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Open Access Publications from the University of California

Scholarly Works (7 results)

  • Thesis
  • Peer Reviewed
UCLA Electronic Theses and Dissertations (2018)

Our ability to read and write DNA is fundamental for understanding Biology. While the past decade has brought about exponential improvements in our DNA sequencing and synthesis capabilities, major challenges remain. First, many DNA sequencers are hindered by their short read lengths, which has hindered genome assemblies, molecular haplotyping, and more recently, multiplexed functional assays. Synthetic Long Reads (SLRs) are a recently developed method that address this issue. SLRs leverage molecular barcodes to guide the computational reassembly of multiple short reads into a longer contiguous molecule. Here we present a novel SLR technology, BAGEL-seq, that can theoretically sequence molecules up to 40 kb, and achieve read lengths of ~1 kb in a proof-of-principle experiment. Second, large-scale synthesis of gene-length, synthetic DNA is cost-prohibitive for many research applications. We present two complementary methods to address this limitation – one to quantify errors in synthetic gene constructs using next-generation sequencing (NGS), and another, DropSynth, to synthesize > 10,000 ~1 kb genes using emulsions and DNA microarrays. Despite these limitations, researcher have recently leveraged DNA sequencing and synthesis to test the functional effects of thousands of variants in multiplex. Known as multiplexed functional assays (MFAs), these experiments have revolutionized the investigation of biological processes across the Central Dogma. In this dissertation we present three different MFAs. In the first, we used DropSynth to build homologogs of an essential E. coli protein, and tested their function in a complimentation assay. In the second, we measured the response of 39 murine olfactory receptors against hundreds of different odorants. Lastly, we assessed the effects of ~7,800 single amino acid changes to the Beta2-adrenergic receptor in the presence of increasing agonist concentration. Taken together, this dissertation represents a fundamental improvement in our ability to read and write DNA, and pushes the state of the art in combining these technologies for large-scale, multiplexed experiments.

    Cover page: Methods for Multiplexed Biology
    • Article
    • Peer Reviewed
    UCLA Previously Published Works (2020)
    Multiplexed assays allow functional testing of large synthetic libraries of genetic elements, but are limited by the designability, length, fidelity and scale of the input DNA. Here, we improve DropSynth, a low-cost, multiplexed method that builds gene libraries by compartmentalizing and assembling microarray-derived oligonucleotides in vortexed emulsions. By optimizing enzyme choice, adding enzymatic error correction and increasing scale, we show that DropSynth can build thousands of gene-length fragments at >20% fidelity.
      Cover page: DropSynth 2.0: high-fidelity multiplexed gene synthesis in emulsions
      • Article
      • Peer Reviewed
      UCLA Previously Published Works (2017)
      Gene synthesis, the process of assembling gene-length fragments from shorter groups of oligonucleotides (oligos), is becoming an increasingly important tool in molecular and synthetic biology. The length, quality and cost of gene synthesis are limited by errors produced during oligo synthesis and subsequent assembly. Enzymatic error correction methods are cost-effective means to ameliorate errors in gene synthesis. Previous analyses of these methods relied on cloning and Sanger sequencing to evaluate their efficiencies, limiting quantitative assessment. Here, we develop a method to quantify errors in synthetic DNA by next-generation sequencing. We analyzed errors in model gene assemblies and systematically compared six different error correction enzymes across 11 conditions. We find that ErrASE and T7 Endonuclease I are the most effective at decreasing average error rates (up to 5.8-fold relative to the input), whereas MutS is the best for increasing the number of perfect assemblies (up to 25.2-fold). We are able to quantify differential specificities such as ErrASE preferentially corrects C/G transversions whereas T7 Endonuclease I preferentially corrects A/T transversions. More generally, this experimental and computational pipeline is a fast, scalable and extensible way to analyze errors in gene assemblies, to profile error correction methods, and to benchmark DNA synthesis methods.
        Cover page: A systematic comparison of error correction enzymes by next-generation sequencing
        • Article
        • Peer Reviewed
        UCLA Previously Published Works (2020)
        Scalable, inexpensive, accurate, and secure testing for SARS-CoV-2 infection is crucial for control of the novel coronavirus pandemic. Recently developed highly multiplexed sequencing assays that rely on high-throughput sequencing (HMSAs) can, in principle, meet these demands, and present promising alternatives to currently used RT-qPCR-based tests. However, the analysis and interpretation of HMSAs requires overcoming several computational and statistical challenges. Using recently acquired experimental data, we present and validate an accurate and fast computational testing workflow based on kallisto and bustools, that utilize robust statistical methods and fast, memory efficient algorithms for processing high-throughput sequencing data. We show that our workflow is effective at processing data from all recently proposed SARS-CoV-2 sequencing based diagnostic tests, and is generally applicable to any diagnostic HMSAs.
          Cover page: Fast and accurate diagnostics from highly multiplexed sequencing assays
          • Article
          • Peer Reviewed
          UCLA Previously Published Works (2020)
          The >800 human G protein-coupled receptors (GPCRs) are responsible for transducing diverse chemical stimuli to alter cell state- and are the largest class of drug targets. Their myriad structural conformations and various modes of signaling make it challenging to understand their structure and function. Here, we developed a platform to characterize large libraries of GPCR variants in human cell lines with a barcoded transcriptional reporter of G protein signal transduction. We tested 7800 of 7828 possible single amino acid substitutions to the beta-2 adrenergic receptor (β2AR) at four concentrations of the agonist isoproterenol. We identified residues specifically important for β2AR signaling, mutations in the human population that are potentially loss of function, and residues that modulate basal activity. Using unsupervised learning, we identify residues critical for signaling, including all major structural motifs and molecular interfaces. We also find a previously uncharacterized structural latch spanning the first two extracellular loops that is highly conserved across Class A GPCRs and is conformationally rigid in both the inactive and active states of the receptor. More broadly, by linking deep mutational scanning with engineered transcriptional reporters, we establish a generalizable method for exploring pharmacogenomics, structure and function across broad classes of drug receptors.
            Cover page: Structural and functional characterization of G protein-coupled receptors with deep mutational scanning
            • Article
            • Peer Reviewed
            UCLA Previously Published Works (2020)

            ABSTRACT

            The rapid spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is due to the high rates of transmission by individuals who are asymptomatic at the time of transmission 1, 2 . Frequent, widespread testing of the asymptomatic population for SARS-CoV-2 is essential to suppress viral transmission. Despite increases in testing capacity, multiple challenges remain in deploying traditional reverse transcription and quantitative PCR (RT-qPCR) tests at the scale required for population screening of asymptomatic individuals. We have developed SwabSeq, a high-throughput testing platform for SARS-CoV-2 that uses next-generation sequencing as a readout. SwabSeq employs sample-specific molecular barcodes to enable thousands of samples to be combined and simultaneously analyzed for the presence or absence of SARS-CoV-2 in a single run. Importantly, SwabSeq incorporates an in vitro RNA standard that mimics the viral amplicon, but can be distinguished by sequencing. This standard allows for end-point rather than quantitative PCR, improves quantitation, reduces requirements for automation and sample-to-sample normalization, enables purification-free detection, and gives better ability to call true negatives. After setting up SwabSeq in a high-complexity CLIA laboratory, we performed more than 80,000 tests for COVID-19 in less than two months, confirming in a real world setting that SwabSeq inexpensively delivers highly sensitive and specific results at scale, with a turn-around of less than 24 hours. Our clinical laboratory uses SwabSeq to test both nasal and saliva samples without RNA extraction, while maintaining analytical sensitivity comparable to or better than traditional RT-qPCR tests. Moving forward, SwabSeq can rapidly scale up testing to mitigate devastating spread of novel pathogens.
              Cover page: Swab-Seq: A high-throughput platform for massively scaled up SARS-CoV-2 testing
              • Article
              • Peer Reviewed
              UCLA Previously Published Works (2021)
              Frequent and widespread testing of members of the population who are asymptomatic for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is essential for the mitigation of the transmission of the virus. Despite the recent increases in testing capacity, tests based on quantitative polymerase chain reaction (qPCR) assays cannot be easily deployed at the scale required for population-wide screening. Here, we show that next-generation sequencing of pooled samples tagged with sample-specific molecular barcodes enables the testing of thousands of nasal or saliva samples for SARS-CoV-2 RNA in a single run without the need for RNA extraction. The assay, which we named SwabSeq, incorporates a synthetic RNA standard that facilitates end-point quantification and the calling of true negatives, and that reduces the requirements for automation, purification and sample-to-sample normalization. We used SwabSeq to perform 80,000 tests, with an analytical sensitivity and specificity comparable to or better than traditional qPCR tests, in less than two months with turnaround times of less than 24 h. SwabSeq could be rapidly adapted for the detection of other pathogens.
                Cover page: Massively scaled-up testing for SARS-CoV-2 RNA via next-generation sequencing of pooled and barcoded nasal and saliva samples.
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