C. elegans revealed that the PCM is composed of partially overlapping territories organized into an inner and outer sphere that are removed from the centrosome at different rates and using different behaviors. We found that phosphatases oppose the addition of PCM by mitotic kinases, ultimately catalyzing the dissolution of inner sphere PCM proteins at the end of mitosis. The nature of the PCM appears to change such that the remaining aging PCM outer sphere is mechanically ruptured by cortical pulling forces, ultimately inactivating MTOC function at the centrosome.The centrosome acts as a microtubule organizing center (MTOC), orchestrating microtubules into the mitotic spindle through its pericentriolar material (PCM). This activity is biphasic, cycling through assembly and disassembly during the cell cycle. Although hyperactive centrosomal MTOC activity is a hallmark of some cancers, little is known about how the centrosome is inactivated as an MTOC. Analysis of endogenous PCM proteins in  New cells are created when existing cells divide, a process that is critical for life. A structure called the spindle is an important part of cell division, helping to orient the division and separate parts of the old cell into the newly generated ones. The spindle is built using filamentous protein structures called microtubules which are arranged by microtubule organizing centers (or MTOCs for short). In animals, an MTOC forms at each end of the spindle around two structures called centrosomes.A network of proteins called the pericentriolar material (PCM) form around centrosomes, converting them into MTOCs. The PCM grows around centrosomes as a cell prepares to divide and is removed again afterward. Enzymes called kinases are important in controlling cell division and PCM assembly; they are opposed by other enzymes known as phosphatases. The processes involved in organization and removal of the PCM are not well understood.Caenorhabditis elegans provides an opportunity to study details of cell division in a living animal. Magescas et al. used fluorescent labels to view proteins from the PCM under a microscope. The images showed two partially overlapping spherical parts to the PCM – inner and outer. Further examination revealed that the inner PCM is maintained by a careful balance of kinase and phosphatase activity. When kinases shut down at the end of cell division, the phosphatases break down the inner PCM. By contrast, the outer PCM is physically torn apart by forces acting through the attached microtubules.The microscopic worm Future work will seek to examine which proteins are specifically affected by phosphatases to identify the key regulators of PCM persistence in the cell and to reveal the proteins needed for MTOC activity at the centrosome. Since poor MTOC regulation can play a part in the growth and spread of cancer, this could lead to targets for new treatments. Numerous cell functions such as transport, migration, and division are achieved through the specific spatial organization of microtubules imparted by microtubule organizing centers (MTOCs). The best-studied MTOC is the centrosome, a membrane-less organelle composed of two barrel-shaped microtubule-based centrioles surrounded by a cloud of pericentriolar material (PCM). Microtubules at the centrosome are mainly nucleated and localized by complexes within the PCM, which generate a radial array of microtubules in dividing animal cells and some specialized cell types such as fibroblasts.Drosophila and human cell lines, PCM proteins including a subset of scaffolding proteins are organized in cumulative layers ultimately recruiting microtubule nucleation and organization factors, such as the conserved microtubule nucleating γ-tubulin ring complex (γ-TuRC)  . In C. eRAP2/Cnn . TogetheT-1/MZT1 . γ-TuRC s zygote . Additio the PCM .C. elegans, the organization of proteins within the PCM has been generally unexplored. One notable exception is that microtubules have been shown to localize to the periphery of the PCM by electron microscopy , microtubules (early packets), AIR-1 (early packets), and TPXL-1, but neither SPD-2 nor MZT-1 /LGN, and (GOA-1/GPA-16)/Gαi, which localizes dynein-dynactin and can pull on the astral microtubules extending from the PCM . Given tntrosome . Moreoventrosome .gpr-1/2(RNAi)) or increase (csnk-1(RNAi)) cortical forces. In control embryos treated with lacZ RNAi, SPD-5 ruptured starting 6 min post-NEBD  treated embryos (csnk-1(RNAi) treated embryos, we observed slightly earlier SPD-5 rupture  treated embryos, but no significant change in csnk-1(RNAi) treated embryos (csnk-1 RNAi had no effect on the timing of centriole separation suggests that a force-independent licensing event is necessary to initiate separation (gpr-1/2(RNAi) treated embryos had defects in effectively clearing SPD-5, but not SPD-2, from the PCM prior to the subsequent round of PCM accumulation in the next cell cycle . As previously reported, let-92 inhibition caused severe defects in cell division, necessitating analysis in the one-cell zygote rather than 4-cell embryo  at three defined timepoints during mitosis : (1) jushenotype , growth henotype  or GIP-1henotype  at the cThe precocious disassembly of PCM following CDK inhibition suggested that the association of PCM proteins with the centrosome is normally actively opposed such that turning off assembly immediately triggers disassembly. To test if this opposition is phosphatase dependent, we treated embryos with both FP and OA. Pre-growth stage treated embryos showed no addition of SPD-2 or SPD-5, consistent with a requirement for CDK activity in centrosome maturation. Treatment with both inhibitors at growth or metaphase stage led to a stabilization of SPD-5, consistent with the hypothesis that SPD-5 assembly driven by CDK activity is normally opposed by phosphatase activity. In contrast, SPD-2 was precociously disassembled in the presence of OA and FP in growth and metaphase stage embryos, identically to what was observed in embryos treated with OA alone. These results suggest that the maintenance of SPD-2 at the centrosome is controlled by an OA sensitive phosphatase and indicate that regulation of SPD-2 and SPD-5 can be uncoupled.2, 2 centrosome. Finally, the process of assembly and disassembly could be mutually resistant to the factors that induce the converse process, that is cell fusion would have no impact on the assembling P2 centrosome or the disassembling ABp centrosome.The differential behavior of PCM proteins in response to the timing of kinase and phosphatase inhibition suggests that assembling and disassembling PCM are inherently different structures. We therefore wanted to test whether the factors that contribute to PCM assembly had any impact on disassembling PCM or vice versa. Using in vivo cell fusion experiments, we previously found that cytoplasm from pre-anaphase cells could rapidly induce the assembly of PCM and microtubules onto inactive centrosomes in both cycling and differentiated cells, indicating that mitotic cytoplasm dominantly selects for PCM assembly . Using a2  method that has been previously described . DNA mixEmbryos dissected from one-day old adults were mounted on a pad (3% agarose dissolved in M9) sandwiched between a microscope slide and no. 1.5 coverslip. Time-lapse images were acquired on a Nikon Ti-E inverted microscope (Nikon Instruments) equipped with a 1.5x magnifying lens, a Yokogawa X1 confocal spinning disk head, and an Andor Ixon Ultra back thinned EM-CCD camera (Andor), all controlled by NIS Elements software (Nikon). Images were obtained using a 60x Oil Plan Apochromat (NA = 1.4) or 100x Oil Plan Apochromat (NA = 1.45) objective. Z-stacks were acquired using a 0.5 µm step every minute. Images were adjusted for brightness and contrast using ImageJ software.Drugs treatments were performed as previously described . Briefly2 cells were fused using the Micropoint dye laser (coumarin 435 nm) and confocal described above.Embryos were prepared and mounted the same way as described above for image acquisition. ABp and Pcsnk-1(RNAi), gpr-1/2(RNAi), and let-92(RNAi) expressing HT115 bacteria from the Ahringer RNAi library (RNAi treatment was performed by feeding as previously described using  library . L4 stagPCM volume was measured from stacks of images taken through the ABp centrosome closest to the coverslip at each timepoint. Image stacks were first processed to eliminate the cytosolic background by subtracting the mean intensity of 10 random points in the cytoplasm at each plane and each timepoint. Image stacks were then thresholded using the Otsu method (ImageJ) to delimit the PCM structure. Volume measurements were performed using the 3D object counter imageJ plugin . Only thlet-92 depletion results in centriole duplication defects in the one cell embryo (let-92 depleted embryos at the end of disassembly (t = 15’). This type of measurement was in contrast to the total centriole/centrosome measurement shown in Total intensity was measured by defining an image stack 15 µm wide x 7.5 µm deep around the centrosome for each timepoint. Another stack of the exact same dimensions was generated in the cytoplasm. Both stacks were sum projected and the total intensity was measured by subtracting the total intensity of the cytoplasmic sum projection from the total intensity of the centrosome sum projection. Centrosomal intensity was calculated in the same way, but ROIs were selected manually following initial thresholding to specifically select for the centrosome and not the surrounding packets upon rupture. Only the PCM that was connected to the centrioles was considered in the intensity measurement. Packet intensity was determined by subtracting the intensity measurement for the centriole and contiguous PCM from the total intensity measurement. In l embryo . In contThe different steps of disassembly were defined based on hallmarks of both volume and intensity measurements. ‘Dissolution’ was defined as the timepoint at which the first decrease in PCM intensity was detected, which corresponded to a decrease in SPD-2 intensity. ‘Rupture’ was defined as the timepoint at which holes first appear in the PCM, which corresponded to a drop in SPD-5 volume. Packet formation was defined as the timepoint at which individualized foci of SPD-5 appeared around the centrioles.t test. All other data were analyzed using an ANOVA analysis followed by Tukey’s multiple comparison test; P-values for the Tukey’s multiple comparison test are reported in corresponding figure legends. To determine the percentage of SPD-5 overlapping with SPD-2, the area under the curve (AUC) of the mean intensity profile of SPD-5 was used. The portion of the SPD-5 overlapping with SPD-2 was defined as the SPD-5 AUC in the region defined by the half-max values of the SPD-2 mean intensity profile. The total portion of SPD-5 was defined as the AUC in the region defined by the half-max values of the SPD-5 mean intensity profiles. The percentage of overlap was then defined as the SPD-5 AUC in SPD-2 half-max interval divided by the SPD-5 AUC in the SPD-5 half-max interval.Statistical analyses were performed using R and Prism . PCM size reported in  In the interests of transparency, eLife includes the editorial decision letter and accompanying author responses. A lightly edited version of the letter sent to the authors after peer review is shown, indicating the most substantive concerns; minor comments are not usually included.eLife. Your article has been reviewed by three peer reviewers, and the evaluation has been overseen by a Reviewing Editor and a Senior Editor. The reviewers have opted to remain anonymous.Thank you for submitting your work entitled "A two-step mechanism for the inactivation of microtubule organizing center function at the centrosome" for consideration by eLife.Our decision has been reached after consultation between the reviewers. Based on these discussions and the individual reviews below, we regret to inform you that your work will not be considered further for publication in eLife (such as identification of PP2A substrates) is too substantial and beyond the scope of standard revision per eLife's policy, as only revisions with straightforward experiments that can be carried out within approximately two months are encouraged by eLife.All three reviewers agreed that the present study is of potential interest. However, as you can see from the individual comments of these reviewers, they felt that the progress that has been achieved compared to the existing/published work was not sufficient. The reviewers thus agreed that the revision required for this manuscript to be acceptable for We would be prepared to consider a substantially revised version as a new submission, if the mechanistic part of the paper were significantly extended, for example, by identifying new PP2A substrates or the regulatory details behind the two-step PCM disassembly.Reviewer #1:The manuscript by Magescas et al. reports on centrosome disassembly as cells exit mitosis. This process involves the reduction in PCM components and a corresponding reduction in centrosomal microtubules. The authors begin by defining the localization of 4 PCM components relative to the centriole to show a wider and wider distribution in the following order Spd-2, MZT-1, Spd-5 and then GIP-1. The authors then describe two different disassembly modes: Spd-2 and MZT-1 show a gradual disassembly, while Spd-5 and GIP-1 disassemble in "packets". The authors then use RNAi and chemical perturbations to show that centrosome disassembly requires microtubules to pull the packets away from the centrosome, and that PP2A is also required.The topic is both interesting and important; centrosome disassembly, or dematuration, does not garner anywhere near the attention that centrosome maturation commands. Clearly dematuration is an active process and it is not simply PCM passively falling apart. This study, however, does not provide much new insight into disassembly. I outline this in detail below.Drosophila embryos. Here the authors properly reference the work by Megraw, but they improperly state that the flares are present throughout the cell cycle. Flares form specifically during mitotic exit and they also release packets into the cytoplasm. This was shown in Lerit et al. (2015).1) Centrosome fragmentation. I was surprise that there was no mention of the study from the Wadsworth lab from 2005 .. The Wadsworth lab showed the same phenomenon of disassembling the centrosome into packets, or fragments, and their ability to nucleate microtubules. While the previous study was done in another system, observation of packets in of themselves is not particularly novel. Another example that the authors did mention are the flares from 2) The mechanism of centrosome disassembly. While the authors better describe the effects of reducing microtubule pulling forces (via Grp-1/2 loss), inhibition of PP2A function (drug treatment), and loss of Let-92 on centrosome disassembly, all of these experiments were previously reported in Enos et al., 2018. This previous study greatly reduces the enthusiasm for the current results. I think an advance to the field here would require the identification of PP2A targets.C. elegans PCM that might differ from current models. I was, however, surprised by the choice of imaging. The use of Structured Illumination Microscopy to define the regions occupied by centrosome protein is standard practice in the centrosome field. A localization study using SIM would be more appropriate, not simply because it is standard practice, but rather because SIM imaging has played a critical role in shaping current models and hypotheses regarding centrosome function.3) Centrosome protein distribution. One exciting result was the finding that Spd-5 and Spd-2 do not occupy the same space in the centrosome. This could have important implications on how we view Reviewer #2:C. elegans embryo. The centrosome is the microtubule-nucleating organelle organized into distinct subconcentric domains. The stepwise assembly of the various centrosomal components resulting in the recruitment of γ-TURC complexes is well-studied based on work from a variety of systems.Magescas and coworkers investigate the regulation of PCM disassembly using dynamic imaging of the C. elegans centrosome, albeit at relatively low resolution compared to similar studies from cell lines and Drosophila embryos. Of note, the authors examine the less understood process of PCM disassembly and the associated role of protein phosphatase PP2A. Their work suggests disassembly of the retinue of PCM proteins by at least 2-steps. First, a slower-acting step, regulated in part by protein dephosphorylation, results in the partial dissolution of the PCM. Second, a faster-acting step involves active forces – presumably acting upon microtubules via protein complexes associated with the cortical membrane .In this study, the authors describe the macromolecular organization of the eLife.This is an informative study that adds mechanistic understanding to the important process of centrosome inactivation via PP2A and cortical pulling forces. However, much of this work appears to largely support the conclusions of Enos et al., 2018 published in Biology Open. Nonetheless, the present work does delineate some differences with respect to the temporal requirement of phosphatases versus forces. Further, the authors describe impaired centriole separation in response to impairing the process of PCM disassembly, thereby adding some physiological significance. However, it is not apparent the present study presents enough of an advance to merit publication in 1) Would the authors please describe in more detail what they measure for their quantification of centrosome intensity? Is the ROI a defined shape/size? Do the authors include proteins that have ruptured and migrated away from the centriole? As written, the Materials and methods simply state the ROI "was selected manually". This merits a little more detail as a major conclusion is that changes in centrosomal intensity precede changes in volume .Reviewer #3:C. elegans centrosomal PCM, and two phases of its disassembly, in early embryonic cells. They show that the PCM consists of an inner core that includes the coiled coil proteins SPD-2 and SPD-5, along with γ-tubulin ring components, and an outer shell that includes SPD-5 and in part one γ-tubulin ring component (GIP-1) with a second γ-tubulin ring component (MTZ-1) extending beyond the inner core but extending only partially into the SPD-5/GIP-1 outer shell. The authors also document a two-step PCM dis-assembly process, with a PP2A phosphatase-dependent dissolution of some PCM components, and a cortical-force dependent rupture of the PCM that completes dis-assembly of the SPD-5 scaffold. These results significantly improve our understanding of C. elegans PCM structure and of PCM dis-assembly. However, before the manuscript can be considered suitable for publication in eLife, the authors need to address the following concerns.Magescas et al. document the fine structure of the 1) In all of the figures, the authors show a dissolution of the PCM components SPD-2 and MTZ-1, without the rupture and packets observed for SPD-5 and GIP-1. However, the later time points do show two strong foci for SPD-2 and MTZ-1. Do these represent duplicated centrioles with associated PCM? The authors never described these foci in the text or figure legends and need to more fully describe the images they present for the reader to fully understand these results.2) Similarly to the above comment (1), in the graphs showing quantification of packet intensity , centrosomal intensity  and volume at the centrosome , are the authors excluding the bright foci for SPD-2 and MZT-1, or are the included? Because the graphs in some cases show signal levels close to zero, presumably these bright foci are somehow excluded, but the text and figure legends do not refer to this issue. Again, for clarity, the authors should more fully describe the image data in the figure legends and text. The Materials and methods seem to refer to this issue with respect to Figures 5E and 5F, but it is not clear to me exactly how these quantifications were done with respect to the two bright foci detected at later time points.3) In Figure 2, the authors show that SPD-5 and GIP-1 are both found in packets during dis-assembly. However, Figure 2A shows SPD-5 present only in two foci in the "early packets", while there are several SPD-5 foci in early packets in Figure 2B. Thus the co-localization of SPD-5 and GIP-1 appears very limited early on. The authors do not refer to this in the text or legend. How extensive is the overlap between SPD-5 and GIP-1 in packets? Are there some packets with only one or the other, and some with both, and can the authors quantify this overlap? More information as to the exact nature of their co-localization would be helpful.4) The authors refer to "rupture" and "packet formation" somewhat interchangeably. In the Figure 3 legend, they define these terms with reference to arrows, but they never refer to specific images that would clarify these terms. The authors should refer to specific images in the figures that show the "holes" in the SPD-5/GIP-1 matrix that constitute rupture, and images that show the appearance of individual packets. While the graphs in Figure 3 indicate rupture occurring at 6 minutes, SPD-5 is clearly fragmented at 5 minutes in Figure 3C, and something like "holes" are apparent at 4 minutes in Figure 3C. I am confused by the use of these two terms that seem to imply distinct phases in dis-assembly but also seem to be simply different stages of the same process. Some clarification of these terms would be helpful.5) When addressing the cortical forces to promote packet formation/dis-assembly in Figure 4, the text refers to rupture starting at 6 minutes post-NEBD and packets forming at 8 minutes in the control/WT embryos . However, the figure only goes to 7 minutes. Moreover, SPD-5 shows distinct puncta at 5 minutes in Figure 1A control, and what seem to be definite packets at 6 minutes. Thus the text description does not seem to be very consistent with what is shown in the figure. This needs clarification.csnk-1 depletion. What is being increased and what is being decreased, and in what background. I could not understand this sentence as written, and it seemed to me that in Figure 4 the knockdowns led only to increases.6) In the second paragraph of the subsection “Cortical forces mediate the disassembly of the PCM and more specifically SPD-5”, the authors refer to SPD-5 intensity and volume being increased or decreased by either grp-1/2 or 7) In the second paragraph of the Discussion, the authors state that removal of PCM proteins from the inner sphere weakens the remaining PCM, allow for rupture of the outer sphere. This is stated as if it is a clear conclusion, but what data supports this interpretation/conclusion, or is it a model and speculation?C. elegans and a substantially more in depth analysis of PCM dis-assembly. The authors need to more explicitly address how their analysis goes beyond what was shown by Enos et al., either in the Results or the Discussion. This could be done briefly but it seems to me such a comparison is warranted, given the substantial amount of overlap in the two manuscripts. Similarly, has any evidence for this partial independence of SPD-2 and SPD-5 localization been previously noted?8) The authors cite Enos et al. 2018 as showing the PP2A and cortical forces have been shown to be required for PCM dis-assembly. Thus the two factors that contribute to dis-assembly have already been published. However, Enos et al. examined only SPD-5 and no other PCM components, and did not distinguish between dissolution and dissolution as two distinct processes. They simply refer to PP2A and cortical forces as two independent contributions without assigning them to distinct aspects of dis-assembly. The work by Enos et al. 2018 thus could be viewed as making the results presented here as somewhat incremental and perhaps better suited for publication in a more specialized journal. But Magescas et al. do provide novel findings concerning the layered nature of the PCM in [Editors’ note: what now follows is the decision letter after the authors submitted for further consideration.]eLife. Your article has been reviewed by three peer reviewers, and the evaluation has been overseen by a Reviewing Editor and Anna Akhmanova as the Senior Editor. The reviewers have opted to remain anonymous.Thank you for submitting your article "A two-step mechanism for the inactivation of microtubule organizing center function at the centrosome" for consideration by The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.As you can see in the individual comments, all reviewers agreed that the newly submitted version of the manuscript has greatly improved over the previous version. Their comments are mostly straightforward and thus can be addressed without the guide of consolidated review.Thus, we would like to invite you to submit the revision. Please provide point-by-point responses to review comments, such that we can reach the decision in a timely manner, once we receive the revision.Reviewer #1:eLife.This revised manuscript from Magescas, Zonka and Feldman thoroughly addresses the comments from all three reviewers on the original submission. The authors have added a substantial amount of new data ; additional inhibitor studies that uncouple the regulation of SPD-2 and SPD-5; and an interesting cell fusion experiments that suggest assembly and disassembly states are stable and resistant to influence from cytoplasms that promote the opposite processes. The authors also now include reference to Megraw et al. from JCB in 2002, in which cell cycle-dependent centrosome fragmentation was observed, and provide a more detailed comparison of their work to a recent publication . I agree with the authors that their analysis is substantially more extensive and goes well beyond what has been reported previously, significantly advancing our understanding of centrosome disassembly. In my opinion the revised manuscript warrants publication in Reviewer #2:C. elegans to describe a two-step disassembly model of PCM – dissolution followed by rupture. The study shows that some centrosome components such as Spd2 follow the dissolution pathway of disassembly, while others such as Spd5 undergo rupture to generate packets of smaller PCM assemblies that move outward away from the centrioles. Overall, I found the study quite a bit improved over the previous version with addition of new experiments, references and discussion. I am also now convinced that it does goes sufficiently beyond the Enos 2018 study. I have one major comment.The manuscript by Magescas et al. is a resubmission/new submission from the Feldman lab on the topic of centrosome disassembly during mitotic exit. The study uses live cell imaging and RNAi in 1) Related to the description of spheres and the use of confocal microscopy. An important point in this paper is to define regions of the centrosome occupied by different proteins. The authors describe three regions: the centriole, the inner sphere, and the outer sphere. The description of these regions, along with comparison with other systems in which SIM was used, leaves the reader with the impression that Spd2 (and other proteins) occupies a toroid (donut) area surrounding the centriole with edges of 0.51-1.15, while Spd5 occupies a toroid (donut) with edges of 1.15-1.66. I think that the imaging method and data presented do not support this view. The intensity profiles in Figure 1B suggests that roughly 80-90% of Spd5 is actually found within Spd2 localization area from -1.15 and +1.15. Thus one cannot conclude that the proteins are in distinct locations.Drosophila embryos  to describe centrosome zones  and many publication form the Raff lab  and even SIM in the worm (PMID: 28103229). I can only conclude that SIM is very much possible and routine. Given that SIM was not performed in this study, the authors' description of these proteins as "distinct localization", “discrete layers”, and "novel protein territories"  are not supported by the data. I recommend the following:The response by the authors related to the reviewer's comment about why SIM was not used in this study does not acknowledge SIM imaging done in - Change the description to 'outer edge of the small spd2 sphere' and 'the outer edge of the larger Spd5 sphere'. That way the author will not misunderstand the localization as toroids.- Indicate the outer edge measurements on Figure 1D.- Report the% of total Spd5 that overlaps with Spd2 (between -1.15 and 1.15) and that falls outside of the Spd2 sphere (<-1.15 + >1.15) using the area under the curve. This way the reader will get a better impression that there is actually only a small amount of Spd5 that does not overlap with Spd2.- Soften the comparison between these measurement and previous SIM reports. The data in this study shows no toroid structure other than TPXL-1 and AIR-1; thus the direct comparison to Cnn, for example, is not supported. A comparison to other systems should be reserved for a future SIM study.These changes will not impact any of the subsequent results. I think it is even more intriguing that two proteins that mostly occupy the same area (in my estimate from the linescans that 80% of Spd5 overlaps with Spd2) can behave so differently.Reviewer #3:Largely through live imaging and quantitative analysis, Magescas and coworkers present a detailed study of PCM disassembly and the unique behaviors of several PCM constituents. In this resubmission, the authors present a more comprehensive localization analysis of endogenously tagged PCM molecules at mitotic centrosomes and corresponding time-lapse imaging of their disassembly. Additional experimentation includes extended pharmacological inhibition to parse apart relative contributions of the pro-maturation kinase CDK1 versus phosphatase activity, which also complement RNAi studies. Elegant cell fusions between mitotic P2 cells and ABp cells undergoing PCM disassembly test the competency of centrosomes to respond to presumptive cytoplasmic cues.C. elegans centrosome shows a subconcentric organization consisting of distinct and separable zones, similar to those reported in cultured human and Drosophila cells and Drosophila embryos. (3) Several pieces of evidence support the conclusion that disassembly of Spd2 and Spd5 may be uncoupled. This point is significant given their interdependent localization to the PCM. (4) Analysis of these and other PCM molecules support the overall conclusion that inner zone molecules and outer zone molecules tend to be differentially regulated during the process of PCM disassembly. (5) As previously noted, another strength of the work in the physiological link between timely PCM disassembly and proper centriole separation kinetics.Strengths of the revised work include beautiful, carefully documented imaging which supports the conclusions: (1) PCM disassembly occurs by two distinct steps. First, a slow dissolution step that requires PP2A/phosphatase activity. Next, a more rapid rupturing phase rips the PCM apart in a MT-derived force-dependent manner. (2) The mitotic eLife.This work contains several interesting insights and opens up many lines of future investigation; however, in the absence of more mechanistic insight, it is not apparent the present study presents enough of an advance to merit publication in  [Editors’ note: the author responses to the first round of peer review follow.]Reviewer #1:[…] The topic is both interesting and important; centrosome disassembly, or dematuration, does not garner anywhere near the attention that centrosome maturation commands. Clearly dematuration is an active process and it is not simply PCM passively falling apart. This study, however, does not provide much new insight into disassembly. I outline this in detail below.1) Centrosome fragmentation. I was surprise that there was no mention of the study from the Wadsworth lab from 2005 . The Wadsworth lab showed the same phenomenon of disassembling the centrosome into packets, or fragments, and their ability to nucleate microtubules. While the previous study was done in another system, observation of packets in of themselves is not particularly novel. Another example that the authors did mention are the flares from Drosophila embryos. Here the authors properly reference the work by Megraw, but they improperly state that the flares are present throughout the cell cycle. Flares form specifically during mitotic exit and they also release packets into the cytoplasm. This was shown in Lerit et al. 2015.We thank the reviewer for this recommendation and now cite the Wadsworth paper in multiple places. We have also added a paragraph to our Discussion where we compare and contrast packets, flares, and centrosome fragments. These structures share some interesting similarities but also differ in some ways that we now highlight. In regards to the timing of flares, Megraw et al., 2002, stated that “The number of flares associated with centrosomes varies with the cell cycle. […] The intensity of flares is highest at cleavage telophase/interphase centrosomes and lowest at mitotic centrosomes, especially during metaphase and anaphase. In addition, Cnn appears to be associated with metaphase/anaphase centrosomes more tightly, giving the centrosome a more rounded appearance, with fewer of the projections that spawn flare particles seen on centrosomes at other phases of the cleavage cycle …”. The quantification shown in this paper indicates that flares are present during the entire span of the cell cycle, although the flares decrease in number and intensity in metaphase. In addition, the more recent study by Lerit et al., 2015, showed that flares are present and active throughout interphase. We have changed our statement concerning flares, highlighting the fact that packets are found during disassembly exclusively, while flares are mainly found during interphase and telophase.2) The mechanism of centrosome disassembly. While the authors better describe the effects of reducing microtubule pulling forces (via Grp-1/2 loss), inhibition of PP2A function (drug treatment), and loss of Let-92 on centrosome disassembly, all of these experiments were previously reported in Enos et al., 2018. This previous study greatly reduces the enthusiasm for the current results. I think an advance to the field here would require the identification of PP2A targets.We fully agree with the reviewer that we confirm the results that were published by Enos et al., 2017 while our experiments were underway. However, although some of the mechanistic aspects between the two papers appear similar on the surface, our manuscript has several important differences that we feel make it a more complete story of centrosome inactivation that will still appeal to a wide audience:a) Enos et al. focused entirely on SPD-5, while our manuscript analyzes a more complete repertoire of PCM proteins and finds that SPD-5 removal is preceded by removal of several exclusively inner sphere proteins including SPD-2 and the γ-TuRC component MZT-1. Our data not only paint a more complete picture of centrosome inactivation, but also identify specific regulated steps in the disassembly process,C. elegans PCM. That known binding partners apparently localize to distinct regions of the PCM changes the way we think about the nature of PCM assembly and function,b) By looking at several PCM components, our study identifies novel protein territories within the c) We identify important behavioral differences in the manner by which PCM proteins are removed from the centrosome. Through this analysis we discovered a phase of gradual dissolution that precedes the formation of smaller sub-PCM ‘packets’ that retain MTOC potential. As Enos et al. only characterized SPD-5 and did not comment on its disassembly behavior, these modes of disassembly we find are completely novel and point to distinct regulatory mechanisms.d) Although Enos et al. find a role for phosphatase activity and cortical forces in SPD-5 disassembly, again, we elucidate a more complete picture of how these mechanisms impact overall PCM disassembly. We find that centrosome inactivation is initiated by a dissolution behavior that appears to be controlled by phosphatase activity. This process potentially weakens the PCM, which is then fully cleared by cortical forces. While SPD-5 is dependent on cortical forces for its complete removal, we find that SPD-2 can be removed in the absence of cortical forces and instead relies on phosphatase activity for proper clearance.e) We identify functional significance for the timely removal of PCM proteins; both subsequent centriole separation and accumulation of the next round of PCM are affected when SPD-5 is not properly cleared from the PCM,f) Our study uses only endogenously tagged proteins for our analysis, rather than overexpressed transgenes, allowing us to more confidently describe endogenous behaviors and mechanisms.These points have been added to the Discussion. We have also added additional experiments that further differentiate our paper from that of Enos. et al., 2017 and expand our understanding of PCM disassembly.1) New localization studies reveal additional aspects of PCM organization and behavior: We imaged endogenously tagged PLK-1, TAC-1, ZYG-9, LET-92, AIR-1, and TPXL-1, measuring their distribution in the PCM  as well as observing their disassembly behavior . We found that these proteins also occupy distinct regions within the inner and outer sphere of PCM, notably with TAC-1 and binding partner ZYG-9 localization being distinguishable in the outer sphere, AIR-1 and TPXL-1 occupying an almost exclusively outer sphere donut localization, and AIR-1 and PLK-1 (two mitotic kinases) adopting complimentary localization patterns within the PCM. PLK-1 and TAC-1 were disassembled by dissolution, while ZYG-9, AIR-1, TPXL-1, and perhaps LET92 ruptured and formed packets. Intriguingly, AIR-1 and TPXL-1 appeared to rupture and spread onto microtubules several minutes before SPD-5 and GIP-1 rupture, suggesting that their reorganization might play key roles in the microtubule network reorganization leading to rupture of the remaining PCM proteins.2) New inhibitor studies reveal the timing of phosphatase activity, a role for phosphatases in shaping PCM assembly, and uncouple the regulation of SPD-2 and SPD-5:We wanted to test the model that phosphatase activity is present at the centrosome throughout mitosis and that disassembly is the result of continued phosphatase activity coupled to a decrease in kinase activity . We tested this model by observing the localization of LET-92, which we found to be associated with the centrosome throughout assembly and disassembly. We further tested this model by treating embryos at different times in mitosis with the CDK inhibitor flavopiridol (FP) and the broad-spectrum phosphatase inhibitor okadaic acid (OA). Our previous studies had indicated that FP treatment could force precocious disassembly of g-tubulin. We repeated this experiment in embryos expressing tagRFP::SPD-5; SPD-2::GFP and found that both of these proteins were also precociously disassembled by dissolution in the presence of FP. Notably, this precocious disassembly could be inhibited in the presence of both FP and OA, indicating that CDK activity on PCM assembly is normally opposed by phosphatase activity. Intriguingly, OA treatment alone stabilized the association of SPD-5 with the centrosome, but also forced the precocious removal of SPD-2 at NEBD. This experiment not only suggests that an OA sensitive phosphatase controls SPD-2 maintenance at the centrosome, but also further uncouples the regulation and centrosomal association of SPD-2 and SPD-5: SPD-2 leaves the centrosome without affecting the ability of SPD-5 to remain associated.1) to determine whether the cytoplasmic factors promoting either state had an effect on the other . We found PCM assembly and disassembly to be mutually resistant processes whereby the disassembling centrosome kept disassembling and the assembling centrosome kept assembling upon cell fusion. These results indicate that disassembling PCM is resistant to addition of new PCM by mitotic kinase and that assembling PCM is resistant to disassembly by disassembly competent cytoplasm. Intriguingly, once the old PCM was stripped from the disassembling centrosome, new PCM was precociously added in accordance with the influx of mitotic kinases upon cell fusion. These studies provide in vivo evidence for a change in the nature of the PCM throughout mitosis.3) New cell fusion experiments indicate that the nature of the PCM changes throughout mitosis: PCM disassembly could merely be the exact converse of assembly, i.e. kinases catalyze the addition of PCM and phosphatases catalyze their subtraction. However, we found a role for cortical forces in outer sphere disassembly suggesting that phosphatases are not sufficient to remove total PCM from the centrosome, especially during the disassembly phase. These data as well as recent in vitro data support a model where the nature of the PCM changes throughout mitosis such that assembling and disassembling PCM are different. To test this model, we fused a cell with a disassembling centrosome (ABp) with a cell with an assembling centrosome . With time, kinases are naturally inactivated in the cell cycle allowing phosphatase activity to dominate and remove a subset of inner sphere PCM. However, the nature of the PCM also changes such that the outer sphere PCM becomes resistant to removal by phosphoregulation, requiring mechanical disruption by cortical pulling forces for effective clearance.3) Centrosome protein distribution. One exciting result was the finding that Spd-5 and Spd-2 do not occupy the same space in the centrosome. This could have important implications on how we view C. elegans PCM that might differ from current models. I was, however, surprised by the choice of imaging. The use of Structured Illumination Microscopy to define the regions occupied by centrosome protein is standard practice in the centrosome field. A localization study using SIM would be more appropriate, not simply because it is standard practice, but rather because SIM imaging has played a critical role in shaping current models and hypotheses regarding centrosome function.C. elegans PCM proteins displayed a dramatic difference in organization and behaviors such that we were still able to observe using conventional spinning-disk confocal microscopy. We agree that our conclusions are limited by our choice of imaging technique and have added a statement to this effect in the Discussion (second paragraph).We agree that SIM microscopy and other super-resolution techniques have been instrumental and a standard in the characterization of the organization of PCM proteins. To date, these studies have focused on characterizing PCM organization in cell lines, fixed samples, or isolated centrosomes . Here, we sought to understand PCM organization in a live organism by observing endogenously tagged proteins. Due to the nature of the sample, we were not able to use SIM microscopy or other super-resolution techniques. However, Reviewer #2:[…] This is an informative study that adds mechanistic understanding to the important process of centrosome inactivation via PP2A and cortical pulling forces. However, much of this work appears to largely support the conclusions of Enos et al., 2018 published in Biology Open. Nonetheless, the present work does delineate some differences with respect to the temporal requirement of phosphatases versus forces. Further, the authors describe impaired centriole separation in response to impairing the process of PCM disassembly, thereby adding some physiological significance. However, it is not apparent the present study presents enough of an advance to merit publication in eLife.1) Would the authors please describe in more detail what they measure for their quantification of centrosome intensity? Is the ROI a defined shape/size? Do the authors include proteins that have ruptured and migrated away from the centriole? As written, the Materials and methods simply state the ROI "was selected manually". This merits a little more detail as a major conclusion is that changes in centrosomal intensity precede changes in volume .We have now added additional details on the quantification of centrosomal intensity in the Materials and methods section (subsection “Intensity measurements”). We defined the ‘centrosomal’ region as the centrioles plus the region of the PCM that was physically connected to the centrioles as determined by our thresholding method. This region was manually selected for both the intensity and volume measurements. During the dissolution period, PCM intensity was effectively all of the imageable PCM as holes were not apparent in the PCM until several minutes later. Once rupture had occurred and holes became apparent, we only included the region of the PCM that was contiguous with the centrioles for intensity and volume measurements. The other non-contiguous regions were considered packets once they were clearly individualized from the centrioles and contiguous PCM.Reviewer #3:[…] Before the manuscript can be considered suitable for publication in eLife, the authors need to address the following concerns.1) In all of the figures, the authors show a dissolution of the PCM components SPD-2 and MTZ-1, without the rupture and packets observed for SPD-5 and GIP-1. However, the later time points do show two strong foci for SPD-2 and MTZ-1. Do these represent duplicated centrioles with associated PCM? The authors never described these foci in the text or figure legends and need to more fully describe the images they present for the reader to fully understand these results.The two bright foci are indeed the separating centrioles and newly forming centrosomes. We have indicated these structures in the figures with joined double arrows and have added a reference to them in the text  and figure legends.2) Similarly to the above comment (1), in the graphs showing quantification of packet intensity , centrosomal intensity  and volume at the centrosome , are the authors excluding the bright foci for SPD-2 and MZT-1, or are the included? Because the graphs in some cases show signal levels close to zero, presumably these bright foci are somehow excluded, but the text and figure legends do not refer to this issue. Again, for clarity, the authors should more fully describe the image data in the figure legends and text. The Materials and methods seem to refer to this issue with respect to Figures 5E and 5F, but it is not clear to me exactly how these quantifications were done with respect to the two bright foci detected at later time points.5 for intensity, so the minimum values are on the order of 20,000. Our volume measurements decrease to <1-2 microns3 but are not zero. This measurement would be the expectation for naked centrioles given their dimensions and the diffraction limited approach we used for our quantifications. Compared to the very large size of the mature centrosomes, this small size is even more exaggerated.Please see our response to Comment 1 of reviewer 2. For centrosomal intensity and volume, we manually measured the centrioles and physically contiguous PCM for our quantifications. Please note that our graphs show arbitrary units x 103) In Figure 2, the authors show that SPD-5 and GIP-1 are both found in packets during dis-assembly. However, Figure 2A shows SPD-5 present only in two foci in the "early packets", while there are several SPD-5 foci in early packets in Figure 2B. Thus the co-localization of SPD-5 and GIP-1 appears very limited early on. The authors do not refer to this in the text or legend. How extensive is the overlap between SPD-5 and GIP-1 in packets? Are there some packets with only one or the other, and some with both, and can the authors quantify this overlap? More information as to the exact nature of their co-localization would be helpful.We had accidentally switched SPD-5 and GIP-1 single panel images in Figure 2A, although they were correctly colored in the merge. The proteins do colocalize in early packets, there is just significantly more SPD-5 than GIP-1 in packets. This co-localization is also short lived as later packets lose GIP-1 as well as microtubule association .Quantification of the overlap proved difficult due to the relatively dim nature of packets compared to the surrounding cytoplasm, the ephemeral nature of packets, and the mixture of packets with persistent PCM, thus prompting us to look at microtubules and EBP-2/EB1 to further confirm whether packets retain MTOC potential.4) The authors refer to "rupture" and "packet formation" somewhat interchangeably. In the Figure 3 legend, they define these terms with reference to arrows, but they never refer to specific images that would clarify these terms. The authors should refer to specific images in the figures that show the "holes" in the SPD-5/GIP-1 matrix that constitute rupture, and images that show the appearance of individual packets. While the graphs in Figure 3 indicate rupture occurring at 6 minutes, SPD-5 is clearly fragmented at 5 minutes in Figure 3C, and something like "holes" are apparent at 4 minutes in Figure 3C. I am confused by the use of these two terms that seem to imply distinct phases in dis-assembly but also seem to be simply different stages of the same process. Some clarification of these terms would be helpful.Rupture is a gradual process that begins with the formation of holes in the PCM and ultimately results in packet formation. We see some variation in when rupture occurs and have included images in the figures that represent the mean timing for clarity. We have also included a more thorough description of what we define as rupture in the text . We have also eliminated packet formation as an independent step in the figures for clarity as we consider it as part of rupture.5) When addressing the cortical forces to promote packet formation/dis-assembly in Figure 4, the text refers to rupture starting at 6 minutes post-NEBD and packets forming at 8 minutes in the control/WT embryos . However, the figure only goes to 7 minutes. Moreover, SPD-5 shows distinct puncta at 5 minutes in Figure 1A control, and what seem to be definite packets at 6 minutes. Thus the text description does not seem to be very consistent with what is shown in the figure. This needs clarification.See our response to point 4 above. We have clarified what we mean by rupture in the text and included images in the figures that reflect the mean value for rupture, although there is some variation in the timing of this process. We have eliminated ‘packet formation’ as a discrete step as we see it as part of the process of rupture.6) In the second paragraph of the subsection “Cortical forces mediate the disassembly of the PCM and more specifically SPD-5”, the authors refer to SPD-5 intensity and volume being increased or decreased by either grp-1/2 or csnk-1 depletion. What is being increased and what is being decreased, and in what background. I could not understand this sentence as written, and it seemed to me that in Figure 4 the knockdowns led only to increases.csnk-1 depletion and the increase in SPD-5 intensity following grp-1/2 depletion: “Interestingly, SPD-5 levels at the PCM were increased by gpr-1/2 and decreased by csnk-1 depletion .”We have clarified this admittedly confusing statement to reflect the decrease in SPD-5 intensity following 7) In the second paragraph of the Discussion, the authors state that removal of PCM proteins from the inner sphere weakens the remaining PCM, allow for rupture of the outer sphere. This is stated as if it is a clear conclusion, but what data supports this interpretation/conclusion, or is it a model and speculation?This statement was indeed meant to be speculation. We have reworked our Discussion considerably and have removed this statement.8) The authors cite Enos et al., 2018, as showing the PP2A and cortical forces have been shown to be required for PCM dis-assembly. Thus the two factors that contribute to dis-assembly have already been published. However, Enos et al. examined only SPD-5 and no other PCM components, and did not distinguish between dissolution and dissolution as two distinct processes. They simply refer to PP2A and cortical forces as two independent contributions without assigning them to distinct aspects of dis-assembly. The work by Enos et al., 2018 thus could be viewed as making the results presented here as somewhat incremental and perhaps better suited for publication in a more specialized journal. But Magescas et al. do provide novel findings concerning the layered nature of the PCM in C. elegans and a substantially more in depth analysis of PCM dis-assembly. The authors need to more explicitly address how their analysis goes beyond what was shown by Enos et al., either in the Results or the Discussion. This could be done briefly but it seems to me such a comparison is warranted, given the substantial amount of overlap in the two manuscripts. Similarly, has any evidence for this partial independence of SPD-2 and SPD-5 localization been previously noted?Please see our response to Comment 2 of reviewer 1. We have also modified the Discussion to highlight the differences between our two papers. We are unaware of any other indication in the literature of the partial independence of SPD-2 and SPD-5 and see even more support for this independence in our newly added inhibitor experiments where SPD-2 can be forced from the centrosome with no impact on SPD-5 localization.[Editors' note: the author responses to the re-review follow.]Reviewer #2:[…] 1) Related to the description of spheres and the use of confocal microscopy. An important point in this paper is to define regions of the centrosome occupied by different proteins. The authors describe three regions: the centriole, the inner sphere, and the outer sphere. The description of these regions, along with comparison with other systems in which SIM was used, leaves the reader with the impression that Spd2 (and other proteins) occupies a toroid (donut) area surrounding the centriole with edges of 0.51-1.15, while Spd5 occupies a toroid (donut) with edges of 1.15-1.66. I think that the imaging method and data presented do not support this view. The intensity profiles in Figure 1B suggests that roughly 80-90% of Spd5 is actually found within Spd2 localization area from -1.15 and +1.15. Thus one cannot conclude that the proteins are in distinct locations.C. elegans PCM is organized into an inner and outer sphere”. We have also changed our graph in Figure 1C and our cartoon in Figure 1D to make these points more clear.We did not intend to give the impression that SPD-2 and SPD-5 form interlocking toroids, but rather that both SPD-2 and SPD-5 localize to the inner sphere and that only SPD-5 extends into the outer sphere. With our imaging approach, we cannot resolve whether there is a hole in either localization pattern where the centrioles reside. The only toroids we observed was with AIR-1 and TPXL-1, as has been previously reported. As measured by the distance from center at half maximum intensity, SPD-2 falls in a region between -0.575 – 0.575 ± 0.02 and SPD-5 falls in a region between -0.83 – 0.83 ± 0.03 µm. 77.8 ± 0.8% of SPD-5 is found in the SPD-2 delimited region. These values are now reported in the second paragraph of the subsection “The response by the authors related to the reviewer's comment about why SIM was not used in this study does not acknowledge SIM imaging done in Drosophila embryos  to describe centrosome zones  and many publication form the Raff lab  and even SIM in the worm (PMID: 28103229). I can only conclude that SIM is very much possible and routine. Given that SIM was not performed in this study, the authors' description of these proteins as "distinct localization", “discrete layers”, and "novel protein territories"  are not supported by the data. I recommend the following:- Change the description to 'outer edge of the small spd2 sphere' and 'the outer edge of the larger Spd5 sphere'. That way the author will not misunderstand the localization as toroids.We have changed our description to read:“SPD-2 and SPD-5 localization at the PCM is co-dependent , however these proteins displayed distinct outer localization boundaries within the PCM; both SPD-2 and SPD-5 localized to a more proximal region surrounding the centrioles , and SPD-5 extended more distally to a region lacking SPD-2 . Based on the outer edge of these two matrix proteins, we divide the PCM into an ‘inner’ and ‘outer’ sphere, with the smaller inner sphere defined by the outer edge of SPD-2 localization and the larger outer sphere defined by the outer edge of SPD-5localization ”.- Indicate the outer edge measurements on Figure 1D.We have now reported this measurement . We have also changed our graph in Figure 1C to more clearly depict the outer edges of localization .- Report the% of total Spd5 that overlaps with Spd2 (between -1.15 and 1.15) and that falls outside of the Spd2 sphere (<-1.15 + >1.15) using the area under the curve. This way the reader will get a better impression that there is actually only a small amount of Spd5 that does not overlap with Spd2.C. elegans PCM is organized into an inner and outer sphere” .We now report the percent total in the second paragraph of the subsection “- Soften the comparison between these measurement and previous SIM reports. The data in this study shows no toroid structure other than TPXL-1 and AIR-1; thus the direct comparison to Cnn, for example, is not supported. A comparison to other systems should be reserved for a future SIM study.We have softened our comparison:Drosophila and human cells”.“Although our imaging approach did not allow us to resolve toroidal localization patterns of the majority of the PCM proteins we analyzed, the boundaries of PCM protein localization follows the general pattern of the predicted orthologs in


In Ghana, initiation of Antiretroviral Therapy (ART) is recommended for all patients with an HIV diagnosis, regardless of CD4+ T-cell count. However, measurement of CD4 count remains an important metric for identifying patients with advanced HIV disease, and assessing a person’s overall immune status, which informs the decision to offer opportunistic infection screening and prophylaxis. Access to CD4+ T cell count in rural health facilities remains a major challenge in Ghana and other resource-limited settings. This study aimed to validate the accuracy of the BD FACSPresto near-patient device for measurement of CD4 count and hemoglobin concentration against the FACSCount (CD4) and Sysmex (hemoglobin) diagnostic machines when operated in both a district hospital and rural laboratory, serving a network of health posts in Ashanti Region, Ghana.In the first phase of the study, patients were recruited from a district hospital, and both venous and capillary blood samples were tested using the FACSCount and Sysmex as reference tests and compared to results of the FACSPresto performed in the clinic laboratory at the district hospital. In the second phase, patients were recruited from both the hospital and from rural health clinics, and samples were tested using the FACSPresto at a rural laboratory. Sensitivity and specificity among samples categorized into different clinically relevant CD4 count ranges were calculated, along with correlation between the Presto and the reference measurements, and mean and relative bias with limits of agreement.The FACSPresto was successfully operated in both clinical settings. A total of 59 samples in the first phase and 48 samples in the second phase were included. Positive bias was observed when comparing CD4 count measured by BD FACSPresto to FACSCount in the district hospital  and in the rural laboratory setting . In addition, capillary blood samples were shown to give higher measures when compared to venous blood samples from the same participant. All results were statistically significant (p<0.05) apart from hemoglobin measurement in venous blood in the rural laboratory. Correlation coefficients were high for CD4 count measures and lower for hemoglobin measures.Overall, the Presto gave higher estimates of CD4 count compared to FACSCount, and hemoglobin measurements were higher than from Sysmex. Samples of capillary blood in turn gave higher results for both measurements compared to venous blood, consistent with previous analyses. These findings should be considered when selecting CD4 count machines for use at the point of care, especially in remote areas where capillary blood sampling may be preferable, but are likely balanced by device’s ease of use, portability, and ability to expand access to services. These results are some of the first to demonstrate the accuracy of the FACSPresto in West Africa and show that this device can be successfully operated in a very rural lab setting and may therefore assist to provide CD4 count and hemoglobin concentration measurement to populations in need. Proper clinical management of people living with HIV (PLHIV) requires access to laboratory testing, including CD4 enumeration, liver and renal function tests and viral load (VL) monitoring. Since 2015, the World Health Organization (WHO) has recommended that antiretroviral treatment (ART) be initiated as soon as possible after diagnosis with HIV, regardless of CD4 count. In addiAccess to advanced diagnostic equipment for CD4 and viral load testing can be limited in rural or remote communities, and patients may need to travel long distances for testing. Point-of-care (POC) diagnostic tests, which are those used at or near the patient and outside of a laboratory, can greatly increase access to services when lab capacity is limited. POC testing for HIV infection has been widely adopted, and POC CD4 count testing shows potential for improving disease management in many settings. A 2016 systematic review found that POC CD4 testing is generally acceptable and feasible in low and middle income countries, and overall, prompt CD4 count testing upon diagnosis with HIV has been shown to improve rates of linkage to care, and initiation of ART . TherefoThere are numerous CD4 testing machines on the market, which vary greatly in sample throughput and size, ranging from high-volume devices such as the BD FACSCalibur and FACSCount, to smaller devices such as the CyFlow Mini POC (Sysmex), Pima (Abbott), and CD4NOW (PointCare), which also provides hematology. Wide ranges of bias have been reported across devices, highlighting the importance of using the same technology for longitudinal patient monitoring whenever possible . For theThe BD FACSPresto —referred to here as Presto—is a portable, near-patient device which weighs less than 7 kg and able to be run using battery-power , 13. TheThe Presto has been primarily studied in sub-Saharan Africa , 14–21 aThe aim of this study was to evaluate the accuracy of the Presto in comparison to the BD FACSCount (CD4 Count) and to the Sysmex KX– 21N (hemoglobin concentration) when the Presto was operated in a district hospital and at a rural laboratory in Ghana. To our knowledge, this is the first study of the diagnostic accuracy of Presto in Ghana, one of few in West Africa, and one of few to investigate the feasibility of operating Presto in a limited-resourced, rural laboratory.This diagnostic accuracy study was conducted in two phases in Amansie West, Ashanti Region, Ghana. Phase 1 took place from June to August 2015 at St. Martins District Hospital (DH) in Agroyesum , and phase 2 from February to August 2016, in which the Presto was operated in a small rural laboratory in Tontokrom village. Amansie West is one of Ashanti region’s 27 districts and in 2010, had a population of 134,331, 95.5% of whom live in rural areas, and 74.1% subsist off agriculture . The rurAt the time of this study, Ghana’s National Guidelines (2010) recommended ART initiation for all PLHIV with CD4 counts less than 300, and for all pregnant women after 14 weeks gestation, regardless of CD4 count. At the same time, WHO recommended ART initiation for PLHIV with CD4 counts of 350 cells/μl or below , 26. AshThis was a diagnostic accuracy study, separated into two phases, and distinguished by the location of the Presto device either in the district hospital DH (phase 1) or the rural lab (phase 2). In the first phase, all participants were recruited from the DH clinic, and samples were tested on-site. Results from the Presto were compared to the FACSCount  for CD4 Count, and to the Sysmex KX– 21N  for hemoglobin, which were also operated at the DH. In the second phase, the Presto was operated in the rural laboratory, and results were compared again to the FACSCount and Sysmex, which were still operated at the DH. Participants in phase 2 were recruited from rural clinics, as well as from the DH. Samples from the DH were therefore transported to the rural laboratory for testing on the Presto. Using Presto at the rural laboratory provided insight into the feasibility of using near-patient CD4 counters in low-resource areas, as compared to the larger and better equipped laboratory at the DH. The Presto test results were never used for patient care in either phase, and all clinical decisions were made based on results from venous blood samples tested on the reference machines.Training in the operation of the device, sample collection and basic trouble-shooting, was provided to all participating phlebotomists and technologists by the manufacturer through a one-day training course. During the study, each sample was run on a total of 3 devices: the experimental Presto (for CD4 and hemoglobin), the FACSCount as control for CD4, and the Sysmex as control for Hgb concentration. In phase 1, a capillary blood sample (applied using a lancet to the test cartridge) and a 5 ml aliquot of venous blood from each patient were tested using Presto and the reference machines at the DH HIV clinic. Samples were run on the Presto machine within 30 minutes. All control hemoglobin analyses were performed on the Sysmex on the same day, within a few hours of collection, but control CD4 count analyses were sometimes performed in batches, meaning some samples were stored overnight according to manufacturer’s recommendations and tested the day after collection on the FACSCount.In phase 2, venous blood was collected at the DH and kept in cold chain at ~8°C, before being transported to the rural laboratory in test tubes by motorbike for testing by Presto the same day. The laboratory is approximately one hour away by motorbike and all samples were tested within 4–5 hours. A second aliquot of blood was tested at the DH on the reference devices (FACSCount and Sysmex). Venous and capillary blood were also both collected from patients at the rural lab, and an aliquot of venous blood was separated into a separate tube and transported by motorbike to the DH laboratory for testing using the control devices; capillary blood was never transported.Adults (≥ 18 years old) from two groups were invited to participate: one group of patients at the DH who came for HIV management and required a CD4 test, and a second group of people from one of the community-level health clinics surrounding rural lab and also required a test. Since chronic HIV care was not yet offered at the majority of community-level clinics (only two out of ten nearby clinics offer ART), only ten participants were recruited from the lower-tier health care facilities. Only participants 18 years or older who gave written consent were included. Subjects included pregnant women but excluded children under 18.The aim was to collect samples from 100 participants (50 in each phase), but all eligible patients were invited to enroll during the designated study period; 65 patients were recruited to phase 1 and 53 to phase 2. This was a convenience sample and all participants were enrolled consecutively. The sample size was limited by time constraints of the study, and based on normal volume at the district hospital. In phase 2, most participants were recruited from the district hospital, with only ten eligible patients identified and included from the rural health posts; due to low attendance for HIV care at rural clinics at the time. The Clinical and Laboratory Standards Institute (CLSI) recommends at least 40 samples of appropriate range  when conducting accuracy studies ; similarEligible participants were informed about the purpose, benefits, and risks of the study, and could ask questions. They gave written consent by circling “Yes” or “No”. When patients were illiterate, the consent form (available in English and Twi) was read aloud. Ethical approval was received from the Institutional Review Board (IRB) at Columbia University (IRB-AAAM4706) and the Ghana Health Service Ethical Review Committee (GHSERC) for both phase 1 and phase 2. Approval from the Ghana Food and Drug Authority (FDA) was obtained for using Presto in Ghana.Descriptive statistics and measures of association between Presto and the reference methods were calculated using Microsoft Excel, GraphPad Prism, and SAS version 3.5. Two sample T-tests were used to compare mean age of male and female participants, and Wilcoxon Rank Sum tests were used to compare CD4 count between males and females. Three different clinically-relevant cutoff thresholds of CD4+ T Cell count were used: 100 to define the cut-off for use of recommended screening tests for opportunistic infections (OIs)  in patients with advanced HIV disease; and 350 and 500 cells/μl to reflect past ART initiation recommendations. Rates of upward, downward, and total misclassification, along with sensitivity and specificity for specific cutoffs were calculated to compare performance of the Presto to that of the FACSCount or Sysmex. Wilcoxon Signed Rank tests and Spearman correlation were then used to compare results between methods, using a significance level of 0.05. Bland Altman plots were produced to visualize bias and limits of agreement (LOA) when comparing Presto to FACSCount. Only data from samples which have pair-wise results available was included.65 patients consented to participate in phase 1, and paired results (Presto and control) from 59 venous samples and 57 capillary blood samples were obtained . In phasThe majority (87.3%) of phase 1 study participants were female, with an average age of 40.3 years, of whom 4 were pregnant . Men werMean and median CD4 T cell counts for both venous and capillary blood were compared between Presto and FACSCount, at the DH and rural lab. When Presto was operated in the DH (phase 1), higher estimates of both CD4 count and Hgb in venous blood (p<0.001) as well as in capillary blood (p<0.05) were observed. Bland Altman plots were produced to visualize absolute mean bias in CD4 count for samples tested by Presto compared to FACSCount. Bias was 44  for venous blood, and 74  for capillary blood . The PreIn the rural laboratory setting, the Presto overestimated CD4 counts in both sample types . HemogloSpearman’s correlation coefficients demonstrated good correlation for CD4 count .When comparing results from venous blood to capillary blood in the DH setting, capillary blood samples gave significantly higher results for both CD4 count and Hgb concentration (Wilcoxon Signed Rank test p = 0.0017 and <0.0001 respectively). Due to a small number of capillary blood samples (n = 10) in the rural laboratory setting, this analysis was restricted to phase 1 data. While capillary blood gave higher CD4 counts overall, Spearman correlation coefficients revealed that CD4 count from capillary and venous blood were highly correlated , and correlation between hemoglobin results from capillary and venous blood was lower but still significant .Lastly, rates of misclassification, sensitivity and specificity were analyzed across 3 different CD4 count thresholds. There was one instance of downward misclassification, when the Presto classified a sample of venous blood in the rural laboratory as under 350 cells/μl CD4 count, whereas the FACSCount had classified it as above; all other misclassification was upward . Accordi3, enhanced antimicrobial prophylaxis was associated with reduced rates of death and a large proportion (47%) of patients were either asymptomatic or mildly symptomatic at baseline [Advanced HIV disease is defined by the WHO as having a CD4 count of below 200 cells/μL, or a disease stage of 3 or 4. Despite advancements in access to ART treatment, 30–40% of PLHIV globally have advanced HIV disease when starting or re-initiating ART , 30. It baseline .Demonstration of device-specific performance can inform the selection of diagnostic technologies for different settings . We evalThe Presto presents several major advantages, including speed , throughput (up to 60 samples in 8 hours), and portability (less than 7 kg and able to be run using battery-power) , 13. On Like many other West African countries, Ghana has a relatively low HIV burden with an estimated HIV prevalence of 1.6% among adults aged 15 to 49 in 2016, compared to 7% prevalence in Eastern and Southern Africa –34. ContThere are several limitations to this study design. Firstly, the sample size is small, with less than 60 patients in each phase. At the time of this study (2015–2016), it was uncommon for HIV patients to seek care at low-level health facilities in Ghana, and only 13 patients were recruited from rural clinics. This resulted in only ten capillary blood samples for this phase of the study, and these were excluded from some analyses due to the small sample size. Overall, CD4 counts were relatively high, so it may not be appropriate to extrapolate these results to patients with low CD4 count.The technician operating the FACSCount machine at the district hospital (for both phases of the study) was different from the technician operating the Presto. While neither machine requires advanced technical skill, and the same training was provided to all technicians, operator-related differences are possible. Additionally, there are several unknown factors affecting the second phase of the study . The exact conditions of storage and transport were not systematically documented, and it is possible that the samples were exposed to different temperatures and wait times, potentially impacting the accuracy of the Presto in phase 2. However, as lab testing in resource limited settings often relies on sample transportation to more centralized sites, this scenario may reflect real-world operation of near-patient CD4 testing devices.Lastly, this study used BD FACSCount as the reference standard, while BD FACSCalibur is normally considered the gold standard among these devices. . HoweverReliable CD4 count testing is needed in health facilities to monitor the immune status of PLHIV, even as access to VL monitoring expands. This study found that the Presto overestimates CD4 count in comparison to FACSCount, which is consistent with other studies comparing Presto to FACSCount or FACSCalibur –21, 23, S1 TableThis table includes the study ID numbers for all samples analyzed, and the CD4 count and hemoglobin results from BD Presto, BD FACSCount (CD4 Count) and the Sysmex KX– 21N.(XLSX)Click here for additional data file.


Sprouting angiogenesis is a necessary process in regeneration and development as well as in tumorigenesis. VEGF-A is the main pro-angiogenic chemoattractant and it can bind to the decoy receptor VEGFR1 or to VEGFR2 to induce sprouting. Active sprout cells express Dll4, which binds to Notch1 on neighboring cells, in turn inhibiting VEGFR2 expression. It is known that the balance between VEGFR2 and VEGFR1 determines tip selection and network architecture, however the quantitative interrelationship of the receptors and their interrelated balances, also with relation to Dll4-Notch1 signaling, remains yet largely unknown. Here, we present an agent-based computer model of sprouting angiogenesis, integrating VEGFR1 and VEGFR2 in a detailed model of cellular signaling. Our model reproduces experimental data on VEGFR1 knockout. We show that soluble VEGFR1 improves the efficiency of angiogenesis by directing sprouts away from existing cells over a wide range of parameters. Our analysis unravels the relevance of the stability of the active notch intracellular domain as a dominating hub in this regulatory network. Our analysis quantitatively dissects the regulatory interactions in sprouting angiogenesis. Because we use a detailed model of intracellular signaling, the results of our analysis are directly linked to biological entities. We provide our computational model and simulation engine for integration in complementary modeling approaches. Angiogenesis is a pivotal process in various aspects of vertebrate life. In development Breier,  as well In sprouting angiogenesis, quiescent endothelial cells (ECs) in an existing vessel adopt a motile tip cell phenotype, release matrix metalloproteases (MMPs) to degrade the extracellular matrix (ECM) around the vessel, and lead a sprout followed by proliferative stalk cells  which in turn represses VEGFR2 expression (and subsequently tip cell markers and dll4 expression) through regulation of transcription factors HES2 and HEY2  binds VEGF-A with a higher affinity than VEGFR2, however leads to negligible activation of downstream targets . Basic functions for diffusion, degradation, and adding molecules are implemented in a base class Localvar. These functions can be used to implement derived classes of local variables that exhibit custom dynamics. AngioABM uses forward integration to compute local variables' temporal and spatial evolution. The simulator assumes Dirichlet boundary conditions.Agents represent cells. Basic functions for agent movement and interaction with the environment are implemented in a base class Agent. Derived classes representing specific cells can use these functions, lists of internal variables and parameters and can additionally use custom rules or formulas to define cell dynamics. Agents are updated asynchronously in random order. Hence, changes in one agents' state can influence another agents' dynamics immediately. This reduces numerical errors arising from the discrete time intervals between agents' information exchange and induces stochasticity into the simulation. To reduce errors in integration, especially in the computation of local variables, numerical stability is checked and internal steps are fine grained accordingly. Agents' parameters can be specified to refer to a fixed value for all agents or to be sampled from a random distribution for each agent. Drawing agents' parameters from random distributions induces cellular heterogeneity.VEGF-A, sVEGFR1, and sVEGFR1b (sVEGFR1 bound to VEGF-A) and agents representing endothelial cells (ECs). VEGF-A, sVEGFR1, and sVEGFR1b diffuse, are degraded and can associate and dissociate.The model described here consists of the local variables VEGF-A influx to each grid cell that depends on the difference between a global reference value  and the local value. The reference value is maintained constant as the culture medium in experiments was renewed every 48 h  releases the active Notch1 intracellular domain NICD. NICD induces transcription via different downstream factors (Hey2/Hes2). We omit intermediate steps, so NICD directly activates transcription of notch1_mRNA and VEGFR1_mRNA while repressing expression of VEGFR2_mRNA. We model transcription rates vtranscription by using Hill-Equations  and soluble VEGFR1 (sVEGFR1). mVEGFR1 and sVEGFR1 both bind to extracellular VEGF-A, mVEGFR1 directly, sVEGFR1 only after export. Binding to VEGF-A leads to inactive complexes that can diffuse, degrade, or dissociate. VEGFR2 binding to VEGF-A is converted to VEGFR2bound in the model. After dissociation of VEGF-A, VEGFR2 is converted to VEGFR2a, also representing the activity of the downstream signaling cascade. Both VEGFR2bound and VEGFR2a enhance transcription of dll4_mRNA . We describe transcription and translation as individual processes for each protein, which also generates time delays.All other reactions  follow standard Mass-Action kinetics. VEGFR1 is regarded in two isoforms, membrane-bound VEGFR1  from published experimental results  and the NICD degradation rate (k_nicd_degradation) we modified not only mean values, but also the deviations of the log-normal distributions from which they are sampled. Parameters related to entity specific characteristics  are not sampled since we assume that the general state of cells is more variable than the entity specific characteristics.For initial values and parameters related to the general condition of a cell . This analysis depends on the parameterization chosen and the effects of changes in two (or more) parameters can not be predicted from combining the effects of two individual parameter changes.We analyzed the sensitivity of the simulation results with regard to changes in parameters. We used the percentage of the area occupied by ECs . Branch points/mm are also comparable to experimental data . VEGFR1-/- strain, comparable to the experimental results shown in Kappas et al. Kappas et al.  for transcription.To analyze the contribution of the different VEGF-A receptors to sprouting, we evaluated the sensitivity of Vmax of transcription for VEGFR2, we observe that too little VEGFR2 transcription renders cells insensitive to VEGF-A while too much VEGFR2 leads to a hyperactivation of Dll4 and thus too high NICD levels that suppress sprouting. This is true for both VEGFR2 transcription (VEGFR2_mRNA>VEGFR1_mRNA) and a reduction in available VEGF-A through binding of VEGF-A to VEGFR1 isoforms. For a complete knockout of VEGFR1, the Concerning cription  as well cription . As showbranch points/mm exhibits similar trends as the sensitivity of the relative vessel area  reduces sprouting and (2) directs sprouts to grow orthogonal to existing structures. The second effect leads to a faster vascularization of an avascular area under homogeneous VEGF-A conditions. We observe this impact of VEGFR1 under a wide range of parameters. Our results are consistent with previous findings on the interaction of VEGF and sVEGFR1 in a static environment  to generate a parameterization that is within sensible boundaries based on literature data.Finding the appropriate balance of model detail or resolution is a fundamental challenge in modeling. Any increase in model complexity increases the amount of experimental data necessary to find a reliable parameterization. Here, we have not included all molecules involved in VEGF signaling in sprouting angiogenesis (see e.g., Ferrara et al., This parameterization is not guaranteed to be equal to the physiological parameterization. Because we have restricted parameter boundaries based on experimental data and our data reproduces findings reported in literature (Hashambhoy et al., VEGFR1-/- mutants in in-vitro cultures of mouse embryonic bodies. These defects can be restored by additional expression of sVEGFR1 (Roberts et al., Kearney et al.  have shoThe analysis of our model indicates that VEGFR1 suppresses sprouting by reducing the global VEGF-A concentration with increasing cell density (compare the upper and lower row of simulation results in Diffusion properties and morphogen gradients are notoriously difficult to quantify in tissues experimentally (Bothma et al., in-silico cells sense any difference in external VEGF concentrations, unlike in-vitro or in-vivo situations, where cells sense the VEGF-A gradient by differential binding of VEGF-A to receptors on their filopodia.Also, our analysis indicates that only the complete removal of VEGFR1 transcription abolishes the spatial cues provided by sVEGFR1 . This isIn contrast to the gradual changes in simulation output caused by changes in VEGFR1 or VEGFR2 production rates, changes in parameters involved in Delta-Notch1 signaling cause stronger and more abrupt changes over certain parameter value ranges , 5. ThisIn the model we present, the base state of a cell is a quiescent stalk-cell like state, and the basic activity of lateral inhibition is relatively high. For sprouting, cells have to overcome this basal lateral inhibition. Cellular heterogeneity through sampled parameters is an important driver of the differentiation of individual cells in our model. Although the sampling is random, a specific cell can be primed for sprouting by the sampled parameter values. Neighboring cells might be assigned parameter values that make them less likely to sprout and the difference between these cells is then further amplified through lateral inhibition. The most important parameter to generate heterogeneity for sprouting is the degradation rate of NICD. Even small stochasticity in NICD degradation increases cellular heterogeneity in the lateral inhibition pathway and significantly improves sprouting efficiency. Because the stability of NICD does not directly affect sprouting but the heterogeneity between neighboring cells, larger stochasticity in NICD degradation does not lead to a breakdown of the system, as observed when sampling transcription or translation parameters from wide distributions . The impBeyond this specific finding, our analysis on the role of parameter distributions in computational models of multicellular ensembles also has a general relevance. Assuming a fixed value for NICD degradation for all cells and varying this value showed only a narrow band of parameter values that lead to efficient sprouting . SamplinThe agent based model we present here omits cell shape dynamics and ensures vessel connectivity by dividing stalk cells upon tip movement. This neglects cell shape changes and their effect on network formation (Boas and Merks, The complete model code can be downloaded and reused and we hope that further development of the model by us and other groups will help to further understand the dynamics of sprouting angiogenesis. Future development of the model could focus on the interactions between chemical and mechanical signals or in the cross-talk between different signaling pathways.In order to generate reliable and clinically relevant predictions of angiogenesis to improve regeneration, enable fine-tuned tissue engineering or ablate tumor-dependent angiogenesis, we need to integrate various mechanisms in a dynamic environment. Moreover, these models need to be parameterized based on dedicated experimental data. By providing our model in an open and reproducible manner, we enable its integration into models that consider cell shape dynamics, interactions with the ECM, or network formation in 3D.We present an agent based computer model of sprouting angiogenesis focusing on intracellular signaling and its effects on pattern formation. Specifically, we focus on the role of VEGFR1 and its interrelation with VEGFR2 and Delta-Notch signaling. Our findings do not replace published modeling efforts but are complementary because our focus differs from existing literature. Our simulations go beyond comparable models concerning level of detail of intracellular signaling, cell numbers considered, and simulation time.Our results support the hypothesis that soluble VEGFR1 provides spatial cues to guide sprouts away from their origin and it predicts that this effect is robust over a wide range of parameters. Our model analysis shows that lateral inhibition, and especially the regulation of NICD stability and its variability across cells, is critical for the regulation of sprouting angiogenesis.This leads us to argue that complementary modeling approaches need to combined and supplemented with dedicated experimental data to generate reliable predictions, to generate models that do not only reproduce training data but are also capable of predicting validation data correctly and function over a wide range of conditions. The advantage of incorporating dedicated signaling models into cell-based models of angiogenesis is that these models provide direct links between experimental perturbations and model dynamics.https://gitlab.com/ModularABM/AngioABM/tree/VEGFR1 and https://gitlab.com/ModularABM/ABMTools/tree/VEGFR1. The model of intracellular dynamics has been submitted in SBML format to the biomodels repository (Chelliah et al., Source Code for the simulator and analysis can be found at CK and SC designed the study, wrote and revised the manuscript, read the manuscript, and approved its content. CK implemented simulator and analysis software, constructed and parameterized models, and analyzed simulation results.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.