Harnessing the NEON data revolution to advance open environmental science with a diverse and data-capable community

It is a critical time to reflect on the National Ecological Observatory Network (NEON) science to date as well as envision what research can be done right now with NEON (and other) data and what training is needed to enable a diverse user community. NEON became fully operational in May 2019 and has pivoted from planning and construction to operation and maintenance. In this overview, the history of and foundational thinking around NEON are discussed. A framework of open science is described with a discussion of how NEON can be situated as part of a larger data constellation—across existing networks and different suites of ecological measurements and sensors. Next, a synthesis of early NEON science, based on \u3e100 existing publications, funded proposal efforts, and emergent science at the very first NEON Science Summit (hosted by Earth Lab at the University of Colorado Boulder in October 2019) is provided. Key questions that the ecology community will address with NEON data in the next 10 yr are outlined, from understanding drivers of biodiversity across spatial and temporal scales to defining complex feedback mechanisms in human–environmental systems. Last, the essential elements needed to engage and support a diverse and inclusive NEON user community are highlighted: training resources and tools that are openly available, funding for broad community engagement initiatives, and a mechanism to share and advertise those opportunities. NEON users require both the skills to work with NEON data and the ecological or environmental science domain knowledge to understand and interpret them. This paper synthesizes early directions in the community’s use of NEON data, and opportunities for the next 10 yr of NEON operations in emergent science themes, open science best practices, education and training, and community building

Harnessing the NEON data revolution to advance open environmental science with a diverse and data-capable community

It is a critical time to reflect on the National Ecological Observatory Network (NEON) science to date as well as envision what research can be done right now with NEON (and other) data and what training is needed to enable a diverse user community. NEON became fully operational in May 2019 and has pivoted from planning and construction to operation and maintenance. In this overview, the history of and foundational thinking around NEON are discussed. A framework of open science is described with a discussion of how NEON can be situated as part of a larger data constellation—across existing networks and different suites of ecological measurements and sensors. Next, a synthesis of early NEON science, based on >100 existing publications, funded proposal efforts, and emergent science at the very first NEON Science Summit (hosted by Earth Lab at the University of Colorado Boulder in October 2019) is provided. Key questions that the ecology community will address with NEON data in the next 10 yr are outlined, from understanding drivers of biodiversity across spatial and temporal scales to defining complex feedback mechanisms in human–environmental systems. Last, the essential elements needed to engage and support a diverse and inclusive NEON user community are highlighted: training resources and tools that are openly available, funding for broad community engagement initiatives, and a mechanism to share and advertise those opportunities. NEON users require both the skills to work with NEON data and the ecological or environmental science domain knowledge to understand and interpret them. This paper synthesizes early directions in the community’s use of NEON data, and opportunities for the next 10 yr of NEON operations in emergent science themes, open science best practices, education and training, and community building

Universal Method for the Purification of Recombinant AAV Vectors of Differing Serotypes

The generation of clinical good manufacturing practices (GMP)-grade adeno-associated virus (AAV) vectors requires purification strategies that support the generation of vectors of high purity, and that exhibit a good safety and efficacy profile. To date, most reported purification schemas are serotype dependent, requiring method development for each AAV gene therapy product. Here, we describe a platform purification process that is compatible with the purification of multiple AAV serotypes. The method generates vector preparations of high purity that are enriched for capsids with full vector genomes, and that minimizes the fractional content of empty capsids. The two-column purification method, a combination of affinity and ion exchange chromatographies, is compatible with a range of AAV serotypes generated by either the transient triple transfection method or the more scalable producer cell line platform. In summary, the adaptable purification method described can be used for the production of a variety of high-quality AAV vectors suitable for preclinical testing in animal models of diseases. Keywords: AAV purification, epitope swapping, analytical ultracentrifugatio

CNS-targeted gene therapy improves survival and motor function in a mouse model of spinal muscular atrophy

Spinal muscular atrophy (SMA) is a neuromuscular disease caused by a deficiency of survival motor neuron (SMN) due to mutations in the SMN1 gene. In this study, an adeno-associated virus (AAV) vector expressing human SMN (AAV8-hSMN) was injected at birth into the CNS of mice modeling SMA. Western blot analysis showed that these injections resulted in widespread expression of SMN throughout the spinal cord, and this translated into robust improvement in skeletal muscle physiology, including increased myofiber size and improved neuromuscular junction architecture. Treated mice also displayed substantial improvements on behavioral tests of muscle strength, coordination, and locomotion, indicating that the neuromuscular junction was functional. Treatment with AAV8-hSMN increased the median life span of mice with SMA-like disease to 50 days compared with 15 days for untreated controls. Moreover, injecting mice with SMA-like disease with a human SMN–expressing self-complementary AAV vector — a vector that leads to earlier onset of gene expression compared with standard AAV vectors — led to improved efficacy of gene therapy, including a substantial extension in median survival to 157 days. These data indicate that CNS-directed, AAV-mediated SMN augmentation is highly efficacious in addressing both neuronal and muscular pathologies in a severe mouse model of SMA

Harnessing the NEON data revolution to advance open environmental science with a diverse and data‐capable community

It is a critical time to reflect on the National Ecological Observatory Network (NEON) science to date as well as envision what research can be done right now with NEON (and other) data and what training is needed to enable a diverse user community. NEON became fully operational in May 2019 and has pivoted from planning and construction to operation and maintenance. In this overview, the history of and foundational thinking around NEON are discussed. A framework of open science is described with a discussion of how NEON can be situated as part of a larger data constellation — across existing networks and different suites of ecological measurements and sensors. Next, a synthesis of early NEON science, based on >100 existing publications, funded proposal efforts, and emergent science at the very first NEON Science Summit (hosted by Earth Lab at the University of Colorado Boulder in October 2019) is provided. Key questions that the ecology community will address with NEON data in the next 10 yr are outlined, from understanding drivers of biodiversity across spatial and temporal scales to defining complex feedback mechanisms in human–environmental systems. Last, the essential elements needed to engage and support a diverse and inclusive NEON user community are highlighted: training resources and tools that are openly available, funding for broad community engagement initiatives, and a mechanism to share and advertise those opportunities. NEON users require both the skills to work with NEON data and the ecological or environmental science domain knowledge to understand and interpret them. This paper synthesizes early directions in the community’s use of NEON data, and opportunities for the next 10 yr of NEON operations in emergent science themes, open science best practices, education and training, and community building