Brain-derived neurotrophic factor (BDNF) is a critical growth factor involved in the maturation of the CNS, including neuronal morphology and synapse refinement. Herein, we demonstrate astrocytes express high levels of BDNF’s receptor, TrkB (in the top 20 of protein-coding transcripts), with nearly exclusive expression of the truncated isoform, TrkB.T1, which peaks in expression during astrocyte morphological maturation. Using a novel culture paradigm, we show that astrocyte morphological complexity is increased in the presence of BDNF and is dependent upon BDNF/TrkB.T1 signaling. Deletion of TrkB.T1, globally and astrocyte-specifically, in mice revealed morphologically immature astrocytes with significantly reduced volume, as well as dysregulated expression of perisynaptic genes associated with mature astrocyte function. Indicating a role for functional astrocyte maturation via BDNF/TrkB.T1 signaling, TrkB.T1 KO astrocytes do not support normal excitatory synaptogenesis or function. These data suggest a significant role for BDNF/TrkB.T1 signaling in astrocyte morphological maturation, a critical process for CNS development. While t4 (Aqp4) , glutama4 (Aqp4) , and con4 (Aqp4) .Brain-derived neurotrophic factor (BDNF) is a critical growth factor in the development, maturation, and maintenance of the CNS. Its role in neuronal cell growth, differentiation, morphology, and synaptogenesis via TrkB receptor signaling is well characterized . In the Ntrk2, the gene that encodes BDNF’s receptor is highly enriched in astrocytes during the critical period of astrocyte morphological maturation. RNA sequencing and qPCR reveal that in vivo astrocytes predominately express the truncated TrkB (TrkB.T1) receptor. TrkB.T1 receptor expression mediates increased astrocyte morphological complexity in response to BDNF in vitro, and TrkB.T1 KO astrocytes in vivo remain morphologically immature with significantly reduced cell volumes and morphological complexity. TrkB.T1 KO astrocytes exhibit dysregulation of genes associates with perisynaptic mature astrocyte function. Importantly, astrocyte-specific conditional knockout of TrkB.T1 also results in decreased morphological complexity. Finally, co-culture studies indicate TrkB.T1 KO astrocytes do not support normal synaptic development or function. Together, these data suggest a significant role for BDNF/TrkB.T1 signaling in astrocyte morphogenesis and indicate this signaling may contribute to astrocyte regulation of neuronal synapse development.Here for the first time we demonstrate that Ntrk2, the gene encoding BDNF’s high affinity receptor TrkB, to be in the top 20 of all protein coding RNA’s (#18) detected. The two TrkB isoforms are distinguishable given that the full-length receptor contains exons for the tyrosine kinase domain, while the truncated TrkB.T1 receptor lacks this domain but has an additional exon (exon 12) not found in the full length receptor   mice via magnetic separation (n = 5 replicates) . Postnatreceptor . Therefo1025074) .Ntrk2 mRNA expression in astrocytes relative to other CNS cell populations. Sequential isolation of oligodendrocytes, microglia, astrocytes, and neurons was performed as we have previously described =13.39, p<0.0001; To examine astrocyte morphological complexity in vitro, we utilized the Shape Index (SI); this equation, given as perimeterGiven the high levels of astrocytic TrkB expression during a period of astrocyte morphological maturation we next evaluated a role for BDNF on astrocyte morphology. Astrocytes were isolated and cultured as described above, and experiments performed after 14 DIV. Wildtype (WT) astrocytes were exposed to 10 ng, 30 ng, or 100 ng BDNF for 24 hr, followed by paraformaldehyde fixation. These concentrations were chosen based upon their previous use in investigating BDNF’s effects on neurons  and astrWe next performed two loss of function experiments to ascertain the specificity of BDNF/TrkB.T1 effects on astrocytes. Current pharmacological TrkB receptor antagonists do not specifically target the truncated TrkB.T1 receptor. Therefore, we utilized TrkB-Fc to scavenge BDNF from the culture media. TrkB-Fc mimics the binding site of TrkB, allowing it to bind to BDNF and prevent BDNF binding to endogenously expressed TrkB receptors . WT 14DITo determine the necessity of TrkB.T1 receptor signaling in astrocytes we utilized a TrkB.T1 KO mouse model . We firsThe experiments above established that BDNF signaling through the TrkB.T1 receptor induces an increase in astrocyte morphological complexity in a simplified model system. We set out to examine astrocyte morphogenesis as an indicator of astrocyte developmental maturation in TrkB.T1 KO mice. Astrocyte morphology was examined in WT and TrkB.T1 knockout male animals at PND 14, PND 28, and PND 50. Here the early time point represents a period in astrocyte development when astrocytes are considered morphologically immature . IntraceWe next assessed cortical thickness and astrocyte number in male TrkB.T1 KO and wildtype littermate PND 28 mice . Due to Kcnj10  = 2.943; p=0.04) and Aq4  = 2.807; p=0.04), with trending decrease in Slc1a2  = 2.242; p=0.056) relative to WT littermate controls  = 0.5491, p=0.612) across the two genotypes, in line with previous studies indicating stable expression after p15 in rodents  cultured astrocytes are removed from other cellular influence (i.e. endogenous BDNF expression) and 2) the utilization of a global TrkB.T1 mouse model whereby loss of the receptor is found in all cells. In order to query if—in otherwise normal environments—the loss of TrkB.T1 signaling specifically in astrocytes changes astrocytic morphology, we performed three experiments. First, astrocyte complexity was assessed in WT and .T1 KO astrocytes co-cultured with WT neurons. To this end, we developed a novel neuron-astrocyte co-culture model system. This system allows us to specifically and directly evaluate the interplay between astrocytes and neurons. Wildtype cortical neurons were cultured from p0/1 pups. After 3–5 days of recovery, astrocytes from p3-5 WT or TrkB.T1 KO animals were isolated via MACS and subsequently layered on top of the neurons. After 12-14DIV, cells were paraformaldehyde fixed and confocal images of astrocytes acquired. A combination of Glast and Gfap was used to visualize total (Glast) and branch complexity (Gfap) in the cultured astrocytes . Sholl afl/fl) (+ astrocytes (t(21) = 2.407; p=0.0254; + control astrocytes revealed no significant difference in astrocyte complexity in the same WT and .T1fl/fl animals (t(23) = 0.7276; p=0.4742; The above experiment suggests that TrkB.T1 expression in astrocytes is necessary for proper astrocyte complexity in a simplified system. We next examined astrocyte morphological complexity in a TrkB.T1 floxed mouse line (.T1fl/fl)  utilizinfl/fl) . We agai+ or Cre-. All animals were intraperitoneally injected with 20 µl (0.2 mg) 4-OH tamoxifen (TAM) once daily  = 1.919; p=0.01), Kcnj10  = 2.525; p=0.035), and Aq4  = 5.944; p=0.004) compared to cWT littermates. Similar to the global TrkB.T1 KO animals, no change was found in Gja1 expression  = 0.3699; p=0.7211) compared to cWT littermates. Thus, our data combined demonstrate that loss of the TrkB.T1 receptor in astrocytes, in an otherwise normal environment, results in reduced astrocyte morphogenesis and aberrant gene expression.In a subset of cKO animals we also examined the same array of perisynaptically located astrocytic genes as above. To this end RNA was collected from the cortex of PFA fixed slices of PND25-28 animals and qPCR performed. QPCR analysis revealed significantly reduced expression of the same genes found in the global TrkB.T1 KO mice. Specifically, cKO animals exhibited decreased expression of The period of astrocyte morphological maturation overlaps with neuronal synaptogenesis, and a large body of work has characterized astrocytic contributions to this process. In order to query if BDNF/TrkB.T1 signaling onto astrocytes contributes to neuronal synapse development, we returned to our neuron/astrocyte co-culture system. Wildtype cortical neurons were again cultured from p0/1 mouse pups and allowed 3–5 days to recover, with subsequent plating of WT or .T1 KO astrocytes on top. After 8-12DIV, cells were paraformaldehyde fixed and confocal images of excitatory (VGlut1+/PSD95+) synapses acquired . ExcitatHerein we have demonstrated for the first time that BDNF is involved in the maturation of a non-neuronal cell type. Within cortical astrocytes, TrkB.T1 receptor expression is in the top 20 of all protein-coding transcripts, with the highest expression during astrocyte morphological refinement. We developed and utilized a novel astrocyte culture paradigm to demonstrate that BDNF induces an increase in astrocyte morphological complexity, which is dependent upon the TrkB.T1 receptor. Importantly, in vivo astrocyte morphology is less complex with loss of the TrkB.T1 receptor in both global and astrocyte-specific murine models. In particular, the lack of TrkB.T1 prevented normal morphogenesis during the time of astrocyte morphological refinement, between PND 14 and PND 28 and in fact persisted into adulthood (PND 50), indicating BDNF/TrkB.T1 signaling contributes to astrocyte morphological maturation. Additionally, loss of the TrkB.T1 receptor in astrocytes resulted in aberrant expression of genes associated with mature astrocyte functions that are known to be developmentally regulated. Furthermore, BDNF signaling onto astrocytes appears to have consequences on neuronal synapse development, with decreased numbers and aberrant function of excitatory synapses in neurons co-cultured with TrkB.T1 KO astrocytes. These findings have broad implications, given the wealth of neurological disorders within which BDNF and, increasingly more often, astrocytes are implicated.Ntrk2 over other CNS cellular populations. Others have demonstrated that astrocytes express TrkB.T1 , did not change in expression. Interestingly, although Cx43 is associated with mature astrocyte function, previous work demonstrates mRNA expression stabilizes after PND 15 in rodents  are dramatically increased in complexity during the morphological refinement phase, and facilitate many known astrocyte biological functions. We therefore examined expression of known PAP-targeted genes associated with mature astrocyte function. TrkB.T1 KO astrocytes demonstrated decreased mRNA expression of Kir4.1, Glt1, and Aq4 in juvenile (PND 28) mice. Noteworthy, these genes are known to be developmentally regulated . Another rodents . ImportaAstrocytes actively contribute to synaptogenesis through release of astrocyte derived factors such as hevin , thromboWe demonstrated that scavenging BDNF from the media within an hour of exposure prevented the increase in cellular complexity 24 hr later, suggesting that BDNF must be actively present to elicit an increase in astrocyte morphological complexity. This experiment is particularly interesting given that following synaptogenesis, BDNF secretion from neurons is largely targeted to synaptic zones and is secreted in an activity-dependent manner . While oHere we demonstrate BDNF’s receptor, TrkB.T1, is highly enriched in cortical astrocytes, particularly during the period of astrocyte morphological maturation, and that BDNF/TrkB.T1 signaling in astrocytes plays a critical role in astrocyte morphogenesis and may play a role in proper astrocyte maturation. Furthermore, proper neuronal synaptogenesis was lost with deletion of the TrkB.T1 receptor in astrocytes. Our studies suggest that BDNF/TrkB.T1 signaling is a novel unexplored pathway in the role of astrocytes in synapse development. Given the role of aberrant synapse development in neurological dysfunction, our results herein suggest astrocyte BDNF/TrkB.T1 signaling may contribute to neurodevelopmental disorders in which BDNF signaling is implicated.ad libitum. Every effort was made to minimize pain and discomfort. Wild-type and -/-TrkB.T1 and wild-type littermate  with food and water available ttermate  C57/B6 mfl/fl Cre+ males to homozygous. T1fl/fl females such that all offspring were homozygous floxed, and either Cre+ or Cre-. Each experimental animal was injected to with 4-OH tamoxifen prior to knowing genotype. Tamoxifen was made to stock concentration of 20 mg/ml in 1:19 ethanol:canola oil via sonication for 60 min at 50°C. Injections were administered intraperitoneally at 20 µL between PND 8–11.Astrocyte-specific conditional knockout mice were generated by crossing Aldh1l1-cre/ERT2 (Jackson Labs #029655) to TrkB.T1 floxed mice. Experimental animals were generated by crossing homozygous. T12 and decapitated. Whole cortex was microdissected in ice-cold ACSF  bubbled with 95% oxygen. Tissue was minced into 1 mm3 pieces and dissociated for 15–30 min using Worthington Papain Dissociation Kit. Tissue was subsequently triturated until a single-cell suspension was achieved and filtered through a 70 µM filter.Briefly, mice , late juvenile mice (PND 28 + /- 3 days (PND 28) or adult mice (PND 60+ /- 10 days (PND 60) were anesthetized via CO+ MicroBeads. The suspension was then applied to a prepped LS column, washed three times, and the flow-through collected. This flow through was subsequently used to isolate astrocytes utilizing Miltenyi Biotec’s ACSA-2+ MicroBead kit. The cell suspension (in 150 µL 0.5% fatty-acid free BSA in PBS) was incubated at 4°C for 15 min with 15–20 µL FcR blocker, followed by a 15 min incubation with 15–20 µL ACSA-2 microbeads. Cells were applied to a prepped LS column. Astrocytes were eluted from the LS column after three washes, with 5 mL buffer and the supplied plunger.Astrocytes were acutely isolated as previously described . FollowiCells were acutely isolated as previously described . FollowiTotal RNA was isolated using Ambion’s PureLink RNA Mini Isolation kit according to the manufacturer’s instructions. RNA samples designated for RNA Sequencing were eluted in 30 µL filtered, autoclaved Mill-Q water. Subsequently, 2 ng of RNA was reverse transcribed into cDNA using BioRad’s iScript kit or BioRad’s iScript SuperMix. All cDNA was normalized to 350 or 500 ng (for BDNF mRNA assays) following conversion. The relative mRNA expression levels were determined using real-time quantitative PCR by General Taqman PCR master mix and TaqMan specific probes. Relative mRNA expression levels were determined by the ddCt method, with each normalization indicated where appropriate.RNA samples were tested for quality on the Agilent Tapestation 2200 . The NEB Next rRNA Depletion Kit (NEB #E6310X) was used to process 250 ng of total RNA. RNA-Seq libraries (400 bp) were created using the NEBNext Ultra II Directional RNA Library Prep Kit for Illumina (NEB #E7760L). Samples were individually indexed using the NEBNext Multiplex Oligos for Illumina (NEB #E6609S). Adapter ligated DNA was amplified in 13 cycles of PCR enrichment. Libraries were quantified with the Quanti-iT dsDNA HS Kit (Invitrogen) and qPCR. Library validation was performed on the Agilent 2200 Tapestation. Independently indexed stranded cDNA libraries were pooled and sequenced for 150 cycles with the Illumina NovaSeq 6000 S2 Kit. All samples were sequenced at 85–90 million read depth, paired-end 2 × 150 bp, and in reverse-stranded orientation.Ntrk2 transcript expression levels (FPKM) were extracted from the second Stringtie run’s Assembled Transcripts output files per respective biological replicate. All detailed scripts used for these analyses are available upon request.Initial analyses  were run in the University of Alabama at Birmingham’s Cheaha High Performance Computing (HPC) cluster environment. Raw RNA-Seq reads were concatenated  and quality trimmed using Trim Galore! Version 0.4.3. Sequence quality of trimmed reads was inspected using FastQC (version 0.11.15). The STAR aligner (version 2.5.2)  was usedg. ThermoScientific’s Peirce BCA assay was utilized to determine protein concentrations. Proteins were heated to 60°C for 15 min with 2x loading buffer , and 20% glycerol). Equal amounts of protein per sample (5 or 10 ug) was loaded into a 4–20% gradient precast mini-PROTEAN TGX gel (Bio-Rad) and proteins were separated with 200V in 1x running buffer . Proteins were transferred to a nitrocellulose membrane using the Trans-blot turbo system (Bio-Rad), mixed molecular weight protocol , followed by 1 hr blocking with LI-COR blocking buffer at a 1:1 ratio with TBS. Primary antibodies, including concentration and incubation times, are given in the Key Resources Table. All secondary antibodies were LI-COR, and incubated at 1:10,000 for 1 hr at room temperature. Imaging was performed on a LI-COR Odyssey machine on both the 680 and 800 channels.Proteins were extracted by homogenizing samples in lysis buffer (1% sodium dodecyl solfate (SDS), 100 mM Tris(hydroxymethyl)aminomethane (Tris) buffer, pH 7.5), supplemented with protease and phosphatase inhibitors (Sigma), followed by two rounds of sonication for seven seconds. Lysates were subsequently centrifuged for 5 min at 16,000 x5 cells were plated on 13 mm glass coverslips in a 24-well plate. The coverslips were poly-l-ornithine treated and laminin-coated. Astrocytes were maintained in serum-free, defined media . On the first day post-plating, fresh media was added. On the third day post-plating, a complete media change was performed. Subsequent media changes occurred every 3–4 days. Astrocytes were collected at 7 and 14 days in vitro (DIV).Astrocytes were isolated from postnatal day 3–6 pups as described above and previously . FollowiPrimary astrocyte cultures were utilized at 14 DIV for experiments. Exogenous BDNF (Promega) was applied in warmed media to a final concentration of 0 ng, 10 ng, 30 ng, or 100 ng for 24 hr. For scavenger experiments, a final concentration of 2 ug of TrkB-Fc (R and D Systems) was added to the wells in warmed media 60 min post-BDNF exposure. Equal volumes of warmed media as the TrkB-Fc condition was additionally added to controls.Astrocytes were fixed at 15 DIV, after experiments described above. First, pre-warmed paraformaldehyde (PFA) was added to the culture dish to a final concentration of 2% PFA, and incubated for 5 min at 37°C. This initial step was utilized to preserve any fine peripheral astrocyte processes that might be sensitive to cold temperatures. After incubation, cells were washed with cold PBS, followed by fixation with 4% PFA for 15 min at room temperature. Subsequently, cells were incubated for 1 hr in blocking buffer . Astrocyte filaments were visualized with GFAP, total membrane with Glast and Ezrin. Following primary antibody incubations, AlexaFlour 488, 546, and 647 were utilized to visualize the primary antibodies with 1 hr incubations. Prior to image acquisition, the experimenter was blinded to experimental conditions. Fluorescent images were acquired with an Olympus VS-120 system or Nikon A1 confocal.2/area - 4π . AAV2/5 GfaABC1D.eGFP-Cre was obtained from UNC Gene Therapy Center Vector Core. AAV p2.1GfaABC1D.tdTomato was a gift from Baljit Khakh . Postnatal day 0–1 pups were intraventricularly injected with 2–3 µL 2.3 × 10ollowing , with eqWildtype and TrkB.T1 KO mice at PND 28 were collected via transcardial perfusions as described above, post-fixed for 72 hr, and sectioned into 50 µM slices. Sections containing the motor cortex were selected as detailed in Three serial sagittal sections from each subject were collected via systematic random sampling . For each section, a 500 μm wide contour of the cortex above area CA2 of the hippocampus was drawn using a 4x objective lens and StereoInvestigator . The number of astrocytes and neurons in the cortex was assessed with the Optical Fractionator probe from Stereo Investigator  and an Olympus BX51TRF motorized microscope (Olympus America). After delineation of the ROIs, StereoInvestigator systematically overlaid optical dissector grids that represented the individual fields for sampling/counting . Approximately 100 randomized sites were assessed to identify DAPI, Sox9+ and NeuN+ cells per animal. The number of cells per contour, average section thickness, section interval, and the number of sections were used to calculate the total number of cells within the sampled areas of the somatosensory cortex.Serial sagittal sections used for stereological quantification were imaged at 5x magnification on a Zeiss Axio Observer D1 Inverted Phase Contrast Florescent Microscope using an Axiocam 506 Mono camera and Zen Blue Edition software . Cortical regions above hippocampal CA2 were imaged using Zeiss DAPI Filter Set 49 for cortical thickness determination. The stratum oriens of CA2 was used as a central marker for drawing segmented lines from layer I through layer VI in Fiji software (version 1.52 n), where segments would span from the most dorsal portion of the somatosensory region to the fiber tracts of the corpus callosum. Fiji ROI Manager measure tool assessed the length of each segment for determination of total length and segment length corresponding to each cortical layer.+ and Mbp+ microbeads for 10 min. The flow through was collected and used to further isolate neuronal populations utilizing Miltenyi Biotec’s Neuron Isolation Kit. The cell suspension was incubated with 10 µL biotinylated antibodies for 10 min at 4°C, followed by a 10 min incubation with 15 µL anti-biotin microbeads. Cells were applied to a prepped LS column. Neurons were collected in the flow through of two washes. Neuronal cell number was determined, and 0.75–1.0 × 105 cells were plated on 13 mm glass coverslips in a 24-well plate. The coverslips were poly-l-lysine treated and laminin-coated. Neurons were maintained in neuronal maintenance media . Glast and Gfap immunohistochemistry was performed as described above. Following primary antibody incubations, AlexaFlour 488 and 647 were used to visualize the primary antibodies with 1 hr incubations at 1:500. Prior to image acquisition, the experimenter was blinded to experimental conditions. Confocal images were acquired on Nikon A1 confocal with 40x objective and two digital zoom. Astrocyte complexity was assessed by Sholl analysis plugin in FIJI software according to Cells were collected at 8–9 DIV and 12–14 for synapse quantification. Cells were fixed as described above. Subsequently, cells were incubated for 1 hr in blocking buffer . Excitatory synapses were visualized with presynaptic marker VGLUT1 and with postsynaptic marker PSD95. In a subset of experiments, synapses were visualized with presynaptic marker Bassoon and with postsynaptic marker Homer1. Following primary antibody incubations, AlexaFlour 488 and 647 were utilized to visualize the primary antibodies with 1 hr incubations at 1:500. These secondaries were chosen for their excitation/emission spectrum, which demonstrate no overlap. Therefore, co-localization analysis of pre- and post-synaptic markers can be utilized with confidence of true co-localization. Prior to image acquisition, the experimenter was blinded to experimental conditions. Confocal images were acquired on Nikon A1 confocal with 40x objective and three digital zoom. Care was taken to ensure each individual neuron imaged was equidistance from other neurons and astrocytes. Co-localization, and therefore synapse number, was determined utilizing Puncta Analysis FIJI plug-in . Briefly2 0.8, NaHCO3 26.2, glucose 11.1, HEPES 5.0). Patch pipettes were made from thin-walled  borosilicate glass  and had resistances of 4–8 MΩ when filled with Cs-gluconate solution pipette solution contained (in mM) 120 Cs-gluconate, 17.5 CsCl, 10 Na-Hepes, 4 Mg-ATP, 0.4 Na_GTP, 10 Na2-creatine phosphate, 0.2 Na-EGTA; 290–300 mOsm; pH 7.3  were used for evaluation neuronal spontaneous miniature excitatory post-synaptic currents. Experimenter was blinded to condition prior to recording. Briefly, coverslips were transferred to a recording chamber on an inverted Zeiss Observer.D1 microscope and continuously perfused (2 mL/minute at room temperature) with aCSF containing (in mM), NaCl 116, KCl 4.5, MgCl; pH 7.3 . CurrentTo determine statistical significance, Origin and Graphpad Prism were utilized. All data is represented as mean + /- SEM, with n’s indicated where appropriate. D’Agostino-Pearson normality test was performed to determine the normality distribution of each data set, and outliers were determined via GraphPad Prism’s ROUT method. Student’s t-tests were performed, or Mann Whitney U tests for nonparametric data, for all data in which only one comparison was needed. One-way ANOVAs, or Kruskal-Wallis test for nonparametric data, followed by Tukey’s post-hoc test performed for all data with multiple comparisons. 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 guest Reviewing Editor and Didier Stainier as the Senior Editor. The following individual involved in the review of your submission has agreed to reveal their identity: Marc Freeman (Reviewer #1).Thank you for submitting your article "BDNF/TrkB.T1 signaling is a novel mechanism for astrocyte morphological maturation" 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. Please aim to submit the revised version within two months. If you feel this is an unrealistic amount of work for 2 months, please send back within a week an action plan that outlines what you consider reasonable revisions and the editors and reviewers will discuss it.Summary:In this study, the authors report a role for BDNF/TrkB.T1 signaling in astrocyte morphogenesis and morphological complexity. The authors show data that loss of TrkB.T1 impacts astrocyte maturation and dysregulates expression of genes involved in astrocyte function. Additionally, the authors show astrocytes lacking TrkB.T1 do not support normal synaptogenesis. Key data supporting their model includes astrocyte-specific expression of TrkB.T1 in vitro and in vivo, a developmental upregulation of TrkB.T1, KO data in vitro and in vivo supporting a role for TrkB.T1 in promoting astrocyte morphological complexity (as well as Fc-depletion of BDNF), changes in the expression of key astrocyte functional genes, and a reduced capacity of these astrocytes to promote post-synaptic development. The three reviewers and the reviewing editor all found the data convincing and experiments well conducted. However, they also agreed that to fully support the claims of this study, additional electrophysiological and in vivo data are required. Moreover, the reviewers pointed out several necessary clarifications and textual edits to ensure that the data presented and the conclusions drawn from the are in line.Essential revisions:Major concerns to be addressed during revision:1) Electrophysiological analyses are needed to confirm the claim that loss of TrkB in astrocytes alters the ability of astrocytes to induce synapse formation and enhance synaptic function in vitro.Sox9 positive nuclei in the KO and WT .2) The decrease in astrocyte volume/complexity in TrkB.T KO mice in vivo requires more investigation. Is this difference maintained in later ages? Does it lead to reduced neuropil infiltration by astrocytes and/or generation of more astrocytes due to reduced territory sizes? For example, is there still a deficit in astrocyte volume at older ages, such as P60, when astrocyte volume has stabilized ? If the volume of all astrocytes in the cortex is decreased, this would predict that there is now an increase in the volume of the extracellular space. If so, this would be expected to have a significant impact on neuronal activity, for example by altering potassium uptake and neurotransmitter recycling. Are the mice reported to show any behaviors that would correlate with this, for example seizures? Alternatively, are there more astrocytes in the KO cortex that fill in the space? This could be quantified by counting the number of 3) A key limitation of the study is the utilization of a global TrkB.T1 knockout mouse. In order to draw conclusions on the role of this protein in astrocytes in vivo, the authors should manipulate TrkBT1 expression only in astrocytes and test the effects on astrocyte morphogenesis. Targeting of astrocytes for gene manipulation by viral or electroporation approaches provide the means for doing this without the need for generating conditional KOs. So, we believe this experiment can be conducted within a reasonable time frame during revisions.4) The data provided is not strong enough to firmly link impaired synaptogenic signaling by sparcl1 and sparc signaling to the phenotypes associated with loss of TrkB in astrocytes. We ask the authors to remove these experiments or conduct new experiments that will causally link sparcl1/sparc-signaling as a potential mechanism. However, the authors should also consider that astrocytes secrete a number of synapse modulating proteins and those may also be at play here. They should be able to rule them in or out before landing on sparcl1 and sparc. But we also agreed that this may be beyond the scope of one study. Therefore, it is recommended that you focus on the top three points in the revisions and leave this aspect for future research.Textual Clarifications/Changes Required:1) It is difficult to understand exactly how astrocyte complexity was quantified. Please provide more clarity on this point. It is hard to tell from the images how dramatic the change is with BDNF manipulation. This is difficult to do, but is a key part of the study.2) Claims to 'first time' and 'novelty' should be avoided. For example, the last paragraph of the Introduction states this is the first time the TrkB receptor has been detected in astrocytes, however there are many reports of this in the literature e.g. Rose et al., 2003, Ohira et al., 2005, Ohira et al., 2007, Matyas et al., 2017. Further, in two of these papers a role for truncated TrkB in regulating astrocyte morphology in vitro and in brain slices (fine process motility) was investigated . While we appreciate the current study uses a more physiological astrocyte model , and is looking at overall astrocyte growth during postnatal maturation, the 'first time' and 'novelty' claims cannot be supported due to these earlier studies.3) The utilization of a global TrkB.T1 knockout mouse does not allow support for the claim "the majority effects within the global TrkB.T1 KO mouse may be attributable to astrocytes." In cortical circuit development, neuron generation happens before astrocyte generation, which is a quite different from the cell-specific astrocyte culture system employed in this study. Using cell-specific astrocyte cultures, the authors assessed the impact of TrkB.T1 on astrocytes, however it does not necessarily represent the systemic effects of TrkB.T1 on astrocytes. Please carefully go through the manuscript to ensure that no overarching comments that cannot be fully supported by the experiments conducted are present.4) Related to the point raised above, the authors show impairments of morphological maturation of astrocytes in the TrkB.T1 KO mouse compared to that in WT mouse in vivo; however, the impact of morphological complexity demonstrated in TrkB.T1 KO astrocyte cultures only occurred under external BDNF application. This is an important point that is not addressed and may suggest various processes are in play. Please discuss/clarify.5) In the WT astrocyte cultures , the enhancement of TrkB.T1 mRNA expression was detected at DIV14; however, the astrocyte morphological complexity in TrkB WT and TrkB.T1 KO astrocyte cultures had no difference under the control treatment at the same DIV14 . The authors should comment on this point. Moreover, in separate experiments the authors assessed synaptic development 5 days after seeding WT or TrkB.T1 KO astrocytes on the top of neurons . Given the various timeframes examined and the varying results, it is difficult to conclude that the impact of excitatory synaptic development measured at DIV8-9 in Figure 5 resulted from astrocytes lacking TrkB.T1 in their co-culture experiment. Explain the differences between the timelines utilized between different experiments.6) It is mentioned in the Discussion that both excitatory and inhibitory synapses were affected, with TrkB manipulation in astrocytes, but only data for excitatory synapses is shown. Please correct this error.7) The authors collected samples from neurons, astrocytes or microglia at various time points, but the indication of the expression of RNA or protein at these time points were unclear in the figures and figure legends. Please label the time points on the figure or make a developmental timeline and pinpoint the time window for each experiment in each figure.8) There should be some discussion as to why BDNF only has an effect on astrocyte morphology at 30ng/ml, and not 100ng/ml. Is BDNF acting through the truncated TrkB receptor known to have a bell-shaped dose response? Essential revisions:Major concerns to be addressed during revision:1) Electrophysiological analyses are needed to confirm the claim that loss of TrkB in astrocytes alters the ability of astrocytes to induce synapse formation and enhance synaptic function in vitro.Thank you for this suggestion. We agree that electrophysiological analysis is necessary to support our in vitro synaptic data. New electrophysiological experiments were performed and are now added to Figure 6. These data support the notion that TrkB.T1 astrocytes do not support normal excitatory synaptogenesis.2) The decrease in astrocyte volume/complexity in TrkB.T KO mice in vivo requires more investigation. Is this difference maintained in later ages? Does it lead to reduced neuropil infiltration by astrocytes and/or generation of more astrocytes due to reduced territory sizes? For example, is there still a deficit in astrocyte volume at older ages, such as P60, when astrocyte volume has stabilized ? If the volume of all astrocytes in the cortex is decreased, this would predict that there is now an increase in the volume of the extracellular space. If so, this would be expected to have a significant impact on neuronal activity, for example by altering potassium uptake and neurotransmitter recycling. Are the mice reported to show any behaviors that would correlate with this, for example seizures? Alternatively, are there more astrocytes in the KO cortex that fill in the space? This could be quantified by counting the number of Sox9 positive nuclei in the KO and WT .Thank you. We have broken the reviewer comments into separate sections in order to clearly address each point.A) Change in astrocyte morphological complexity at later ages.We agree that this is an important question. We have now included astrocyte morphological complexity analysis at PND 50  in Figure 4. These data demonstrate a significant 20% reduction in astrocyte morphological complexity at P50.B) Change in extracellular space / astrocyte number as compensation.The reviewers bring up a very interesting point. As suggested, we performed stereological microscopy to determine the number of astrocytes and neurons in the TrkB.T1 KO mice. We have included new experimental analysis of astrocyte cell numbers as suggested by the reviewer and included the following in the Discussion:“We did not observe a difference in astrocyte number by stereological microscopy across the motor cortex, nor did we observe a difference cortical motor thickness. […] Studies in astrocyte specific TrkB.T1 KO are needed to determine if loss of TrkB.T1 in astrocytes contribute to this aberrant behavior.”Additionally, we have found no publications investigating seizure susceptibility in the TrkB.T1 KO mice, and little investigation of neuronal activity in this model. However, published reports  demonstrate that the mice do exhibit behaviors associated with increased anxiety. We feel that the susceptibility of the mice to seizures is outside of the scope of this manuscript, however behavioral assessment in the conditional-TrkB.T1 KO mouse we have generated are an area we plan to investigate.3) A key limitation of the study is the utilization of a global TrkB.T1 knockout mouse. In order to draw conclusions on the role of this protein in astrocytes in vivo, the authors should manipulate TrkBT1 expression only in astrocytes and test the effects on astrocyte morphogenesis. Targeting of astrocytes for gene manipulation by viral or electroporation approaches provide the means for doing this without the need for generating conditional KOs. So, we believe this experiment can be conducted within a reasonable time frame during revisions.Thank you. We agree with the reviewers that the utilization of the global TrkB.T1 KO model is a key limitation to the study, and that astrocyte-specific loss of TrkB.T1 in an otherwise normal environment is an important experiment. We therefore performed three experiments in parallel, presented in a new Figure 5, to address this concern. These data unambiguously indicate that the loss of TrkB.T1 in astrocytes alone is sufficient to result in reduced astrocyte morphological complexity. We have outlined the experiments and findings below:A) We assessed the complexity of astrocyte morphology from WT and TrkB.T1 KO astrocytes co-cultured with WT neurons. Using both Glast to demarcate the membrane  and Gfap to demarcate the processes, we found that TrkB.T1 KO astrocytes demonstrated decreased morphological complexity in comparison to WT astrocytes.fl/fl mice were co-injected with an astrocyte-specific AAV driving Cre recombinase with an EGFP florescent reporter and a control astrocyte-specific AAV driving only a tdTomato fluorescent reporter. Astrocyte morphology was assessed in both egfp+(Cre) and tdtom+(control) astrocytes in both WT and.T1fl/fl mice. Egfp+(Cre+) astrocytes from. T1fl/fl animals exhibited decreased volume compared to Egfp+(cre+) WT astrocytes. Importantly, we found no difference between tdtom+(control).T1fl/fl and WT astrocytes.B) We utilized viral-mediated Cre-recombinase to knockdown TrkB.T1 specifically in astrocytes. Using a previously generated TrkB.T1 floxed mouse line and our ICV injection paradigm, WT and. T1C) We generated an astrocyte-specific TrkB.T1 knockout model. Using the same TrkB.T1 floxed line as above, we crossed these mice to astrocyte targeted Aldh1l1-CreERT2 mice. Following tamoxifen injections between P8-11, we found loss of the TrkB.T1 receptor specifically in astrocytes. Animals were injected with the AAV2/5 Gfap-egfp virus, TAM injected, and astrocyte morphology assessed. We again found decreased astrocyte complexity in the cKO animals compared to cWT littermates.4) The data provided is not strong enough to firmly link impaired synaptogenic signaling by sparcl1 and sparc signaling to the phenotypes associated with loss of TrkB in astrocytes. We ask the authors to remove these experiments or conduct new experiments that will causally link sparcl1/sparc-signaling as a potential mechanism. However, the authors should also consider that astrocytes secrete a number of synapse modulating proteins and those may also be at play here. They should be able to rule them in or out before landing on sparcl1 and sparc. But we also agreed that this may be beyond the scope of one study. Therefore, it is recommended that you focus on the top three points in the revisions and leave this aspect for future research.Thank you. As the reviewers suggested, we have removed the sparcl/sparc data from the manuscript.Textual Clarifications/Changes Required:1) It is difficult to understand exactly how astrocyte complexity was quantified. Please provide more clarity on this point. It is hard to tell from the images how dramatic the change is with BDNF manipulation. This is difficult to do, but is a key part of the study.Thank you for this highlighting this ambiguity in the manuscript. We have added the following sentence to the Results section clarify how the Shape Index quantifies cellular complexity.2/area – 4π, relates area and perimeter of a cell to a circle such that a perfect circle receives an SI of 0, and increasingly complex cells have correspondingly larger SI values.”“We utilized the Shape Index (SI) to examine in vitro astrocyte complexity; this equation, given as perimeterAnalysis of shape index data indicate a > 2-fold increase in morphological complexity. Cumulative frequency also shows the rightward shift in morphological complexity in astrocytes treated with BDNF. The images of astrocytes presented are representative. The 30 ng BDNF image demonstrates a striking difference in astrocyte morphology compared with the 4 other images in the figure. We now provide additional images in Figure 3—figure supplement 1 with example tracing of individual astrocytes used for data analysis in Image J.2) Claims to 'first time' and 'novelty' should be avoided. For example, the last paragraph of the Introduction states this is the first time the TrkB receptor has been detected in astrocytes, however there are many reports of this in the literature e.g. Rose et al., 2003, Ohira et al., 2005, Ohira et al., 2007, Matyas et al., 2017. Further, in two of these papers a role for truncated TrkB in regulating astrocyte morphology in vitro and in brain slices (fine process motility) was investigated . While we appreciate the current study uses a more physiological astrocyte model , and is looking at overall astrocyte growth during postnatal maturation, the 'first time' and 'novelty' claims cannot be supported due to these earlier studies.Thank you. We have carefully reviewed the manuscript and have striven to remove language that suggests incorrect novelty. However, we do feel that our data does represent novel findings in regards to TrkB receptor expression in astrocyte development. In particular, we are indeed the first examine TrkB receptor expression specifically in astrocytes across cortical development. To ensure we do not overgeneralize, we have included the following in the Discussion:“BDNF’s role in CNS growth and maturation has been intensely studied, with a particular emphasis on the full length receptor and neuronal function. […] Publicly available RNA sequencing databases corroborate our data , and, in fact, additionally demonstrate that human astrocytes express the highest levels of Ntrk2 .”3) The utilization of a global TrkB.T1 knockout mouse does not allow support for the claim "the majority effects within the global TrkB.T1 KO mouse may be attributable to astrocytes." In cortical circuit development, neuron generation happens before astrocyte generation, which is a quite different from the cell-specific astrocyte culture system employed in this study. Using cell-specific astrocyte cultures, the authors assessed the impact of TrkB.T1 on astrocytes, however it does not necessarily represent the systemic effects of TrkB.T1 on astrocytes. Please carefully go through the manuscript to ensure that no overarching comments that cannot be fully supported by the experiments conducted are present.Thank you. We have removed this section. We have reviewed the manuscript and have striven to remove overgeneralization of our results.4) Related to the point raised above, the authors show impairments of morphological maturation of astrocytes in the TrkB.T1 KO mouse compared to that in WT mouse in vivo; however, the impact of morphological complexity demonstrated in TrkB.T1 KO astrocyte cultures only occurred under external BDNF application. This is an important point that is not addressed and may suggest various processes are in play. Please discuss/clarify.Thank you. We agree that this is an important and complicated point. We have addressed this within the Discussion of the manuscript. We feel that our data can be explained, in part, due to the differences in in vitro and in vivo astrocytes. It is well characterized that astrocyte cultures are not fully representative of in vivo astrocytes. While many of these differences can be attributed to the presence of serum in traditional astrocyte cultures , culturing astrocytes in isolation also removes them from the influence of other cellular populations. The loss of various signaling molecules from other CNS populations, and in this context, the lack of BDNF present in the media, may explain why the in vitro WT and TrkB.T1 KO astrocyte morphology does not differ except under external application.5) In the WT astrocyte cultures , the enhancement of TrkB.T1 mRNA expression was detected at DIV14; however, the astrocyte morphological complexity in TrkB WT and TrkB.T1 KO astrocyte cultures had no difference under the control treatment at the same DIV14 . The authors should comment on this point.The reviewers bring up an interesting point. As mentioned in response to #4, culturing astrocytes removes them from communication with other cellular populations, and thus under control conditions the media will not contain BDNF. Under this assumption, with no stimulation from BDNF, it would be predicted that control conditions between WT and TrkB.T1 KO astrocytes would not exhibit differences in morphological complexity. Only in the presence of the TrkB.T1 receptor’s ligand, BDNF, would WT astrocytes be signaled to increase in morphological complexity. Our assertion that TrkB.T1 increases astrocyte morphological complexity only with BDNF stimulation is also supported by our TrkB-Fc scavenge data, whereby removing the exogenously applied BDNF from the media results in astrocytes with morphological complexity similar to control astrocytes.Moreover, in separate experiments the authors assessed synaptic development 5 days after seeding WT or TrkB.T1 KO astrocytes on the top of neurons . Given the various timeframes examined and the varying results, it is difficult to conclude that the impact of excitatory synaptic development measured at DIV8-9 in Figure 5 resulted from astrocytes lacking TrkB.T1 in their co-culture experiment. Explain the differences between the timelines utilized between different experiments.Ntrk2 expression in astrocytes. In fact, preliminary data from our lab indicates that Ntrk2 RNA expression is in the top 50 most highly expressed genes found in acutely isolated wildtype astrocytes from postnatal day 6-60. Thus, BDNF may exert effects on astrocytes across their development and maturation. We feel that the impact on excitatory synaptic development measured at DIV8-9 can only be explained by the one manipulated variable, the loss of the truncated receptor in astrocytes. However, to address this concern, we performed synaptic quantification in wildtype neurons co-cultured with astrocytes for a longer, more extended timeframe with collection at 12-14DIV. As demonstrated in While our data does demonstrate an upregulation of TrkB.T1 in the astrocytes at 14DIV, we feel that it is not indicative of a lack of TrkB.T1 receptor expression in 7DIV astrocytes. We highlighted this observation in the manuscript only as it is on a similar to the upregulation we found between PND 7 and PND 28 astrocytes, and thus suggests an intrinsic regulation of 6) It is mentioned in the Discussion that both excitatory and inhibitory synapses were affected, with TrkB manipulation in astrocytes, but only data for excitatory synapses is shown. Please correct this error.Thank you. This has been corrected in the manuscript.7) The authors collected samples from neurons, astrocytes or microglia at various time points, but the indication of the expression of RNA or protein at these time points were unclear in the figures and figure legends. Please label the time points on the figure or make a developmental timeline and pinpoint the time window for each experiment in each figure.Thank you for highlighting the ambiguity of the figure. We have updated both the figures and figure legends to make the time line of assessment more clear.8) There should be some discussion as to why BDNF only has an effect on astrocyte morphology at 30ng/ml, and not 100ng/ml. Is BDNF acting through the truncated TrkB receptor known to have a bell-shaped dose response?The reviewers bring up a very interesting point. To the authors’ knowledge, thus far experimental determination of a dose-response of TrkB.T1 has not been performed. The authors chose the experimental BDNF concentrations as they have been used previously to examine BDNF’s effects on cultured cellular populations. We have added the following into the Discussion section of the manuscript:“A potential interaction and/or regulation of RhoGTPases by TrkB.T1 may also offer insight into the BDNF dose-specific response we observed in cultured astrocytes. […] However, our data suggests TrkB.T1 plays an active, direct role in astrocyte biology.”


N-linked glycan decoration of PD-L1, thereby promoting the endoplasmic reticulum retention of a mannose-rich, abnormally glycosylated form of PD-L1. RSV was also predicted to interact with the inner surface of PD-L1 involved in the interaction with PD-1, almost perfectly occupying the target space of the small compound BMS-202 that binds to and induces dimerization of PD-L1. The ability of RSV to directly target PD-L1 interferes with its stability and trafficking, ultimately impeding its targeting to the cancer cell plasma membrane. Impedance-based real-time cell analysis (xCELLigence) showed that cytotoxic T-lymphocyte activity was notably exacerbated when cancer cells were previously exposed to RSV. This unforeseen immunomodulating mechanism of RSV might illuminate new approaches to restore T-cell function by targeting the PD-1/PD-L1 immunologic checkpoint with natural polyphenols.New strategies to block the immune evasion activity of programmed death ligand-1 (PD-L1) are urgently needed. When exploring the PD-L1-targeted effects of mechanistically diverse metabolism-targeting drugs, exposure to the dietary polyphenol resveratrol (RSV) revealed its differential capacity to generate a distinct PD-L1 electrophoretic migration pattern. Using biochemical assays, computer-aided docking/molecular dynamics simulations, and fluorescence microscopy, we found that RSV can operate as a direct inhibitor of glyco-PD-L1-processing enzymes (α-glucosidase/α-mannosidase) that modulate  Unlike immunologically “hot” tumors such as lung cancer, melanoma, and bladder cancer, most breast carcinomas are not inherently immunogenic. Consequently, they typically exhibit low T-cell infiltration and are unlikely to benefit from immune checkpoint-centric therapies –5. Excepbona fide driver of immune checkpoint signaling in tumor cells is a largely neglected area in cancer immunometabolism. Indeed, we are lacking even a minimal understanding of how pharmacological manipulations targeting core metabolic checkpoints such as AMPK, mTOR, and SIRT1, might fine-tune the expression of immune checkpoint receptors in cancer cells.In recent years, the cancer immunometabolism field has started to provide important insights into the pivotal role of metabolism in controlling immune cell function –35. IndeHere, we took advantage of the JIMT-1 cell line, a unique model of highly-aggressive basal-like/HER2-positive breast cancer naturally overexpressing the immunosuppressive molecule PD-L1 with 100% of the cells positive for PD-L1 , to explPD-L1 is a type I transmembrane glycoprotein with an apparent molecular weight of ~45 kDa. We first examined the protein expression of PD-L1 in JIMT-1 cells cultured with the following metabolism-targeting drugs: the SIRT1 agonist RSV, the mitochondrial complex I inhibitor phenformin, the acetyl-coA carboxylase inhibitor soraphen A, the fatty acid synthase inhibitor C75, and the AMPK/mTOR regulators AICAR, compound C, PP242, and Torin . Based oN-glycosylated mature protein /CIno effector × 100).T-cell-mediated lysis of tumor cells was monitored using an impedance-based approach. One hundred microliters of DMEM containing 10% FBS was added to each well of an E-Plate 16 . Background impedance was measured using the xCELLigence RTCA instrument (Roche) at 37°C and 5% COP-value was < 0.01.Cytolytic activity means were compared using a two-way ANOVA with Sidak’s multiple comparison post-test. Results were designated significant when the Supplementary FiguresSupplementary Tables


Anderson localization, the unusual phenomenon discovered in a disordered medium, describes the phase transition from the extended to localized state. Owing to the interference in multiple elastic scattering, this concept is firstly demonstrated in an electron system, then to photon and matter waves. However, Anderson localization has not been observed for polaritonic waves with its unique features of strong field confinement and tunability. Here, Anderson localization of plasmon polaritons is experimentally reported in a flat graphene sheet simultaneously with homogenous charge carrier and random tensile‐strain distributions. By selectively choosing different disordered levels, the transition from quasi‐expansion to weak localization, and finally Anderson localization are observed. Relying on the infrared nanoimaging technique, the spatial dependence of the localization is further studied, and finally the transition window from weak to Anderson localization of graphene plasmon polaritons is identified with the aid of the scaling theory. The experimental approach paves a new way to study Anderson localization in other polaritonic systems such as phonon, exciton, magnon polaritons, etc. Emax) is inversely proportional to the ξ, as Emax  ≈ E0ε′/ε′′(a/ξ)2 . However, the experimental observation of Anderson localized polaritons remains challenging, because of hyperdispersion of polaritonic signal itself caused by rough morphology and electric heterogeneity. Compared with the case for metal, grapheneThe phase transition from ballistic state to localization in a disordered medium is first predicted by Anderson.In this communication, we report Anderson localization of plasmon polaritons in flat graphene flakes simultaneously having randomly distributed tensile‐strains and homogeneous charge carrier. By carefully selecting graphene samples with different levels of disorder, we observe the transition for plasmon polaritons from quasi‐expansion, weak localization, to Anderson localization. With the aid of scaling theory, we identify the criterion for the transition from weak to Anderson localization. Using nanoinfrared imaging technique, we analyze the properties of graphene plasmon in different states. These experimental results shed light on studying the Anderson localization of various polaritons and provide a new freedom for manipulating graphene plasmons.Due to good flexibility of single‐layer graphene, the mechanically exfoliated process is similar to throw a soft handkerchief on stiff surface, resulting in inhomogeneous strain. The thermal treatment during fabrication can also give rise to roughness of strain due to different thermal expansion efficiencies of graphene and substrate. It is worth noting that the spatial distribution of strains and carrier density varies from sample to sample. By preparing hundreds of graphene samples, we characterize the distribution of strains and doping level by Raman spectroscopymax and ρmin represent the largest and smallest value in strain map, respectively. Figure12cm−3). This homogenous doping level and atomically flat graphene surface are necessary for the observation of Anderson localization.Here, ρFigureY‐directionX‐ and Y‐direction. However, it is more difficult to distinguish Anderson localization from inherent damping property along the Y‐direction, compared with X‐direction. In order to extract the localization length, we evaluate the average intensity (〈|E(x)|2〉  =∫〈|E|2〉Ly dy, yL denotes the decay length of graphene plasmon in the Y‐direction), and the corresponding results are shown as black dot‐lines in Figure exp (−2x2ξ2)) and exponential (exp(−2∣x∣/ξ)) fitting. When the graphene lattice is almost periodic (Δ ≈ 0%), the plasmon undergoes quasi‐extended transport with the localization length (ξ) close to infinite, manifested by almost uniform average field intensity in Figure For a 2D system, the scaling theoryBased on the criterion mentioned above, we conclude that plasmon exhibits the weak localization in this disordered level. When Δ further increases to 31.3%, we confirm Anderson localization Figure f of grapY‐direction) at the incident frequency of 901 cm−1 in Figurep ≈ 216.7 nm for the quasi‐expansion, λp ≈ 206.7 nm for the weak localization and λp ≈ 220.0 nm for the Anderson localization. The similarity is mainly arisen from same doping level (or Fermi level) for these three samples. The plasmonic damping increases when Anderson transition occurs, i.e., γ ≈ 0.20 for the quasi‐expansion, γ ≈ 0.24 for the weak localization and γ ≈ 0.26 for the Anderson localization. By choosing different working frequencies for these samples, we further study how the dispersion of graphene plasmon depends on the localization state see Figure 0/2) and to confine light on nanoscale. The Y‐confinement factor ) remains almost unchanged for all three modes. However, the confinement of light in the X‐direction is realized through the mode localization arisen from the disordered system. As shown in Figure 0/ξ) increases from zero, ≈30, and finally ≈40, when the state changes from quasi‐expansion, weak localization to Anderson localization.In order to study intrinsic properties of plasmonic modes for different disordered graphene, we show the line‐profiles of average field intensity along vertical edge direction , where kp and l* are wavevector and mean free path of photon, respectively) and Ioffe–Regel criterionkpl* ≈ 1) are commonly used to analyze the scattering behavior. Taking the photonics‐polaritonics analogyIn l* and kpl* in both the weak and the strong localization. In a pristine graphene flake, the plasmonic mean free path (l* ≈ 1 µm) is much larger than its wavelength (≈200 nm) and kpl* ≈ 30 is much larger than one.−1, l* is 50.8 nm for the weak condition and 44.1 nm for the strong condition. The strong multiple scattering induces Anderson localization. Also, the observed Anderson transition indicates that the intravalley elastic scattering occurs much more often than the intervalley scattering in the disordered graphene system.kpl*). Our scattering strength (1.1–1.2) for the Anderson localization case is close to the Ioffe–Regel criterionkpl* ≈ 1), while a bit far away for the weak localization (>1.3). This measurement from Anderson to weak localization allows us to identify the Anderson transition window for the graphene plasmons.We evaluate In summary, we experimentally observe Anderson localization of graphene plasmon polaritons and study the corresponding properties in 2D disordered systems. Noting that the doping levels in three samples are similar and homogenously spatially distributed, the Anderson localization of plasmons addressed here is mainly caused by random distribution of tensile‐strains. We apply s‐SNOM to directly access the localization length in both weak (ξ ≈ 374.08 nm) and strong (ξ ≈ 247.30 nm) scattering regime. The Anderson localized mode exhibits enhanced near‐field amplitude and strong field confinement. The localization has weak influence on the intrinsic properties of plasmons. Based on the scaling theory, we show the transition window from the weak to Anderson localization of graphene plasmons. Our findings pave a promising way to study polaritonic phenomena in disordered system and to stimulate further work in random polaritonics field.Sample Preparation and Characterization: Microcrystals of graphene are mechanically exfoliated from bulk samples and then transferred to 285 nm thick SiO2/Si substrates. To get rid of the air between graphene and substrate and to induce strains, thermal treatment (90 °C for 20 min) was conducted on fabricated samples. The monolayer graphene was further identified by optical measurement and Raman Spectroscopy. The surface roughness of graphene was characterized by atomic force microscopy (AFM), as shown in Figure S7 in the Supporting Information. By analyzing the shift of Raman peaks (G/2D), the spatial distribution of tensile‐train and doping level in graphene flakes was obtained. It is worth noting that the mechanical exfoliation was relatively a random process and the fabrication varied sample to sample. Three different disordered graphene samples were selected with similar and homogenous carrier density over hundreds of preparations.Infrared s‐SNOM Measurements: The nanoimaging experiments were performed using an s‐SNOM. The s‐SNOM was a commercial system (Neaspec GmbH) based on an AFM operating in the tapping mode with Ω ≈ 300 kHz and an amplitude of ≈30 nm. The incident frequency spanned from 901 to 980 cm−1. A pseudo‐heterodyne interferometric method was applied to extract both the near‐field amplitude and phase of graphene plasmons. The near‐field amplitude was normalized as:s4 (ω)=s40 (ω)/s4Si(ω). Here, s40(ω) and s4Si(ω) are the forth‐order demodulated harmonics of the near‐field amplitude detected for graphene and Si standard reference samples, respectively. All nanoIR images were collected at ambient atmosphere.Theoretical Calculation of the Dispersion Diagram: In order to get the dispersion, the complex reflectivity pr  of graphene/SiO2 structure was calculated. The reflectivity is expressed as0 is the vacuum permittivity, ε1 and ε2 are relative permittivity of air and SiO2. ω is incident frequency and q is the plasmonic wavevector, respectively. The kz1 and kz2 represent the z‐components of the wavevector of the incident and the transmitted plane‐waves, respectively. The conductivity of graphene ) was derived with random‐phase‐approximation (RPA) with the local limit. The Fermi level was extracted from Raman spectrum.The authors declare no conflict of interest.SupplementaryClick here for additional data file.


Dopamine D1 receptor (D1R) signalling is involved in contextual fear conditioning. The D1R antagonist SCH23390 impairs the acquisition of contextual fear when administered systemically or infused locally into the dorsal hippocampus or basolateral amygdala.We determined if state dependency may account for the impairment in contextual fear conditioning caused by systemic SCH23390 administration. We also examined if the dorsomedial prefrontal cortex (dmPFC), nucleus accumbens (NAc), and ventral hippocampus (VH) are involved in mediating the effect of systemic SCH23390 treatment on contextual fear conditioning.In experiment 1, SCH23390 (0.1 mg/kg) or vehicle was given before contextual fear conditioning and/or retrieval. In experiment 2, SCH23390 (2.5 μg/0.5 uL) or vehicle was infused locally into dmPFC, NAc, or VH before contextual fear conditioning, and retrieval was tested drug-free. Freezing was quantified as a measure of contextual fear.In experiment 1, SCH23390 given before conditioning or before both conditioning and retrieval decreased freezing at retrieval, whereas SCH23390 given only before retrieval had no effect. In experiment 2, SCH23390 infused into dmPFC before conditioning decreased freezing at retrieval, while infusion of SCH23390 into NAc or VH had no effect.The results of experiment 1 confirm those of previous studies indicating that D1Rs are required for the acquisition but not retrieval of contextual fear and rule out state dependency as an explanation for these findings. Moreover, the results of experiment 2 provide evidence that dmPFC is also part of the neural circuitry through which D1R signalling regulates contextual fear conditioning. Dopamine is a neurotransmitter that is important for memory processing and its role in mediating appetitive learning is well established  weighing 280–390 g at the start of the experiment (experiment 1) or before surgery (experiment 2) were used. Rats were group housed in individually ventilated cages and kept on a 24-h light/dark cycle (lights on at 07.00) with ad libitum access to food and water. All behavioral testing occurred during the rats’ light cycle. The principles of laboratory animal care were followed and all experimental procedures were performed with institutional ethical approval and under the UK Animals (Scientific Procedures) Act 1986 (Home Office Project Licence 30/3230).SCH23390 hydrochloride  was dissolved in 0.9% sterile saline. This dose has previously been shown to disrupt contextual fear conditioning . The freezing detection threshold was set to detect the absence of movement apart from that related to respiration. During conditioning, the cumulative duration of freezing during the 2-min intervals before the first and after the last shock was calculated and expressed as a percentage of both 2-min durations. Differences in freezing before and after conditioning between the four groups were analyzed using a two-way analysis of variance (ANOVA), with treatment as the between-subject factor and time  as the within-subject factor. Freezing during the retrieval session was determined as above. Differences in freezing during retrieval testing between the four groups were analyzed in two ways. Freezing throughout the whole session was analyzed using a one-way ANOVA, with treatment as the between-subject factor. Freezing during each 1-min bin of the session was also analyzed using a two-way ANOVA, with treatment as the between-subject factor and time as the within-subject factor. Post hoc analysis was conducted using the Newman-Keuls test where indicated. The data are presented in scatter plots, with the mean ± SEM indicated by horizontal lines and error bars, respectively, or in line graphs as the mean + SEM. The level of significance for all comparisons was set at 2 and an opioid analgesic  was administered immediately post-induction. Anesthesia was maintained during surgery with 1.5–2.5% isoflurane to ensure complete inhibition of the hindpaw withdrawal reflex. Rats were placed in a stereotaxic frame and the incisor bar was adjusted to maintain the skull horizontal. Rats were implanted bilaterally with guide cannulae  fitted with obturators  targeting dmPFC  to bregma, 2.0–2.3 mm ventral to the brain surface), NAc  to bregma, 6.5 mm ventral to the brain surface), or VH  (Paxinos and Watson Anesthesia was induced with ~ 3% isoflurane in OSCH23390 (2.5 μg) was dissolved in 0.5 μL of 0.9% sterile saline. This dose has previously been shown to impair contextual fear conditioning when infused locally into the BLA , NAc (core or shell), and VH (CA1) were included in the analysis Fig. .Fig. 2Ret tests. Freezing during each 1-min bin of the session was also analyzed using a two-way ANOVA, with treatment as the between-subject factor and time as the within-subject factor. Separate analyses were conducted for each brain area. Digitally recorded behavior in the open field was analyzed using Ethovision software . The percentage time spent in the center of and the total horizontal distance moved in the open field were determined and taken as indices of innate fear and locomotor activity, respectively . The effects of SCH23390 given before conditioning on freezing before and after shock presentations during conditioning are shown in Fig. F = 6.28, P = 0.0013) and time  = 754.6, P < 0.0001) but no treatment x time interaction  = 1.20, P = 0.32). Post hoc analysis indicated that freezing was significantly increased in the SCH-VEH and SCH-SCH groups, compared to the VEH-VEH and VEH-SCH groups, across both time points  (P < 0.05). This indicates that SCH23390 increased freezing acutely during contextual fear conditioning.To determine if disrupted contextual fear conditioning caused by systemic SCH23390 treatment involves state dependency, we examined the effects of SCH23390 given before conditioning and/or retrieval testing  = 9.46, P = 0.0002). Post hoc analysis found no difference in freezing between the VEH-VEH and VEH-SCH groups (P > 0.05), indicating that SCH23390 had no effect on contextual fear retrieval. However, freezing in the SCH-VEH group was significantly decreased, compared to both the VEH-VEH and VEH-SCH groups (P < 0.01), suggesting that SCH23390 impaired contextual fear conditioning. Importantly, freezing in the SCH-SCH group was also significantly decreased, compared to both the VEH-VEH and VEH-SCH groups (P < 0.05). This was confirmed by the more detailed time course analysis  = 9.46; P = 0.0002) but no main effect of time  = 2.27; P = 0.066) or treatment x time interaction  = 1.11; P = 0.36). Post hoc analysis indicated that, again, while there was no difference between the VEH-VEH and VEH-SCH groups or between the SCH-VEH and SCH-SCH groups (P > 0.05), freezing in the SCH-VEH and SCH-SCH groups was significantly decreased, compared to the VEH-VEH and VEH-SCH groups (P < 0.05). These results indicate that the effect of SCH23390 on contextual fear conditioning does not reflect drug effects on state-dependent learning but rather that SCH23390 disrupts contextual fear encoding.The effects of SCH23390 given before conditioning and/or retrieval on freezing at retrieval are shown in Fig. s P < 0.0, suggestF = 1493, P < 0.0001) but no main effect of treatment  = 3.12, P = 0.087) or treatment x time interaction  = 1.88, P = 0.18). This indicates that SCH23390 (n = 16) had no effect on freezing, compared to vehicle (n = 16), during conditioning. The effect of intra-dmPFC infusion of SCH23390 before conditioning on freezing during retrieval is shown in Fig. t(30) = 2.27, P = 0.031), indicating that SCH23390 infusion into dmPFC disrupted contextual fear conditioning  = 5.13; P = 0.031) and time  = 21.04; P < 0.0001), and a significant treatment x time interaction  = 4.67; P = 0.0015). Post hoc analysis showed that intra-dmPFC SCH23390 infusion significantly decreased freezing during the fourth and fifth minute of the retrieval session (P < 0.01).SCH23390 was previously shown to impair the acquisition of contextual fear when infused into the DH or BLA  = 381.1, P < 0.0001) but no main effect of treatment  = 1.11, P = 0.30) or treatment x time interaction  = 0.36, P = 0.56). This indicates that there was no effect of SCH23390 (n = 10), compared to vehicle (n = 9), on freezing during conditioning. The effect of SCH23390 infusion into the NAc before conditioning on freezing at retrieval is shown in Fig. t(17) = 0.54, P = 0.60), over the whole retrieval session  = 9.64; P < 0.0001) but no main effect of treatment  = 0.29; P = 0.60) or treatment x time interaction  = 1.08; P = 0.38). These results indicate that SCH23390 infusion into the NAc did not affect contextual fear conditioning.The effect of infusing SCH23390 into the NAc before conditioning on freezing before and after shock presentations during conditioning is shown in Fig. F = 158.6, P < 0.0001) but no main effect of treatment  = 0.64, P = 0.44) or treatment x time interaction  = 1.44, P = 0.25). This indicates that there was no effect of SCH23390 (n = 10), compared to vehicle (n = 7), on freezing during conditioning. The effect of intra-VH SCH23390 infusion before conditioning on freezing during retrieval is shown in Fig. t(15) = 0.31, P = 0.76), over the entire retrieval session  = 10.82; P < 0.0001) but no main effect of treatment  = 0.093; P = 0.76) or treatment x time interaction  = 1.18; P = 0.33). These results indicate that SCH23390 infusion into the VH also had no effect on contextual fear conditioning.The effect of infusing SCH23390 into the VH before conditioning on freezing before and after shock presentations during conditioning is shown in Fig. n = 14), SCH23390 (n = 18) had no effect on the percentage of time spent in the center (t(30) = 0.26, P = 0.79; Fig. t(30) = 0.58, P = 0.57; Fig. n = 10) had no significant effect on the percentage of time spent in the center (t(17) = 1.95, P = 0.067; Fig. t(17) = 2.68, P = 0.016; Fig. n = 9). The effects of intra-VH infusion of SCH23390 on behavior in the open-field test are shown in Fig. n = 10) on the percentage of time spent in the center (t(15) = 1.20, P = 0.25, Fig. t(15) = 1.44, P = 0.17; Fig. n = 7). These results indicate that, while SCH23390 does not act in any of these areas to regulate innate fear, the NAc is a site of action for the modulatory effects of this drug on locomotor activity.We also examined the effects of infusing SCH23390 into dmPFC, NAc, or VH on locomotor activity and innate fear during open-field testing to determine if the effects of systemic SCH23390 treatment reported in previous studies involve these areas. The effects of SCH23390 infusion into dmPFC on behavior in the open-field test are shown in Fig. This study investigated the role of D1Rs in modulating contextual fear conditioning in two ways. First, we determined if the impairing effect of systemic SCH23390 administration on the acquisition of contextual fear reported previously involves state dependency. In experiment 1, we confirmed previous results indicating that SCH23390 treatment disrupts contextual fear conditioning but not its retrieval. We also extended these findings by showing that its effect on the acquisition of contextual fear was not attributable to a state-dependent effect of this drug, given that SCH23390 administered before both learning and memory testing still resulted in impaired contextual fear conditioning. Second, we further characterized the neural substrates involved in mediating D1R regulation of contextual fear conditioning by examining the effect of infusing SCH23390 into VH, dmPFC, or NAc on the acquisition of contextual fear. In experiment 2, we found that SCH23390 infusion into dmPFC, but not VH or NAc, disrupted the acquisition of contextual fear, indicating that D1R signalling in dmPFC is involved in regulating contextual fear conditioning. We also showed that SCH23390 infused into the NAc, but not VH or dmPFC, reduced locomotor activity in the open-field test, confirming previous findings indicating that D1Rs in NAc play a role in modulating locomotion.Our results showing that systemic SCH23390 treatment impaired the acquisition but not retrieval of contextual fear confirm previous findings . Both the hippocampus and BLA project to NAc, making this area well-placed for integrating contextual and associative aspects of contextual fear conditioning McDonald . ExcitotInfusing SCH23390 into the VH was also without effect on the acquisition of contextual fear. This area receives input from the DH and projects to the BLA  recently shown to be involved in this process (Heath et al.


We developed hardware and software to implement microfluidic chip-based gene expression quantification in vivo. We altered position, number and sequence of introns in reporter genes controlled by the hsp-90 promoter. Consistent with plant and mammalian studies, we determined a single, natural or synthetic, 5′-intron is sufficient for the full IME effect conferred by three synthetic introns, while a 3′-intron is not. We found coding sequence can affect IME; the same three synthetic introns that increase mcherry protein concentration by approximately 50%, increase mEGFP by 80%. We determined IME effect size is not greatly affected by the stronger vit-2 promoter. Our microfluidic imaging approach should facilitate screens for factors affecting IME and other intron-dependent processes.Introns can increase gene expression levels using a variety of mechanisms collectively referred to as Intron Mediated Enhancement (IME). IME has been measured in cell culture and plant models by quantifying expression of intronless and intron-bearing reporter genes  Introns can affect gene expression in several ways (reviewed in3). For example, introns facilitate creation of different protein isoforms – a phenomenon known as alternative splicing5. Introns can also encode catalytic and regulatory RNAs11. And, introns may restrict genomic instability12. Finally, and the focus of this report, introns can increase the expression level of a gene via a number of different mechanisms. The expression level increase is referred to as intron mediated enhancement of gene expression level .Introns are noncoding DNA sequences interspersed between protein-coding DNA sequences called exons. When a gene is transcribed, introns are removed by the splicing machinery to generate a spliced messenger RNA (mRNA)16. There are several mechanisms by which introns can increase expression levls15. In mammalian and plant systems, introns increase the rate of transcription, and this can be mediated by splicing independent functions of splicing factors such as U1 snRNA19 or by gene looping20. Moreover, proteins deposited onto spliced transcripts, called the exon junction complex (EJC), increase mRNA transport from the nucleus to the cytoplasm22. The EJC can also increase translation efficiency of spliced transcripts25. Experiments swapping the sequences and orientations of introns suggest the proximity of the intron to the promoter is critical for IME26, and not the orientation of the sequence. Rose and Gallegos created a model wherein promoter-proximal introns contain stimulatory signals controlling transcription initiation or re-initiation, in a chromatin state dependent manner, either allowing an open chromatin state, or facilitating activating histone modifications14.In general, IME is defined as the increase in expression of an intron-containing gene compared to an otherwise-identical intronless version of the same gene28. 5′-introns can increase gene expression levels by increasing recruitment of RNA polymerase II to the transcription initiation site29. Promoter-proximal introns can also affect transcription initiation via chromatin modifications31. A 5′-intron is sufficient to recruit chromatin opening marks30. Previous reports measured 5′-intron IME in terms of RNA abundance32, protein activity28 or phenotype (related directly to protein activity33). The contemporaneous best available technologies for these studies had technical caveats like the inability to control transgene copy number and locus (either of which could have affected transgene expression level35). The in vitro measurements of IME at the RNA and protein level were assayed via biochemical extracts28. Finally, in some cases, reporter gene expression was transient23 . With modern genome editing and microfluidic technologies, we are able to quantify IME in live C. elegans with improved technical precision.A 5′-intron near the promoter is often sufficient for IMEin vivo in C. elegans. We designed a system that is higher throughput than confocal microscopy but still image based (unlike worm-flow)34, and compatible with fluorescent stereoscopes found in most C. elegans labs. We show the effects of different sequences and positions of natural and synthetic introns on the expression level of mCherry, controlled by the hsp-90 promoter. We also show the effects of a different promoter (vit-2) and a different coding sequence (mEGFP) on IME. We compare the size distribution of introns using modern drafts of the C. elegans and human genomes. Understanding details of IME is important for basic biology36, biotechnology38, and human diseases. There are now several diseases in which mutations in introns affect gene regulation40. Utilizing C. elegans to understand the biology of introns in vivo may offer complementary, novel physiological or molecular insights.Below we describe a microfluidic imaging system we developed to study IME 42 to develop an instrument to quantify gene expression in whole animals while acquiring an image of each animal. In this system, air pressure moves the worms from a pressurized 1.5 mL tube into the PDMS chip where they are subsequently imaged , and/or number, position or sequence of introns ; we used the unc-54 terminator in all constructs. The constructs integrated into the genomes of the resulting strains are shown in Fig. We designed and constructed a set of eleven different 46, we first determined the magnitude of IME using these introns. We used the constitutive, ubiquitously expressed, hsp-90 promoter to control expression of mCherry with and without these synthetic introns. We expressed these reporter genes from the same locus on chromosome II (inserted at ttTi560545). By measuring average voxel mCherry signal in our microfluidic chip , we found the canonical three synthetic introns increase mCherry expression level by 46% , shown in Fig. The canonical introns used in ons Fig. . The nat33. Therefore, we tested if single 5′-introns are sufficient for IME. We generated strains containing one, two or three synthetic or natural introns at different positions in the coding sequence, shown in Fig. Prior reports demonstrated a single 5′-intron is sufficient for some level of IME34. We compared IME for mEGFP and mCherry measured from the same cell (Int1DL) from ~40 animals. Using this approach, we again found coding sequence affected IME  in adulthood48, which is when we measured the animals (day one of adulthood). If IME were primarily constrained by free translational capacity, the magnitude of protein increase could depend on the transcriptional strength of the promoter. Stronger promoters would thus receive less of a boost. We constructed two strains using the vit-2 promoter to drive mCherry with either no introns, or the three synthetic introns . Our previous measurements of gene expression in whole animals51 utilized a higher throughput  flow sorting device  that measures signal from animals as they pass by a photomultiplier tube. This instrument does not acquire images of each animal, forgoing acquisition of potentially useful image features. By contrast, our system collects an image of each animal in a fixed orientation . It is possible that future studies will identify C. elegans intron sequences that confer greater IME effect sizes than we found here.In this report, we found that single or multiple introns increased protein expression level by about 50% or 80%, depending on coding sequence, and these data fit within the previously reported range of IME. In Nott in vitro studies showing that a single 5′-intron is sufficient for IME using phenotypes33, extracted RNA27 or extracted protein activity28 as readouts for the effect of introns on gene expression level. Our results are consistent with the idea that IME occurs via transcription, translation, or both. Our results are consistent with a transcriptional mechanism in which the splicing machinery at the 5′-intron re-recruits RNA polymerase back to the transcriptional start site. Our results are consistent with the possibility that a 5′-intron may affect transcription by opening chromatin; this may occur via recruitment of molecular machinery that makes access-permissive histone modifications to promoter-proximal histones. Our results are also consistent with the possibility that a 5′-intron can affect translation via proteins deposited onto the EJC during splicing54, which can recruit the translation machinery to EJC-marked transcripts55. Clearly, more work is needed to answer many lingering questions about IME56.Our findings corroborate results from prior 57 and cancers62. The intron-dependent processes affected are often unknown, poorly understood, or if understood, lack experimental means to determine how to suppress the intron-related pathology. For example, in a bipolar risk allele, STRs in the third intron of the calcium encoding CACNA1C gene seem to affect IME40. However, the mechanism by which this large, relatively 3′-intron acts to increase gene expression level remains unknown. The reagents and tools described here will allow investigators to perform genetic screens for factors affecting intron-related phenotypes. Moreover, the recent development of synthetic food medium as an alternative to the OP50 E. coli strain should allow execution of chemical genetic screens, using, for example, FDA approved pharmaceuticals packaged into liposomes and delivered into the intestine cells via the alimentary canal63. It is our hope that the screenable in vivo system we presented here will provide insight into intron-related disease mechanisms, and lead to therapeutic treatments to alleviate human diseases.Many previous reports have shown that introns influence human diseases. These diseases fall into two broad classes: heritable diseasesC. elegans, RBW6699 and the strains we listed in Fig. E. coli in an incubator at 20°. Strains were maintained for at least three generations at 20° in a well-fed state before experimentation. For experiments, animals were synchronized via alkaline hypochlorite treatment followed by overnight hatchout in sterile S-basal to cause entry into the L1 diapause, described in detail in34. Synchronous cohorts of animals were grown to gravid adulthood (72 hours at 20° on NGM after the L1 diapause) at a density of approximately 175 animals per 10 cm NGM plate seeded with 1 mL of OP50 E. coli from an overnight 500 mL or 1000 mL LB growth culture.Here, we used wild-type N2 strain of 64. To make the reporter genes, we used 2 kb upstream of the ATG for the hsp-90 promoter and 4 kb upstream of the ATG for the vit-2 promoter. We used the same unc-54 terminator in all strains64. For the pieces of DNA in which we varied introns, we created those with overlap extension PCR and then used those fragments in our yeast HR cloning system. These DNA repair templates were then used in microinjection-based MosSCI transgenesis to insert these reporter genes into the genome at the ttTi5605 Mos transposon locus on Chromosome II in strain RBW6699, which is an outcrossed version of EG6699 containing unc-119(ed3). We injected constructs @ 50 ng/µL of repair template + coinjection and selection markers as described previously in45). We sequenced the reporter sequences of all DNA constructs to ensure their sequence integrity and genotyped animals to verify insertion at the ttTi5605 locus. Thus, in this way, we generated all the strains listed in Fig. 34. We show the sequences of the fluorescent proteins and introns used in Supplementary Information.To make the DNA used for the transgenes we inserted, we used a yeast homologous recombination based cloning system we described recently to generate DNA repair templates65. Worms were physically constrained by the 65 × 50 micrometer dimensions of the imaging chamber preventing them from moving their bodies out of plane. We measured between 30 and over 100 animals per strain per experiment. We manually controlled the flow into the imaging and image acquisition in real time on the computer using Matlab and Micromanager, respectively.To prepare animals for entry into the microfluidic imaging device, we washed them from their growth plates into 1.5 mL Eppendorf tubes with filter-sterilized S-basal (to remove particulate matter) containing 0.01% tween (to prevent worms from sticking to plastic). We allowed animals to settle for 5–10 minutes in a 50 mL conical vial, and then removed the supernatant, and added fresh S-basal. We repeated this process three times to ensure that that any dust or embryos washed from the plates were removed prior to use. We then placed a “slurper” tube into the 1.5 mL Eppendorf tube. After we sealed and pressurized the Eppendorf tube and slurper lid, animals flowed into the slurper tube, and we manually loaded animals, one at a time, into the imaging chamber of the microfluidic device. We measured all strains, one worm at a time. To quantify signal from the animals in microfluidic device, we mounted the device on a wooden jig under a LED-illuminated, fluorescent Leica MFC165 stereoscope  set to 12X magnification, equipped with a 1.0x Planapo objective and a Lumenera 3–3UR camera with a 0.63X optical coupler, in a room at approximately 20°. With this setup our depth of field was approximately 55 micrometers and our xy resolution was approximately 2.7 micrometers. We focused the image on the approximate central plane of the worm body by focusing on the grinder and lumen of the pharynx, shown in Fig. 42, using standard soft-lithography practices. Briefly, a microfluidic master mold was constructed in the University of Washington Nanofabrication facility using a transparency mask from OutputCity. The AutoCAD® design files are available at GitHub at https://github.com/nomadcrane/elegansImaging. The mold was made using SU8 2025 and following fabrication was coated with a monolayer of silane to prevent PDMS adhesion. The individual microfluidic devices were constructed using a two layer fabrication process similar to42 wherein a very small amount high pre-polymer to cross-linker (20:1) ratio of Sylgard 184 was poured on the microfluidic mold sufficient to cover the mold with 1–4 mm of polymer. This 20:1 ratio has a very low Young’s Modulus which allows the side valve mechanism to work. This base layer is partially cured for 45 minutes in a 70 °C oven, and then a volume of 10:1 (pre-polymer:cross-linker) Sylgard 184 is poured on top. Because the low Young’s Modulus layer is prone to damage or tearing due to the limited polymer cross-linking, this second layer provides much needed structural support for inlet hole punching and bonding. This stability layer is poured to a thickness of 15–20 mm.Devices are constructed as previously detailed inFollowing curing of the stability layer (2 + hours in 70 °C oven), devices are cut and removed from the mold. Holes for media and valves were punched using a 1 mm diameter biopsy punch. To ensure that PDMS debris was not introduced to the flow channels as a result of the hole punching, the quality of the biopsy punch was inspected prior to use, and holes were only punched cleanly once. All holes were punched from the device side through the low Young’s Modulus flow layer. Devices were cleaned using scotch tape prior to bonding to slide glass. Bonding was performed using a Harrick PDC-001 plasma cleaner. Devices and slide glass were exposed to high energy plasma for 35 seconds, and then the device was placed on the slide glass. Bonded devices were allowed to rest for at least 1 h in the 70 °C oven prior to use.To prevent diffusion of gas from the pressurized valves into the flow channels, valves were filled with water prior to use. This was done by connecting tubes containing DI water to the valve channels, and pressurizing the channels. The flushing media for the device used to push out the worms uses filtered M9 media containing 0.01% Triton X-100. To ensure that there was no cross-contamination between samples, the flushing media was used at moderate pressure for 5 min to rinse the device and the loading tubes. Loading and flushing pressures were optimized for each experimental run, but were typically within the range of 1–9 psi. The valve pressures were similarly optimized for individual variation in devices, but typically were used in the range of 45–60 psi.66. A complete list of parts is available on GitHub at https://github.com/nomadcrane/elegansImaging.To control both the valve pressures, and whether the valves are pressurized or released, we developed a control box composed of pressure regulators, solenoid valves, and a USB switch to provide computerized control of all on-chip valves. This system was modeled on earlier systemshttps://github.com/nomadcrane/elegansImaging.Computerized control of both the microfluidic valve control box and the microscope camera was implemented using custom written Matlab® software. To provide generalizability, all interaction with microscope and camera was implemented using micromanager, and controlled through Matlab®. The code, is freely available on GitHub at 67. Following subtraction of the camera noise from image, all animals containing transgenes with the same promoter/fluorescent protein combination were segmented using the same threshold. Segmented images were then opened to remove any spurious pixels. This whole animal segmentation provided consistent size measurements between strains, and had a high degree of accuracy when compared with manual segmentation of the brightfield images.Image segmentation was automated to ensure consistency in quantification of expression level between different strains. Images from all strains for the same promoter, fluorescent protein combination were loaded into memory, and an appropriate segmentation threshold that minimized intraclass variance was selected using Otsu’s thresholdThere are multiple sources of noise and variation that are generated during conventional epifluorescent imaging. To ensure we operated in the linear range of our camera, we quantified a mCherry dilution series we generated from lyophilized mCherry, shown in Supplementary Fig. 68 are relatively stronger when excited and imaged with mEGFP optics , compared to the same images acquired using an mCherry filter set. Because of this increased background effect, to accurately determine the level of fluorescence derived from the GFP transgene, it is critical to calculate and then remove the level of autofluorescence from the imaged cells69 .For those who care to undertake these endeavors comparing mCherry and mEGFP, we note that the intrinsic fluorescence signals emanating from secondary lysosomes and other intrinsically fluorescent (autofluorescent) bio molecules in wild-type N2 animals34, except that the animals were mounted in a microfluidic imaging chamber, described in64. Briefly, in four independent experiments we loaded animals expressing mEGFP or mCherry with or without introns, under control of the hsp-90 promoter, into 80-lane microfluidic mounting devices. We imaged the int1DL cell in ten animals per experiment for animals expressing reporter genes with and without introns in four independent experiments. We quantified expression level of reporters using the equatorial nuclear z slice from the image stacks of each animal, described in34, shown in Supplementary Fig. We performed microscopy as in34. Briefly, we synchronized three large populations of worms as described above, and placed the starved L1s onto five 10-cm OP50-seeded NGM plates @ 175 larvae per plate. Then, after 72 hours of development, for each strain , we used S-basal buffer to wash the adult animals off of the plates and into 15 mL conical vials and allowed the adults to sediment for five minutes, and then aspirated the L1-rich supernatant (the progeny of the adults) three times. We then placed these adult-enriched solutions of worms into the COPAS Biosort and measured fluorescent intensity using mCherry detection optics. We collected the data as a text file and then plotted and analyzed it using SigmaPlot 12.5 , shown in Supplementary Fig. We performed measurement of worms in flow as previously described inCaenorhabditis elegans (WBcel235 Ensembl release 94) and the human GRCh38 (Gencode v29 release GTF file). We used the Bioconductor GenomicRanges package (https://www.bioconductor.org/about/) to extract intron sizes in protein coding genes in C. elegans and H. sapiens. We plotted the log10 transformed intron size distribution for both C. elegans and H. sapiens using violin plots overlapped with boxplots, shown in Fig. To collect our data, we used GTF file for We used SigmaPlot 12.5  for all statistical analyses. We performed at least three independent experiments  for each of the strains we measured on our microfluidic device. To analyze the data, we first determined if the data was normally distributed and had equal variance using one or two-way ANOVA, and then performed appropriate statistical tests to account for multiple comparisons. We detail the major analyses used in this paper below.ia at the most 3′ position in the coding sequence, all other intron bearing strains expressed significantly more protein than the intronless strain; Kruskal-Wallis One Way Analysis of Variance on Ranks followed by Dunn’s Method, P < 0.05 for all comparisons. We performed at least three independent experiments with at least 100 total worms per strain . Synthetic introns significantly increase mCherry expression level under vit-2 control. Mann-Whitney Rank Sum Test, P < 0.001. Results are from three independent experiments with at least 130 total animals per group (134–163). The same three synthetic introns in mCherry significantly increase mEGFP expression level by 83%. P < 0.001, Two Way ANOVA followed by the Holm-Sidak method for multiple comparison procedures. Results are from three independent experiments measuring at least 200 total animals per group (215–260). Details for each of the statistical analyses performed in SigmaPlot are included in Supplementary Information.The specific statistical tests and results for the microfluidic measurements are as follows: Three synthetic introns increase expression level by 45.88%; P < 0.001, Mann-Whitney Rank Sum Test. Given that we measured several different strains compared to the control, we also performed a Kruskal-Wallis One Way Analysis of Variance on Ranks followed by Dunn’s Method to compare to the intronless control and detected a significant difference P < 0.05. At least three independent experiments with at least 185 animal were performed (185–297). Natural introns significantly increase the expression level of mCherry by 47.98%; P < 0.001, Mann-Whitney Rank Sum Test. Given that we measured several different strains compared to the control, we also performed a Kruskal-Wallis One Way Analysis of Variance on Ranks followed by Dunn’s Method to compare to the intronless control and detected a significant difference P < 0.05. We performed at least three experiments with at least 179 total animals were performed . With the exception of animals bearing the reporter gene with only Supplementary Infromation