Cells were trypsinized, pelleted at 1200 rcf for 5 min at RT and resuspended in 1x SDS loading buffer (150mM Tris-HCl pH 6.8, 6% SDS, 0.3% bromophenol blue, 30% glycerol). Samples were boiled for 10 min and electrophoresed on 12% SDS-PAGE gels. Proteins were transferred to PVDF membranes using semi-dry transfer (Bio-Rad Trans-Blot) using the preset 1.5 mm gel protocol. Membranes were blocked in 5% milk in TBST (1x TBS with 0.1% Tween-20) for 1 h at RT and then primary antibodies were added for overnight incubation at 4°C. Membranes were washed three times for 10 min each with TBST, and secondary antibodies were added for 1 h at RT followed by three additional 10 min washes with TBST. Membranes were incubated with chemiluminescent substrate (Thermo # A43840) for imaging. Primary antibodies used were: rabbit anti-PPIA (Thermo #PA1-025), mouse anti-alpha tubulin (Sigma #T6199), rabbit anti-Sca2 (in-house purified from polyclonal serum), mouse anti-RpoB (BioLegend #663905). Secondary antibodies used were HRP-conjugated goat anti-mouse or rabbit IgG (Jackson Immunoresearch #115-035-003 (mouse) and #111-035-003 (rabbit)). All antibodies were diluted in 2.5% milk in TBST. Purification of GST-tagged R. parkeri Sca2 To purify recombinant GST-Sca2 proteins, overnight cultures of Rosetta2 E. coli transformed with pGEX-6P3-Sca2 derivatives were diluted 1:500 into 1 L cultures of 2xYT media with ampicillin and chloramphenicol. Cultures were grown at 37°C at 200 rpm until OD ∼0.8, at which point they were induced with 0.1mM IPTG and grown at 18°C overnight. Cultures were harvested by centrifugation at 5000 rcf for 15 min and resuspended in 10 mL/L lysis buffer (50 mM Tris pH 8, 150 mM KCl, 0.1% Tween-20) freshly supplemented with 1 mM PMSF, 20 µg/mL Dnase I and protease inhibitors (Roche cOmplete Mini). Cells were incubated with 1 mg/mL lysozyme for 15 min at 4°C. Then, 1 mM DTT was added, and cells were lysed by sonication followed by centrifugation at 30,000 rcf for 30 min. Clarified lysate was rocked overnight at 4°C with glutathione 4B Sepharose (Cytiva) before gravity column purification. Resin was washed with 2 column volumes of high-salt wash buffer (50 mM Tris pH 8, 500 mM KCl, 1 mM DTT, 1 mM PMSF) followed by 6 column volumes of standard wash buffer (50 mM Tris pH 8, 150 mM KCl, 1 mM DTT, 1 mM PMSF) and elution in freshly prepared GST elution buffer (50 mM Tris pH 8, 150 mM KCl, 1 mM DTT, 10 mM reduced glutathione). Fractions were pooled, concentrated by centrifugation and further purified by size exclusion chromatography on a Superose 6 10/300 GL column (Cytiva) into the final buffer (50 mM Tris pH 8, 150 mM KCl, 1 mM TCEP). Pure protein fractions were pooled, re-concentrated and stored at -80°C for use. GST did not require purification by size exclusion and was purified by an identical glutathione affinity procedure using buffers containing NaCl rather than KCl and omitting the high-salt wash step. All purification steps were performed at 4°C. Purification of OSF-tagged human cyclophilin A One-STrEP-FLAG (OSF)-tagged PPIA was purified largely as previously described 74 . Overnight cultures of BL21(DE3) E. coli transformed with pET3a-OSF-CypA were diluted 1:1000 into 1 L cultures of ZYP-5052 autoinduction media (10 g/L tryptone, 5 g/L yeast extract, 1x5052 (0.05% d-glucose, 0.5% glucose, 0.2% α-lactose), 1xNPS (25 mM (NH4)2SO4, 50 mM KH2PO4, 50 mM Na2HPO4)). Cultures were grown at 37°C, shaking at 200 rpm overnight. Cultures were harvested by centrifugation at 5000 rcf for 15 min. and resuspended in 10 mL/L culture lysis buffer (50 mM Tris pH 8, 50 mM NaCl, 0.2% deoxycholate) freshly supplemented with 2.5 nmol avidin, 10 mM β-mercaptoethanol (β-ME), 1 mM PMSF, 20 µg/mL Dnase I, and protease inhibitors (Roche cOmplete Mini). Cells were lysed by sonication and lysates were clarified by centrifugation at 30,000 rcf for 30 min. Clarified lysates were incubated with Streptactin XT 4flow resin (IBA Lifesciences) for 1 hr at 4°C with rotation before gravity column purification. Isolated resin was washed with 6 column volumes of wash buffer (100 mM Tris pH 8, 150 mM NaCl, 10 mM β-ME) before elution with elution buffer (wash buffer + 2.5mM d-desthiobiotin). Fractions were pooled, concentrated and further purified by size exclusion chromatography using a Superdex 200 Increase 10/300 GL column (Cytiva). Pure protein fractions were pooled, re-concentrated and stored at -80°C. All centrifugation steps were performed at 4°C. In vitro pulldown assays GST pulldowns were adapted from a previously published protocol 75 . The GST-Sca2 size exclusion buffer was used as the buffer for all binding assays. 4-10 µM of GST or GST-Sca2 and OSF-PPIA were mixed in equal ratios in a total volume of 50-100 µL, depending on the scale of the assay. Protein mixtures were incubated on ice for 20 min after which 50 µL of equilibrated glutathione 4B Sepharose (Cytiva) was added to the mixture and incubated for a further 10 min. Bound protein on beads was then collected by centrifugation at 300 rcf for 5 min, followed by three washes with 10x bead volume of binding buffer. Proteins were eluted by incubation with GST elution buffer (50 mM Tris pH 8, 10 mM reduced glutathione) for 5 min on ice. Samples were mixed with 3x SDS loading dye and analyzed by SDS-PAGE followed by staining with SimplyBlue Safestain (Life Technologies). Bioinformatic analyses CRISPR screen analysis was performed with Apron (beta version, Broad Institute). Apron uses aggregated log-normalized read constructs for guides targeting each gene to calculate fold changes based on comparison to a reference distribution. P-values were calculated from the standard distribution of gene z-score deviation from fold changes of non-target and intergenic-targeting gRNAs. False discovery rates were calculated using the Benjamini-Hochberg procedure on p-values within each condition. Two analyses were performed. The first compared the bulk output libraries (pooled reads from low, high and unsorted bins) in each replicate to the input plasmid DNA to verify library complexity and essential gene dropout. The second compared the high to low fluorescence bins in each replicate to identify hits (see Fig. S2 ). For STRING network analysis, the top 100 and bottom 100 hits were combined and used to generate a functional and physical interaction network. Clusters were identified with DBSCAN clustering using an epsilon parameter of 5. Structural prediction was performed with the AlphaFold3 server (alphafoldserver.com) 76 . The highest-ranked structure was used for visualization with ChimeraX 77 . PAE plots were generated with PAE Viewer 78 . Assessment of proline isomerase conservation was performed with manual Annotree 48 (version r214 using GTDB R214 database) lookups of PF00160, PF00254 and PF13145 at an e-value less than 0.00001. A cladogram for visualization was generated with the BV-BRC pathogen phylogenetic tree tool 79 using 95 conserved genes and the RAxML phylogenetic tree algorithm. Specific strains used for the cladogram are listed in Table S3 . Statistics and replicates Replicate information is indicated on each figure legend. Biological replicates for tissue culture infections were defined as wells that were infected and harvested or fixed on different days. Unless otherwise stated, graphed summary values represent replicate means with standard deviation error bars. Unless otherwise stated, p-values greater than 0.05 were considered not statistically significant. Statistical analyses are outlined in each figure and were performed with Microsoft Excel or Graphpad Prism. Author Contributions BS and RLL conceived the study. JGD contributed to genetic screen design and feasibility studies. BS, AGS, CYZ and LEB conducted experiments and analyzed data. BS and RLL wrote the manuscript with review from all other authors. Funding B.S. was supported by a fellowship from the National Institutes of Health (F32AI172121). The Lamason Lab receives funding from the National Institutes of Health (R01AI155489 and R01GM141025) and internal MIT funding mechanisms. Supplementary Tables Table S1. Genome-scale CRISPR/Cas12a R. parkeri infection screen results. Table S2. DBSCAN cluster analysis of CRISPR screen hits. Table S3: Species and strains used for cladogram generation. Table S4: Annotree results for PF00160, PF00254 and PF13145. Table S5: Bacteria and plasmids used in this study. Table S6: Guide and ORF sequences used in this study. Download figure Open in new tab Figure S1. Screen optimization and execution. ( A ): Flow cytometry of A549 cells infected with R. parkeri transformed with various fluorescent protein expression constructs at 24 hpi. UI, uninfected. ( B ): Fixation sensitivity of Rp AausFP1 and Rp BFP strains. ( C and D ): Representative plaques (C) and quantification (D) of Vero cells infected with WT R. parkeri or Rp AausFP1. Each point represents the mean of >100 quantified plaques from a biological replicate. Means were used to calculate the p-value (Welch’s t-test). ( E ): Correlation of antibody staining and endogenous fluorescence signal in Rp AausFP1-infected A549 cells. Samples were stained with a secondary antibody conjugated to Alexa Fluor 647. Stained uninfected cells were used to set gates and a secondary antibody-only infected sample was used as a control for nonspecific binding. ( F ): Optimization of MOI for infections. Only the 48 hpi timepoint is shown. ( G ): Optimization of timepoint for infections. Only the MOI 3 infections are shown (48 hpi curve is the same as in panel F). Y-axes in panels A, B, F and G are all normalized to mode. All flow cytometry plots are representative of at least n=3 biological replicates. Download figure Open in new tab Figure S2. Infection screen results and analysis. ( A ): Flow cytometry of each screen replicate. UI, uninfected. ( B and C ): Analysis of screen data comparing either the bulk output libraries versus input pDNA (B, Analysis 1) or high versus low bins (C, Analysis 2). Left - gRNA-level log2 fold change (LFC) correlation between replicates. Right - gene-level receiver-operator curve(s) for recovery of known essential genes in each replicate. Area under the curves (AUCs) are listed next to each condition. AUC values >0.8 indicate strong separation of positive from negative controls, in this case separation of known essential from known non-essential genes. AUCs are low in panel C because there is no selective pressure against essential genes. r-values shown are Pearson’s correlation coefficient. The r-value is low in panel C because there is no selective pressure for or against most of the library, so most gRNAs behave stochastically. ( D ): Scatter plot of gene LFCs between Analysis 1 and 2. Red and blue points identify genes with FDR < 0.05 (same as Figure 1C ). Dashed lines indicate LFC thresholds with FDR < 0.05 for Analysis 1. Genes with strong LFC values for Analysis 1 were generally not selected for validation because they likely have effects on host cell viability. Download figure Open in new tab Figure S3. Characterization of PPIA requirement for R. parkeri actin-based motility. ( A ): Actin tails at 48 hpi in cells treated with 10μM cyclosporin A (CsA), NIM811, FK506 (FKBP inhibitor), or juglone (parvulin inhibitor) for 24 h beginning at 24 hpi. ( B ): Western blot of parental (Par), non-target (NT) and PPIA ko (KO) EA.hy926 vascular endothelial cells. ( C ): Actin tails at 48 hpi in NT or PPIA ko EA.hy926 cells. ( D ): Actin tails at 48 hpi in parental EA.hy926 cells treated with vehicle or 10μM CsA beginning at 24 hpi. All images are representative of n=3 biological replicates infected with WT R. parkeri . Arrowheads highlight bacteria with actin tails. Download figure Open in new tab Figure S4. Additional characterization of the Sca2-PPIA interaction. ( A ): Comparison of Sca2 passenger domain structure to a canonical autotransporter (pertactin). Note the lack of β-stranded-regions in Sca2. Sca2 is colored according to Figure 4A layout. ( B ): Conservation of Gly-Pro containing repeats across selected Rickettsia spp. representative of different rickettsial clades. AG, ancestral group. TRG, transitional group. TG, typhus group. SFG, spotted fever group. Sca2 sequences were identified by protein BLAST with R. parkeri Sca2 and aligned with MAFFT. ( C ): Predicted structure of the PPIA interaction with Sca2(1087-1544) as the input, colored by pLDDT. PPIA is surface shaded. ( D ): Close-up view of PPIA-CRD interaction at second Gly-Pro site. ( E ): Atomic interactions at the predicted binding site between Sca2 Gly-Pro 1284-1285 and PPIA. Right: binding site of PPIA with HIV-1 capsid protein (PDB: 1AK4) Hydrogen bonds are indicated as blue dashed lines. ( F and G ): Glutathione pulldown of WT PPIA by CRD proline (F) or glycine (G) single or double mutants as indicated. Images shown are representative of at least two independent pulldowns. Download figure Open in new tab Figure S5. Additional characterization of Sca2 dependencies on PPIA. ( A ): Sca2 levels at 48 hpi with WT or sca2 ::Tn R. parkeri in NT or PPIA ko A549 host cells. Sca2 is known to blot as a 150kDa and 75kDa band (indicated with arrows). *: truncation product of Sca2 made by sca2 ::Tn bacteria. RpoB and tubulin are loading controls for R. parkeri and host input, respectively. Blot is representative of two independent experiments. ( B ): Sca2 surface exposure in WT A549 cells infected with WT R. parkeri treated with 10μM CsA for 24 h and washed out for the indicated time. Arrowheads highlight bacteria with Sca2 staining and a visible actin tail. Images are representative of at least two biological replicates. Acknowledgements We thank members of the Lamason Lab for helpful discussions throughout this project and Gregory Babunovic, Karthik Hullahalli, and Alyson Warr-Manteiga for critical reading of the manuscript. We also thank Seychelle Vos for access to FPLC equipment and Roberto Vásquez-Núñez for technical assistance with protein purification. 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