Showing papers by "University of Washington published in 2022"

Structural basis of SARS-CoV-2 Omicron immune evasion and receptor engagement

Abstract: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant of concern evades antibody-mediated immunity that comes from vaccination or infection with earlier variants due to accumulation of numerous spike mutations. To understand the Omicron antigenic shift, we determined cryo-electron microscopy and x-ray crystal structures of the spike protein and the receptor-binding domain bound to the broadly neutralizing sarbecovirus monoclonal antibody (mAb) S309 (the parent mAb of sotrovimab) and to the human ACE2 receptor. We provide a blueprint for understanding the marked reduction of binding of other therapeutic mAbs that leads to dampened neutralizing activity. Remodeling of interactions between the Omicron receptor-binding domain and human ACE2 likely explains the enhanced affinity for the host receptor relative to the ancestral virus.

Association Between Immune Dysfunction and COVID-19 Breakthrough Infection After SARS-CoV-2 Vaccination in the US

Abstract:

Importance

Persons with immune dysfunction have a higher risk for severe COVID-19 outcomes. However, these patients were largely excluded from SARS-CoV-2 vaccine clinical trials, creating a large evidence gap.

Objective

To identify the incidence rate and incidence rate ratio (IRR) for COVID-19 breakthrough infection after SARS-CoV-2 vaccination among persons with or without immune dysfunction.

Design, Setting, and Participants

This retrospective cohort study analyzed data from the National COVID Cohort Collaborative (N3C), a partnership that developed a secure, centralized electronic medical record–based repository of COVID-19 clinical data from academic medical centers across the US. Persons who received at least 1 dose of a SARS-CoV-2 vaccine between December 10, 2020, and September 16, 2021, were included in the sample.

Main Outcomes and Measures

Vaccination, COVID-19 diagnosis, immune dysfunction diagnoses (ie, HIV infection, multiple sclerosis, rheumatoid arthritis, solid organ transplant, and bone marrow transplantation), other comorbid conditions, and demographic data were accessed through the N3C Data Enclave. Breakthrough infection was defined as a COVID-19 infection that was contracted on or after the 14th day of vaccination, and the risk after full or partial vaccination was assessed for patients with or without immune dysfunction using Poisson regression with robust SEs. Poisson regression models were controlled for a study period (before or after [pre– or post–Delta variant] June 20, 2021), full vaccination status, COVID-19 infection before vaccination, demographic characteristics, geographic location, and comorbidity burden.

Results

A total of 664 722 patients in the N3C sample were included. These patients had a median (IQR) age of 51 (34-66) years and were predominantly women (n = 378 307 [56.9%]). Overall, the incidence rate for COVID-19 breakthrough infection was 5.0 per 1000 person-months among fully vaccinated persons but was higher after the Delta variant became the dominant SARS-CoV-2 strain (incidence rate before vs after June 20, 2021, 2.2 [95% CI, 2.2-2.2] vs 7.3 [95% CI, 7.3-7.4] per 1000 person-months). Compared with partial vaccination, full vaccination was associated with a 28% reduced risk for breakthrough infection (adjusted IRR [AIRR], 0.72; 95% CI, 0.68-0.76). People with a breakthrough infection after full vaccination were more likely to be older and women. People with HIV infection (AIRR, 1.33; 95% CI, 1.18-1.49), rheumatoid arthritis (AIRR, 1.20; 95% CI, 1.09-1.32), and solid organ transplant (AIRR, 2.16; 95% CI, 1.96-2.38) had a higher rate of breakthrough infection.

Conclusions and Relevance

This cohort study found that full vaccination was associated with reduced risk of COVID-19 breakthrough infection, regardless of the immune status of patients. Despite full vaccination, persons with immune dysfunction had substantially higher risk for COVID-19 breakthrough infection than those without such a condition. For persons with immune dysfunction, continued use of nonpharmaceutical interventions (eg, mask wearing) and alternative vaccine strategies (eg, additional doses or immunogenicity testing) are recommended even after full vaccination.

Safety and immunogenicity of an inactivated COVID-19 vaccine, BBIBP-CorV, in people younger than 18 years: a randomised, double-blind, controlled, phase 1/2 trial

Abstract: Although SARS-CoV-2 infection often causes milder symptoms in children and adolescents, young people might still play a key part in SARS-CoV-2 transmission. An efficacious vaccine for children and adolescents could therefore assist pandemic control. For further evaluation of the inactivated COVID-19 vaccine candidate BBIBP-CorV, we assessed the safety and immunogenicity of BBIBP-CorV in participants aged 3-17 years.A randomised, double-blind, controlled, phase 1/2 trial was done at Shangqiu City Liangyuan District Center for Disease Control and Prevention in Henan, China. In phases 1 and 2, healthy participants were stratified according to age (3-5 years, 6-12 years, or 13-17 years) and dose group. Individuals with a history of SARS-CoV-2 or SARS-CoV infection were excluded. All participants were randomly assigned, using stratified block randomisation (block size eight), to receive three doses of 2 μg, 4 μg, or 8 μg of vaccine or control (1:1:1:1) 28 days apart. The primary outcome, safety, was analysed in the safety set, which consisted of participants who had received at least one vaccination after being randomly assigned, and had any safety evaluation information. The secondary outcomes were geometric meant titre (GMT) of the neutralising antibody against infectious SARS-CoV-2 and were analysed based on the full analysis set. This study is registered with www.chictr.org.cn, ChiCTR2000032459, and is ongoing.Between Aug 14, 2020, and Sept 24, 2020, 445 participants were screened, and 288 eligible participants were randomly assigned to vaccine (n=216, 24 for each dose level [2/4/8 μg] in each of three age cohorts [3-5, 6-12, and 13-17 years]) or control (n=72, 24 for each age cohort [3-5, 6-12, and 13-17 years]) in phase 1. In phase 2, 810 participants were screened and 720 eligible participants were randomly assigned and allocated to vaccine (n=540, 60 for each dose level [2/4/8 μg] in each of three age cohorts [3-5, 6-12, and 13-17 years]) or control (n=180, 60 for each age cohort [3-5, 6-12, and 13-17 years]). The most common injection site adverse reaction was pain (ten [4%] 251 participants in all vaccination groups of the 3-5 years cohort; 23 [9·1%] of 252 participants in all vaccination groups and one [1·2%] of 84 in the control group of the 6-12 years cohort; 20 [7·9%] of 252 participants in all vaccination groups of the 13-17 years cohort). The most common systematic adverse reaction was fever (32 [12·7%] of 251 participants in all vaccination groups and six [7·1%] of 84 participants in the control group of the 3-5 years cohort; 13 [5·2%] of 252 participants in the vaccination groups and one [1·2%] of 84 in the control group of the 6-12 years cohort; 26 [10·3%] of 252 participants in all vaccination groups and eight [9·5%] of 84 in the control group of the 13-17 years cohort). Adverse reactions were mostly mild to moderate in severity. The neutralising antibody GMT against the SARS-CoV-2 virus ranged from 105·3 to 180·2 in the 3-5 years cohort, 84·1 to 168·6 in the 6-12 years cohort, and 88·0 to 155·7 in the 13-17 years cohort on day 28 after the second vaccination; and ranged from 143·5 to 224·4 in the 3-5 years cohort, 127 to 184·8 in the 6-12 years cohort, and 150·7 to 199 in the 13-17 years cohort on day 28 after the third vaccination.The inactivated COVID-19 vaccine BBIBP-CorV is safe and well tolerated at all tested dose levels in participants aged 3-17 years. BBIBP-CorV also elicited robust humoral responses against SARS-CoV-2 infection after two doses. Our findings support the use of a 4 μg dose and two-shot regimen BBIBP-CorV in phase 3 trials in the population younger than 18 years to further ascertain its safety and protection efficacy against COVID-19.National Program on Key Research Project of China, National Mega projects of China for Major Infectious Diseases, National Mega Projects of China for New Drug Creation, and Beijing Science and Technology Plan.For the Chinese translation of the abstract see Supplementary Materials section.

Global Carbon Budget 2022

Abstract: Abstract. Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate is critical to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe and synthesize data sets and methodologies to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (EFOS) are based on energy statistics and cement production data, while emissions from land-use change (ELUC), mainly deforestation, are based on land use and land-use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly, and its growth rate (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) is estimated with global ocean biogeochemistry models and observation-based data products. The terrestrial CO2 sink (SLAND) is estimated with dynamic global vegetation models. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the year 2021, EFOS increased by 5.1 % relative to 2020, with fossil emissions at 10.1 ± 0.5 GtC yr−1 (9.9 ± 0.5 GtC yr−1 when the cement carbonation sink is included), and ELUC was 1.1 ± 0.7 GtC yr−1, for a total anthropogenic CO2 emission (including the cement carbonation sink) of 10.9 ± 0.8 GtC yr−1 (40.0 ± 2.9 GtCO2). Also, for 2021, GATM was 5.2 ± 0.2 GtC yr−1 (2.5 ± 0.1 ppm yr−1), SOCEAN was 2.9 ± 0.4 GtC yr−1, and SLAND was 3.5 ± 0.9 GtC yr−1, with a BIM of −0.6 GtC yr−1 (i.e. the total estimated sources were too low or sinks were too high). The global atmospheric CO2 concentration averaged over 2021 reached 414.71 ± 0.1 ppm. Preliminary data for 2022 suggest an increase in EFOS relative to 2021 of +1.0 % (0.1 % to 1.9 %) globally and atmospheric CO2 concentration reaching 417.2 ppm, more than 50 % above pre-industrial levels (around 278 ppm). Overall, the mean and trend in the components of the global carbon budget are consistently estimated over the period 1959–2021, but discrepancies of up to 1 GtC yr−1 persist for the representation of annual to semi-decadal variability in CO2 fluxes. Comparison of estimates from multiple approaches and observations shows (1) a persistent large uncertainty in the estimate of land-use change emissions, (2) a low agreement between the different methods on the magnitude of the land CO2 flux in the northern extratropics, and (3) a discrepancy between the different methods on the strength of the ocean sink over the last decade. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding of the global carbon cycle compared with previous publications of this data set. The data presented in this work are available at https://doi.org/10.18160/GCP-2022 (Friedlingstein et al., 2022b).

The 2021 flexible and printed electronics roadmap

Abstract: Author(s): Bonnassieux, Y; Brabec, CJ; Cao, Y; Carmichael, TB; Chabinyc, ML; Cheng, KT; Cho, G; Chung, A; Cobb, CL; Distler, A; Egelhaaf, HJ; Grau, G; Guo, X; Haghiashtiani, G; Huang, TC; Hussain, MM; Iniguez, B; Lee, TM; Li, L; Ma, Y; Ma, D; McAlpine, MC; Ng, TN; Osterbacka, R; Patel, SN; Peng, J; Peng, H; Rivnay, J; Shao, L; Steingart, D; Street, RA; Subramanian, V; Torsi, L; Wu, Y | Abstract: This roadmap includes the perspectives and visions of leading researchers in the key areas of flexible and printable electronics. The covered topics are broadly organized by the device technologies (sections 1–9), fabrication techniques (sections 10–12), and design and modeling approaches (sections 13 and 14) essential to the future development of new applications leveraging flexible electronics (FE). The interdisciplinary nature of this field involves everything from fundamental scientific discoveries to engineering challenges; from design and synthesis of new materials via novel device design to modelling and digital manufacturing of integrated systems. As such, this roadmap aims to serve as a resource on the current status and future challenges in the areas covered by the roadmap and to highlight the breadth and wide-ranging opportunities made available by FE technologies.

Non-Volatile Reconfigurable Silicon Photonics Based on Phase-Change Materials

Abstract: The traditional ways of tuning a silicon photonic network are mainly based on the thermo-optic effect or the free carrier dispersion. The drawbacks of these methods are the volatile nature and the extremely small change in the complex refractive index (Δn<0.001). In order to achieve low energy consumption and smaller footprint for applications such as photonic memories, optical computing, programmable gate array, and optical neural network, it is essential that the two optical states of the system exhibit high optical contrast and remain non-volatile. Phase change materials (PCMs) such as Ge2Sb2Te5 provide an excellent solution, thanks to the drastic contrast in refractive index between two states which can be switched reversibly and in a non-volatile fashion. Here, we review the recent progress in the field of non-volatile reconfigurable silicon photonics based on PCMs. We start with a general introduction to the material properties of PCMs that have been exploited in integrated photonics and discuss their operating wavelengths. The various photonic switches that are built upon these PCMs are reviewed. Lastly, we review the recent applications of PCM-based photonic integrated circuits and discuss the potential future directions of this field.

Structural definition of a pan-sarbecovirus neutralizing epitope on the spike S2 subunit

Abstract: Three betacoronaviruses have crossed the species barrier and established human-to-human transmission causing significant morbidity and mortality in the past 20 years. The most current and widespread of these is SARS-CoV-2. The identification of CoVs with zoonotic potential in animal reservoirs suggests that additional outbreaks could occur. Monoclonal antibodies targeting conserved neutralizing epitopes on diverse CoVs can form the basis for prophylaxis and therapeutic treatments and enable the design of vaccines aimed at providing pan-CoV protection. We previously identified a neutralizing monoclonal antibody, CV3-25 that binds to the SARS-CoV-2 spike, neutralizes the SARS-CoV-2 Beta variant comparably to the ancestral Wuhan Hu-1 strain, cross neutralizes SARS-CoV-1 and binds to recombinant proteins derived from the spike-ectodomains of HCoV-OC43 and HCoV-HKU1. Here, we show that the neutralizing activity of CV3-25 is maintained against the Alpha, Delta, Gamma and Omicron variants of concern as well as a SARS-CoV-like bat coronavirus with zoonotic potential by binding to a conserved linear peptide in the stem-helix region. Negative stain electron microscopy and a 1.74 Å crystal structure of a CV3-25/peptide complex demonstrates that CV3-25 binds to the base of the stem helix at the HR2 boundary to an epitope that is distinct from other stem-helix directed neutralizing mAbs.

Engineering the multiscale complexity of vascular networks

Abstract: The survival of vertebrate organisms depends on highly regulated delivery of oxygen and nutrients through vascular networks that pervade nearly all tissues in the body. Dysregulation of these vascular networks is implicated in many common human diseases such as hypertension, coronary artery disease, diabetes and cancer. Therefore, engineers have sought to create vascular networks within engineered tissues for applications such as regenerative therapies, human disease modelling and pharmacological testing. Yet engineering vascular networks has historically remained difficult, owing to both incomplete understanding of vascular structure and technical limitations for vascular fabrication. This Review highlights the materials advances that have enabled transformative progress in vascular engineering by ushering in new tools for both visualizing and building vasculature. New methods such as bioprinting, organoids and microfluidic systems are discussed, which have enabled the fabrication of 3D vascular topologies at a cellular scale with lumen perfusion. These approaches to vascular engineering are categorized into technology-driven and nature-driven approaches. Finally, the remaining knowledge gaps, emerging frontiers and opportunities for this field are highlighted, including the steps required to replicate the multiscale complexity of vascular networks found in nature.

Regiospecific N-alkyl substitution tunes the molecular packing of high-performance non-fullerene acceptors

Abstract: The rapid development of non-fullerene acceptors (NFAs) with strong near-infrared absorption has led to remarkably enhanced short-circuit current density (Jsc) values in organic solar cells (OSCs). NFAs based on the benzotriazole (Bz) fused-ring π-core have great potential in delivering both high Jsc and decent open-circuit voltage values due to their strong intramolecular charge transfer with reasonably low energy loss. In this work, we have designed and synthesized a series of Bz-based NFAs, PN6SBO-4F, AN6SBO-4F and EHN6SEH-4F, via regiospecific N-alkyl engineering based on the high-performance NFA mBzS-4F that was reported previously. The molecular packing of mBzS-4F, AN6SBO-4F, and EHN6SEH-4F single crystals was analyzed using X-ray crystallography in order to provide a comprehensive understanding of the correlation between the molecular structure, the charge-transporting properties, and the solar cell performance. Compared with the typical honeycomb single-crystal structure of Y6 derivatives, these NFAs exhibit distinctly different molecular packing patterns. The strong interactions of terminal indanone groups in mBzS-4F and the J-aggregate-like packing in EHN6SEH-4F lead to the formation of ordered 3D networks in single-crystals with channels for efficient charge transport. Consequently, OSCs based on mBzS-4F and EHN6SEH-4F show efficient photon-to-current conversions, achieving the highest power conversion efficiency of 17.48% with a Jsc of 28.83 mA cm−2.

Opportunistic experiments to constrain aerosol effective radiative forcing

Abstract: Aerosol-cloud interactions (ACIs) are considered to be the most uncertain driver of present-day radiative forcing due to human activities. The nonlinearity of cloud-state changes to aerosol perturbations make it challenging to attribute causality in observed relationships of aerosol radiative forcing. Using correlations to infer causality can be challenging when meteorological variability also drives both aerosol and cloud changes independently. Natural and anthropogenic aerosol perturbations from well-defined sources provide "opportunistic experiments" (also known as natural experiments) to investigate ACI in cases where causality may be more confidently inferred. These perturbations cover a wide range of locations and spatiotemporal scales, including point sources such as volcanic eruptions or industrial sources, plumes from biomass burning or forest fires, and tracks from individual ships or shipping corridors. We review the different experimental conditions and conduct a synthesis of the available satellite datasets and field campaigns to place these opportunistic experiments on a common footing, facilitating new insights and a clearer understanding of key uncertainties in aerosol radiative forcing. Cloud albedo perturbations are strongly sensitive to background meteorological conditions. Strong liquid water path increases due to aerosol perturbations are largely ruled out by averaging across experiments. Opportunistic experiments have significantly improved process-level understanding of ACI, but it remains unclear how reliably the relationships found can be scaled to the global level, thus demonstrating a need for deeper investigation in order to improve assessments of aerosol radiative forcing and climate change.

A Crash Course in Good and Bad Controls

Abstract: Many students of statistics and econometrics express frustration with the way a problem known as “bad control” is treated in the traditional literature. The issue arises when the addition of a variable to a regression equation produces an unintended discrepancy between the regression coefficient and the effect that the coefficient is intended to represent. Avoiding such discrepancies presents a challenge to all analysts in the data intensive sciences. This note describes graphical tools for understanding, visualizing, and resolving the problem through a series of illustrative examples. By making this “crash course” accessible to instructors and practitioners, we hope to avail these tools to a broader community of scientists concerned with the causal interpretation of regression models.

Design and synthesis of chromophores with enhanced electro-optic activities in both bulk and plasmonic–organic hybrid devices

Abstract: This study demonstrates enhancement of in-device electro-optic activity via a series of theory-inspired organic electro-optic (OEO) chromophores based on strong (diarylamino)phenyl electron donating moieties. These chromophores are tuned to minimize trade-offs between molecular hyperpolarizability and optical loss. Hyper-Rayleigh scattering (HRS) measurements demonstrate that these chromophores, herein described as BAH, show >2-fold improvement in β versus standard chromophores such as JRD1, and approach that of the recent BTP and BAY chromophore families. Electric field poled bulk devices of neat and binary BAH chromophores exhibited significantly enhanced EO coefficients (r33) and poling efficiencies (r33/Ep) compared with state-of-the-art chromophores such as JRD1. The neat BAH13 devices with charge blocking layers produced very large poling efficiencies of 11.6 ± 0.7 nm2 V−2 and maximum r33 value of 1100 ± 100 pm V−1 at 1310 nm on hafnium dioxide (HfO2). These results were comparable to that of our recently reported BAY1 but with much lower loss (extinction coefficient, k), and greatly exceeding that of other previously reported OEO compounds. 3 : 1 BAH-FD : BAH13 blends showed a poling efficiency of 6.7 ± 0.3 nm2 V−2 and an even greater reduction in k. 1 : 1 BAH-BB : BAH13 showed a higher poling efficiency of 8.4 ± 0.3 nm2 V−2, which is approximately a 2.5-fold enhancement in poling efficiency vs. JRD1. Neat BAH13 was evaluated in plasmonic–organic hybrid (POH) Mach–Zehnder modulators with a phase shifter length of 10 μm and slot widths of 80 and 105 nm. In-device BAH13 achieved a maximum r33 of 208 pm V−1 at 1550 nm, which is ∼1.7 times higher than JRD1 under equivalent conditions.

Robust deep learning based protein sequence design using ProteinMPNN

Abstract: Abstract While deep learning has revolutionized protein structure prediction, almost all experimentally characterized de novo protein designs have been generated using physically based approaches such as Rosetta. Here we describe a deep learning based protein sequence design method, ProteinMPNN, with outstanding performance in both in silico and experimental tests. The amino acid sequence at different positions can be coupled between single or multiple chains, enabling application to a wide range of current protein design challenges. On native protein backbones, ProteinMPNN has a sequence recovery of 52.4%, compared to 32.9% for Rosetta. Incorporation of noise during training improves sequence recovery on protein structure models, and produces sequences which more robustly encode their structures as assessed using structure prediction algorithms. We demonstrate the broad utility and high accuracy of ProteinMPNN using X-ray crystallography, cryoEM and functional studies by rescuing previously failed designs, made using Rosetta or AlphaFold, of protein monomers, cyclic homo-oligomers, tetrahedral nanoparticles, and target binding proteins. One-sentence summary A deep learning based protein sequence design method is described that is widely applicable to current design challenges and shows outstanding performance in both in silico and experimental tests.

Omnipose: a high-precision morphology-independent solution for bacterial cell segmentation

Abstract: Advances in microscopy hold great promise for allowing quantitative and precise measurement of morphological and molecular phenomena at the single-cell level in bacteria; however, the potential of this approach is ultimately limited by the availability of methods to faithfully segment cells independent of their morphological or optical characteristics. Here, we present Omnipose, a deep neural network image-segmentation algorithm. Unique network outputs such as the gradient of the distance field allow Omnipose to accurately segment cells on which current algorithms, including its predecessor, Cellpose, produce errors. We show that Omnipose achieves unprecedented segmentation performance on mixed bacterial cultures, antibiotic-treated cells and cells of elongated or branched morphology. Furthermore, the benefits of Omnipose extend to non-bacterial subjects, varied imaging modalities and three-dimensional objects. Finally, we demonstrate the utility of Omnipose in the characterization of extreme morphological phenotypes that arise during interbacterial antagonism. Our results distinguish Omnipose as a powerful tool for characterizing diverse and arbitrarily shaped cell types from imaging data.

StainedGlass: interactive visualization of massive tandem repeat structures with identity heatmaps

Abstract: Abstract Summary The visualization and analysis of genomic repeats is typically accomplished using dot plots; however, the emergence of telomere-to-telomere assemblies with multi-megabase repeats requires new visualization strategies. Here, we introduce StainedGlass, which can generate publication-quality figures and interactive visualizations that depict the identity and orientation of multi-megabase tandem repeat structures at a genome-wide scale. The tool can rapidly reveal higher-order structures and improve the inference of evolutionary history for some of the most complex regions of genomes. Availability and implementation StainedGlass is implemented using Snakemake and available open source under the MIT license at https://mrvollger.github.io/StainedGlass/. Supplementary information Supplementary data are available at Bioinformatics online.

The Alzheimer’s gene SORL1 is a regulator of endosomal traffic and recycling in human neurons

Abstract: Loss of the Sortilin-related receptor 1 (SORL1) gene seems to act as a causal event for Alzheimer's disease (AD). Recent studies have established that loss of SORL1, as well as mutations in autosomal dominant AD genes APP and PSEN1/2, pathogenically converge by swelling early endosomes, AD's cytopathological hallmark. Acting together with the retromer trafficking complex, SORL1 has been shown to regulate the recycling of the amyloid precursor protein (APP) out of the endosome, contributing to endosomal swelling and to APP misprocessing. We hypothesized that SORL1 plays a broader role in neuronal endosomal recycling and used human induced pluripotent stem cell-derived neurons (hiPSC-Ns) to test this hypothesis. We examined endosomal recycling of three transmembrane proteins linked to AD pathophysiology: APP, the BDNF receptor Tropomyosin-related kinase B (TRKB), and the glutamate receptor subunit AMPA1 (GLUA1).We used isogenic hiPSCs engineered to have SORL1 depleted or to have enhanced SORL1 expression. We differentiated neurons from these cell lines and mapped the trafficking of APP, TRKB and GLUA1 within the endosomal network using confocal microscopy. We also performed cell surface recycling and lysosomal degradation assays to assess the functionality of the endosomal network in both SORL1-depleted and -overexpressing neurons. The functional impact of GLUA1 recycling was determined by measuring synaptic activity. Finally, we analyzed alterations in gene expression in SORL1-depleted neurons using RNA sequencing.We find that as with APP, endosomal trafficking of GLUA1 and TRKB is impaired by loss of SORL1. We show that trafficking of all three cargoes to late endosomes and lysosomes is affected by manipulating SORL1 expression. We also show that depletion of SORL1 significantly impacts the endosomal recycling pathway for APP and GLUA1 at the level of the recycling endosome and trafficking to the cell surface. This has a functional effect on neuronal activity as shown by multi-electrode array (MEA). Conversely, increased SORL1 expression enhances endosomal recycling for APP and GLUA1. Our unbiased transcriptomic data further support SORL1's role in endosomal recycling. We observe altered expression networks that regulate cell surface trafficking and neurotrophic signaling in SORL1-depleted neurons.Collectively, and together with other recent observations, these findings suggest that one role for SORL1 is to contribute to endosomal degradation and recycling pathways in neurons, a conclusion that has both pathogenic and therapeutic implications for Alzheimer's disease.