s2fieldsofstudy: Biology Medicine

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Neutrophils promote venular thrombosis by shaping the rheological environment for platelet aggregation

In advanced inflammatory disease, microvascular thrombosis leads to the interruption of blood supply and provokes ischemic tissue injury. Recently, intravascularly adherent leukocytes have been reported to shape the blood flow in their immediate vascular environment. Whether these rheological effects are relevant for microvascular thrombogenesis remains elusive. Employing multi-channel in vivo microscopy, analyses in microfluidic devices, and computational modeling, we identified a previously unanticipated role of leukocytes for microvascular clot formation in inflamed tissue. For this purpose, neutrophils adhere at distinct sites in the microvasculature where these immune cells effectively promote thrombosis by shaping the rheological environment for platelet aggregation. In contrast to larger (lower-shear) vessels, this process in high-shear microvessels does not require fibrin generation or extracellular trap formation, but involves GPIbα-vWF and CD40-CD40L-dependent platelet interactions. Conversely, interference with these cellular interactions substantially compromises microvascular clotting. Thus, leukocytes shape the rheological environment in the inflamed venular microvasculature for platelet aggregation thereby effectively promoting the formation of blood clots. Targeting this specific crosstalk between the immune system and the hemostatic system might be instrumental for the prevention and treatment of microvascular thromboembolic pathologies, which are inaccessible to invasive revascularization strategies.

in larger vessels (as assessed in models of arterial injury and deep vein thrombosis) and hepatic sinusoids (during the clearance of circulating pathogens) in a process termed 'immunothrombosis': Under exposure to relatively low shear stress, neutrophils support thrombus growth by the release of extracellular traps (NETs; network of extracellular fibers containing DNA and other molecules 10 ) which, in turn, activate components of the coagulation system and facilitate platelet aggregation [11][12][13][14] . Whether these elementary immune cell-driven events are relevant for the formation of thrombi in the microvasculature of inflamed tissue, however, is still unclear.
Various studies have demonstrated that interactions of leukocytes and platelets in the inflamed microvasculature are vital for proper immune cell responses [15][16][17][18][19][20][21][22][23] . Conversely, it has been shown that an inflammatory environment exacerbates the thrombotic phenotype of microvessels 24 . In this context, neutrophils have been reported to promote the clotting of the cerebral microvasculature in experimental sickle cell disease 25 . In vivo microscopy observations further suggest that such events require interactions of intravascularly adherent neutrophils with platelets that rely on thrombin, tissue factor, elastase, cathepsin G, and ATP/adenosine-dependent inhibition of tissue factor pathway inhibitor [26][27][28] .
In addition to these molecular mechanisms, rheological factors contribute to intravascular platelet adhesion and thrombus formation [29][30][31][32] . Interestingly, it has recently been reported that intravascularly adherent leukocytes shape the blood flow in their immediate vascular environment 33 . Consequently, we hypothesize that these distinct rheological effects arising from leukocytes recruited to the inner vessel wall of inflamed tissue propagate microvascular thrombus formation.

Results
Thrombus formation in the microvasculature of inflamed tissue. To investigate the mechanisms underlying microvascular thrombosis in inflamed tissue, we performed in vivo microscopy analyses in the mouse cremaster muscle. In unstimulated tissue, non-perfused microvessels were barely detected (Fig. 1A). Upon induction of inflammation (elicited by an intrascrotal injection of lipopolysaccharide (LPS)), however, the number of non-perfused capillaries and post-capillary venules was significantly increased, whereas arteriolar perfusion remained unaffected. This increase in numbers of non-perfused venules, but not in non-perfused capillaries, was significantly decreased in neutrophil-depleted animals.
To characterize the mechanisms underlying microvascular thrombus formation in inflamed tissue in more detail, we further enhanced the inflammatory status of selected parts of the tissue by applying a 'second hit' (photochemical injury; Video S1) which is supposed to injure endothelial cells (resulting in excessive release of von Willebrand factor (vWF) as observed under severe inflammatory conditions) without extensively destroying subendothelial structures (e.g., as opposed to models of ferric chloride-induced thrombosis 34,35 ). This procedure allowed us to reproducibly visualize interactions of neutrophils, platelets, and endothelial cells in high spatio-temporal resolution during thrombus formation in a given vessel segment (see below). In a priori unstimulated venules, platelets were observed to adhere to the surface of microvascular endothelial cells immediately upon photochemical injury, whereas the complete occlusion of these microvessels by the growing thrombi occurred at later time points. Upon prestimulation of the cremaster muscle with LPS, however, cessation of blood Figure 1. Spatio-temporal dynamics of thrombus formation in inflamed venular microvessels. Non-perfused arterioles, capillaries, and venules were quantified in the cremaster muscle of unstimulated control animals and in animals receiving an intrascrotal injection of LPS as well as intravenously neutrophil-depleting anti-Ly-6G mABs or isotype control Abs (A; mean ± SEM for n = 4 per group; *p < 0.05 vs. control, # p < 0.05 vs. neutrophil depletion). Thrombus formation in postcapillary venules of the mouse cremaster muscle was induced by photochemical injury as detailed in Methods, representative in vivo fluorescence microscopy images of timelapse video recordings are shown (B; scale bar: 20 μm, Video S1, 4). Panels show quantitative data for onset and cessation times in WT mice receiving a local, intrascrotal injection of PBS ('unstimulated') or LPS ('inflamed') (C,D; mean ± SEM for n = 9 per group; *p < 0.05 vs. unstimulated control) and undergoing treatment with heparin, platelet-depleting antibodies, or vehicle/isotype control antibodies (E,F; mean ± SEM for n = 3-4 per group; *p < 0.05 vs. vehicle/isotype control). Aggregation patterns of fluorescence-labeled platelets during thrombus formation in unstimulated or inflamed capillary and venular cremasteric vessels were visualized by multi-channel in vivo fluorescence microscopy as detailed in Methods, representative images of time lapse video recordings are shown (G; platelets in white, scale bar: 40 μm, Video S2, 3).

Role of platelets and the plasmatic coagulation for thrombus formation in the venular microvasculature of inflamed tissue.
To identify the mechanisms underlying the accelerated thrombus formation in venular microvessels of inflamed tissue, we sought to evaluate the individual contributions of platelets and the plasmatic coagulation system to this process. Inhibition of fibrin generation with heparin (which also dismantles the NET scaffold and interferes with thrombin-mediated platelet activation) did not significantly alter the cessation times of blood flow upon photochemical injury in unstimulated or prestimulated venules (Fig. 1E). In contrast, antibody-mediated depletion of platelets (by > 90% as compared to controls; Table S1) substantially prolonged the average time to the cessation of blood flow upon photochemical injury in both unstimulated and inflamed venules (Fig. 1F).
To characterize the role of platelets for thrombus formation in venular microvessels in further detail, interactions of fluorescence-labeled platelets with endothelial cells were visualized by multi-channel in vivo fluorescence microscopy. In the a priori unstimulated cremaster muscle, discoid platelets began to adhere and aggregate upon photochemical injury predominantly in capillaries, from where the forming thrombi progressively grew into the lumen of venules. Having reached postcapillary venules, the single thrombi merged into large thrombi that finally occluded the venules together with their preceding capillary vessel segments. In striking contrast, discoid platelets were found to directly adhere at multiple sites on endothelial cells of prestimulated postcapillary venules instantly after photochemical injury thereby forming a venular thrombus. This process resulted in an accelerated cessation of blood flow in the capillary and venular vasculature ( Fig. 1G; Video S2, 3, 4).

Role of neutrophils for thrombus formation in venular microvessels of inflamed tissue.
In a next step, we sought to evaluate the functional relevance of neutrophils for thrombus formation in the microvasculature of inflamed tissue. Performing in vivo microscopy in postcapillary venules of the unstimulated cremaster muscle, only few intravascularly adherent leukocytes were found. As expected, intravascular adherence and transmigration of leukocytes (>90% Ly-6G + neutrophils) was significantly elevated in inflamed tissue as elicited by intrascrotal stimulation with LPS ( Fig. 2A,B), whereas leukocyte adherence in arterioles was virtually absent (0.4 ± 0.2/10 4 μm 2 ).
Antibody-mediated depletion of neutrophils (eliminating > 90% of neutrophils compared to controls; Table S2) completely reversed the acceleration of microvascular thrombus formation in LPS-stimulated cremasteric venules to the level of unstimulated venules (Fig. 2C) indicating that neutrophils significantly contribute to thrombus formation under these inflammatory conditions. In vivo immunostaining and multi-channel fluorescence microscopy revealed that platelets preferentially form aggregates in inflamed postcapillary venules at sites downstream of adherent or shortly adhered and subsequently detached neutrophils. From these multiple 'hot spots' , platelet aggregates further grow and merge into one large thrombus finally occluding the entire venule ( Fig. 2D; Video S5). Simultaneously, the number of intravascularly adherent neutrophils did not further increase upon thrombus formation in inflamed venules (Fig. S2). Noteworthy, we are not able to clearly answer the question whether the shortly adherent neutrophils 'create' appropriate vascular sites for platelets to accumulate or whether platelets and shortly adherent neutrophils simply adhere to similar vascular sites.
Previously, the role of neutrophils for venular thrombus formation has been analyzed upon intra-peritoneal administration of LPS, mimicking initial stages of a systemic inflammatory response 24 . In this study, depletion of neutrophils and inflammatory monocytes by anti-Gr-1 antibodies did not affect accelerated thrombus formation in cremasteric venules. We were able to reproduce these results in neutropenic animals (using neutrophil-selective anti-Ly-6G antibodies; Table S2) Fig. S3A,B. The missing effect of neutrophil/inflammatory monocyte depletion on venular thrombus formation here might be, at least in part, attributed to the low degree of local inflammation in the cremaster muscle under these specific experimental conditions (indicated by lacking intravascularly adherent leukocytes in cremasteric venules; Fig. S3C) as opposed to our findings under severe local inflammation (elicited by local, intra-scrotal injection of LPS) in which numerous neutrophils accumulated in the microvasculature (see above).
Effect of physical characteristics of the inner microvessel surface on platelet deposition under flow. Based on our in vivo microscopy observations, we hypothesized that perturbations of the blood flow around intravascularly adherent neutrophils facilitate platelet capture and thrombus propagation. In order to separate physical effects from neutrophil-specific molecular interactions, we constructed a polydimethylsiloxane (PDMS) microfluidic device, which mimics the surface geometry of postcapillary venules and is uniformly thrombogenic (Fig. 3A). The device consists of four channels with different densities of 'bump' structures of the same material (Fig. 3B) mimicking intravascularly adherent neutrophils (8 µm in diameter, consistent with the protrusion of adherent neutrophils into the vessel lumen, Fig. S4A,B; up to 50 bumps per 10 4 µm 2 surface area). After 10 min of perfusion with mouse blood at physiological microvascular shear rates (1500 s −1 ), only few thrombocytes (fluorescence-labeled by an anti-GPIbβ mAb) were adherent in the channel with a 'flat' surface (mimicking unstimulated conditions). In channels with bumps (mimicking intravascularly adherent neutrophils in inflamed venules), however, the number of adherent platelets was dramatically increased as compared to the channel with a flat surface, more than 100-fold for the highest density tested.
Employing high-resolution time-lapse microscopy, we found that platelets were initially captured on the central region of a bump (Fig. 3D, Video S7; 4 min), from where these cellular blood components migrated on the bump to the obstacles' downstream face (6.5 min). Having arrived in the wake of a bump, the first platelets began to form membranous (GPIbβ-positive) tethers anchoring to the bump (up to 15 μm in length; 7.5 min), which allowed the platelets to freely rope down in the bloodstream (Fig. 3E). These events, in turn, promoted the capturing of following platelets thereby facilitating aggregation of these blood components and promoting microvascular thrombus growth. Moreover, tethered platelets were also observed to adhere to downstream bumps thereby further increasing the number of growing microthrombi (Fig. 3D, 13 min). In line with previous observations 29, 36 , platelets remained discoid in shape during the entire capture and aggregation process and adhered to the PDMS surface via deposited patches of vWF (but not strings of vWF, most probably due to ADAMTS13-dependent degradation of endothelially released vWF 32 ; Fig. S5), which was abrogated when blood was incubated with anti-GPIbα Fab' fragments before the onset of microfluidic experiments (Fig. 3C).
For a better understanding of the hydrodynamic effect of bump structures on platelet recruitment, we employed a fluid dynamics simulation ( Fig. 4A-D). We found that platelets are exposed to higher blood flow velocity gradients when bypassing the bump structure. This causes drag that induces a spinning and flipping motion in platelets, thereby eventually bringing the platelets' surface in close contact to the bump's surface allowing molecular interactions and subsequent adhesion.
Molecular mechanisms underlying thrombus formation in the venular microvasculature of inflamed tissue. In a next step, we sought to elaborate the molecular basis of this neutrophil-driven acceleration of thrombus formation in the venular microvasculature of inflamed tissue. To avoid interference with inflammatory processes arising during the prestimulation period of the cremaster muscle (6 h stimulation with LPS), blocking antibodies directed against the target proteins were applied 10 min prior to the induction of photochemical injury and in vivo microscopy. . Panel (B) shows quantitative data for leukocyte intravascular adherence in venules (mean ± SEM for n = 4 per group; *p < 0.05 vs. unstimulated control). Thrombus formation in postcapillary venules of the cremaster muscle of WT mice was induced by photochemical injury as detailed in Methods. Panel (C) shows quantitative data for cessation times in WT mice undergoing intrascrotal stimulation with LPS after treatment with neutrophildepleting or isotype control antibodies (mean ± SEM for n = 4 per group; *p < 0.05 vs. isotype control). Interactions of platelets (white) and neutrophils (orange) during thrombus formation in postcapillary venules of the cremaster muscle of WT mice induced by photochemical injury were visualized by multi-channel in vivo fluorescence microscopy as detailed in Methods, representative images are shown (D; arrow indicates flow direction, scale bar: 20 μm, Video S5, 6).
Inhibition of vWF or its major platelet receptor GPIbα, but not of its alternative platelet receptor GPIIb/IIIa, significantly prolonged the time to complete microvascular thrombus formation in inflamed venules as compared to isotype control/vehicle treated animals (Fig. 5A). Furthermore, blockade of CD40 or its ligand CD40L/CD154 lead to a significant prolongation of thrombus formation in the inflamed venular microvasculature as compared to controls. In contrast, blockade of P-selectin/CD62P (facilitating platelet-or leukocyte-endothelial cell and platelet-leukocyte interactions through leukocyte PSGL-1/CD162 16 ) or Mac-1/CD11b (facilitating interactions of leukocytes with fibrin(ogen) or platelet GPIbα 37 ) did not significantly alter thrombus formation in inflamed venular microvessels. Noteworthy, only few NETs were found in the inflamed cremaster muscle (Fig. S7) and disruption of these structures (that are able to activate platelets and the coagulation system in lower-shear vessels [11][12][13][14] with DNase I did not affect microvascular thrombus formation (Fig. S6).
Employing in vivo immunostaining and multi-channel fluorescence microscopy as well as ex vivo confocal microscopy analyses, the role of vWF, GPIbα, CD40, and CD40L/CD154 for the spatial distribution of platelet interactions in the venular microvasculature was analyzed in a next step. Blockade of vWF (which is uniformly distributed throughout the entire thrombus) or of its platelet receptor GPIbα and -to a lesser degree -of CD40 (predominantly present on neutrophils and platelets) or its ligand CD40L/CD154 (predominantly present on platelets) significantly diminished the initial interactions of platelets in inflamed venules, but did not show any prevalence regarding the relation of platelets to adherent neutrophils (Fig. 5B,C).

Systemic leukocyte counts, microhemodynamic parameters, and FITC dextran perfusion.
To assure intergroup comparability, systemic leukocyte counts, microhemodynamic parameters including blood flow velocity, inner vessel diameter, and wall shear rate, as well as fluorescence intensities measured in analyzed FITC dextran-perfused vessel segments prior to induction of photochemical injury were determined in each experiment. No significant differences were detected among experimental groups (Table S3).

Discussion
Microvascular thrombosis is a hallmark of advanced inflammatory disease which leads to the interruption of blood supply and provokes ischemic tissue injury 1,3,4 . In this context, immune cells have been observed to collaborate with platelets and the plasmatic coagulation system for the generation of blood clots, employing a complex molecular interplay. Recently, intravascularly adherent leukocytes have been reported to alter their surrounding rheological environment 33 . Whether these distinct effects of immune cells are relevant for microvascular thrombogenesis is still unknown.
To understand the mechanisms controlling microvascular thrombosis in inflamed tissue, we here sought to determine the basic principles underlying this commonly encountered process. In line with previous reports under early systemic inflammatory conditions 24 , thrombus formation in the microvasculature of inflamed tissue critically involved platelets, but did not require fibrin generation by the coagulation system (as opposed to thrombosis in arteries, veins, or liver sinusoids 1,2 ). Most interestingly, inflammation dramatically accelerated thrombus formation in venules, but not in arterioles. A closer look on these microcirculatory events revealed that in unstimulated tissue thrombi originate from capillaries and progressively grow into the lumen of postcapillary venules ultimately occluding these vessel segments. In inflamed tissue, however, platelets directly accumulate at multiple sites in postcapillary venules thereby leading to an accelerated cessation of blood flow in the capillary   www.nature.com/scientificreports www.nature.com/scientificreports/ and venular vasculature. Thus, inflammation changes the spatio-temporal interaction patterns of platelets in the microvasculature which effectively promotes microvascular clot formation. These experimental findings might contribute to the explanation of clinical observations suggesting inflammatory conditions as independent risk factor for thromboembolic events 38 .
Leukocyte recruitment to the site of inflammation is an integral part of the inflammatory response [39][40][41][42][43] . Whereas immune cells were initially thought to be dispensable for thrombus formation in the microvasculature (during initial stages of endotoxemia) 24 , recent observations implicated these immune cells in the generation of microvascular clots upon focal laser-injury of the a priori unstimulated vessel wall 27,28 . Since platelets primarily accumulated in postcapillary venules (representing the vessel segments where neutrophils arrest on the endothelium upon induction of inflammation 17 ) during thrombus formation in inflamed tissue, we proposed that neutrophils critically support microvascular thrombosis under these pathological conditions. Consistent with our assumption, the acceleration of thrombus formation in the venular microvasculature was completely abolished in the absence of neutrophils clearly documenting that these cells drive inflammatory microvascular thrombosis. In this context, we found that platelets preferentially adhered at the vessel wall of postcapillary venules in areas downstream of adherent neutrophils during clot formation. At these 'hot spots' , platelets immediately formed aggregates that gradually merged into a large thrombus occluding the entire vessel segment. Conversely, under inflammatory conditions lacking significant leukocyte responses (e.g., in peripheral tissues during initial stages of endotoxemia 24 ), neutrophils are not involved in microvascular thrombogenesis. Hence, intravascularly adherent neutrophils recruit platelets to specific sites in the microvasculature of inflamed tissue from which thrombus formation can emerge. Our findings might thereby explain why neutropenia protects from thrombus formation in the cerebral microvasculature of mice suffering from experimental sickle cell disease (which is associated with leukocyte accumulation in microvessels) 25 .
With respect to these distinct interaction patterns of platelets in microvascular thrombosis, to the previously described streamlines around intravascularly adherent neutrophils 33 , and to reports on the shear-dependency of platelet interactions 30-32 , we further hypothesized that intravascularly adherent neutrophils promote platelet aggregation by perturbing the blood flow in the microvasculature. To analyze the contribution of such rheological effects of intravascularly adherent neutrophils to microvascular thrombogenesis, we constructed microfluidic devices consisting of flow channels with the size of postcapillary venules. In selected flow channels, the inner wall of these constructs exhibited 'bump' structures mimicking intravascularly adherent neutrophils. Upon perfusion with blood, we found that platelet deposition on the wall of these devices increased more than 100-fold when bumps were present. In this process, platelets adhered on the bump structure, migrated to its downstream face, and formed tethers anchoring to the obstacle. These membranous tethers (containing F-actin 44 ), in turn, promoted the capture of following platelets ultimately mediating aggregation of these cellular blood components and facilitating thrombus growth. Theoretical simulations revealed that the initial platelet adhesion to bump structures is supported by hydrodynamic forces approximating platelets to the bump structure and additionally inducing a flipping motion 45 in these cellular blood components when approaching the obstacle. This facilitates molecular binding of platelets and their subsequent arrest. Consequently, our data demonstrate for the first time that intravascularly adherent neutrophils promote microvascular thrombus formation by shaping the rheological environment for platelet aggregation.
Towards a more comprehensive understanding of the molecular mechanisms underlying neutrophil-driven thrombus formation in the microvasculature of inflamed tissue, we systematically screened a variety of candidate adhesion and signaling molecules for their functional relevance in this particular biological process 19,22,46,47 . In line with studies under early systemic inflammatory conditions [48][49][50][51][52][53][54][55] , clot formation in the inflamed venular microvasculature strictly required vWF (which is scattered throughout the thrombus) and its platelet counter receptor GPIbα, but not its alternative platelet receptor GPIIb/IIIa. In a more detailed analysis, we found that vWF mediated the initial intravascular interactions of platelets during thrombus formation. These vWF-and GPIbα-dependent events occurred irrespective of their relative localization to intravascularly adherent neutrophils. Blockade of other adhesion/signaling molecules facilitating interactions of platelets and neutrophils, including the β2 integrin CD11b/Mac-1 (leukocyte receptor for GPIbα 56,57 ) or CD62P/P-selectin (endothelial and platelet ligand for leukocyte PSGL-1/CD162 16,52,58,59 ), did not affect thrombus growth. Accordingly, blockade of GPIbα completely disrupted the attachment of discoid platelets to bump structures in our microfluidic channels, collectively suggesting that vWF serves as the 'molecular glue' for platelets during the onset of microvascular thrombus formation. Furthermore, we show that CD40 (present on adherent leukocytes and platelets) and its ligand CD40L (predominantly present on platelets) are also -but to a much lesser degree -involved in microvascular thrombosis in inflamed tissue, extending previously published observations 60 . Taken together, neutrophils play a critical role in the initiation of microvascular thrombus formation in inflamed tissue by facilitating GPIbα-vWF-and CD40-CD40L/CD154-depedent thrombus growth. To which extent physical rheological effects and neutrophil-specific molecular interactions mediate platelet accumulation in the inflamed venular microvasculature cannot clearly be stated.
In addition to adhesion and signaling molecules, extracellular traps released by neutrophils have recently been demonstrated to activate platelets and to bind components of the coagulation system thereby promoting thrombosis in lower-shear vessels such as liver sinusoids, arteries, and veins [11][12][13] . In line with recent observations 61 , however, NETs were dispensable for thrombus formation in the inflamed (high shear) microvasculature. These findings might be explained by the limited mechanical stability of complexes between DNA and other proteins (e.g., fibrin) under high shear stress 62 collectively emphasizing neutrophil-driven thrombosis in this common type of microvasculature as a biological process distinct from the mechanisms triggering 'immunothrombosis' in vascular beds with lower shear rates.
Whereas invasive intervention techniques for the removal of thrombi from arteries and veins revolutionized the treatment of thromboembolic events 6 www.nature.com/scientificreports www.nature.com/scientificreports/ smaller vessel segments, are still limited due to their inaccessibility to interventional procedures. Consequently, our findings urgently suggest the inclusion of neutrophils as targets in treatment regimens for microvascular thrombosis.
In conclusion, our experimental data uncover previously unrecognized functional properties of neutrophils in inflamed tissue that endow these immune cells with the ability to promote thrombosis by shaping the rheological environment in the venular microvasculature for platelet aggregation (Fig. 6). Targeting this distinct, leukocyte-directed interplay between the immune system and the hemostatic system might be instrumental to prevent microvascular clotting in advanced stages of inflammatory pathologies.

Methods
Animals. For our experiments, male C57BL/6 J mice (ageing 8-12 weeks; Charles River (Sulzfeld, Germany) were used. Animals had free access to food and water and were housed under conventional conditions. All experiments were conducted according to the German legislation for the protection of animals with approval of the local government authorities ('Regierung von Oberbayern').
Neutrophils were visualized by in vivo microscopy using an anti-Ly6G mAb (clone 1A8; PE-labeled; 5 μg in 100 μl PBS i.a.; BD Biosciences or clone AP-MAB0866; DyLight 550-labeld, 10 µg in 100 µl PBS i.a.; Novus Biologicals, Littleton, CO, USA). Platelets were visualized in vivo and in vitro by an anti-GPIbβ derivate (X-649; DyLight 649-labeled; 5 μg in 100 μl PBS i.a.; emfret Analytics). In microfluidic devices, vWF was visualized by an anti-vWF polyclonal Ab (100 μg per ml blood; Dako Deutschland GmbH, Hamburg, Germany) conjugated with a secondary anti-rabbit IgG antibody (green; Alexa Fluor 488 chicken anti-rabbit IgG; Invitrogen, Thermo Fisher Scientific, Rockford, IL). Please see the Major Resource Table in  In vivo microscopy on the mouse cremaster muscle. Surgical procedure. The surgical preparation of the mouse cremaster muscle was performed as originally described by Baez 65 with minor modifications 66 . Briefly, mice were anesthetized using a ketamine/xylazine mixture (100 mg/kg ketamine and 10 mg/kg xylazine), administered by intraperitoneal (i.p.) injection. The left femoral artery was cannulated in a retrograde manner for administration of microspheres, antibodies, or inhibitors. The right cremaster muscle was exposed through a ventral incision of the scrotum. The muscle was opened ventrally in a relatively avascular zone, using careful electrocautery to stop any bleeding, and spread over the pedestal of a custom-made microscopy stage. Epididymis and testicle were detached from the cremaster muscle and placed into the abdominal cavity. Throughout the procedure as well as after surgical preparation during in vivo microscopy, the muscle was superfused with warm buffered saline.
Photochemical injury. Microvascular thrombus formation was induced by photochemical injury as described before 52 . For this purpose, animals received an i.a. injection of a FITC-dextran solution (150 kDa, 2,5%, 6 ml/ kg bodyweight, Sigma-Aldrich). 5 min later, the vessel of interest (300 μm in length) was exposed to continuous epi-illumination using the FITC filter cube and appropriate illumination (λ = 488 nm). The field of illumination covers the entire field of view under investigation (as shown in figures and videos; in selected experiments all types of microvessels were epi-illuminated: Video S2, S3, S6). To assure intergroup comparability, the mean fluorescence intensity was determined in each of the analyzed vessels immediately after onset of light exposure.
In vivo microscopy. The setup for in vivo microscopy was centered around an Olympus BX 50 upright microscope (Olympus Microscopy, Hamburg, Germany), equipped for stroboscopic fluorescence epi-illumination microscopy as described before 67 . Briefly, light from a 75-W xenon source was narrowed to a near-monochromatic beam of a wavelength of 700 nm by a galvanometric scanner (Polychrome II, TILL Photonics, Graefelfing, Germany) and directed onto the specimen via a FITC filter cube equipped with dichroic and emission filters (DCLP 500, LP515, Olympus). Microscopy images were obtained with Olympus water immersion lenses [60×/numerical aperture (NA) 0.9, 20×/NA 0.5, and 10×/NA 0.3] and recorded with an analog black-and-white charge-coupled device (CCD) video camera (Cohu 4920, Cohu, San Diego, CA, USA) and an analog video recorder (AG-7350-E, Panasonic, Tokyo, Japan).
To visualize the behavior of leukocytes and platelets during microvascular thrombus formation, selected experiments were performed using an in vivo microscopy setup centered around an AxioTech-Vario 100 Microscope (Zeiss MicroImaging GmbH, Goettingen, Germany), equipped with a Colibiri LED light source (Zeiss MicroImaging GmbH) for fluorescence epi-illumination microscopy as described before 68  Quantification of leukocyte kinetics and microhemodynamic parameters. In vivo microscopy records were analyzed offline using ImageJ (National Institutes of Health, Bethesda, MD) and Cap-Image (Dr. Zeintl, Heidelberg, Germany) image analysis software as described before 69 . Briefly, the onset of thrombus was defined as the first observation of endothelially adherent platelets during thrombus formation. Cessation of thrombus formation was defined as the complete occlusion of the vessel segment with flow cessation for > 60 s. The cut off time for thrombus formation in venules was 1500 s, in arterioles 2700 s. Firmly adherent leukocytes were determined as those resting in the associated blood flow for 30 s and related to the luminal surface per 100 μm vessel length. Transmigrated leukocytes were counted in regions of interest (ROI), covering 75 μm on both sides of a vessel over 100 μm vessel length. Non-perfused micorvessels in controls and LPS treated animals were quantified by counting occluded arterioles, capillaries and venules per high power field (HPF) with 175 HPF per animal this being equivalent to the total quantifiable area of an exteriorized cremaster muscle. By measuring the distance between several images of one fluorescent bead under stroboscopic illumination, centerline blood flow velocity was determined. From measured vessel diameters and centerline blood flow velocity, apparent wall shear rates were calculated, assuming a parabolic flow velocity profile over the vessel cross-section. www.nature.com/scientificreports www.nature.com/scientificreports/ Experimental protocols and groups. In a first set of experiments, perfusion of arterioles, capillaries, and venules was analyzed in 15 high power fields (HPF) in a central area of the spread-out cremaster muscle of unstimulated WT mice and in WT mice undergoing four hours of intrascrotal stimulation with LPS as well as receiving an intra-venous application of neutrophil-depleting anti-Ly-6G mAb or isotype control Ab (n = 4 per group). In further experiments, thrombus formation in three randomly chosen postcapillary venules (diameter: 30-50 µm) and one arteriole (diameter: 20-35 µm) was analyzed upon photochemical injury 6 h after intra-scrotal injection of PBS or LPS (n = 9 per group). In separate experiments, the effect of heparin (administration 10 min prior to photochemical injury), platelet depletion, or neutrophil depletion on microvascular thrombus formation was analyzed 6 h after intra-scrotal or intra-peritoneal injection of PBS or LPS (n = 3-4 per group). In further experiments, the role of various adhesion/signaling molecules potentially mediating interactions of endothelial cells, leukocytes, and/or platelets for venular thrombus formation was analyzed upon application of blocking mAb or inhibitors (administration 10 min prior to photochemical injury) 6 h after i.s. injection of LPS (n = 4 per group). After in vivo microscopy, blood samples were collected by puncturing the inferior vena cava for the determination of systemic leukocyte and platelet counts using a ProCyte Dx cell counter (IDEXX Laboratories, Westbrook, ME, USA). Anesthetized animals were then killed by bleeding to death.
Microfluidic experiments. Construction of microfluidic devices. Microfluidic devices were fabricated by molding silicone elastomer (PDMS Slygard 184, Dow Corning; Midland, MI, USA) to master molds constructed by photolithography on silicon wafers. The mold consisted of two layers of SU-8 photoresist (MicroChem Corp., Westborough, MA, USA), created by two superimposed patterns. A 32 µm thick layer of the channel layout was superimposed with an 8 µm thick layer of the channel layout with cut-outs of 'bump structures' , yielding a negative mold with 40 µm thick channels and 8 µm thick bumps. The bump diameter was chosen to be 8 µm, resulting in cylindrical bumps with blunt edges due to photolithography limitation. The channel width was chosen to be 40 µm, resulting in a quadratic 40 µm × 40 µm cross-section. The channel layout consisted of four channels of different bump densities (0, 10, 25, and 50 bumps per 10 4 µm 2 ), fed from the same source and leading into the same sink. Bumps were randomly placed at non-overlapping positions throughout the channel using a standard MATLAB random number generator routine. A serpentine (40 µm × 40 µm × 16 mm) between channels and sink was designed as hydrodynamic resistance to reduce the flow rates to physiological conditions. The PDMS was mixed according to the manufacturer's instructions, poured onto the wafer and cured for one hour at 80 °C. The cured PDMS was separated from the wafer and inlets and outlets were punched. The chip was then cleaned, exposed for 30 s to oxygen plasma (Diener electronics GmbH + Co. KG, Ebhausen, Germany) and irreversibly bond to a microscope slide.
Fluorescence microscopy. Microscopy was performed using a Nikon Ti-E inverted microscope system with automated stage and shutters controlled by NIS-Elements (Nikon, Tokio, Japan). Five positions spanning a total of 40 µm × 830 µm were recorded in each of the four channels every minute using a CFI P-Apo DM 100x objective and a SCMOS camera (Zyla-5.5, Andor, Belfast, Northern Ireland). Platelets were labeled with anti-GPIbβ derivate (X-649; emfret Analytics, Germany) and fluorescence emission was recorded.
Experimental protocol. Microfluidic chips were flooded and flushed with phosphate-buffered saline (PBS) before microfluidic flow experiments. A reservoir of heparinized mouse whole blood was connected to the microfluidic chip by silicone tubing and directed into the inflow of the device. Four channels with different densities of bump structures (as described above) were simultaneously perfused with whole blood containing fluorescence-labeled platelets. Upon application of fluorescence-labeled microspheres, the distance between several images of one fluorescent bead under stroboscopic illumination was measured allowing to determine the centerline blood flow velocity in the flow channels and to calculate the apparent wall shear rates as described above. The flow velocity was controlled by modulating the hydrostatic pressure, ultimately adjusting a shear rate of 1500 s −1 in the flow channels (corresponding to the shear rates present in the analyzed postcapillary venules; Table S3). After 10 minutes of perfusion, the number of adherent platelets was counted. In separate experiments, blood was diluted 10-fold with PBS for time-lapse high-resolution microscopy in order to avoid that the high density of cells obstructed the microscopy light passing through the cross-section of the channel. During perfusion, time-lapse microscopy was performed on the four channels to visualize capture, adhesion, and aggregation of platelets. In additional experiments, vWF deposition was visualized after 10 min of perfusion of PDMS channels with blood containing differentially fluorescence-labeled anti-vWF antibodies and platelets.
Fluid dynamics simulation. The fluid was simulated in a geometry representing a venule of 40 µm diameter under physiological flow conditions. We simulate a longitudinal cross section of the venule (2D, 160 µm × 40 µm), due to the observed adherence over the top of the bump structure, using commercial finite element simulation tools (COMSOL Multiphysics, Stockholm, Sweden). Due to the low Reynolds numbers found in the microvasculature, we assumed laminar flow. The platelet was considered a discrete, inelastic object that due to its small size does not alter the fluid flow in its vicinity. This allows for calculation of the fluid flow first, and afterwards using the solution to solve the translational and rotational movement of the platelet. Translation was calculated assuming Stokes drag, using the fluid velocity at the center of mass of the platelet. Rotation was induced by choosing the rotational velocity such that the average torque along the surface of the platelet was zero. Both translational and rotational movements in this approximation do not alter the fluid flow and were calculated using a custom-written MATLAB (Mathworks, Natick, MA, USA) script.
Confocal microscopy. For the analysis of CD40, CD40L/CD154, or vWF expression in microvascular thrombi, mouse cremaster muscles were prepared (6 h after i.s. injection of 10 ng LPS diluted in 400 µl PBS) and


extfieldsofstudy: Biology Medicine

text:
Co-expression Network Analysis Elucidated a Core Module in Association With Prognosis of Non-functioning Non-invasive Human Pituitary Adenoma

Non-functioning pituitary adenomas (NFPAs) are tumors with clinically challenging features since they have insidious progression. A complex network of gene interactions is thought to have roles in tumor formation and progression. Therefore, revealing the genetic network behind NFPA tumorigenesis is not only essential to attain further knowledge of tumor biology, but also plays a fundamental role in the development of efficacious treatment strategies. Differential co-expression network analysis is an outstanding approach for elucidation of groups of genes which show distinct co-expression patterns among phenotypes. In this study, we carried out a differential co-expression network analysis of NFPA-associated transcriptome dataset (n = 40) considering invasive (n = 22) and non-invasive (n = 18) phenotypes. Furthermore, we identified differentially co-expressed and co-regulated mRNA modules, which might be considered as potential systems biomarkers for NFPA prognosis and invasiveness. As a result, we have identified a novel 13-gene module, including CEACAM6, CYP4B1, EIF2S2, HID1, IFFO1, MYO18A, PDCD2, SGIP1, SWSAP1, and four unknown genes (A_24_P127621, A_24_P255786, A_24_P683553, and A_24_P916979), which was able to categorize the patients into two groups as invasive and non-invasive NFPA with distinct prognosis. The prognostic core module genes were associated with progression and prognosis of brain and glandular based cancers as well. Furthermore, these module genes were also expressed in blood, salivary gland, and spinal cord tissues. These results may provide the evidence on featured gene module which might play a prominent role in NFPA prognosis and sub-typing as effective biomarkers and therapeutic targets in the future.

INTRODUCTION
Pituitary adenomas (PAs) are the second most frequently reported primary brain tumors that are associated with increased mortality and morbidity (1,2). Non-functioning pituitary adenomas (NFPAs) are the most common type of PAs that are not hormonally active (3). In contrast with the functioning pituitary adenomas (FPAs), which secrete excess levels of hormones that can lead easily to track endocrine syndromes, the detection of pituitary adenomas including NFPAs is clinically challenging. They are diagnosed usually in the context of mass effect (compress adjacent neurovascular tissues) leading to visual loss, dysfunction of the pituitary, and cranial neuropathies. PAs are usually non-invasive and benign neoplasms in nature, but some of them exhibit an aggressive attitude and represent invasive characteristics through cells from a neoplasm extend to the adjacent healthy tissues and infiltrating into them. Invasive PAs display local invasion, elevated risk of postoperative recurrence, and inadequacy of therapeutic response (4). Even in the perturbation of surrounding tissues, invasive PAs are not considered as malignant.
In the classification of tumors of the endocrine system, World Health Organization (WHO) offers several markers associated with invasiveness such as the Ki-67 proliferative index, the number of mitotic figures, and the expression of p53 (5). Moreover, FSH-β, LH-β, and/or α-subunit immunostain positivity and expressivity of SF-1, GATA-2, and ER-α transcription factors were proposed as the indicators of the gonadotroph lineage in NFPAs, and null cell adenomas were defined as negative immunoreactivity for both pituitary hormones and pituitary transcription factors (5,6).
The expression profiling studies at RNA level intending the identification of molecular markers associated with NFPA invasiveness are very limited. The upregulation of MYO5A, and downregulation of E-cadherin (CDH1) and H-cadherin (CDH13) were proposed as markers of invasiveness at mRNA level (7,8). Several microRNAs including miR-135a, miR-140-5p, miR-582-3p, miR-582-5p, and miR-938 were found as overexpressed in the invasive state, and they were also associated with tumor size and tumorigenesis (9). Moreover, the expression levels of lncRNAs, maternally-expressed gene 3 (MEG3) and Hox transcript antisense intergenic RNA (HOTAIR), were correlated with NFPA development and invasion (10).
Despite the proposed molecular markers and immunohistochemical indicators of invasiveness, early prediction of invasive NFPA remains considerably arduous since there is no consistent pattern that differentiates invasive from non-invasive PA. Thus, invasive PA needs to be properly defined with molecular markers in order to identify patients at increased risk of early recurrence or subsequent tumor progression. The present markers and classification systems are insufficient to guide precise diagnostic and therapeutic decisions in pituitary tumor invasiveness.
Differential co-expression is defined as the altered coexpression patterns of genes between two phenotypes and represents significant potential to identify gene clusters associated with the phenotype of interest (11). In several studies, co-expression analyses were performed to elucidate the PA metastasis, invasion and progression. Zhang et al. identified co-expressed gene pairs for prolactin (PRL) secreting pituitary tumor metastasis and hypothesized that SLC2A11, TENM1, IPO7, and CHGB are associated with metastasis in prolactinoma cases (12). Co-expression of somatostatin and dopamine receptors were also investigated and invariable loss in expression of both receptors in invasive growing corticotroph adenomas was reported (13).
In this study, we aimed to determine whether invasive and non-invasive PAs display differences in mRNA expression profiles through a differential co-expression network analysis framework. A novel gene module, which was differentially coexpressed in non-invasive PA when compared to invasive PA state, was presented, and its prognostic performance was tested in several tumor types through survival analyses. Topological and functional enrichment analyses were performed to elucidate the molecular mechanisms. Transcriptional regulatory elements (i.e., transcription factors and miRNAs) associated with the prognostic gene module were investigated, and expression levels of the module genes in various tissues were also screened.

Selecting Gene Expression Profiling Dataset
In order to gather NFPA associated gene expression profiling datasets, we comprehensively screened the publicly available functional genomics data repositories including ArrayExpress (14), NCBI Gene Expression Omnibus (GEO) (15) and The Cancer Genome Atlas (TCGA, http://cancergenome.nih.gov/). Among three transcriptome datasets, GSE63357 (16), GSE77517 (17), and E-TABM-899 (7), carried out with NFPA samples (with no hormone secretion), we preferred to employ E-TABM-899 considering its large sample size and sampling characteristics. Expression profiles of mRNA and related clinical data of invasive and non-invasive PA were downloaded from ArrayExpress database (https://www.ebi.ac.uk/arrayexpress/). Gene expression profiles generated using Agilent whole human genome oligo microarrays were used as a training set to construct coexpression networks, identify hub genes, and differentially expressed genes (DEGs) in this study. Transcriptome data was composed of 40 samples classified as invasive (n = 22) or non-invasive (n = 18). NFPA samples were characterized in terms of clinical and pathological features including age, sex, hormonal secretion (LH, FSH), immunohistochemical staining, tumor volume (varied between 0.5 and 77 cm 3 ), tumor grade, follow-up time, and outcome (recurrence, stably remnant, and remnant). Immunostaining for FSH-β and LH-β and/or αsubunit was used for tumor characterization. According to WHO 2017 classification of tumors of the pituitary gland (5), the dataset was composed of 38 samples with gonadotroph lineage (positive immunostains FSH-β and LH-β and/or α-subunit) and 2 samples with null cell adenoma (negative for immunostains) (5,6). Tumor size and invasiveness were determined with regard to preoperative magnetic resonance imaging and perioperative findings, by employing the modified Hardy criteria (18), which is grade I, if tumor < 10 mm, it is enclosed microadenoma; grade II, if tumor > 10 mm, it is enclosed macroadenoma; grade III, localized perforation of the sellar floor; and grade IV, diffusive destruction of the sellar floor. Tumor recurrence was classified according to radiological findings of re-growth of the tumor remnant or new tumor growth (in patients with no surgical remnants). Remnant tumors were accepted as stable if there was no sign of growth on two MRI within the 1-year interval and no clue of disease reactivation. Follow-up times were years that passed after surgery and varied between 3 and 10.5 years. This dataset included tumors in varied grades, 1 of grade I, 18 of grade II, 6 of grade III, and 15 of grade IV. Grade III and IV tumors, as well as one Grade II tumor exhibiting extradural extension, were accepted as invasive.

Data Processing and Identifying Differentially Expressed Genes
Pre-processing of microarray data was performed in R using expression profiles (E-TABM-899.eSet.r) downloaded from ArrayExpress database (14). The expression profiles were normalized through quantile normalization. DEGs between invasive and non-invasive PAs were identified from the normalized expression values by using Linear Models for Microarray Data (LIMMA) package (version 3.34.5) (19). The Benjamini-Hochberg method was used to control the false discovery rate. In addition, cross-validation of the DEGs was performed using the two-sample t-test. To determine the statistical significance, adjusted p < 0.05 was used, and genes that showed at least 10% change in expression were selected for further consideration in the network construction.

Pathway and Functional Enrichment Analysis for DEGs
The pathway and functional enrichment analyses were performed using ConsensusPathDB (Release 32) (20) to identify functional annotations significantly associated with the DEGs. The Kyoto Encyclopedia of Genes and Genomes (KEGG) (21) database was preferably used as the pathway database. The Gene Ontology (GO) terminology (22) was employed as the source for annotating the molecular functions and biological processes. P-values were obtained via Fisher's Exact Test. Benjamini-Hochberg's correction was used as the multiple testing correction techniques, and enrichment results with adjusted p < 0.01 were considered statistically significant. Comparison of the significant GO terms and KEGG pathways was performed to identify the different biological functions and processes between the invasive and non-invasive samples.

Co-expression Network Construction for Invasive vs. the Non-invasive States
Co-expression networks were constructed for invasive and noninvasive PA states as previously described (11). Initially, among the 29,754 genes detected in the pituitary samples, DEGs were identified. In the case of the repetition in expression values of DEGs, the mean expression values were computed and used in further analyses. Pearson's correlation coefficient (PCC) was employed to determine the co-expression levels between DEG pairs in each state. Benjamini-Hochberg's correction was used as the multiple testing correction techniques, and the gene pairs were regarded as co-expressed if |PCC| ≥ 0.80 and adjusted p ≤ 0.05.
To identify differential co-expression profiles between two states, the following criterion was employed: where PCC NONINV and PCC INV are the PCC of a DEG pair in non-invasive and invasive states, respectively. Resultant gene pairs were selected to construct the co-expression networks, ICON (invasive co-expression network) and NICON (noninvasive co-expression network), representing invasive and noninvasive states of PA, respectively.

Identification of Differentially Co-expressed Gene Modules
To elucidate highly connected network modules, co-expression networks were analyzed using MCODE (23) plugin of Cytoscape (v.3.5.1) (24). Modules with at least 10 nodes (genes), average connectivity ≥10 and clustering coefficient ≥ 0.5 were considered as differentially co-expressed modules between invasive and noninvasive states. Modules were further analyzed with Network Analyzer (25) and Cytohubba (26) plug-ins to determine the significantly altered hub genes with respect to local and global topological metrics (i.e., degree and betweenness centrality).

Sub-type Clustering Performance of Co-expressed Gene Modules
Considering the expression profiles of module genes, Principal component analysis (PCA) was performed to cluster invasive and non-invasive samples. The principal components explaining at least 85% of the total variance was considered in the determination of clustering performance, i.e., the ability hereupon "sub-typing" of PA.

Prognostic Power and Survival Analyses
PCA was performed based on gene expression profiles of module genes, and samples were categorized into three clusters using k-means algorithm taking into consideration the first three principal components (explaining 98% of the total variance). Cox regression was performed via MedCalc Statistical Software (v.18.2.1, Ostend, Belgium) to elucidate survival-associated genes. Analysis results were visualized and compared through Kaplan-Meier plots using the follow-up times of invasive and non-invasive groups. The prognostic power of the module was determined using the log-rank test p-value, the hazard ratio (HR), and its confidence intervals (CI).

In silico Validation in Related Tumor Types
We used SurvExpress (27) web-based biomarker validation tool in order to test the validity of the proposed prognostic gene module in various cancer types. Validation analyses were carried out through independent RNA-seq datasets obtained from TCGA (28) and microarray datasets from NCBI-GEO. Core module genes were tested through glandular based cancers including adrenocortical carcinoma (TCGA, n = 77), breast invasive carcinoma (TCGA, n = 502), and ovarian serous cystadenocarcinoma(TCGA, n = 247); brain tumors including glioblastoma (TCGA, n = 660), meningioma (NCBI-GEO, GSE16581, n = 68), and medulloblastoma (NCBI-GEO, GSE37418, n = 76) (29,30); and other cancers including prostate adenocarcinoma (TCGA, n = 497) and lung adenocarcinoma (TCGA, n = 475). For each dataset employed, samples were partitioned into low and high-risk groups according to their prognostic index, survival multivariate analyses, and risk assessments. The prognostic performance of modules in each dataset was determined using Kaplan-Meier plots, log-rank test p-values, hazard ratios (HR), and their confidence intervals (CI). Differences in gene expression levels between high and low-risk groups were presented by box-plots and statistical significance of the difference was calculated through t-test. Heatmaps were also created to clarify the correlation of the survival analysis with gene expression levels. Samples were sorted by their prognostic index and genes were clustered by using Euclidean distance.

Screening of Gene Expressions in Varied Tissues
The expression levels of modules genes in easily collectible tissues were obtained from The Genotype-Tissue Expression (GTEx) project (31), which provides a genome-scale expression profiling (RPKM) of 51 normal human tissues, cells, and fluids.

Transcriptional Profiling in Non-functioning Non-invasive Human Pituitary Adenoma
Transcriptome data (E-TABM-899) was composed of 40 NFPA samples, which were characterized in terms of clinical and pathological features including age, sex, hormonal secretion (LH, FSH), immunohistochemical staining (FSH-β and LH-β and/or α-subunit), tumor volume (0.5-77 cm 3 ), tumor grade (I-IV), follow-up time (3-10.5 years), and outcome (recurrence, stably remnant, and remnant). Tumor size and invasiveness were determined with regard to preoperative magnetic resonance imaging and perioperative findings, by employing the modified Hardy criteria (18), Tumor recurrence was characterized according to radiological findings of re-growth of the tumor remnant or new tumor growth (in patients with no surgical remnants). As a result, the samples were classified into invasive (n = 22) and non-invasive (n = 18) groups.
Further verification of sample classification was carried out employing the expression values of MKI67 gene, which encodes Ki-67 protein accepted as a labeling index of proliferation (32). MKI67 expression levels in two groups were compared and a statistically significant difference (p = 0.02) was observed between mean expression levels of invasive (88.49 ± 2.32) and non-invasive groups (81.62 ± 1.56; Figure 1).

Identification and Functional Annotation of Differentially Expressed Genes (DEGs)
Following up a standard protocol including quantile normalization of raw data, statistical comparisons of expression levels through "limma" package, and multiple testing correction with Benjamini-Hochberg method, a total of 4,091 genes were identified as differentially expressed between two phenotypes, i.e., invasive and non-invasive pituitary adenoma, considering a statistical confidence level of p < 0.05. In addition to p-values, we also considered at least 10% change in mean expression levels (FC < 0.9 for down-regulation, FC > 1.1 for up-regulation) as a criterion in the identification of DEGs and determination of their direction of regulation. This filtering resulted in 641 DEGs of which 145 were down-regulated and 496 were up-regulated.
The functional annotations of the down-regulated DEGs were significantly enriched with transmembrane transport of organic substances (especially the cations), disassembly of protein complexes and its regulation, endocytic recycling, and response to copper ion; whereas genes associated with responses to lipids, DNA damage stimulus, and cytokines, regulation of protein localization, proteasomal protein catabolism, endoplasmicreticulum-associated protein degradation (ERAD) pathway, regulations of telomere maintenance and oxidoreductase activity, cell aging, and oxidative demethylation were up-regulated (Figure 2A). The major KEGG pathways significantly associated with DEGs (p < 0.01) were axon guidance (17 genes), ABC family mediated transport (8 genes), SUMOylation of DNA damage response and repair (6 genes), estrogen receptor alpha signaling pathway (5 genes), imatinib pathway (3 genes), and warfarin pathway (2 genes; Figure 2B).

Detection of Differentially Co-expressed Gene Modules
The possible co-expression patterns of 641 DEGs were analyzed through the employment of PCCs in invasive and noninvasive phenotypes separately to construct phenotype-specific co-expression networks. This resulted with a denser, centralized, and modular co-expression network in invasive phenotype  (ICON) with 183 links among 162 genes ( Figure 3A) when compared to the non-invasive co-expression network (NICON), which includes 2,385 links among 562 genes ( Figure 3B). Not only the number of genes exhibiting co-expression pattern was almost 4-fold higher in the non-invasive state, but also the network centralization (0.835) and the clustering coefficient (0.348) were higher in NICON when compared to those in ICON (0.394 and 0.002, respectively).
Comparative analysis of the phenotype-specific co-expression networks yielded with 10 differentially co-expressed gene modules (ranging in size from 5 to 69 genes), which were activated in non-invasive phenotype when compared to invasive. Differentially co-expressed gene modules were named as M1 (Module 1)   PA were tabulated ( Table 1). M1 was composed of 41 genes and these genes were enriched in regulation of cell adhesion. M2 had 45 genes that were enriched in GTPase activator activity and nucleoside triphosphatase regulator activity. M3 included 14 genes that related to Actin filament binding and Ras protein signal transduction processes. M4 had 69 genes which were enriched in DNA damage checkpoint and regulation of cellular response to stress. There were 10 genes in M5 and enriched in DNA damage checkpoint process. M6 had 8 genes that were related with metal ion binding process. M7 included 8 genes that enriched in pyrophosphatase activity, hydrolase activity, and acting on acid anhydrides. M8, M9, and M10 included 5 genes that were enriched in nervous system development, Ras and GTPase mediated signal transduction, and protein complex binding, respectively. Core module included 13 genes which were enriched in ATPase activity and regulation of endocytosis. These modules have been associated with neither PA diagnosis nor PA prognosis in literature.
To determine the possible associations of the identified coexpression modules with clinicopathological features (i.e., age, tumor size, tumor grade, hormonal status, follow-up time, and clinical outcome), we conducted the Principal Components Analyses (PCA) as well as Kaplan Meier survival analyses, and detected significant correlations with tumor grade and sub-type for several gene modules.
Three modules, i.e., M3 with 14 genes associated with actin filament binding and Ras protein signal transduction, M6 with 8 genes associated with metal ion binding, and M7 with 8 genes associated with pyrophosphatase and hydrolase activities, presented considerable accuracy in discrimination of two sub-groups of invasive and non-invasive states in PA (Figure 4). Considering the similar discriminatory behavior of these modules, we combined them and narrowed the co-expression patterns with a higher PCC cut-off (increasing from 0.8 to 0.9) to obtain a "core module" consisting of the minimum number of genes with higher discrimination ability. This resulted with a core module of 13 genes (CEACAM6, CYP4B1, EIF2S2, HID1, IFFO1, MYO18A, PDCD2, SGIP1, SWSAP1, A_24_P127621, A_24_P255786, A_24_P683553, A_24_P916979), which indicates higher discrimination accuracy, since clusters representing invasive and non-invasive states were clearly separable and distinguishable without any overlaps in PCA plots (Figure 4). Interestingly, the genes in the core module were not enriched in any molecular pathway or biological process as a whole; but some sub-groups were enriched in ATPase activity and regulation of endocytosis (p < 0.001). Notably, four genes (A_24_P127621, PDCD2 -Encodes a highly conserved nuclear protein, -Abnormal PDCD2 expression alters cell apoptosis.
-Alteration of PDCD2 expression could be conducive to human cancer development and progression.

SGIP1
-One of the key regulators of clathrin-mediated endocytosis.
-Functions as an endocytic protein that alters signaling by receptors in neuronal systems -Affects energy homeostasis via interaction with endophilins.   A_24_P255786, A_24_P683553, A_24_P916979) located in distinct chromosomes were not annotated with any molecular function yet ( Table 2).

The Prognostic Performance of the Core Module Between Different PA States
The genes in the core module indicated significantly different co-expression patterns between invasive and non-invasive phenotypes of PA ( Figure 5). The clustering of samples based on the expression profiles of core module genes via the first principle component (PC1) of the PCA analysis (describing 89.8% of the total variance) and k-means algorithm resulted with three distinct sub-groups of patients ( Figure 6A). The cluster representing lower loadings on PC1 consisted of only invasive and grade IV tumor samples; whereas the cluster with higher loadings on PC1 included non-invasive and grade II tumors. Furthermore, survival analysis with the Cox regression model and Kaplan-Meier estimates indicated the predictive power of patient survival among the sub-types ( Figure 6B). There was a significant difference among groups in terms of survival probability estimates (p = 0.0024, log-rank test), and the average survival probability of non-invasive and grade II tumors was significantly higher than that of invasive and grade IV tumors with a hazard ratio of 2.96 (p = 0.011).

Transcriptional Regulators of the Core Module Genes
In order to elucidate the regulatory mechanism behind the co-expression pattern of module genes and to evaluate the condition-specific expression pattern alterations, we performed serial analyses to link the key regulators of transcriptional control, i.e., transcription factors (TFs) and microRNAs (miRNAs), to genes in the core module. A total of 10 TFs were found as regulators of the module genes and GATA1, GATA2, ETS1, ESR1, and PRDM14 were top five regulators with highest degree values ( Figure 7A). The majority of the core module genes were co-regulated by ETS1 and GATA2. Furthermore, among module genes EIF2S2, IFFO1, and PDCD2 were co-regulated by the same TFs. In contrast to TFs, core module genes were regulated by distinct miRNAs (Figure 7B). Among those, mir-335-5p was the only common regulator between two gene pairs (HID1 and MYO18A). Members of the core module were found in varied chromosomal locations. CEACAM6 and SWSAP1 were located on chromosome 19 whereas HID1 and MYO18A were on chromosome 17, CYP4B1, and SGIP1 were on chromosome 1, PDCD2 was on chromosome 6, A_24_P127621 was on chromosome 7, A_24_P683553 was on chromosome 9, A_24_P255786 was on chromosome 10, IFFO1 was on chromosome 12, EIF2S2 was on chromosome 20, and A_24_P916979 located on chromosome X.

The Specificity of the Core Module to NFPA
In order to analyze NFPA-specific expression and prognostic performance of the core module, we carried out several analyses over various human cancers with or without tissue similarity with PA. First of all, we tested its prognostic performance in other glandular based cancers including adrenocortical carcinoma, breast invasive carcinoma and ovarian serous Lastly, we tested the prognostic performance of the core module in two other unrelated tissue but highly prevalent cancers, namely lung, and prostate adenocarcinoma. This time survival analyses pointed out insignificant performance in both lung (p = 0.08) and prostate (p = 0.15) adenocarcinomas ( Figure S1). As a consequence, our core module could be considered as prognostic for both glandular-origin cancers and brain cancers, but not for lung and prostate cancers.

Tissue-Specific Expressions of Core Module Genes
We searched for the expression levels of module genes in easily collectible tissues (especially not need to biopsy or taking by minimally invasive operations) in order to decipher whether these genes can be detectable at mRNA level. Core module genes have detectable expression values in varied tissue types like blood, kidney, lung, spleen, spinal cord, saliva, pancreas, and uterus. It was also difficult to obtain a cumulative behavior in expression patterns of the genes in the same tissue; however, we found that every core module genes have considerable expression values in three tissue types, which are blood, salivary gland, and spinal cord (Figure 10).

DISCUSSION
There is a great need for interpretation of omics data to elucidate the multi-layered molecular mechanisms lay behind the invasion of PA. However, omics datasets associated with PA invasiveness is scarce in the publicly available databases. Even in TCGA, which is the most comprehensive and multi-dimensional database for cancer genomics with 33 cancer types, genomics and/or transcriptomics of PA were not considered. The scarcity of omics datasets indicates the urgent need for further efforts on mRNA profiling in NFPA. Despite designated markers associated with invasive behavior of PA tumors such as the Ki-67 proliferative index, the number of mitotic figures, and the expression of p53 (48,49), the early prediction of PA invasiveness is still considerably hard, since the patient's state tends to be delayed due to the clinical symptoms of NFPA which are not obvious in the early stage. In the era of precision medicine, accurate biomarkers for cancer-specific prognosis and early prediction were urgently required and this convincingly enhances decision making for patient management.
Instead of the construction of the commonly used biological networks in literature like PPIs and metabolic networks, we constructed gene co-expression networks since it has several advantages such as almost complete coverage of human genes, little knowledge bias obtained from the published literature, and the ability to create cancer type-specific networks. Identification of changes in co-expression patterns of genes among invasive and non-invasive samples provides information about the invasiveness of PA-specific gene modules. Previous studies in literature objected to predict candidate prognostic biomarkers or protein-protein interaction networks constructed around differentially expressed genes in PA, not co-expressed gene modules. The altered co-expression schemes of module genes among invasive to the non-invasive state were neglected in these studies. Here, we made a differential co-expression analysis to elucidate PA genes and their coexpression pairs. As a result, the novel co-expressed gene module presented here may be regarded as "systems biomarkers" that lead to the design of effective therapeutic strategies in PA prognosis.
In the present study, co-expressed gene networks were constructed for invasive and non-invasive states (ICON and NICON, respectively) separately. ICON hub genes were enriched mostly in signaling processes like Ras, Rho, and small-GTPase signaling. It was reported that Ras small GTPase had a key signal transduction role in activating MAPK cascade (50). Rho GTPases are activated by G-protein-coupled receptors (GPCRs) and play critical roles in the invasion and metastasis of cancer cells (51). Hub genes of NICON were enriched in biological processes like urogenital system development, thyroid gland development, tyrosine kinase activity, protein kinase B signaling, and intracellular receptor signaling. The pituitary is part of the endocrine system and it was expected to found urogenital system development and thyroid gland development processes considering the secretion of TSH and FSH in the pituitary. Protein kinase B (Akt) signaling was found as over-expressed and over-phosphorylated in human PAs and proposed a potential role for Akt with respect to p27 deregulation (opposite direction to each other) (52).
The differential co-expression profiling followed by clustering and survival analyses resulted with a prognostic core module composed of 13 genes; namely, CEACAM6, CYP4B1, EIF2S2, HID1, IFFO1, MYO18A, PDCD2, SGIP1, SWSAP1, and 4 unknown genes (A_24_P127621, A_24_P683553, A_24_P255786, A_24_P916979). The unknown genes, A_24_P127621, A_24_P683553, A_24_P255786, and A_24_P916979, have specific gene sequences and distinct chromosomal locations (chromosome 7, chromosome 9, chromosome 10, and chromosome X, respectively); however, there was no known functional annotation of them in any of the annotation sources. Further in-depth experimental research studies might be performed to elucidate their function and association with PA tumorigenesis and/or invasiveness. The high prognostic power of the core module was not specific to NFPA but also observed in cancers with the same tissue origin such as glandular-origin cancers and brain cancers.
Among the module genes, CEACAM6 encodes a protein that is a member of the carcinoembryonic antigen (CEA) family whose crew are cell surface glycoproteins (33). Members of this family have a function in cell adhesion and they are widely employed as serum tumor markers for determinations of carcinoma (53). Moreover, over-expression of CEACAM6 modulates cancer progression through aberrant cell differentiation, anti-apoptosis, cell growth, and resistance to therapeutic agents (54). In addition, CEACAM6 over-expression in varied malignancies promoting cell invasion and metastasis, therefore, it represents a characteristic advantage of tumor cells which are responsible for an invasive phenotype (55). It is also FIGURE 10 | Tissue-specific expressions of core module genes. a major determinant for malignant phenotype of pancreatic cancer through over-expression of the positive regulation of epithelial-mesenchymal transition (35,36,56).
CYP4B1 gene encodes a member of the cytochrome P450 superfamily of enzymes which is responsible for the oxidation of steroids, fatty acids, and xenobiotics therefore involved in reactions in drug metabolism (37). CYP4B1 was reported as procarcinogen for some chemicals in bladder carcinoma, downregulated in esophageal squamous cell carcinoma and upregulated in breast tumors when comparing the surrounding healthy tissues (38,57,58).
EIF2S2 encodes eukaryotic translation initiation factor 2 and functions as a vehicle in the early phases of protein synthesis. The deletion of EIF2S2 gene has been reported with suppression of testicular germ cell tumor incidence and recessive lethality in mice (39). It is also reported that EIF2S2 is up-regulated and involved in major enriched genes in epithelial ovarian carcinoma (EOC) samples and cervical cancer vs. normal group (53,59,60). In ER-negative breast cancer, EIF2S2 gene was found as a member of novel loci (61).
HID1 gene encodes a protein functioning in the trafficking of cargos that are important for the sorting/biogenesis/maturation of dense core vesicles and plays an important role in the development of cancers in a broad range of tissues (40,62). It is alternatively named as DMC1 (down-regulated in multiple cancer 1). The loss of expression of HID1 was reported in breast, cervical, lung, thyroid, renal, and gastrointestinal cancer cell lines (62).
IFFO1 gene is a member of the intermediate filament family which include essential components of the cytoskeleton and nuclear envelope (41,42). In ovarian cancer, its promoter was hypermethylated and IFFO1 was proposed as a biomarker (63). In addition, it has been identified as a strong prognostic indicator of breast cancer (63). The hypomethylation and up-regulation of IFFO1 have been also reported in endometrioid endometrial adenocarcinoma samples (64).
MYO18A encodes a protein which is part of a complex that unifies lamellar actomyosin bundles and needed for cell migration. MYO18A has been found highly expressed in metastatic prostate cancer and its knockdown affects the cytoskeleton and cell migration (65). MYO18A gene fusion has been identified in an acute cell leukemia patient (66).
PDCD2 (programmed cell death 2) gene encodes a nuclear protein expressed in a variety of tissues and its expression is controlled by transcriptional repressor BCL6. It plays an important role in cell death and/or in the regulation of cell proliferation. PCDC2 has been found as a tumor suppressor and involved in the pathogenesis of osteosarcoma. Aberrant expression of PDCD2 is associated with many tumors, such as leukemia and gastric cancer (44,67). PDCD2 is an important predictor of clinical relapse in acute leukemia patients (67). Plus, loss of PDCD2 expression could induce gastric cancer development and progression through cell growth arrest at the early S phase of the cell cycle and reported as a putative tumor suppressor in gastric stromal tumors (68).
SGIP1 (SH3 domain GRB2 like endophilin interacting protein) functions as an endocytic protein that has effects on signaling in neuronal systems including energy homeostasis (45,46). Hypomethylation and retrotransposition of SGIP1 have been reported in colorectal cancer samples (69). SGIP1 has been found as a potential therapeutic target for obesity-and diabetesrelated symptoms, since the selective reduction of the expression of SGIP1 consequenced with inhibition of food intake and the decrement of body weight in rat models (70). SGIP1 has been identified as the second most significantly upregulated gene in the colon and rectal cancers samples (71). The expression level of SGIP1 has been shown significantly decreased in gastric cancer when compared to control samples (72).
SWSAP1 (SWS1-Associated Protein 1) gene is involved in homologous recombination repair by binding single-stranded DNA activity and it also has ATPase activity. Depletion of SWSAP1 contributes to defects in homologous recombination repair and Knockdown of SWSAP1 ends up with increased cell sensitivity to the DNA damaging (47).
Remaining core module gene members (A_24_P127621, A_24_P255786, A_24_P683553, A_24_P916979) were unknown with their unknown functions. The present study may contribute to assigning function/ functions to these genes. Known module genes were briefly explained with their functions and roles in various types of cancers. But there was no research found that could report module members for PA progression and prognosis. Therefore, identified module genes and module itself are novel for PA prognosis and they might be considered as the indicator of the non-invasiveness.
While our study provides some insight into the prognosis of PA in different states, more efforts should be performed to validate them clinically and extend our findings. We examined the prognosis of PA through core module genes in the context of gene co-expression networks. Results were in silico validated through various cancer types and it can be concluded that the core module is novel for PA prognosis. In addition, core module has also found as prognostic for brain tumors (glioblastoma, meningioma, and medulloblastoma) and glandular-originated tumors (adrenocortical carcinoma, breast invasive carcinoma, and ovarian serous cystadenocarcinoma). Our findings are based on TCGA, ArrayExpress, and GEO data (module investigation and validation), so a critical extension of this work would be to learn whether the patterns can be recapitulated by clinical trials. All in all, future efforts should be carried out to incorporate this systems-level understanding of prognostic genes into the practice of construction of effective clinical prognostic vehicles.

CONCLUSION
Pituitary adenomas are the most common intracranial tumors in the central nervous system. They are accepted as benign in general but somehow tumors can exhibit gross invasion into surrounding tissues rarely. Invasion results in resistance to conventional treatment methods and leading to early and frequent recurrences. In order to shed light on the multilayered molecular mechanism lay behind the invasion of PA, there is a great need for omics-level data and their integration into meta-analyses. Our study used gene co-expression analysis to construct a gene co-expression network, elucidate and validate network modules associated with the invasiveness and prognosis of PA. Eventually, a core module with 13 genes including CEACAM6, CYP4B1, EIF2S2, HID1, IFFO1,MYO18A, PDCD2, SGIP1, SWSAP1, and 4 unknown genes (A_24_P127621, A_24_P255786, A_24_P683553, A_24_P916979) were identified and in silico validated in association with the indicator of invasiveness and prognosis of PA, plus some related cancer types. The research not only increases the theoretical knowledge but also provides a novel prognostic module and therapeutic strategy for PA.

DATA AVAILABILITY
Publicly available datasets were analyzed in this study. This data can be found here: https://www.ebi.ac.uk/arrayexpress/ experiments/E-TABM-899/.

AUTHOR CONTRIBUTIONS
BA and KYA designed the data analysis framework. BA performed the data analyses and evaluated the results. KYA conceived and directed the study. BA drafted the manuscript. KYA revised the manuscript. All authors read and approved the final manuscript.

SUPPLEMENTARY MATERIAL
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fendo. 2019.00361/full#supplementary-material Figure S1 | Prognostic performance of core module genes through lung and prostate cancers. Survival analyses indicated insignificant prognostic performance in both lung (p = 0.08) and prostate (p = 0.15) carcinomas.


The (p)ppGpp-binding GTPase Era promotes rRNA

Ribosome assembly cofactors are widely conserved across all domains of life. One such group, the ribosome-associated GTPases (RA-GTPase), act as molecular switches to coordinate ribosome assembly. We previously identified theStaphylococcus aureusRA-GTPase Era as a target for the stringent response alarmone (p)ppGpp, although the function of Era in ribosome assembly is unclear. Era is highly conserved throughout the bacterial kingdom and is essential in many species. Here we show that Era is not essential inS. aureusbut is important for 30S ribosomal subunit assembly. Protein interaction studies reveal that Era interacts with the endonuclease YbeY and the DEAD-box RNA helicase CshA. We determine that both Era and CshA are required for growth at suboptimal temperatures, virulence and 16S rRNA processing. Era and CshA also form direct interactions with the (p)ppGpp synthetase RelSA, with RelSA positively impacting the GTPase activity of Era. We propose that Era acts to direct enzymes involved in rRNA maturation and ribosome subunit assembly to their site of action, an activity that is regulated by components of the stringent response.The bacterial ribosome is an essential cellular component and as such is the target for a number of currently used antimicrobials. Correct assembly of this complex macromolecule requires a number of accessory enzymes, the functions of which are poorly characterised. Here we examine the function of Era, a GTPase enzyme involved in 30S ribosomal subunit biogenesis in the important human pathogenS. aureus. We uncover that Era is not an essential enzyme inS. aureus, as it is in many other species, but is important for correct ribosome assembly. In a bid to uncover the cellular function of this enzyme, we identify a number of protein interaction partners with roles in ribosomal RNA maturation and degradation, supporting the idea that Era acts as an intermediary protein facilitating ribosomal biogenesis. We also uncover a link between Era and the (p)ppGpp synthetase RelSA, revealing an additional level of control of rRNA levels by the stringent response. With this study we elaborate on the functions of GTPases in ribosomal assembly, processes that are controlled at multiple points by the stringent response.

Introduction
Era is not an essential protein in S. aureus, it is important for optimal growth and 161 ribosome maturation. 162 163

Uncovering Era protein interaction dynamics in a native background 164
In S. aureus, Era is encoded in an operon with five other genes, one of which encodes 165 YbeY (Fig 1a). YbeY is an endoribonuclease implicated in the maturation of the 3' 166 terminus of 16S rRNA in E. coli, as well as a quality control checkpoint protein that 167 together with RNase R is involved in eliminating defective 70S ribosomes [19,28]. 168 Era interacts with YbeY in E. coli [18], although these two genes are not encoded in 169 the same operon in that organism (Fig 1a). To determine whether Era from S. aureus 170 interacts with YbeY, and/or any other proteins encoded in the S. aureus era operon, 171 we first used a bacterial two-hybrid approach, heterologously expressing Era in 172 combination with YbeZ, YbeY, DgkA, Cdd or RecO in E. coli. Using this approach, 173 we observed that Era potentially interacts with YbeY and YbeZ (Fig 2a). 174 In order to look at these interactions natively in an S. aureus background, we 175 adapted a split-luciferase system recently developed to analyse protein-protein 176 interactions in Clostridium difficile for use in S. aureus (Fig 2b) [29]. The era gene, in 177 combination with itself and each of the operon genes, were cloned into the split-178 luciferase plasmid pAP118 and introduced into S. aureus strain LAC*. Induction of 179 protein expression with Atet revealed a strong positive interaction for Era with itself 180 (Fig 2c), indicating that Era can form dimers. Dimerisation of Era has previously been 181 observed while solving the crystal structure of the E. coli protein [30], and so this 182 interaction confirms the functionality of the split-luciferase system in S. aureus. In 183 addition, a significant interaction was also observed for Era and YbeY (2 x above the 184 control), although not for YbeZ (1.40 x above the control) (Fig 2c). In agreement with 185 the bacterial two-hybrid results, no interactions occurred between Era and DgkA,Cdd 186 or RecO. A decrease in luminescence below the Era control pAP256-era SB -LB occurred 187 when co-expressing Era with DgkA and RecO. The reason for this is unclear but could 188 be due to toxicity upon over-expression of a second copy of these genes from a multi-189 copy plasmid. To confirm the validity of the Era-YbeY interaction in vitro, we 190 performed pulldown assays using glutathione beads coupled to either GST or  tagged Era and incubated them with His-tagged YbeY (Fig 2d). Here we observed 192 low-level cross reactivity of YbeY with the gluthatione beads that could not be 193 reduced despite increased washes. However, His-YbeY was pulled down significantly 194 more in the presence of Era (Fig 2d). Altogether the bacterial two-hybrid, split 195 luciferase and affinity pulldown assays confirm an interaction between Era  interaction between Era and CshA, full-length cshA was cloned into both pUT18 and 209 pUT18C. Upon co-transformation, interactions occurred between CshA-T18 and both 210 T25-Era and Era-T25 (Fig 3a). 211 To assess this interaction in vitro, we performed pulldown assays using 212 glutathione beads coupled to either GST or GST-tagged CshA and incubated them 213 with His-tagged Era, revealing that while His-Era did not interact with the control 214 GST protein, it was pulled down in the presence of CshA (Fig 3b). Finally, to analyse 215 and confirm this interaction in the context of the native host, we used the split 216 luciferase assay (Fig 2b). Assaying for luminescence revealed a 4-fold increase in 217 luciferase activity upon co-expression of Era and CshA (Fig 3c), confirming the 218 identification of a novel Era interaction partner. 219 220

The N-terminal region of CshA is crucial for interacting with Era 221
CshA is a DEAD-box RNA helicase with an N-terminal helicase core containing two 222 RecA-like domains and a disordered C-terminal (CT) region involved in RNA binding 223 (Fig 3d)  assays reveal that the G domain is sufficient for this interaction (Fig 3f). 237 238

Interactions between Era and CshA do not affect enzymatic activity 239
CshA is an RNA helicase, while Era has GTPase activity. To investigate whether the 240 interaction between these two proteins affects the enzymatic activity of either one, we 241 first performed helicase assays. A double stranded RNA oligo was incubated with each 242 protein singly or in combination. While CshA was able to unwind the dsRNA, the 243 addition of Era had no effect on its activity ( Fig S2a). In addition, the GTPase activity 244 of Era was unaltered in the presence of either CshA or YbeY (Fig S2b and S2c), 245 indicating that while these proteins do interact, this binding has little effect on their 246 enzymatic functions. As previously proposed, we suggest that these interactions fit 247 with a role for Era as a guide for rRNA/ribosome maturation enzymes to their showed significant growth defects at 37°C (Fig 1b and S3a), the growth of both was 257 severely compromised at 25°C (Fig 4a and S3b). This defect was enhanced in a double 258 Δera cshA mutant, which failed to grow at 25°C even after 48 h (Fig 4a and S3b),

12
highlighting that these two proteins are essential for bacteria to cope with growth at 260 suboptimal temperatures. 261 Era is an RA-GTPase that, along with a second RA-GTPase RsgA, binds to the 262 While the wildtype bacteria were fully virulent, both the era and cshA mutant strains 272 displayed reduced killing, with the combined double mutant being completely 273 avirulent (Fig 4b). 274 To understand why Era and CshA are so important for growth at cold 275 temperatures and for virulence, we sought to assess the impact of deleting these genes 276 on the cellular rRNA. We observed that RNA extracted from both the single Δera and 277 double Δera cshA strains grown at 37°C had a processing or degradation intermediate 278 migrating slightly below the 16S band (Fig 4c). At 25°C we also observed a defect for 279 the ΔcshA mutant strain and multiple additional bands were evident in the Δera cshA 280 double mutant (Fig 4c), which could represent either processing intermediates from 281 the 16S, or degradation intermediates from both the 23S and the 16S. A build-up of 282 degradation products are expected in the cshA mutant due to its role in the RNA 283 degradosome. However, to determine whether processing defects could be occurring 284 13 in these mutant strains when grown at low temperatures, we performed qRT-PCR with 285 probes that either amplified internally to the 16S rRNA sequence, or either flanked the 286 5' or 3' processing junctions required to convert 17S into mature 16S rRNA (Fig 4d). 287 While the levels of 16S rRNA were not significantly different between wildtype and 288 mutants, large increases in unprocessed 5' and 3' rRNA were evident in the Δera strain 289 (Fig 4d). As Era is known to interact with the 30S ribosomal subunit, this could 290 potentially be due to mis-localisation of endonuclease YbeY in the absence of Era. It is 291 therefore, possible that Era acts as an intermediary protein on the 30S ribosomal 292 subunit, enabling proteins such as the endonuclease YbeY, and the RNA-degradosome 293 helicase CshA to access the 17S rRNA, allowing for processing (maturation or 294 degradation as appropriate) of rRNA under normal and stress conditions, such as 295 growth at cold temperatures. 296 297

Rel SA interacts with both Era and CshA 298
Our previous work demonstrated that the GTPase activity of Era is inhibited by the 299 stringent response alarmone ppGpp [22]. To examine whether ppGpp also interacts 300 with CshA we performed DRaCALA assays, revealing that this nucleotide does not 301 interact with CshA ( Fig S5a), nor does the affinity of ppGpp for Era alter in the 302 presence of CshA (K d of 3.1 ± 0.4 µM in the absence versus 3.2 ± 0.3 µM in the 303 presence of CshA) (Fig S5b). 304 To investigate whether the stringent response has any additional points of 305 interaction with either Era and CshA, we examined whether one of the (p)ppGpp 306 synthetases might directly interact with either protein via bacterial two-hybrid. This 307 revealed that Rel SA , but not RelP or RelQ, interacts with CshA and that Rel SA interacts 308 with Era (Fig 5a). To confirm this interaction, we first used affinity pulldown assays, 309 showing that although no significant interaction occurred with Era, CshA and Rel SA 310 interacted quite strongly (Fig 5b). Following this, we again used the split luciferase 311 assay, which confirmed an interaction between Rel SA and CshA (Fig 5c) or Era (Fig  312   5d). It was interesting to note that the CshA-Rel SA interaction only occurred in the 313 We wished to ascertain whether the interactions between Rel SA and Era impact the 319 activity of either enzyme. Recombinantly purified full-length Rel SA is known to be in 320 the synthetase-off/hydrolase-on conformation in vitro [37]. Using purified Rel SA , we 321 determined that Era and CshA have no effect on the pppGpp hydrolase activity of this 322 enzyme ( Fig S5c). However, upon examination of the GTPase activity of Era, we 323 observed significantly increased activity in the presence of Rel SA (Fig 6a). 324 Through Rel SA , the stringent response appears to interact with components of the 325 ribosome and 16S rRNA processing machinery. To analyse the importance of the 326 stringent response for rRNA processing, we grew the wildtype S. aureus LAC* at 327 to the 16S rRNA sequence, or either flanked the 5' or 3' processing junctions of the 332 17S rRNA. For the probe internal to the 16S rRNA we observed a significant decrease 333 in 16S rRNA in the presence of mupirocin (Fig 6b). This is expected, as it is known 334 that rRNA levels decrease upon activation of the stringent response. However, when 335 we compare the amount of unprocessed 5' or 3' sequences relative to the level of 16S 336 in each strain, we observed a significant increase in the amount of unprocessed leader 337 17S rRNA upon induction of (p)ppGpp (Fig 6c: p = 0.0031). We have previously 338 shown that ppGpp interacts with Era and that mature ribosome formation is inhibited proteins encoded in the era operon in S. aureus with Era (Fig 2). As in E. coli, YbeY 386 from S. aureus interacts with Era. YbeZ also interacted by bacterial two-hybrid but not 387 significantly using the quantitative luciferase assay (Fig 2). YbeZ has been shown to 388 interact with YbeY in E. coli [18]. This protein has an ATPase domain and an RNA 389 binding motif, and so is likely to also bind to the 17S rRNA and may form a complex 390 with Era and YbeY to aid in processing the 17S rRNA to the mature 16S form. 391 Here we use interaction studies to show that Era interacts with a protein 392 involved in survival at suboptimal temperatures, the DEAD-box RNA helicase CshA 393 that Era and CshA interact in vitro and when expressed heterologously in E. coli (Fig  402   3a and 3b). We additionally used an adapted split luciferase assay to show this 403 interaction natively in S. aureus (Fig 3c). Using this assay has also allowed us to 404 determine that the CT disordered region of CshA, which is important for binding to 405 mRNA and the degradosome [32], is dispensable for interacting with Era (Fig 3). 406 Using cshA and era deletion strains we show that both single mutants are 407 important for growth at cold temperatures, with a double mutant unable to survive at 408 25°C (Fig 4). By examining the rRNA of these strains we observe that the era mutant 409 strain has increased 17S unprocessed rRNA intermediates (Fig 4d). Additionally, a 410 double Dera cshA mutant has multiple processing and degradation defects (Fig 4c). It 411 has been proposed that Era may act to guide processing enzymes to their site of action 412 [18]. In keeping with this, we have observed that these proteins have little effect on the 413 enzymatic activity of each other. Therefore, we propose a model whereby Era acts as 414 an intermediary protein, allowing proteins such as the endonuclease YbeY and the 415 RNA helicase CshA, and potentially others, access to their substrate rRNA. It has been 416 suggested that CshA helps RNase components of the degradosome access cleavage 417 sites that may be otherwise inaccessible [45], and so it is tempting to speculate that Era 418 is responsible for recruiting CshA to target misfolded ribosomal subunits for 419 degradation under stress conditions. 420 interaction between the (p)ppGpp synthetase Rel SA and both CshA and Era (Fig 5), 426 and show that Rel SA has a positive effect on the GTPase activity of Era (Fig 6a). 427 Additionally, we observed that the activation of the stringent response results in 428 increased processing defects in a wildtype strain grown at 25°C (Fig 6c). RA-GTPases 429 are reported to have increased association to the ribosome in the GTP-bound form. 430 Hydrolysis of GTP then acts as a signal to promote dissociation, presumably following 431 a maturation event [49,50]. The increased GTPase activity of Era in the presence of 432 Rel SA could promote premature dissociation of Era from the ribosome, leading to 433 processing defects (Fig 6c) and contributing to the stalled growth phenotype 434 synonymous with the stringent response. The precise dynamics of processing-enzyme 435 association under stress conditions requires further in-depth research but is beyond the 436 scope of this study. For instance, under what growth conditions is Rel SA binding to Era 437 and CshA promoted and how does this affect the localisation of processing proteins to 438 the ribosome? 439 Taken together, we demonstrate a cellular function for Era as a protein 440 important for coordinating 30S ribosomal biogenesis in a stringent response-dependent 441 manner. It is possible that defects in ribosomal assembly lead to altered protein 442 translation, which may be the reason for the plethora of other phenotypes associated 443 with depletion of Era. As Era can complement a defect in RsgA (Fig S4a, [36 Synthesis of (p)ppGpp and differential radial capillary action of ligand assay 554 (DRaCALA). The synthesis of (p)ppGpp and DRaCALA binding assays were 555 performed as described previously [22]. Precipitated proteins were pelleted by centrifugation at 17,000 x g for 10 min. 594 Reaction products were then visualized by spotting 1 µl on PEI-cellulose thin layer 595 chromatography (TLC) plates (Merck Millipore) and separated using 1 M KH 2 PO 4 , 596 pH 3.6 buffer. The radioactive spots were visualised using an LA 7000 Typhoon 597 PhosphorImager and images quantified using ImageJ.