Abstract Celiac Disease (CD) is an autoimmune disease characterized by inflammation of the intestinal mucosa due to an immune response to wheat gliadins. Some gliadin peptides (e.g., A-gliadin P57-68) induce an adaptive Th1 pro-inflammatory response. Other gliadin peptides (e.g., A-gliadin P31-43) induce a stress/innate immune response involving interleukin 15 (IL15) and interferon α (IFN-α). In the present study, we describe a stressed/inflamed celiac cellular phenotype in enterocytes and fibroblasts probably due to an alteration in the early-recycling endosomal system. Celiac cells are more sensitive to the gliadin peptide P31-43 and IL15 than controls. This phenotype is reproduced in control cells by inducing a delay in early vesicular trafficking. This constitutive lesion might mediate the stress/innate immune response to gliadin, which can be one of the triggers of the gliadin-specific T-cell response.
The constant increase in cancer incidence and mortality pushes biomedical research towards the development of in vitro3D systems able to faithfully reproduce and effectively probe the tumor microenvironment. Cancer cells interact with this complex and dynamic architecture, leading to peculiar tumor-associated phenomena, such as acidic pH conditions, rigid extracellular matrix, altered vasculature, hypoxic condition. Acidification of extracellular pH, in particular, is a well-known feature of solid tumors, correlated to cancer initiation, progression, and resistance to therapies. Monitoring local pH variations, non-invasively, during cancer growth and in response to drug treatment becomes extremely important for understanding cancer mechanisms. Here, we describe a simple and reliable pH-sensing system based on a thermoresponsive hydrogel embedding optical pH-sensors that enable non-invasive and accurate metabolism monitoring in colorectal cancer (CRC) spheroids. We characterized the physico-chemical properties of this platform, in terms of stability, rheological and mechanical properties, morphology, pH sensitivity. Finally, proton gradient distribution in the spheroid proximity, in the presence or absence of drug treatment, was quantified over time by time lapse confocal light scanning microscopy, highlighting the effects of the treatment in the extracellular pH. These findings will be essential for the study of solid tumors in vitro and the development of personalized medicine approaches.
The 17th International NETTAB workshop was held in Palermo, Italy, on October 16-18, 2017. The special topic for the meeting was "Methods, tools and platforms for Personalised Medicine in the Big Data Era", but the traditional topics of the meeting series were also included in the event. About 40 scientific contributions were presented, including four keynote lectures, five guest lectures, and many oral communications and posters. Also, three tutorials were organised before and after the workshop. Full papers from some of the best works presented in Palermo were submitted for this Supplement of BMC Bioinformatics. Here, we provide an overview of meeting aims and scope. We also shortly introduce selected papers that have been accepted for publication in this Supplement, for a complete presentation of the outcomes of the meeting.
Pyranine (HPTS) is a remarkably interesting pH-sensitive dye that has been used for plenty of applications. Its high quantum yield and extremely sensitive ratiometric fluorescence against pH change makes it a very favorable for pH-sensing applications and the development of pH nano-/microsensors. However, its strong negative charge and lack of easily modifiable functional groups makes it difficult to use with charged substrates such as silica. This study reports a methodology for noncovalent HPTS immobilization on silica microparticles that considers the retention of pH sensitivity as well as the long-term stability of the pH microsensors. The study emphasizes the importance of surface charge for governing the sensitivity of the immobilized HPTS dye molecules on silica microparticles. The importance of the immobilization methodology, which preserves the sensitivity and stability of the microsensors, is also assessed.
Optical fluorescent pH sensors based on positively charged silica microparticles containing anionic pyranine molecules were developed by using a modified Stöber method with a gradual immobilization of ratiometrically pH-sensing pyranine molecules during the growth of silica seed particles and an overall positive charge in a one-step reaction. The overly pH-sensitive nature of pyranine is preserved and long-term stability is ensured by silica shell coating. These cytocompatible ratiometric pH sensors can be used for pH sensing and pH tracking applications where each microparticle can be observed individually due to resolvable size. More information can be found in the Communication by A. Chandra, L. L. del Mercato et al. (DOI: 10.1002/chem.202101568).
A crucial challenge in medicine is choosing which drug (or combination) will be the most advantageous for a particular patient. Usually, drug response rates differ substantially, and the reasons for this response unpredictability remain ambiguous. Consequently, it is central to classify features that contribute to the observed drug response variability. Pancreatic cancer is one of the deadliest cancers with limited therapeutic achievements due to the massive presence of stroma that generates an environment that enables tumor growth, metastasis, and drug resistance. To understand the cancer-stroma cross talk within the tumor microenvironment and to develop personalized adjuvant therapies, there is a necessity for effective approaches that offer measurable data to monitor the effect of drugs at the single-cell level. Here, we develop a computational approach, based on cell imaging, that quantifies the cellular cross talk between pancreatic tumor cells (L3.6pl or AsPC1) and pancreatic stellate cells (PSCs), coordinating their kinetics in presence of the chemotherapeutic agent gemcitabine. We report significant heterogeneity in the organization of cellular interactions in response to the drug. For L3.6pl cells, gemcitabine sensibly decreases stroma-stroma interactions but increases stroma-cancer interactions, overall enhancing motility and crowding. In the AsPC1 case, gemcitabine promotes the interactions among tumor cells, but it does not affect stroma-cancer interplay, possibly suggesting a milder effect of the drug on cell dynamics.
After leaving the endoplasmic reticulum, secretory proteins traverse several membranous transport compartments before reaching their destinations. How they move through the Golgi complex, a major secretory station composed of stacks of membranous cisternae, is a central yet unsettled issue in membrane biology. Two classes of mechanisms have been proposed. One is based on cargo-laden carriers hopping across stable cisternae and the other on "maturing" cisternae that carry cargo forward while progressing through the stack. A key difference between the two concerns the behavior of Golgi-resident proteins. Under stable cisternae models, Golgi residents remain in the same cisterna, whereas, according to cisternal maturation, Golgi residents recycle from distal to proximal cisternae via retrograde carriers in synchrony with cisternal progression. Here, we have engineered Golgi-resident constructs that can be polymerized at will to prevent their recycling via Golgi carriers. Maturation models predict the progress of such polymerized residents through the stack along with cargo, but stable cisternae models do not. The results support the cisternal maturation mechanism.
Full text Figures and data Side by side Abstract eLife digest Introduction Results Discussion Materials and methods References Decision letter Author response Article and author information Metrics Abstract The mechanism of transport through the Golgi complex is not completely understood, insofar as no single transport mechanism appears to account for all of the observations. Here, we compare the transport of soluble secretory proteins (albumin and α1-antitrypsin) with that of supramolecular cargoes (e.g., procollagen) that are proposed to traverse the Golgi by compartment progression–maturation. We show that these soluble proteins traverse the Golgi much faster than procollagen while moving through the same stack. Moreover, we present kinetic and morphological observations that indicate that albumin transport occurs by diffusion via intercisternal continuities. These data provide evidence for a transport mechanism that applies to a major class of secretory proteins and indicate the co-existence of multiple intra-Golgi trafficking modes. https://doi.org/10.7554/eLife.02009.001 eLife digest The Golgi is a structure within cells where proteins and other large molecules are modified and prepared for delivery to locations inside or outside of the cell. Each Golgi is made from a stack of flattened sacs called cisternae that are filled with fluid and enclosed by a membrane. Proteins and other molecules are transported to the Golgi by packages called vesicles, which fuse with the outermost cisterna, which is known as the 'cis-face' of the Golgi, and unload their contents. From here, the proteins are processed and modified by enzymes as they move through the Golgi towards the 'trans-face' on the opposite side. The modified proteins are then re-packaged into vesicles before being sent to their intended destinations. But how do proteins move through the Golgi? Some researchers have suggested that proteins do not actually move: rather, the stacks of the Golgi move like a conveyer belt as new cisterna are added to the cis-face. However, other researchers have proposed that molecules proceed from one cisterna to the next inside small vesicles. It is also possible that proteins are transported through the Golgi in other ways, or by a combination of two or more methods. Now, Beznoussenko, Parashuraman et al. reveal that some small, soluble, proteins can move through the Golgi by diffusion. These proteins move much quicker than large protein complexes, which suggests that multiple transport mechanisms do co-exist within the Golgi. Furthermore, Beznoussenko, Parashuraman et al. found that these soluble proteins are most likely moving through some narrow tunnel-like connections between the individual cisternae. Following on from the work of Beznoussenko, Parashuraman et al., the main challenge is to understand how all the different types of proteins that move through the Golgi are transported—which includes roughly a third of all human proteins. As many of these proteins are important for human health, learning to control their transport might create new opportunities to understand and treat disease. https://doi.org/10.7554/eLife.02009.002 Introduction Nearly one third of the eukaryotic proteins are synthesized at the endoplasmic reticulum (ER) and then transported to their cellular destinations through the secretory pathway. Over the years, the general organization of membrane transport along the secretory pathway has been gradually unraveled (Mellman and Simons, 1992; Mellman and Warren, 2000), and many of the underlying molecular components have been identified (Rothman, 2002; Schekman, 2002; Emr et al., 2009). Some key questions, however, remain unresolved (Pfeffer, 2007; Emr et al., 2009; Glick and Luini, 2011). A central issue is how cargo proteins traverse the Golgi complex (Malhotra et al., 1989; Glick and Malhotra, 1998; Glick and Luini, 2011), a major transport station composed of stacks of flat membranous cisternae. There are three main anterograde transport mechanisms that are in principle possible and might apply to the Golgi: (a) transport by compartment progression–maturation; (b) transport by dissociative anterograde vesicular carriers and, (c) transport via inter-compartment continuities. Among these, the progression–maturation model has gained a degree of consensus as an intra-Golgi traffic mechanism, based on several lines of evidence in mammals (Bonfanti et al., 1998; Lanoix et al., 2001; Martinez-Menarguez et al., 2001; Mironov et al., 2001; Rizzo et al., 2013), yeast (Losev et al., 2006; Matsuura-Tokita et al., 2006; Rivera-Molina and Novick, 2009), algae (Becker et al., 1995), and plants (Donohoe et al., 2013). Under this model, cargo molecules remain in the lumen of the Golgi cisternae while the cisternae themselves progress through the stack and 'mature' through recycling of their resident enzymes. Recently, cisternal progression has been proposed to apply only to the rims (and not to the core) of the cisternae in the mammalian Golgi (Lavieu et al., 2013). In addition to the Golgi, the progression–maturation principle appears to be involved in the endocytic (Rink et al., 2005; Poteryaev et al., 2010) and the phagocytic pathways (Fairn and Grinstein, 2012) in different species. The vesicular transport mechanism, whereby dissociative carriers transport cargoes between successive compartments, operates at many stages of the trafficking pathway and has been proposed to apply also to intra-Golgi trafficking (Rothman, 2002). Here, however, the evidence is less direct and less conclusive than at other transport segments, with conflicting claims about the presence (Orci et al., 2000) or absence (Claude, 1970; Sabesin and Frase, 1977; Severs and Hicks, 1979; Clermont et al., 1993; Dahan et al., 1994; Di Lazzaro et al., 1995; Bonfanti et al., 1998; Orci et al., 2000; Martinez-Menarguez et al., 2001; Mironov et al., 2001; Gilchrist et al., 2006) of anterograde cargo proteins in the peri-Golgi carriers. Moreover in particular cases, like in microsporidia, intra-Golgi transport appears to occur without COPI vesicles (Beznoussenko et al., 2007). Diffusion-based transport via inter-compartment continuities remains the least explored and understood of the traffic mechanisms. Some antecedents, however, are available. Continuity-mediated transport has been observed to occur between endosomes and lysosomes (Luzio et al., 2007), and also the exocytic release of cargo from secretory granules (Rutter and Hill, 2006) or synaptic vesicles through transient pores (kiss-and-run) (Rizzoli and Jahn, 2007; Alabi and Tsien, 2013) at the plasma membrane can be considered to occur via this modality. For intra-Golgi transport, this mechanism has been discussed several times in the past (Mellman and Simons, 1992; Weidman, 1995; Mironov et al., 1997; Marsh et al., 2004; Trucco et al., 2004; Mironov et al., 2005; Beznoussenko et al., 2007; Glick and Luini, 2011) and a few recent intra-Golgi transport models including the mixing–partitioning (Patterson et al., 2008), the kiss-and-run (Mironov and Beznoussenko, 2012; Fusella et al., 2013; Mironov et al., 2013) and the cisternal progenitor schemes (Pfeffer, 2010) have been proposed that imply transient tubular continuities across cisternae. At the molecular/mechanistic level, Golgi tubule formation has been proposed to be initiated by COPI coatomer-mediated budding (Yang et al., 2011), and tubule elongation and fission appear to require the actions of cytosolic phospholipase A2 (cPLA2) and lysophosphatidic acid acyltransferase-γ (LPAATγ), respectively (San Pietro et al., 2009) (Yang et al., 2011). Recent evidence also points to a role for Golgi localized SNAREs and BARS in the dynamics of the intercisternal connections (Fusella et al., 2013). Nevertheless, a complete understanding of the molecular players regulating the intra-Golgi connections remains lacking. Altogether, uncertainties remain about the applicability of continuity-based transport to the Golgi. One main reason for this situation has been the long-standing difficulty of demonstrating intercisternal continuities in thin sections for electron microscopy. This obstacle has now been partly overcome by the use of electron tomography and new methods of three dimensional electron microscopy (Briggman and Bock, 2012), which have revealed the presence of intercisternal tubular continuities under experimental conditions that favor the detection of these tubules, such as the induction of active trafficking (Marsh et al., 2004; Trucco et al., 2004; Vivero-Salmeron et al., 2008; San Pietro et al., 2009; Wanner et al., 2013). The second and main problem, yet to be resolved, is that the mere presence of intercisternal tubules is insufficient to prove a role for these continuities in transport, as these tubules might be too few and unfavorably disposed to support trafficking. To test the continuity-based transport model, it is thus necessary to search for functional evidence of a transport role for these continuities. To this end, we have used soluble secretory proteins as transport markers, as these are globular objects of a few nm in diameter that should easily cross the observed intercisternal tubules and rapidly move from the cis to the trans face of an interconnected stack or ribbon. The transport of some soluble proteins has been studied decades ago using electron microscopic autoradiography (Caro and Palade, 1964; Jamieson and Palade, 1967; Ashley and Peters, 1969; Castle et al., 1972) and biochemical pulse-chase assays (Jamieson and Palade, 1967; Lodish et al., 1983), but their actual mechanism of secretion remains unknown. Comparing the trafficking pattern of prototypic soluble proteins with those of cargoes previously proposed to move by cisternal progression–maturation, we find that soluble proteins cross the Golgi stack at a much faster rate, apparently by diffusion along intercisternal connections; and that this transport mode coexists in the same Golgi complex with the much slower intra-Golgi progression of large, non-diffusible cargo, such as procollagen I (PC-I). Soluble secreted proteins are of great physiological interest because they represent a significant portion (possibly more than 10%) of the mammalian proteome and include hormones, growth factors, serum proteins, antibodies, and digestive enzymes. Thus, these results are consistent with a novel mechanism of transport for a major class of secretory proteins, and provide evidence for multiplicity of transport mechanisms that can help to rationalize most of the observed intra-Golgi trafficking patterns. Results The experimental system: comparing transport of soluble cargo with that of VSVG and PC As prototypes of soluble proteins we used albumin and α1-antitrypsin (hereinafter termed antitrypsin). These are globular, water-soluble proteins roughly 3 nm in diameter that should easily diffuse through the 30–60 nm wide Golgi intercisternal connections (Trucco et al., 2004). Albumin is an abundant, non-glycosylated protein, while antitrypsin is N-glycosylated. The trafficking of soluble proteins (albumin in most experiments) was characterized and compared with that of PC-I (Weinstock and Leblond, 1974; Bonfanti et al., 1998; Mironov et al., 2001) and vesicular stomatitis virus G protein (VSVG) (Bergmann and Singer, 1983; Mironov et al., 2001; Patterson et al., 2008), because these cargoes have been extensively characterized and shown to move by cisternal progression (or rimmal progression [Lavieu et al., 2013] or compartment progression [Mironov et al., 2013]. For the sake of brevity, from now onward we will use the term compartment progression to describe the traffic of procollagen and other similar cargo). Thus, if albumin moves by diffusion via continuities, it should exhibit transport kinetics and patterns different from VSVG and PC-I. PC-I forms large, stable, non-diffusible aggregates that cannot enter tubules or vesicles and cross the Golgi stack in a gradual fashion by compartment progression (Bonfanti et al., 1998; Trucco et al., 2004); and VSVG is a large trimeric transmembrane viral protein that shows the same trafficking pattern as PC-I, at least under certain specific conditions (see below). In this study, we only used conditions under which VSVG crosses the Golgi by compartment progression. Albumin crosses the Golgi stack faster than VSVG and PC: kinetic evidence for fast synchronized albumin movement across progressing cisternae We first compared the kinetics of intra-Golgi transport of albumin with those of VSVG and PC-I in HepG2 cells, a human hepatoma cell line that secretes both albumin and antitrypsin. To assess traffic rates, we used synchronization techniques by which cargoes can be arrested in the intermediate compartment (IC), and then released, to monitor their synchronous passage through the secretory system. To compare albumin with VSVG, HepG2 cells were infected with VSV and subjected to the following synchronization protocol (protocol 2, 'Materials and methods'): the secretory pathway was first cleared of cargo by blocking protein synthesis with cycloheximide (CHX); and then CHX was removed at 15°C. At this temperature albumin and VSVG were re-synthesized relatively efficiently, and were then transported to, and arrested in, the IC (Mironov et al., 2001). Finally, the 15°C transport block was removed by shifting the temperature to 32°C, to allow the synchronous passage of albumin and VSVG from the IC to and through the Golgi complex (Mironov et al., 2001). Notably, this protocol does not seriously overload/perturb the secretory pathway since, under similar conditions, the Golgi complex has been shown to maintain a normal structure and function (Trucco et al., 2004; Mironov et al., 2001). To monitor cargo passage, we used both immuno-electron microscopy (immuno-EM) and immuno-fluorescence. By immuno-EM, albumin was seen at time 0 (i.e., at end of the 15°C block) in the ER and IC at similar levels, with very little in the Golgi stacks (Figure 1A,B, green arrowheads). An earlier study had shown that a soluble protein (soluble secretory GFP) concentrates in the IC/Golgi area at 15°C (Blum et al., 2000); however, no EM experiments were carried out to verify the localization. Using immuno-EM, we do not observe any such concentration of albumin in the Golgi after the 15°C block (time 0). Albumin is clearly restricted to the ER and IC, and absent from the Golgi apparatus (Figure 1A,B,I,L). Within 2 min of release from the 15°C block, albumin entered and filled the entire Golgi, including the trans-Golgi network (TGN), with apparently similar levels throughout (Figure 1C,D,I). After 5 min at 32°C, the distribution of albumin had not changed significantly (Figure 1E,F,I), while at 10 min, albumin was higher in the TGN than in the cis cisternae (Figure 1G,I). Then (by 20 min), albumin began to exit the Golgi, as indicated by its diminishing overall levels in the Golgi stack (Figure 1H,J,L). In sum, albumin spreads through the stack in less than 2 min, then exits the Golgi complex. Figure 1 with 1 supplement see all Download asset Open asset Kinetic patterns of synchronized transport of albumin and VSVG through the Golgi stack. VSV-infected HepG2 cells were synchronized according to the CHX/32-15°C protocol ('Materials and methods'). Following release of the 15°C block, the cells were examined by immuno-EM (A–H) at the indicated times. Panels (I–K) show quantification of immuno-EM values as labeling density (LD) normalized to the density in the ER, to avoid labeling variability across samples. (L) The amount of albumin or VSVG in indicated compartments were normalized to that present at time 0 in the ER and expressed as percentage. Values are mean ± SD from 30 stacks per time point, in three independent experiments for immuno-EM. Bar: 60 nm (A), 50 nm (B, C, E, G), 100 nm (D, H), 80 nm (F). https://doi.org/10.7554/eLife.02009.003 The pattern of VSVG traffic differed from that of albumin. As previously described (Mironov et al., 2001; Trucco et al., 2004), at time 0, VSVG was depleted in the ER, concentrated in the IC, and nearly absent in the Golgi stacks (Figure 1A,B,K). 2 min after the 15°C block release, VSVG was still mostly in IC elements adjacent to the cis-Golgi (Figure 1C,D,K), and at 5 min it had reached only the first cis-cisterna (Figure 1E,F,K). Later, VSVG gradually reached the medial and then the trans-Golgi (Figure 1G,K). Thus, VSVG moves gradually through the stack in over 15 min, consistent with the compartment progression trafficking mechanism, as expected under these synchronization conditions (Mironov et al., 2001; Trucco et al., 2004). For immunofluorescence experiments (Figure 1—figure supplement 1), we monitored arrival of both VSVG and albumin at the cis- and trans-Golgi by determining their degree of co-localization with cis- and trans-Golgi markers (GM130 and TGN46, respectively) (Mironov et al., 2001; Trucco et al., 2004). This is feasible because cis- and trans-Golgi markers can be resolved (to a large though not complete extent) by confocal microscopy (Shima et al., 1997; Trucco et al., 2004) ('Materials and methods'). Albumin showed a diffuse ER-like distribution at time 0, with no clear Golgi staining (Figure 1—figure supplement 1); then, 2 min after the release of the 15°C block, albumin entered the Golgi stack and co-localized to the same extent with both GM130 and TGN46 (i.e., it reached both the cis and trans areas, Figure 1—figure supplement 1), while the ER was still not completely empty. After 5–10 min, albumin had completely left the ER and now localized mostly in the Golgi, where its levels declined in the cis-Golgi, while they remained high in the trans-Golgi (Figure 1—figure supplement 1), compatible with rapid albumin diffusion through the stack followed by concentration in the TGN. Thus, the export of albumin out of the ER was very efficient, so that by 10 min after the release of the temperature block almost all of the protein had been transported to the Golgi apparatus. Antitrypsin showed very similar distribution and trafficking patterns to albumin (Figure 1—figure supplement 1). VSVG, instead, showed a punctate (IC-like) distribution at 15°C, as previously reported (Mironov et al., 2001; Trucco et al., 2004; Figure 1—figure supplement 1). After the release of the block, VSVG reached the cis-Golgi first (at 5 min) (Figure 1—figure supplement 1), and then later, with a lag of 10–15 min, it arrived at the TGN, as previously described (Mironov et al., 2001; Figure 1—figure supplement 1). Again, this is compatible with compartment progression, and is in agreement with the immuno-EM data. Next, we compared albumin and PC-I. We expressed albumin in professional PC-I secretory cells (human fibroblasts) by microinjecting albumin cDNA in the nucleus and subjecting the cells to the synchronization protocol 1 ('Materials and methods'). A limited but sufficient fraction of injected cells expressed albumin. At 15°C (time 0), albumin was mostly diffuse in the ER (as seen in HepG2 cells), while PC-I was seen in scattered fluorescent 'spots' (presumably PC-I aggregates within the IC) (Figure 2A,B; Mironov et al., 2001; Trucco et al., 2004). We then increased the temperature to 32°C. In these cells, the PC-I trafficking pattern has been characterized extensively in previous studies: PC-I arrives at the cis-Golgi from the IC in 2–3 min and later progresses to the TGN by compartment progression in 12–15 min (Bonfanti et al., 1998; Mironov et al., 2001). Here, we confirmed that within 3 min after the release of the 15°C block, PC-I aggregates reach the Golgi area but not the TGN (Figure 2D,E); and by correlative light-immuno-EM (CLEM), we further confirmed that at this time PC-I aggregates reach the cis but not the distal cisternae, well in line with previous reports (Figure 2F) (Bonfanti et al., 1998; Mironov et al., 2001). In the same cells, by contrast, albumin filled the Golgi stack rapidly, as in HepG2 cells: at 3 min, it already co-localized with the TGN marker TGN46 (by immunofluorescence) (Figure 2C,E) and, by EM, it filled the Golgi stacks from cis to trans (Figure 2G). Figure 2 Download asset Open asset Kinetic patterns of synchronized transport of albumin and PC-I through the Golgi stack. Human fibroblast cells were microinjected in the nucleus with cDNA for albumin and incubated for 2 hr before further treatments. Transport was synchronized according to the CHX/32-15°C protocol and the cells were examined by immunofluorescence and immuno-EM. (A) Immunofluorescence localization of albumin and PC at the end of the 15°C block. The area in (A) indicated by white rectangle is enlarged in (B) (C–E). Co-localization between albumin (C) or PC (D) or of both cargoes (E) with TGN46, 3 min after release of the block. (F–G). Localization of PC (F) and albumin (G) 3 min after release of the 15°C block by immuno-EM. PC (indicated by *) localizes selectively to the cis-cisterna. The cis-side of the Golgi is revealed by the presence of GM130 labeled by immuno-nanogold technique (indicated by white arrows) (F). Albumin labeled by immuno-nanogold technique (black dots) shows a diffuse localization throughout the Golgi complex (G). Bars: 5 μm (A), 2 μm (B–E), 125 nm (E and F). https://doi.org/10.7554/eLife.02009.005 Collectively, these results indicate the existence, in the same cells (and in the same stacks), of two different intra-Golgi trafficking patterns for different cargo types, one consistent with gradual compartment progression, for PC and VSVG, and one characterized by the rapid spreading of cargo through the stack, for albumin. Albumin crosses the Golgi stack faster than VSVG and PC also under steady-state transport conditions A possible limitation of these data is that they were obtained using synchronized traffic waves. Albeit relatively mild (Mironov et al., 2001), the traffic synchronization protocols that were applied here might 'overload' the secretory pathway. We therefore sought to examine the transport patterns of albumin and PC in cells at steady-state. This can be achieved using GFP-tagged cargoes in living HeLa cells ('Materials and methods'), which offer controlled expression conditions. GFP-albumin showed steady-state Golgi localization and secretory behavior similar to that of native albumin in HepG2 cells (Figure 3—figure supplement 1), indicating that this construct can be used as an albumin tracer. Moreover, a characterization of the GFP-albumin dynamics in HeLa cells based on fluorescence recovery after photobleaching (FRAP) (Patterson et al., 2008), showed that this construct enters and exits the Golgi with half-times of about 3–4 min (Figure 3—figure supplement 1) and diffuses 'horizontally' along the Golgi ribbon in seconds, as expected from its soluble nature (Figure 3—figure supplement 1). We thus proceeded to assess the steady-state transport behavior of GFP-albumin, and to compare it with that of PC. To this end, we bleached the Golgi area (Figure 3A,B) and monitored the time for arrival of GFP-albumin from the ER at the cis-Golgi and at the trans-Golgi (again by quantifying its co-localization with GM130 and TGN46; see above and 'Materials and methods') (Figure 3C–F). After 1–2 min (i.e., the earliest time at which GFP-albumin had recovered to detectable levels in the Golgi stack) (Figure 3C), GFP-albumin had reached both the cis-Golgi and the TGN (Figure 3D–F); in fact, it showed a slightly higher degree of co-localization with TGN46 than with GM130 (using the unbiased co-localization Method 2 based on automatic thresholding; see 'Materials and methods'), indicating that it had already traversed the Golgi stack (Figure 3D–F, quantification in J). Later (3 min post-bleaching), the GFP-albumin signal became slightly higher in the trans- than the cis-Golgi, and at 12 min (when recovery was nearly complete), it was clearly higher in the trans- than the cis-Golgi (as seen before bleaching, with a ratio of about 1.8) (Figure 3J). To control for the possibility that part of the fluorescence signal recovered in the Golgi area might come from the underlying ER, we repeated this experiment using nocodazole-induced ministacks (Figure 3G–I,K), where the cis and trans-Golgi markers are resolved better (Shima et al., 1997; Trucco et al., 2004) and the very low background fluorescence of the ER present in the cellular periphery allows a better resolution of Golgi fluorescence. The results were very similar to those obtained with the intact ribbon. Next, to confirm these results by EM we resorted to GFP-photooxidation followed by CLEM experiments. For photooxidation studies, the same experiments as those described above were carried out, and the cells were fixed 2 min after photobleaching, when GFP-albumin fluorescence had recovered in the Golgi. Then, the newly arrived fluorescent protein in the Golgi was excited in the presence of DAB under conditions that favor the photo-oxidation reaction and the formation of DAB electron dense precipitates in the close vicinity of GFP (Grabenbauer et al., 2005; Meiblitzer-Ruppitsch et al., 2008) ('Materials and methods'). The Golgi elements that had been monitored by video microscopy were then examined by CLEM (Mironov and Beznoussenko, 2013 and 'Materials and methods'). The results shown in Figure 3O–S clearly indicated that after 2 min of recovery GFP-albumin was already filling the whole Golgi stack. Figure 3 with 2 supplements see all Download asset Open asset Kinetic patterns of transport of GFP-albumin, VSVG-GFP and PC-III-GFP through the Golgi stack under steady-state conditions. HeLa cells were transfected with GFP-albumin (A–K) or PC-III-GFP (L–N). After 16 hr of transfection, the Golgi area was bleached, and entry of these cargoes from the unbleached periphery (ER) into the Golgi area was monitored by FRAP. The cells were then fixed at different time points, stained for GM130 and TGN46, and re-localized for analysis of co-localization of the GFP-tagged cargoes with these Golgi markers. (A–C) Bleaching of the Golgi area, as delineated by the dotted line, with post-bleaching recovery for 1 min (C). (D–F) Detail of the same Golgi area shown in (C), showing co-localization of GFP-albumin (green) with GM130 (D, red), or TGN46 (E, red) or both (F: GM130, blue; TGN46, red). (G–I) Similar experiments carried out on a nocodazole-induced Golgi ministack ('Materials and methods'), with 1-min post-bleaching co-localization of GFP-albumin (green) with GM130 (G, red) or TGN46 (H, red) or both (GM130, blue and TGN46, red) (I). (J) Quantification of the degree of co-localization of GFP-albumin with GM130 and TGN46 at different time points after bleaching, as illustrated in (A–F). These data are expressed by normalizing the degree of co-localization of GFP-albumin in the TGN46 area to that of albumin in the GM130 area (set to 1). (K) Line scan along the arrow across the Golgi ministack shown in (I). The fluorescence intensities from representative points along the distance were plotted. (L and M) Cells were transfected with PC-III-GFP. The Golgi area (within the dotted line) was bleached, and the time course of entry of PC-III-GFP to the TGN was monitored. The cells were fixed and stained for TGN46 at 3 min (L) and 9 min (M) post-bleach, and the overlap between PC-III-GFP with TGN46 was examined. (N) Quantification of data in (L and M), expressed as mean ± SD from at least three independent experiments. (O–S) To ascertain the earlier observations of rapid filling of the Golgi stack by GFP-albumin (A–F), we resorted to electron microscopy. HeLa cells were transfected with GFP-albumin (O and R) or VSVG-GFP (P) or PC-III-GFP (Q). The Golgi localized fluorescence was bleached as before (time 0; O) and entry of cargo into the Golgi area monitored by FRAP and the cells fixed 2 min after recovery. The GFP fluorescence was then converted to a signal visible at the EM by photooxidation (see 'Photooxidation' under 'Materials and methods' section) using Diaminobenzidine (DAB). The DAB product is indicated by arrows. At time 0 the DAB product is present only in the ER with Golgi devoid of staining (O). After 2 min of fluorescence recovery, both VSVG-GFP (P) and PC-III-GFP (Q) are restricted to the cis-side of the Golgi, while GFP-albumin (R) is present throughout the Golgi. In the case of VSVG-GFP, DAB precipitate is visible outside of the Golgi cisternae because GFP is attached to the cytosolic tail of VSVG. In addition, nanogold labeling for Mannosidase II was done in (P) that marks the medial-part of the Golgi. The time 0 image shown is from cells expressing GFP-albumin; similar staining was obtained from both VSVG-GFP and PC-III-GFP expressing cells at time 0. (S) The percentage of cells that showed DAB product throughout the Golgi 2 min after recovery was calculated and presented as mean ± SD. Bar: 2 μm (A–M), 220 nm (O–R). https://doi.org/10.7554/eLife.02009.006 To monitor the behavior of PC under similar conditions, we used HeLa cells transfected with GFP-tagged PC-III (a homotrimer that forms large aggregates in the Golgi complex like PC-I, and in general behaves like PC-1; [Perinetti et al., 2009] and 'Materials and methods'). A limited but sufficient number of cells expressed this cargo. We then bleached the whole Golgi area and monitored the rate of entry of PC-III-GFP into the Golgi complex from the ER. PC-III behaved as expected from our previous experiments on PC-I trafficking (Bonfanti et al., 1998; Mironov et al., 2001; Trucco et al., 2004). At 3 min post-bleaching, some PC-III-GFP
Article13 September 2021Open Access Source DataTransparent process GRASP55 regulates intra-Golgi localization of glycosylation enzymes to control glycosphingolipid biosynthesis Prathyush Pothukuchi Prathyush Pothukuchi orcid.org/0000-0002-6242-2319 Institute of Biochemistry and Cell Biology, National Research Council of Italy, Rome, Italy Search for more papers by this author Ilenia Agliarulo Ilenia Agliarulo Institute of Biochemistry and Cell Biology, National Research Council of Italy, Rome, Italy These authors contributed equally to this work Search for more papers by this author Marinella Pirozzi Marinella Pirozzi Institute of Biochemistry and Cell Biology, National Research Council of Italy, Rome, Italy These authors contributed equally to this work Search for more papers by this author Riccardo Rizzo Riccardo Rizzo Institute of Biochemistry and Cell Biology, National Research Council of Italy, Rome, Italy Search for more papers by this author Domenico Russo Domenico Russo Institute of Biochemistry and Cell Biology, National Research Council of Italy, Rome, Italy Search for more papers by this author Gabriele Turacchio Gabriele Turacchio Institute of Biochemistry and Cell Biology, National Research Council of Italy, Rome, Italy Search for more papers by this author Julian Nüchel Julian Nüchel orcid.org/0000-0002-8126-415X Medical Faculty, Center for Biochemistry, University of Cologne, Cologne, Germany Search for more papers by this author Jia-Shu Yang Jia-Shu Yang Division of Rheumatology, Inflammation and Immunity, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA Search for more papers by this author Charlotte Gehin Charlotte Gehin orcid.org/0000-0003-1164-2968 École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland Search for more papers by this author Laura Capolupo Laura Capolupo École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland Search for more papers by this author Maria Jose Hernandez-Corbacho Maria Jose Hernandez-Corbacho Stony Brook University Medical Center, Stony Brook, NY, USA Search for more papers by this author Ansuman Biswas Ansuman Biswas National Center of Biological Sciences, Bengaluru, India Search for more papers by this author Giovanna Vanacore Giovanna Vanacore Institute of Biochemistry and Cell Biology, National Research Council of Italy, Rome, Italy Search for more papers by this author Nina Dathan Nina Dathan Institute of Biochemistry and Cell Biology, National Research Council of Italy, Rome, Italy Search for more papers by this author Takahiro Nitta Takahiro Nitta Division of Glycopathology, Institute of Molecular Biomembrane and Glycobiology, Tohoku Medical and Pharmaceutical University, Sendai, Japan Search for more papers by this author Petra Henklein Petra Henklein Universitätsmedizin Berlin Institut für Biochemie Charité CrossOver Charitéplatz 1 / Sitz, Berlin, Germany Search for more papers by this author Mukund Thattai Mukund Thattai National Center of Biological Sciences, Bengaluru, India Search for more papers by this author Jin-Ichi Inokuchi Jin-Ichi Inokuchi orcid.org/0000-0002-0703-5746 Division of Glycopathology, Institute of Molecular Biomembrane and Glycobiology, Tohoku Medical and Pharmaceutical University, Sendai, Japan Search for more papers by this author Victor W Hsu Victor W Hsu orcid.org/0000-0002-6763-4636 Division of Rheumatology, Inflammation and Immunity, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA Search for more papers by this author Markus Plomann Markus Plomann orcid.org/0000-0001-6509-5627 Medical Faculty, Center for Biochemistry, University of Cologne, Cologne, Germany Search for more papers by this author Lina M Obeid Lina M Obeid orcid.org/0000-0002-0734-0847 Stony Brook University Medical Center, Stony Brook, NY, USA Deceased. Search for more papers by this author Yusuf A Hannun Yusuf A Hannun Stony Brook University Medical Center, Stony Brook, NY, USA Search for more papers by this author Alberto Luini Alberto Luini Institute of Biochemistry and Cell Biology, National Research Council of Italy, Rome, Italy Search for more papers by this author Giovanni D'Angelo Giovanni D'Angelo orcid.org/0000-0002-0734-4127 Institute of Biochemistry and Cell Biology, National Research Council of Italy, Rome, Italy École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland Search for more papers by this author Seetharaman Parashuraman Corresponding Author Seetharaman Parashuraman [email protected] orcid.org/0000-0001-5113-4592 Institute of Biochemistry and Cell Biology, National Research Council of Italy, Rome, Italy Search for more papers by this author Prathyush Pothukuchi Prathyush Pothukuchi orcid.org/0000-0002-6242-2319 Institute of Biochemistry and Cell Biology, National Research Council of Italy, Rome, Italy Search for more papers by this author Ilenia Agliarulo Ilenia Agliarulo Institute of Biochemistry and Cell Biology, National Research Council of Italy, Rome, Italy These authors contributed equally to this work Search for more papers by this author Marinella Pirozzi Marinella Pirozzi Institute of Biochemistry and Cell Biology, National Research Council of Italy, Rome, Italy These authors contributed equally to this work Search for more papers by this author Riccardo Rizzo Riccardo Rizzo Institute of Biochemistry and Cell Biology, National Research Council of Italy, Rome, Italy Search for more papers by this author Domenico Russo Domenico Russo Institute of Biochemistry and Cell Biology, National Research Council of Italy, Rome, Italy Search for more papers by this author Gabriele Turacchio Gabriele Turacchio Institute of Biochemistry and Cell Biology, National Research Council of Italy, Rome, Italy Search for more papers by this author Julian Nüchel Julian Nüchel orcid.org/0000-0002-8126-415X Medical Faculty, Center for Biochemistry, University of Cologne, Cologne, Germany Search for more papers by this author Jia-Shu Yang Jia-Shu Yang Division of Rheumatology, Inflammation and Immunity, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA Search for more papers by this author Charlotte Gehin Charlotte Gehin orcid.org/0000-0003-1164-2968 École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland Search for more papers by this author Laura Capolupo Laura Capolupo École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland Search for more papers by this author Maria Jose Hernandez-Corbacho Maria Jose Hernandez-Corbacho Stony Brook University Medical Center, Stony Brook, NY, USA Search for more papers by this author Ansuman Biswas Ansuman Biswas National Center of Biological Sciences, Bengaluru, India Search for more papers by this author Giovanna Vanacore Giovanna Vanacore Institute of Biochemistry and Cell Biology, National Research Council of Italy, Rome, Italy Search for more papers by this author Nina Dathan Nina Dathan Institute of Biochemistry and Cell Biology, National Research Council of Italy, Rome, Italy Search for more papers by this author Takahiro Nitta Takahiro Nitta Division of Glycopathology, Institute of Molecular Biomembrane and Glycobiology, Tohoku Medical and Pharmaceutical University, Sendai, Japan Search for more papers by this author Petra Henklein Petra Henklein Universitätsmedizin Berlin Institut für Biochemie Charité CrossOver Charitéplatz 1 / Sitz, Berlin, Germany Search for more papers by this author Mukund Thattai Mukund Thattai National Center of Biological Sciences, Bengaluru, India Search for more papers by this author Jin-Ichi Inokuchi Jin-Ichi Inokuchi orcid.org/0000-0002-0703-5746 Division of Glycopathology, Institute of Molecular Biomembrane and Glycobiology, Tohoku Medical and Pharmaceutical University, Sendai, Japan Search for more papers by this author Victor W Hsu Victor W Hsu orcid.org/0000-0002-6763-4636 Division of Rheumatology, Inflammation and Immunity, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA Search for more papers by this author Markus Plomann Markus Plomann orcid.org/0000-0001-6509-5627 Medical Faculty, Center for Biochemistry, University of Cologne, Cologne, Germany Search for more papers by this author Lina M Obeid Lina M Obeid orcid.org/0000-0002-0734-0847 Stony Brook University Medical Center, Stony Brook, NY, USA Deceased. Search for more papers by this author Yusuf A Hannun Yusuf A Hannun Stony Brook University Medical Center, Stony Brook, NY, USA Search for more papers by this author Alberto Luini Alberto Luini Institute of Biochemistry and Cell Biology, National Research Council of Italy, Rome, Italy Search for more papers by this author Giovanni D'Angelo Giovanni D'Angelo orcid.org/0000-0002-0734-4127 Institute of Biochemistry and Cell Biology, National Research Council of Italy, Rome, Italy École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland Search for more papers by this author Seetharaman Parashuraman Corresponding Author Seetharaman Parashuraman [email protected] orcid.org/0000-0001-5113-4592 Institute of Biochemistry and Cell Biology, National Research Council of Italy, Rome, Italy Search for more papers by this author Author Information Prathyush Pothukuchi1, Ilenia Agliarulo1, Marinella Pirozzi1, Riccardo Rizzo1,9, Domenico Russo1, Gabriele Turacchio1, Julian Nüchel2, Jia-Shu Yang3, Charlotte Gehin4, Laura Capolupo4, Maria Jose Hernandez-Corbacho5, Ansuman Biswas6, Giovanna Vanacore1, Nina Dathan1, Takahiro Nitta7, Petra Henklein8, Mukund Thattai6, Jin-Ichi Inokuchi7, Victor W Hsu3, Markus Plomann2, Lina M Obeid5, Yusuf A Hannun5, Alberto Luini1, Giovanni D'Angelo1,4 and Seetharaman Parashuraman *,1 1Institute of Biochemistry and Cell Biology, National Research Council of Italy, Rome, Italy 2Medical Faculty, Center for Biochemistry, University of Cologne, Cologne, Germany 3Division of Rheumatology, Inflammation and Immunity, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA 4École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland 5Stony Brook University Medical Center, Stony Brook, NY, USA 6National Center of Biological Sciences, Bengaluru, India 7Division of Glycopathology, Institute of Molecular Biomembrane and Glycobiology, Tohoku Medical and Pharmaceutical University, Sendai, Japan 8Universitätsmedizin Berlin Institut für Biochemie Charité CrossOver Charitéplatz 1 / Sitz, Berlin, Germany 9Present address: Institute of Nanotechnology, National Research Council (CNR-NANOTEC), Lecce, Italy *Corresponding author. Tel: +39-081-6132283; E-mail: [email protected] The EMBO Journal (2021)40:e107766https://doi.org/10.15252/embj.2021107766 PDFDownload PDF of article text and main figures. Peer ReviewDownload a summary of the editorial decision process including editorial decision letters, reviewer comments and author responses to feedback. ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InMendeleyWechatReddit Figures & Info Abstract The Golgi apparatus, the main glycosylation station of the cell, consists of a stack of discontinuous cisternae. Glycosylation enzymes are usually concentrated in one or two specific cisternae along the cis-trans axis of the organelle. How such compartmentalized localization of enzymes is achieved and how it contributes to glycosylation are not clear. Here, we show that the Golgi matrix protein GRASP55 directs the compartmentalized localization of key enzymes involved in glycosphingolipid (GSL) biosynthesis. GRASP55 binds to these enzymes and prevents their entry into COPI-based retrograde transport vesicles, thus concentrating them in the trans-Golgi. In genome-edited cells lacking GRASP55, or in cells expressing mutant enzymes without GRASP55 binding sites, these enzymes relocate to the cis-Golgi, which affects glycosphingolipid biosynthesis by changing flux across metabolic branch points. These findings reveal a mechanism by which a matrix protein regulates polarized localization of glycosylation enzymes in the Golgi and controls competition in glycan biosynthesis. SYNOPSIS How the compartmentalized localization of glycosylation enzymes in Golgi is achieved and how it regulates glycosylation is incompletely understood. Here, GRASP55 is found to control competition between glucosylceramide synthase (GCS) and sphingomyelin synthase 1 (SMS1), two enzymes of the glycosphingolipid (GSL) biosynthetic pathway, by regulating trans-Golgi localization of GCS. SMS1 and GCS localize to the trans-Golgi, where they compete for the shared substrate ceramide. GRASP55 binding to the C-terminus of GCS prevents its sorting into retrograde COPI vesicles, thus localizing GCS to the trans-Golgi. Absence of GRASP55-GCS interaction relocates GCS to the cis-Golgi, while SMS1 remains in the trans-Golgi. GCS in the cis-Golgi may have preferential access to ceramide compared to SMS1. Preferential GCS access results in increased glycosphingolipid biosynthesis in the absence of GRASP55. Introduction Glycans are one of the fundamental building blocks of the cell and play key roles in development and physiology (Bishop et al, 2007; Kohyama-Koganeya et al, 2011; Ryczko et al, 2016; Varki, 2017; Akintayo & Stanley, 2019). Cellular glycan profiles are sensitive to changes in cell state and/or differentiation and are also important contributors to the process (Russo et al, 2018b). Indeed, several developmental disorders are associated with impaired production of glycans (Chang et al, 2018). Thus, how the glycan biosynthesis is regulated to achieve specific cellular glycan profiles is an important biological problem. In eukaryotes, glycans are assembled mainly by the Golgi apparatus on cargo proteins and lipids that traverse the organelle (Stanley, 2011). Glycan biosynthesis happens in a template-independent fashion (Varki & Kornfeld, 2015), yet the products are not random polymers of sugars but a defined distribution of glycans that is cell-type and cargo-specific (Rudd et al, 2015; Varki & Kornfeld, 2015). This suggests that their biosynthesis is guided by regulated program(s). Transcriptional programs have been identified that contribute to defining the glycome of a cell, but they only partially account for it (Nairn et al, 2008, 2012; Varki & Kornfeld, 2015). An obviously important but unexplored factor that influences glycosylation is the Golgi apparatus itself (Varki, 1998; Maccioni et al, 2002). The Golgi apparatus is a central organelle of the secretory pathway that processes newly synthesized cargoes coming from the endoplasmic reticulum (ER), primarily by glycosylation, before sorting them toward their correct destination in the cell. It consists of a stack of 4–11 cisternae (Klumperman, 2011), populated by enzymes and accessory proteins that maintain a suitable milieu for the enzymes to act on biosynthetic cargoes. The stack is polarized with a cis-side where cargoes arrive and a trans-side from where they leave. The enzymes are not homogeneously distributed across the Golgi stack but are restricted or compartmentalized to 1–3 specific cisternae. The cisternal maturation model provides a conceptual framework for understanding Golgi enzyme compartmentalization (Nakano & Luini, 2010; Glick & Luini, 2011). According to the model, secretory cargoes are transported forward by the anterograde flux mediated by cisternal progression, which consists of constant formation and consumption of cis and trans cisternae, respectively. The retention of Golgi glycosylation enzymes in the face of this continuous forward flux is mediated by their retrograde transport that acts as counterbalance for the forward transport. The retrograde transport is promoted by coat protein complex I (COPI) machinery (Rabouille & Klumperman, 2005; Popoff et al, 2011; Papanikou et al, 2015; Ishii et al, 2016; Liu et al, 2018) and is assisted in this process by adaptor molecules like GOLPH3 (Tu et al, 2008, 2012; preprint: Rizzo et al, 2019), conserved oligomeric complex (COG) proteins, and Golgi matrix proteins especially Golgins (Eckert et al, 2014; Wong & Munro, 2014; Blackburn et al, 2019). However, the specific molecular mechanisms and processes by which the same retrograde transport pathway promotes localization of enzymes to distinct cisternae remain unknown. The compartmentalized localization of enzymes has been suggested to influence both sequential as well as competing glycosylation reactions. The localization of enzymes along the cis-trans axis reflecting their order of action (Dunphy & Rothman, 1985) has been suggested to influence the efficiency of sequential processing reactions (Fisher et al, 2019). On the other hand, the promiscuity of glycosylation enzymes (Biswas & Thattai, 2020) makes compartmentalized localization of competing enzymes a critical factor in determining the specificity in glycan output (i.e., the type and quantity of glycans produced) (Dunphy & Rothman, 1985; Pothukuchi et al, 2019; Jaiman & Thattai, 2020). When two or more enzymes compete for a substrate, the order in which they get access to it can substantially influence the glycans produced and subsequently the physiological outcomes. Competing reactions are frequent in glycosylation pathways, and all known glycosylation pathways have one or more competing glycosylation steps. Nevertheless, how the compartmentalized localization of competing enzymes is achieved, how it is regulated to influence glycosylation reactions, and what the physiological relevance of this regulation is remain unexplored. To evaluate and understand the contribution of Golgi compartmentalization in regulating glycosylation, we have focused our study on sphingolipid (SL) glycosylation. We chose this model system for several reasons: a. It is well characterized from both biochemical and transcriptional perspectives (Halter et al, 2007; D'Angelo et al, 2013; Russo et al, 2018b); b. the glycosylation reaction is less influenced by the cargo structure in contrast to protein glycosylation and thus is a cleaner system to study effects of Golgi processes on glycosylation; c. there are simple biochemical methods available to analyze SL glycosylation (D'Angelo et al, 2013); and d. finally, SLs have important roles in physiology and development (Hannun & Obeid, 2018; Russo et al, 2018a). The SL glycosylation pathway exhibits the essential features of glycosylation pathways like localization of enzymes reflecting their order of action and also at least two competing reaction steps that are important in determining the metabolic outcome of the pathway (see below). Further, while enzymes of the pathway are well characterized, molecular players regulating their sub-Golgi compartmentalization are unknown. By studying SL glycosylation, we identify GRASP55 as an important factor that compartmentalizes two enzymes catalyzing critical branch points of the SL glycosylation pathway. GRASP55 binds to and prevents the entry of these enzymes into retrograde transport carriers. This retaining action of GRASP55 is essential for dynamic compartmentalization of these enzymes in the Golgi stack. The competing enzymes thus positioned at appropriate levels in the Golgi stack regulate cargo flux across competing reactions of the pathway and determine the metabolic outcome viz. sphingolipid produced by the cell. These results delineate a molecular mechanism of enzyme compartmentalization and how it controls cell surface glycan profile. Results Disruption of Golgi organization alters SL biosynthesis SL biosynthesis starts with the production of ceramide (Cer) in the ER, which is then processed in the Golgi to sphingomyelin (SM) or glycosphingolipids (GSLs). The model cell system we use, HeLa cells, produces two species of GSLs—globosides (Gb3) and gangliosides (GM1 and GM3) (Halter et al, 2007; D'Angelo et al, 2013; Russo et al, 2018b) (See Fig 1A for schematic of the SL system in HeLa cells). This SL pathway includes sequential processing of Cer to complex GSLs as well as two bifurcating steps where the substrates get differentially channeled. The first is the bifurcation between SM and glucosylceramide (GlcCer) biosynthesis, where the substrate Cer is channeled into either of the pathways. The second is the biosynthesis of Gb3 or GM3 from lactosylceramide (LacCer). These two critical steps determine the amount and type of SLs produced by the cell. We first examined the localization of SL biosynthetic enzymes and found that they localize to three distinct zones in the secretory pathway (Fig 1B, Appendix Fig S1): (i) the early secretory pathway including the ER and the cis/medial-Golgi (C1, C2 cisternae), where Cer biosynthetic enzymes are localized (33), have little if any SL biosynthetic enzymes except for a slightly elevated amount of GM3S and GlcCer synthase (GCS) in the cis/medial-Golgi compared with other GSL biosynthetic enzymes; (ii) medial/trans-Golgi (C3, C4 cisternae) where most of the GSL biosynthetic enzymes are present alongside substantial amounts of Sphingomyelin synthase 1 (SMS1) and (iii) trans-Golgi network (TGN), where SMS1 predominates. While all the GSL biosynthetic enzymes show a gradient of increasing concentration from cis- to trans-Golgi, the gradient is much sharper in the case of GB3S and LacCer synthase (LCS) compared with GCS and GM3S (Appendix Fig S1). Thus, the SL biosynthetic enzymes are distributed reflecting their order of action with precursor (Cer) producing enzymes in the early secretory pathway and the Cer processing enzymes in late secretory pathway, which is in turn divided into two distinct zones where GSL and SM biosynthesis predominate. Of note, we expressed HA-tagged enzymes (see Materials and Methods) for our studies since the endogenous enzymes were barely detectable and efficient antibodies for EM studies of endogenous enzymes were not available. Nevertheless, the localization mostly reflects expected localization based on enzyme activity and previously published evidence (Parashuraman & D'Angelo, 2019). A notable exception is the localization of GCS that was shown to be on the cis-side of the Golgi (Halter et al, 2007) contrary to what we report here. This is because the earlier studies had used a construct with a tag that blocks the signal for intra-Golgi localization that we identify and describe here. When this signal is blocked, localization of GCS is altered resulting in localization to cis-Golgi (see below). Figure 1. Disruption of SL biosynthetic machinery organization alters SL output A. Schematic representation of GSL biosynthetic pathway in HeLa cells (Glu, glucose; Gal, galactose; Sia, N-acetylneuraminic acid; Cer, ceramide). Products of biosynthesis are represented in bold and enzymes that catalyze the reactions in gray. The arrows represent the SL metabolic flux from ceramide. B. Schematic representation of GSL biosynthetic zones in HeLa, SM biosynthesis predominates in TGN, whereas GSL and SM productions happen in medial/trans-Golgi (C3 and C4 cisternae). Cis-Golgi/ER is where Ceramide biosynthesis happens with little, if any, SL production. CerS* refers to the group of Ceramide synthases localized to the ER. The size of the lipid label arbitrarily represents the proportion of the lipid expected to be synthesized in the compartment based on the localization of corresponding enzymes. C. High-performance thin-layer chromatography (HPTLC) profile of HeLa cells pulsed for 2 h with [3H]-sphingosine and chased for 24 h. The peaks corresponding to each SL species are indicated, and numbers represent each SL species as percentage of total SL. D. The total radioactivity associated with Cer, SM, and GSLs (GluCer, LacCer, Gb, and GM), or GM and Gb were quantified and presented as percentages relative to total. Data represented as means ± SD of three independent experiments. E, F. Biosynthesis of SL in HeLa cells expressing GTP-locked mutants of Sar1 or ARF1 or treated with Brefeldin A (BFA; 5 μg/ml) was measured by [3H]-sphingosine pulse-chase assay. Radioactivity associated with GSLs was quantified and represented as fold change with respect to control. (E) For BFA-treated cells, the SL output was measured 8 h after pulse. Data represented as means ± SD of two independent experiments. *P < 0.05, **P < 0.01 (Student's t-test). (F) The ratio of GM/Gb is represented. Data represented as means ± SD of two independent experiments. *P < 0.05, **P < 0.01 (Student's t-test). Download figure Download PowerPoint Next, SL output of this system was measured by metabolic labeling with 3H-sphingosine, a precursor of ceramide. This revealed the following distribution of products at quasi steady state i.e., 24 h after labeling: SM (70%), globosides (10%), and gangliosides (5%) and rest remaining as precursors (Cer, GlcCer or LacCer; 15%) (Fig 1C and D). The GSLs (globosides, gangliosides, and GSL precursors GlcCer and LacCer) together constituted 25% of total SLs produced. We will refer to the ratio of GSL:SM::25:70 as SL output and the ratio of gangliosides (GM) to Globosides (Gb), GM:Gb::5:10 as GSL output (Fig 1D). For simplicity, the SL output will be represented as GSL fraction since a change in GSLs is always associated with a proportional change in SM in the opposite direction. For GSL output, the situation is complex since a substantial portion of signal remains as precursors (GlcCer and LacCer), and so GSL output will be represented as a GM/Gb ratio which under the control conditions corresponds to 0.5 (GM:Gb::5:10). To summarize, the SL machinery has a compartmentalized localization across the Golgi in HeLa cells and produces a SL output such that 70% of the Cer is directed toward the production of SM and 25% toward the production of GSLs. Within this 25, 5% is directed toward the production of gangliosides and 10% toward the production of globosides. This distribution of glycoforms produced by the Golgi apparatus has largely been ascribed to the expression of the corresponding glycosylation enzymes (Maccioni et al, 2002; Nairn et al, 2008, 2012). To assess the contribution of enzyme compartmentalization to this, we monitored SL output after disrupting the spatial organization of SL biosynthetic enzymes by a) overexpressing GTP-locked mutants of monomeric GTPases——secretion-associated Ras-related GTPase (Sar1 H79G) and ADP ribosylation factor 1 (ARF1 Q71L) that are well known to disorganize the secretory pathway (Zhang et al, 1994; Aridor et al, 1995) and b) by treating the cells with Brefeldin A, which causes relocation of Golgi enzymes back to the ER. Overexpression of Sar1 H79G led to collapse of the Golgi apparatus into the ER with SL biosynthetic enzymes showing a reticular ER pattern (Appendix Fig S2A). On the other hand, overexpression of ARF1 Q71L mutant led to disruption of stacked cisternal structure of the Golgi, which was replaced by tubulo-vesicular clusters (Appendix Fig S2B), with no separation between cis- and trans-Golgi markers (Appendix Fig S2C) (List of recombinant DNA used in this study are listed in Appendix Table S2). The treatment with Brefeldin A led to the translocation of the enzymes back into the ER as expected, apart from SMS1 which while present in the ER also displayed presence in some punctate structures (Appendix Fig S2A). The SL output was altered in these cells, and consistently, in all three conditions there was an increased production of GSLs over SM and gangliosides over globosides (Appendix Fig S2D and E). The SL output represented as fold change in GSL fraction showed that GSL production in these cells increased by 1.5–1.9 fold over control cells (Fig 1E). Similarly, GSL output measured as GM/Gb ratio changed from 0.5 in control cells to 1.3–1.5 in treated cells (Fig 1F). These data suggest that impaired spatial organization of enzymes correlates with altered SL output, and especially, the output from steps involving competing reactions is sensitive to disorganization of the Golgi. The contribution of enzyme expression to determination of glycosylation is well established (Nairn et al, 2012) but the contribution of the Golgi organization and its importance to this process was not clear. These results underscore a significant and substantive role played by the Golgi apparatus in determining the glycan output of a cell. GRASP55 regulates SL output by controlling substrate flux between competing glycosylation pathways Given the importance of the organization of the Golgi apparatus, and likely of the SL biosynthetic machinery localized to the organelle, to determining SL output, we wanted to identify the molecular players involved in this process. Retention of enzymes in the Golgi depends on their COPI-dependent retrograde transport. Golgi matrix proteins especially Golgins contribute to specificity in this process (Wong & Munro, 2014) and thus to compartmentalization of enzymes. So, to identify specific regulators of compartmentalization of SL biosynthetic enzymes, we systematically silenced Golgi matrix proteins and studied the effect on SL production. Among the 14 matrix proteins tested by depletion, downregulation of GRASP55 significantly increased the production of GSLs (a 40% increase in GSLs compared with control) while downregulation of GOPC and GCC2 led to a decrease in GSL levels (Fig 2A) (siRNA sequences used in this study to downregulate indicated human gene expression are listed in Appendix Table S3). We followed up on GRASP55 since its depletion altered SL output similar to that obtained by disorganization of the Golgi apparatus (Fig 1E). Figure 2. GRASP55 regulates SL biosynthesis A. HeLa cells were treated with control or indicated siRNA (pool of 4 or 2 as indicated in me
