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  1. ; ; ; ( , ACM Journal on Emerging Technologies in Computing Systems)
    As interest in DNA-based information storage grows, the costs of synthesis have been identified as a key bottleneck. A potential direction is to tune synthesis for data. Data strands tend to be composed of a small set of recurring code word sequences, and they contain longer sequences of repeated data. To exploit these properties, we propose a new framework called DINOS. DINOS consists of three key parts: (i) The first is a hierarchical strand assembly algorithm, inspired by gene assembly techniques that can assemble arbitrary data strands from a small set of primitive blocks. (ii) The assembly algorithm relies onmore »our novel formulation for how to construct primitive blocks, spanning a variety of useful configurations from a set of code words and overhangs. Each primitive block is a code word flanked by a pair of overhangs that are created by a cyclic pairing process that keeps the number of primitive blocks small. Using these primitive blocks, any data strand of arbitrary length can be assembled, theoretically. We show a minimal system for a binary code with as few as six primitive blocks, and we generalize our processes to support an arbitrary set of overhangs and code words. (iii) We exploit our hierarchical assembly approach to identify redundant sequences and coalesce the reactions that create them to make assembly more efficient. We evaluate DINOS and describe its key characteristics. For example, the number of reactions needed to make a strand can be reduced by increasing the number of overhangs or the number of code words, but increasing the number of overhangs offers a small advantage over increasing code words while requiring substantially fewer primitive blocks. However, density is improved more by increasing the number of code words. We also find that a simple redundancy coalescing technique is able to reduce reactions by 90.6% and 41.2% on average for decompressed and compressed data, respectively, even when the smallest data fragments being assembled are 16 bits. With a simple padding heuristic that finds even more redundancy, we can further decrease reactions for the same operating point up to 91.1% and 59% for decompressed and compressed data, respectively, on average. Our approach offers greater density by up to 80% over a prior general purpose gene assembly technique. Finally, in an analysis of synthesis costs in which we make 1 GB volume using de novo synthesis versus making only the primitive blocks with de novo synthesis and otherwise assembling using DINOS, we estimate DINOS as 10 5 × cheaper than de novo synthesis.« less
    Free, publicly-accessible full text available July 31, 2023
  2. ; ; ( , International Journal of Molecular Sciences)
    Histone post-translational modifications are small chemical changes to the histone protein structure that have cascading effects on diverse cellular functions. Detecting histone modifications and characterizing their binding partners are critical steps in understanding chromatin biochemistry and have been accessed using common reagents such as antibodies, recombinant assays, and FRET-based systems. High-throughput platforms could accelerate work in this field, and also could be used to engineer de novo histone affinity reagents; yet, published studies on their use with histones have been noticeably sparse. Here, we describe specific experimental conditions that affect binding specificities of post-translationally modified histones in classic protein engineeringmore »platforms and likely explain the relative difficulty with histone targets in these platforms. We also show that manipulating avidity of binding interactions may improve specificity of binding.« less
    Free, publicly-accessible full text available February 1, 2023
  3. ; ; ( , Scientific Reports)
    Abstract UBE3A is an E3 ubiquitin ligase encoded by the neurally imprinted UBE3A gene. The abundance and subcellular distribution of UBE3A has been the topic of many previous studies as its dosage and localization has been linked to neurodevelopmental disorders including Autism, Dup15q syndrome, and Angelman syndrome. While commercially available antibodies have been widely employed to determine UBE3A localization, an extensive analysis and comparison of the performance of different UBE3A antibodies has not been conducted. Here we evaluated the specificities of seven commercial UBE3A antibodies in two of the major experimental models used in UBE3A research, mouse and human pluripotentmore »stem cell-derived neural cells and tissues. We tested these antibodies in their two most common assays, immunofluorescence and western blot. In addition, we also assessed the ability of these antibodies to capture dynamic spatiotemporal changes of UBE3A by utilizing human cerebral organoid models. Our results reveal that among the seven antibodies tested, three antibodies demonstrated substantial nonspecific immunoreactivity. While four antibodies show specific localization patterns in both mouse brain sections and human cerebral organoids, these antibodies varied significantly in background signals and staining patterns in undifferentiated human pluripotent stem cells.« less
    Free, publicly-accessible full text available December 1, 2022
  4. ; ; ; ; ( , Cell Systems)
    Free, publicly-accessible full text available November 1, 2022
  5. ; ; ; ; ( , Water Resources Research)
    Free, publicly-accessible full text available October 1, 2022
  6. ; ; ; ; ; ; ; ; ; ; et al ( , Geoscientific Model Development)
    Abstract. Computational modeling occupies a unique niche in Earth and environmental sciences. Models serve not just as scientific technology and infrastructure but also as digital containers of the scientific community's understanding of the natural world. As this understanding improves, so too must the associated software. This dual nature – models as both infrastructure and hypotheses – means that modeling software must be designed to evolve continually as geoscientific knowledge itself evolves. Here we describe design principles, protocols, and tools developed by the Community Surface Dynamics Modeling System (CSDMS) to promote a flexible, interoperable, and ever-improving research software ecosystem. These includemore »a community repository for model sharing and metadata, interface and ontology standards for model interoperability, language-bridging tools, a modular programming library for model construction, modular software components for data access, and a Python-based execution and model-coupling framework. Methods of community support and engagement that help create a community-centered software ecosystem are also discussed.« less
    Free, publicly-accessible full text available January 1, 2023
  7. ; ; ; ; ; ; ; ; ( , Science)
    Rivers originating in High Mountain Asia are crucial lifelines for one-third of the world’s population. These fragile headwaters are now experiencing amplified climate change, glacier melt, and permafrost thaw. Observational data from 28 headwater basins demonstrate substantial increases in both annual runoff and annual sediment fluxes across the past six decades. The increases are accelerating from the mid-1990s in response to a warmer and wetter climate. The total sediment flux from High Mountain Asia is projected to more than double by 2050 under an extreme climate change scenario. These findings have far-reaching implications for the region’s hydropower, food, and environmentalmore »security.« less
    Free, publicly-accessible full text available October 29, 2022
  8. ; ; ; ; ; ; ; ( , Environmental Modelling & Software)
    Free, publicly-accessible full text available October 1, 2022
  9. ; ; ( , Cell Chemical Biology)
    Full Text Available 
  10. ; ; ; ; ; ( , Physics of Plasmas)
    Full Text Available