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uPIC–M: Efficient and Scalable Preparation of Clonal Single Mutant Libraries for High-Throughput Protein Biochemistry
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  • Mason J. Appel
    Mason J. Appel
    Department of Biochemistry, Stanford University, Stanford, California 94305, United States
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    Orcidhttps://orcid.org/0000-0001-7501-8115
  • Scott A. Longwell
    Scott A. Longwell
    Department of Bioengineering, Stanford University, Stanford, California 94305, United States
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  • Maurizio Morri
    Maurizio Morri
    Chan Zuckerberg Biohub, San Francisco, California 94110, United States
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  • Norma Neff
    Norma Neff
    Chan Zuckerberg Biohub, San Francisco, California 94110, United States
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  • Daniel Herschlag*
    Daniel Herschlag
    Department of Biochemistry, Stanford University, Stanford, California 94305, United States
    *Email: [email protected]
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    Orcidhttps://orcid.org/0000-0002-4685-1973
  • Polly M. Fordyce*
    Polly M. Fordyce
    Department of Bioengineering, Stanford University, Stanford, California 94305, United States
    Chan Zuckerberg Biohub, San Francisco, California 94110, United States
    Department of Genetics, Stanford University, Stanford, California 94305, United States
    ChEM-H Institute, Stanford University, Stanford, California 94305, United States
    *Email: [email protected]
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    Orcidhttps://orcid.org/0000-0002-9505-0638
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ACS Omega

Cite this: ACS Omega 2021, 6, 45, 30542–30554
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https://doi.org/10.1021/acsomega.1c04180
Published November 2, 2021

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Abstract

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New high-throughput biochemistry techniques complement selection-based approaches and provide quantitative kinetic and thermodynamic data for thousands of protein variants in parallel. With these advances, library generation rather than data collection has become rate-limiting. Unlike pooled selection approaches, high-throughput biochemistry requires mutant libraries in which individual sequences are rationally designed, efficiently recovered, sequence-validated, and separated from one another, but current strategies are unable to produce these libraries at the needed scale and specificity at reasonable cost. Here, we present a scalable, rapid, and inexpensive approach for creating User-designed Physically Isolated Clonal–Mutant (uPIC–M) libraries that utilizes recent advances in oligo synthesis, high-throughput sample preparation, and next-generation sequencing. To demonstrate uPIC–M, we created a scanning mutant library of SpAP, a 541 amino acid alkaline phosphatase, and recovered 94% of desired mutants in a single iteration. uPIC–M uses commonly available equipment and freely downloadable custom software and can produce a 5000 mutant library at 1/3 the cost and 1/5 the time of traditional techniques.

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Introduction

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Recent technological advances enable the biochemical interrogation of many protein variants in parallel with the precision and versatility needed to dissect mechanisms of function. These techniques, termed broadly here as high-throughput biochemistry (HTB), report quantitative kinetic and thermodynamic measurements for thousands of individual protein sequences. This advance is made possible by developments in programmable automated liquid handling that increase the scale of plate-based assays, (1,2) and recently, by a miniaturized microfluidic platform that allows parallel measurement of thousands of variants on one microscope slide. (3−5) For basic enzymology and biophysics studies, HTB approaches using mutational scanning libraries allow identification of the effects of all residues on folding, stability, binding, and catalysis. To advance precision medicine, libraries comprising human allelic variants (6) can be assayed for folding and function and “variants of uncertain significance” can be classified by their biophysical propensity to drive disease or respond to therapeutics. (4,7) Finally, within evolutionary biology, measurements of many extant orthologs and ancestral reconstructions can elucidate the molecular underpinnings of evolutionary adaptation (Figure 1A). (8−11) Each of these applications requires moving beyond simply identifying mutants with desired properties from large-scale screens to directly linking each of many sequence perturbations with its functional effects.

Figure 1

Figure 1. Overview of the uPIC–M pipeline to generate user-defined clonal mutant libraries. (A) Examples of clonal libraries from uPIC–M and potential high-throughput biochemistry applications. Applications are listed along with examples of the types of variants involved. (B) Comparison of cost (including materials and labor) of conventional mutagenesis vs uPIC–M for libraries of 50–20,000 mutants. A uPIC–M clone sampling rate of 384 per 50 desired mutants (7.68-fold excess) was used for these calculations. uPIC–M (modified) represents a lower cost version of uPIC–M with the addition of pipet tip washing for plate liquid transfer steps. See Table S1 for full time and cost calculations. (C) Workflow for generating uPIC–M libraries in three phases: (1) Mutagenic oligos are synthesized for ∼50 residue windows on a pooled array and selective PCR amplification of each window generates a primer pool used for QuikChange; (2) pooled QuikChange reactions are transformed and plated, with each plate containing a mixture of ∼50 possible single mutants, facilitating colony picking into multiwell plates to isolate clonal libraries of unidentified variants; (3) clonal libraries are prepared and sequenced by NGS to reveal the genotype and location of each variant.

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As high-throughput biochemistry tools increase the throughput of quantitative protein measurements by 102–103-fold, generating the requisite variant libraries has emerged as the new bottleneck. (1−5) For HTB to provide measurements for rationally chosen protein variants, input libraries must be user-defined clonal mutant libraries in which individual mutants are sequence-validated and physically isolated from one another for downstream assays.
Conventional site-directed mutagenesis generates user-defined, isolated variants by performing each mutagenesis reaction, plasmid isolation step, and downstream sequencing within physically separated reactions. This approach results in high control (the ability to create only mutants of interest), but is prohibitively costly and labor-intensive for applications requiring >100 variants (Figure 1B, Table S1). Conversely, existing techniques for generating mutant libraries, while powerful, are typically not suited for generating large-scale user-defined clonal mutant libraries. (12) For example, error-prone PCR (13−15) and mutagenic oligos containing degenerate codons (16,17) allow generation of extremely large mutant libraries (107–109) at relatively low cost; such libraries are ideal for selecting constructs with desired characteristics, but these mutagenesis strategies do not allow generation of a desired set of defined sequences.
Here, we introduce uPIC–M (User-designed Physically Isolated Clonal–Mutant) libraries, a method to prepare the needed mutant libraries that dramatically reduces the time and cost of conventional mutagenesis to empower high-throughput biochemistry (Figure 1C). uPIC–M can create 102–104 mutants at a material and labor cost of ∼$11 USD/mutant in 40 days for 5000 mutants, compared to an estimated $26 USD/mutant in 200 days for conventional mutagenesis (Figure 1B, Table S1). The uPIC–M pipeline includes three stages of library production: (i) user-directed pooled mutagenesis, using commercially available oligo arrays; (ii) isolation of mutant clones with widely available robotic pickers; and (iii) next-generation sequencing (NGS) to identify clone sequences and their locations, leveraging recent automation developments from single-cell sequencing. (18) uPIC–M uses the robust and accessible Illumina sequencing platform and a combination of existing open-source and custom analyses available on public software repositories to rapidly identify and evaluate library variants.
To develop and test uPIC–M, we set out to produce a scanning mutant library encoding single substitutions for every position in a 541 amino acid enzyme. Guided by stochastic sampling simulations, we picked a total of 4992 colonies to yield 3530 fully sequenced clones containing 507 desired single alanine and valine mutants, representing a library coverage of 94%. The efficiency and speed of this platform will accelerate the adoption and expand the scope of HTB.

Results and Discussion

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Overview of uPIC–M

The uPIC–M library generation pipeline consists of three stages (Figure 1C, 1–3) over approximately 8 days (Figure S1). During stage 1 (“generate mutant plasmids”), E. coli are transformed with pooled libraries of mutant plasmids generated via QuikChange-HT mutagenesis using user-defined, array-synthesized mutagenic oligonucleotides to create the specified variants. During stage 2 (“isolate mutant clones”), transformed E. coli are plated to isolate individual mutant colonies, which are then picked and used to inoculate liquid cultures within multiwell plates. During stage 3 (“sequence and identify clones”), mutant DNA is amplified and “barcoded” with well-specific primer sequences (“barcodes”) prior to pooling for NGS. For amplicons longer than 600 nucleotides (the maximum read length of typical paired end Illumina sequencing reads), amplified sequences can be fragmented using Tn5 transposase prior to barcoding to ensure the ability to acquire and associate reads spanning the complete amplicon. This barcoding strategy allows parallel sequencing while (i) preserving the plate-well origin of each read and (ii) providing a means to group reads for reconstructing the full-length sequence of each clone.
After sequencing, NGS reads are first demultiplexed according to the library barcode (here: 4992 barcodes); reads are then grouped by the barcodes specifying each well and aligned to the WT “reference” amplicon sequence, and variants are “called” from these aligned sequences. uPIC–M thus reports the full-length ORF sequence, physical well location, and quality information of clonal library variants, allowing users to select thousands or more single mutant clones of interest to create curated libraries for downstream high-throughput biochemistry applications.

Design of Tiling ORF Windows Allows Selective Mutagenesis from Oligo Arrays

We used QuikChange-HT mutagenesis, an oligo array-based strategy that provides rationally chosen mutants and offers the following advantages: (1) a simple experimental procedure, thus increasing throughput; (2) the ability to selectively amplify distinct mutagenic oligo subsets from the same array, permitting the use of the same source array for different experiments and targets; and (3) the ability to implement a design strategy that disfavors the production of double and higher-order mutants during pooled mutagenesis reactions, reducing otherwise-costly downstream sampling of clones to identify the desired single mutants. (19) Other previously reported methods can generate large libraries of rationally chosen mutants from oligo arrays but lack these time- and cost-saving features. (20,21)
QuikChange-HT generates mutants by a straightforward approach, the same as conventional PCR mutagenesis, but uses a unique mutagenic oligo design strategy that meets our needs. Coding regions are first divided into ∼200–300 nucleotide “windows” (with the exact length dependent on maximum oligonucleotide synthesis length and cost/nt). The 5′ and 3′ termini of each window (∼25 nt each) act as universal primer sites for amplification of that window from the pooled arrays and the ∼150 nt intervening sequence carries user-defined codon substitutions across ∼50 residues that will be introduced by QuikChange (Figure 2A). Overlapping adjacent windows by ∼20–30 bp makes it possible to uniquely amplify all mutagenic oligonucleotides within single windows with a corresponding primer pair (Figure S2). This strategy allows mutagenic oligos for many uPIC–M targets to be encoded by the same parent array, greatly reducing the cost (per oligo) and makes it possible to continue to generate mutagenic oligos from the array via PCR. Downstream mutagenesis reactions use the amplified mutagenic oligos as primers to produce pooled mutant sublibraries and proceed by iteratively denaturing double-stranded plasmid DNA, annealing the oligonucleotide that encodes the desired mutation and extending via a high-fidelity polymerase. After rounds of annealing and extension, parental methylated and hemi-methylated strands are digested via DpnI prior to transformation. The window approach reduces the likelihood of double and higher-order mutants by dividing sublibraries into separate reactions, which contain only mixtures of mutagenic primers that share the same termini sequences. As such, pooled mutagenic primers bind competitively to the same sequence of template DNA, reducing the likelihood of double and higher-order mutants arising at this step.

Figure 2

Figure 2. Tiling window strategy for uPIC–M mutagenic oligo array design. (A) Tiling window strategy (see Figure 1C) divides the ORF from the protein of interest into mutagenic sublibrary regions, with sublibrary oligo length constrained by DNA synthesis limits. Each window contains unique forward and reverse priming sites (dark shading, here ∼25 nt each) at the 5′- and 3′-termini surrounding a mutational region (light shading, here ∼150 nt). For a scanning library, each codon along the length of a sublibrary mutational region is substituted via an individual mutagenic oligo. (B) Selective amplification of oligos from a single window (sublibrary 11). Forward and reverse primers specific to a single sublibrary are used to amplify oligos from the resuspended array material, yielding an oligo pool containing ∼50 codon substitutions from the same mutagenic window.

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To develop and demonstrate the capabilities of uPIC–M, we designed a library of mutagenic primers to mutate each residue of the 541 amino acid alkaline phosphatase SpAP to Ala or Val. This enzyme, from the organism Sphingomonas. sp. Strain BSAR-1, was selected for its compatibility with a high-throughput assay platform previously reported by our groups. (5,22) For this assay format, SpAP is fused to a C-terminal eGFP reporter, which was not targeted for mutagenesis. The design process generated 13 mutational windows to efficiently encode the selected valine or alanine substitution at each position (Table S2).

QuikChange-HT Mutagenesis

Subsets of mutants are created in sublibrary pools, with one mutagenesis reaction carried out per sublibrary. To generate the material for each of 13 mutagenesis reactions for SpAP, we first amplified mutagenic primers for a given “window” from the total oligonucleotide pool via PCR and window-specific primers (Figure 2B, Table S2). Following spin-column purification, these amplified primers were used directly as QuikChange-HT mutagenic primers. Agilent-designed (see Materials and Methods) primers resulted in clean amplification of sublibrary mutagenic primer pools (Figure S2) from an array containing scans for SpAP as well as four additional genes (see data repository for full array sequence) with purified yields of ∼14–50 nM each (Table S3). We then performed mutagenesis reactions for each sublibrary following standard QuikChange protocols (linear PCR amplification of WT template followed by DpnI digestion).

Simulated Mutant Sampling to Predict Screening Requirements

For randomly sampled clones from a pool of variants, one needs more than the number of desired mutants to obtain complete or near-complete sampling, as the probability of obtaining a novel variant (one that has not already been sampled) decreases with increased sampling (similar to “the birthday problem” or the related “coupon collector’s problem” in probability theory). To estimate the number of clones that must be sampled to recover a given fraction of mutants from a specified variant population, we simulated stochastic sampling experiments in which we sampled clones N times from a pool of M variants without replacement. For libraries of 50, 500, and 5000 variants, 110, 1150, and 11,600 draws were required to recover ≥90% of desired clones, respectively (Table S4). To consider how the presence of WT clones or unwanted variants (e.g., undesired single mutants and/or higher-order mutants) affect recovery rates, an additional term was added specifying the probability that any given draw returns a single mutant (Figure 3A). As expected, lower rates of single mutant recovery led to a requirement for more clone sampling to obtain equivalent library coverage (Table S4).

Figure 3

Figure 3. Simulated sampling of pooled single mutant libraries. (A, B) Simulation of the number of unique mutants obtained as a function of the number of clones sampled for pooled libraries containing 50 (A) or 541 (B) unique single mutants with single mutant frequencies from 0.1 to 1.0. The remaining fraction of each pool represents all other variants (e.g., WT, indels, double, and higher-order mutants). Each curve represents the average of 103 simulations; shaded bands represent the 95% confidence interval; horizontal dashed lines (A, B) indicate the total possible number of unique mutants; vertical line (B) indicates the number of colonies picked for the SpAP library constructed herein (for legend, see A). (C–E) Simulated picking results for a sublibrary containing 50 single mutants at equal relative abundances sampled 384 times with a single mutant frequency of 0.5. (C) Simulated positional frequencies of single mutants; the results of five sampling simulations were chosen at random. (D) Histogram of expected mutant yields and (E) histogram of expected yields per sublibrary position (from 103 sampling events).

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We used these stochastic simulations to estimate the number of clones required to recover ≥90% of desired mutants within the 541 amino acid scanning mutagenesis library (V and A substitutions) for the SpAP construct (Figure 3B). To estimate the rates at which QuikChange-HT mutagenesis returns desired single mutants, we performed a preliminary pooled mutagenesis reaction, plated transformed E. coli, and Sanger sequenced 96 isolated clones. This preliminary sampling experiment returned 11 WT, 60 single mutant, and 5 double, triple, and greater mutant constructs, and 20 additional clones with indels and/or sequencing errors, suggesting an approximate single mutant rate of 63% (Table S5). We elected to oversample each sublibrary, with up to 384 possible clones for each set of up to 50 desired mutants. Simulating this sampling ratio with a single mutant rate of 50% for 50 possible mutants predicts a 92–100% yield (46–50 mutants) (Figure 3C,D). The distribution of the expected number of mutants per position obtained from random sampling revealed expected distributions of 0–11 mutants recovered at each position with a median of 4 (95% confidence interval of 0–8) (Figure 3E). The SpAP sublibraries encoded variable numbers of single mutants (range of 25–48 possible mutants each, Table S2). Sampling at an approximately 384:50 clone to mutant ratio is a compromise as the increase in time is negligible (e.g., compared to sampling half as many clones) and still results in substantial savings in costs compared to conventional mutagenesis (Figure 1B).

Clonal Mutant Isolation from Plasmid Libraries by a Pick-and-Grow Step

Clones must be physically isolated, both as a requirement of downstream high-throughput biochemistry assays and to permit sequence identification and validation (Figure 1C, (2)). To facilitate separation via robotic colony picking, we transformed chemically competent E. coli with pooled mutagenesis reactions for each sublibrary mutational window and then plated transformations on LB agar plates (150 mm) supplemented with antibiotic for outgrowth overnight at 37 °C. These reactions produced a range of colonies (25–440 colonies/plate, Table S6) despite the use of identical concentrations of WT template and sublibrary primer concentrations in each (15 nM stock concentrations). As robotic colony selection by imaging requires colonies within a narrow range of size, shape, and density (∼300–500 evenly spaced colonies per 150 mm plate), we re-plated sublibrary transformations that were outside of this range at higher or lower density (6 of 13); for reactions that still yielded insufficient densities (3 of 13), we successfully repeated QuikChange reactions at the highest stock sublibrary primer concentrations (Table S6). Guided by our stochastic sampling simulations, we selected ∼384 colonies for each sublibrary, with a throughput of 8–10 384 well plates/day, for a total of ∼1.5 days for the 13 SpAP sublibrary plates. The robotic colony picker occasionally picked at the interface of multiple colonies, likely leading to mixtures of multiple variants within some wells. For significantly larger mutant libraries, alternative robotic systems that allow automated agar source and multiwell destination plate handling or single microbe (23) or single droplet-based (24) methods for cell sorting could significantly enhance throughput.

Preparation of Mutant DNA Amplicons

DNA derived from mutant plasmids in E. coli clones must be amplified and enriched prior to NGS library preparation (Figure 1C, (3)). We generated amplicons by PCR (instead of isolating plasmids), as PCR requires minimal sample handling and produces linearized products that are directly compatible with downstream steps (sequencing library preparation and cell-free expression for HTB assays; Figure 4A,C). We amplified a 2525 bp region from each clone using universal primers complementary to the 5′- and 3′-UTR regions surrounding the SpAP-eGFP coding sequence (see Materials and Methods). To reduce contamination from E. coli genomic DNA in the final library, we systematically diluted liquid culture templates and measured contamination by qPCR (Figure S3). A 1:1000 dilution of six sample mutant cultures into H2O (corresponding to a final dilution of 1:5000) reduced E. coli DNA contamination to the limit of detection. To generate uniform amounts of PCR product from variable amounts of DNA templates within culture plates, we performed 25 cycles of PCR using a high-fidelity polymerase (Figure S4). We selected these conditions for amplification of mutant DNA from SpAP sublibrary plates. After dilution and amplification, DNA concentrations measured for half of the wells within each 384 well plate varied by ∼5-fold across all samples, and with median concentrations of ∼20–60 ng/μL (Table S7, Figure S5).

Figure 4

Figure 4. Schematic of uPIC–M sequencing library preparation. Preparation of sequencing libraries takes place in multiwell plate format (96 or 384) via the following steps: (i) ORF regions of target plasmids are amplified from each clone using universal primers to obtain enriched amplicon DNA (A); (iia) For amplicons ≤600 bp, universal Illumina adapters may be ligated directed to amplicons or added by amplification in a second PCR step; (iib) for amplicons >600 bp, DNA is fragmented and tagged using adapter-loaded Tn5 transposase, i.e., tagmented; (iii) amplicons or fragments are further amplified with Nextera primers that incorporate dual-unique i7 and i5 index barcodes; (iv–vii) amplified and barcoded clonal libraries are pooled for NGS, purified, sequenced, and barcodes are used to report the plate-well location and genotype of each variant (B). Mutant amplicons generated at (i) can be used directly for high-throughput biochemistry applications (shown here: cell-free expression and fluorogenic assay of an enzyme library using a microfluidic platform to obtain kinetic parameters) (C).

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Tagmentation and Barcoding of Mutant Amplicons

Mutational regions spanning <600 nucleotides can simply be barcoded, and the entire region can be sequenced using 2 × 300 paired end Illumina reads (Figure 4B, iia). (25) Longer ORFs, as are common and is the case for our example, require an alternative step to enzymatically fragment DNA and associate well-specific barcodes with each fragment, as used here (Figure 4B, iib). Critically, both strategies install universal adapter sequences to the DNA within each sample well, providing priming sites for barcodes that are specific to each well in a subsequent amplification step. Following Tn5 tagmentation of the 2525 bp SpAP-eGFP amplicons, we used the universal adapter sequences attached to fragment ends as priming sites to amplify DNA and add sequences required for Illumina sequencing, including (1) sequences required to bind amplicons to sequencing flow cells (p5/p7), (2) plate/well-specific index 1 and index 2 barcodes (i7/i5), and (3) complementary sites for sequencing primers (R1 and R2) (Figure 4B, iii). (26,27) All barcoded samples can then be pooled and sequenced in a single run via NGS (Figure 4B, iv–vi). We used portions of an available 7680 member (20 × 384) dual unique indexed i5/i7 Nextera barcode library. However, barcoding oligo costs can be significantly reduced using a combinatorial indexing strategy. (28)
Tn5-based library preparation workflows (e.g., for single-cell libraries) often involve a bead-based cleanup and enrichment step of DNA templates prior to quantification, normalization, and tagmentation. This cleanup step is required to remove residual reagents and buffer components from dilute cDNA libraries (18) but adds significant time and cost. We reasoned that the concentrated mutant amplicons (Figure 4A) used in our workflow could be diluted to reduce residual PCR components to avoid this step for uPIC–M while still affording adequate amounts of DNA templates for tagmentation (typically performed at a template concentration of ∼0.1–1 ng/μL). Initial tests confirmed that for templates at identical concentrations, the yield after tagmentation and subsequent library amplification was comparable for purified and diluted samples (Figure S6A) and that the 0.1–0.5 ng/μL template prior to tagmentation resulted in quantifiable libraries with similar size distributions (Figure S6B). We diluted all SpAP sublibrary plates 1:100 in H2O prior to tagmentation, instead of performing the time-consuming normalization of individual wells, yielding final concentrations of ∼0.1–0.5 ng/μL prior to tagmentation (for stock concentrations, see Table S7). In the case of greater variation (>5-fold) in sample well DNA concentrations, multiple dilutions of the same plate could easily be performed and processed for sequencing with only modest increases in time and cost.

Automated Plate Processing

The above steps are labor-intensive if performed manually, but automated liquid handling techniques that are now used widely for single-cell sequencing applications can readily process >20 × 384 sample plates (or 7680 clones) for sequencing per day (see Materials and Methods). This approach allowed tagmentation and barcoding amplification of the 13 × 384 plate SpAP library in less than 1 day and used Mosquito and Mantis liquid handling systems. However, these liquid handling steps can be performed using a wide variety of other liquid-handling instruments. (29) Moreover, most of the liquid handling steps in the pipeline are associated with the tagmentation reactions required for sequencing ORFs ≥600 bp (see Materials and Methods). For libraries that do not require tagmentation (ORFs <600 bp), many of these liquid handling steps are not necessary, making manual pipetting a feasible option. Even for libraries requiring tagmentation, producing smaller libraries containing <1000 clones via manual pipetting increases library production time ∼2 to 3-fold but still provides a cost advantage compared to conventional mutagenesis.

Sequencing Library QC

The final step prior to pooled NGS involves evaluating library quality by quantifying the final concentration and distribution of fragment sizes. We pooled barcoded and amplified single clone libraries from each plate (i.e., one pooled sample per plate), purified and enriched them via a magnetic bead cleanup with size selection (see Materials and Methods), and then estimated fragment sizes and concentrations by microelectrophoresis (Figure 5). The library quality and concentration varied by sample plate (Figure S7, Table S7); 7/13 sublibraries contained clear fragment peaks at 400–500 bp and all samples contained measurable fragments between 400 and 1000 bp without detectable contamination from low-molecular-weight sequencing adapters. This library quality allowed recovery of 65% of barcodes at high read depth across sublibrary plates (see below).

Figure 5

Figure 5. Sequencing library quality control results. (A) Plot of fluorescence (arbitrary units) vs fragment length for sublibary 1 following tagmentation and barcoding amplification. See Figure S7 for analogous data for the other sublibraries. (B) Electropherograms of sublibraries 1–13 (see Table S6 for integrated peak concentrations).

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Sequencing Library Analysis

Analyzing results from NGS sequencing requires (1) grouping reads by barcode, (2) eliminating barcodes with low coverage, (3) removing poor quality bases and residual adapter sequences from reads, (4) aligning reads to the “reference” ORF (here, the SpAP-eGFP amplicon sequence), and (5) identifying and evaluating sequence variants (Figure 6A,B).

Figure 6

Figure 6. NGS data processing and read mapping pipeline and results for the SpAP scanning library. (A) Data processing steps and observed statistics. Raw FASTQ files (demultiplexed and unpaired) are filtered for barcodes containing 1 or more reads followed by adapter sequence trimming and pairing with read mates (if both reads are present and meet length/quality thresholds). Sequence-redundant readthrough read pairs are flagged at this stage and redundant read mates are discarded. (B) Trimmed and paired reads are mapped to the SpAP-eGFP amplicon, E. coli, and full plasmid genomes. (C) Histogram of total reads per barcode across all sublibraries following read trimming and pairing (n = 4645). (D) Barcode counts for each sublibrary plate at several read depth thresholds for the SpAP-eGFP ORF (>0 represents barcodes containing any mapped reads and remaining thresholds represent the minimum number of mapped reads at all positions; only barcodes containing at least one mapped read are included). The horizontal dashed line at 384 barcodes represents the maximum possible number of barcodes.

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From a 25 million capacity MiSeq v3 (2 × 300 bp) run, we obtained 4.5 × 107 total reads (read 1 and read 2) that were demultiplexed by the instrument using supplied i7/i5 barcodes (4992 barcodes total). We then discarded FASTQ files for barcodes with 0 reads (4646 retained barcodes, Figure 6A), trimmed off the universal Illumina adapter sequences, filtered reads based on quality scores and length using standard criteria, (30) and paired reads with their mate if present. If paired reads were fully redundant, i.e., with readthrough to an adapter sequence on the opposing terminus, one mate was discarded (typically R2). (30) We recovered 2.9 × 107 reads after the trimming and associated filtering step (Figure 6A), with a median of 6 × 103 reads per barcode (Figure 6C, Table 1). Even for sublibraries with relatively poor tagmentation yields (4, 7, 9, 11–13; Table S7), median reads per barcode were comparable (within <3-fold) to efficiently tagmented sublibraries (Table 1). This consistency was likely aided by sample normalization prior to sequencing, which accounted for differences in library concentrations.
Table 1. SpAP Mutational Sublibrary Sequencing Statistics
sublibrarytotal reads (×106)barcodesamedian readsSpAP readsbE. coli readsbplasmid readsbunmapped readsb
all28.6464559740.9600.020.02
12.736977940.9700.020.02
22.537275610.9600.020.02
32.734477710.9400.030.02
41.438334210.9400.020.03
52.335663390.9600.020.02
61.538235600.9600.020.02
72.337767820.9700.010.02
81.73804690.0800.020.89
8c1.618494180.9500.020.03
91.735944710.9300.030.04
103.838497870.9600.020.02
113.437790110.9700.020.01
121.425361710.9600.010.02
131.230937550.9600.020.02
a

Number of barcodes (out of a possible 4992 total or 384 per sublibrary) with >0 reads (mapped or unmapped).

b

Reported as the median value across barcodes with >0 reads.

c

This entry contains only sublibrary 8 barcodes with ≥500 reads.

Next, we mapped the reads to multiple reference genomes using the Burrows-Wheeler Aligner. (31) For the SpAP mutagenesis library presented here, 95.3% of these reads mapped to the SpAP amplicon reference sequence (this sequence includes the 5′-UTR, eGFP fusion, and the 3′-UTR) and an additional 0.3% mapped to the E. coli genome. The remaining reads were mapped to plasmid-derived sequences outside of the amplicon region (2.1%) or were unmapped (2.4%), likely representing either low quality reads or contamination from human or other sources (Figure 6B). The ratio of SpAP-eGFP to E. coli reads was highly consistent across sublibrary plates (Table 2). The read depth per barcode (calculated as the median read depth for all nucleotide positions of the SpAP-eGFP ORF within each barcode) varied from 0 to 1700 reads, with a median of 433 reads. Across the entire library, 65% of recovered barcodes were sequenced to a depth of ≥100 reads at all positions (Figure 6D, Table 1).
Table 2. SpAP Read Depth Statistics
sublibrarybarcodesadepth ≥1bdepth ≥10bdepth ≥100bdepth ≥1000bkeptc
all457136033386292603530
13693253012620318
23672772602460274
33423002892440298
43672512341940247
53553272992340315
63782762501920264
73712522302090241
83761511391310146
93452632472020260
103843523423310352
113563293203020329
122522182091800216
133092822661990270
a

Number of barcodes (out of a possible 4992 total or 384 per sublibrary) with ≥1 SpAP reads.

b

Number of barcodes with at least this read depth at all positions in the SpAP-eGFP genome.

c

Number of barcodes meeting the depth threshold of at least 1 read at all positions, and ≥10 reads at ≥95% of positions. Only barcodes meeting this depth threshold were carried forward for subsequent variant analyses.

Quantifying the Yield of Single Mutants

The next stage of assembling a ready-to-use library for high-throughput biochemistry assays is to identify the clones containing single mutations and map each mutant to plate-well locations. We selected barcodes meeting the following depth threshold for further analysis: ≥1 read at all reference sequence positions and ≥10 reads at ≥95% of all reference sequence positions. Of 4645 barcodes with ≥1 mapped read, 3530 (76%) met this threshold across the entire library. To detect variants associated with each barcode in batch, we applied a SAMtools module (32,33) to process all mapped reads and generate output files (variant call files, .vcf) for each barcode containing SpAP-eGFP variants (single nucleotide substitutions, indels, or null if WT). WT and indel-containing barcodes were discarded (Figure 7A). For barcodes containing single nucleotide substitutions, we determined the corresponding codon and amino acid changes, assessed whether observed substitutions were intended (correct mutant identity and sublibrary) or unintended, and evaluated whether these barcodes contained single, double, or triple and greater numbers of amino acid substitutions. We also stored variant quality statistics at this stage, including the number of forward and reverse reads containing variant vs WT nucleotide sequence. Among barcodes containing single mutants, most observed mutations were intended (97%) (Figure 7A).

Figure 7

Figure 7. Characterization of the SpAP alkaline phosphatase scanning mutant library created with uPIC–M. (A) Overview of variant detection analyses and calculated yields (red) for the SpAP mutant library. (B) Overall distribution of single mutants, WT, double mutants, triple and greater mutants, and indels across all mutational sublibraries (indel count reflects variants containing one or more indels). (C) Location and frequency of intended single mutants across the entire SpAP-eGFP ORF. (D) Scatter plot and histograms of variant reads vs WT reads for all intended single mutants. (E) Comparison of simulated and observed single mutant frequency distributions for three sublibraries. The legend specifies the observed yield of unique single mutants and simulated 95% confidence interval from 1000 events; “n” indicates the total number of observed intended single mutants. Results for all sublibraries are shown in Figure S9.

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Across all sublibraries, single mutants comprised 57% of the clones, ranging from 52–68% within each sublibrary (Figure 7B; Table 3), similar to the results of small-scale testing (60%, Table S5) and within the range of mutant picking simulations (10–100%; see “Simulated mutant sampling to predict screening requirements”) (Table 3). Double and triple and greater mutants comprised 28% of the sequenced clones (Figure 7B), higher than the 5% observed during small-scale testing. This higher percentage may arise in part from cross-contamination between single mutant clones during plate handling steps prior to barcode introduction, which was absent during small scale testing. Variant:WT read ratios across single, double, and triple and greater mutants are consistent with this model (Figure S8).
Table 3. Variant Content of the SpAP Scanning Library
sublibraryresiduestotal positionsbarcodesasingle totalsingle intendedsingle unintendeddoubletriple+indelsWT
all2–54254135302056199660761212174327
12–4140318178175361182041
242–894827415414866617829
390–13748298168161765201431
4138–18548247135131443272418
5186–23247315175169685112123
6233–27947264141138360232317
7280–3264724114113475912524
8327–3563014694913215224
9357–40246260148142650111635
10403–4484635221020468124730
11449–4914332923022466015519
12492–51726216120120052201212
13518–5422527016215935891724
a

Number of barcodes meeting the depth threshold of at least 1 read at all positions, and ≥10 reads at ≥95% of positions.

Next, we examined the identity and location of single mutant variants and found that mutants were evenly distributed with minimal positional bias (Figure 7C). Overall, we recovered 507 of 541 desired single mutants (94% coverage) from 3530 colonies, with coverage ranging from 87 to 98% within sublibraries (Table S8). These data demonstrate that uPIC–M is capable of producing user-defined single mutant libraries at high coverage.

Assessment of Single Mutant Purity

High-throughput biochemistry demands different levels of mutant purity depending on the application. Quantitative measurements of variant stabilities or ligand affinities can tolerate low amounts of contamination, as this contamination leads to accordingly low errors on thermodynamic parameters. By contrast, measurements of enzyme turnover are highly sensitive to contamination as a small (∼1%) fraction of WT enzyme could dominate apparent rates when attempting to measure a catalytically impaired mutant with activity that is ≪1% of WT.
Above, we classified all barcodes containing only one amino acid mutation as single mutants without considering the fraction of mutant reads at that position. Here, we assess mutant purity by quantifying the number of forward and reverse reads containing either the mutant or WT nucleotide at the mutated position. Across this library, single mutants contained a wide range (10–1000) of variant reads and relatively few but detectable WT reads (Figure 7D). To calculate mutant purities, we devised a quality threshold representing the minimum number of variant reads and the minimum ratio of variant:WT reads (Table S8); as many barcodes contained 0 WT reads, this threshold represents a lower limit on single mutant purities. Library yield dropped from 507 mutants (94%) to 498 (92%) mutants and 484 (89%) mutants when applying thresholds of 10 and 100, respectively.

Evaluation of Method Performance

To measure the success of uPIC–M compared to picking simulations, we calculated expected unique mutant yields per SpAP sublibrary. We repeated simulations, this time substituting values for experimental variables that were assumed using only generic estimates in the initial simulations described above. These parameters were (1) the number of sequenced barcodes per sublibrary, which is then used as the number of simulated draws, and for each sublibrary was fewer than the 384 possible, (2) observed single mutant frequency, as this defines the chance of drawing a single mutant among a pool containing multiple categories of variants, and (3) the total number of possible unique mutants, which varied by sublibrary (Table S2) and is proportional to the number of draws necessary to achieve a desired level of library coverage.
For each sublibrary, we ran 104 picking simulations to estimate the expected median number of unique mutants (and 95% confidence interval) and distribution of mutants per position (Figure 7E, selection of 3 sublibraries; Figure S9, all sublibraries). Observed unique single mutant yields matched expectations for 10 of 13 sublibraries (2–8, 11–13) (Table S9). The remaining 3 plates (1, 9, 10) yielded one fewer single mutant than expected at the 95% confidence interval, suggesting that an unequal abundance of some single mutants slightly decreased library coverage. Together, these results establish that the picking simulations presented here can accurately guide experimental pipelines for generating uPIC–M libraries.

Conclusions

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uPIC–M delivers user-designed, clonal, single mutant libraries at a significant savings of time and cost compared to conventional mutagenesis by combining commercially available oligonucleotide arrays with commonly used automated liquid handling platforms and barcoded Illumina sequencing strategies. Here, we used this method to rapidly generate a single mutant scanning library of a 541 amino acid enzyme and achieved a >90% yield of desired variants. This method is immediately applicable to new protein targets, and we provide a detailed workflow for rigorous characterization of library sequences using a collection of open-source and custom data analysis tools.
In future work, uPIC–M can readily be extended to a variety of applications beyond generating single mutant libraries. The relatively long mutagenic primers used in QuikChange-HT mutagenesis hybridize efficiently and specifically even in the presence of several nucleotide substitutions, making it possible to introduce multiple mutations within the same mutagenic window. (34,35) uPIC–M’s window design strategy can also be adapted to create deletion or insertion libraries using assembly-based strategies in pool. (36,37) A software tool under development by the Fordyce group will facilitate the design of single mutant and other variant libraries. (38) Finally, uPIC–M can be readily adapted for sequencing with other Illumina instruments or long-read sequencing approaches. (39)
High-throughput biochemistry reveals biophysical insights on an unprecedented scale, but constructing variant libraries has become the new rate-limiting step. (4) The ability of uPIC–M to generate the required variant libraries rapidly and efficiently will expand HTB to the study of new protein targets, systems, and questions.

Materials and Methods

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Description of Plasmid

The plasmid mutagenized here encoded the SpAP alkaline phosphatase family monoesterase (22,40) (Uniprot KB – A1YYW7) fused to a C-terminal eGFP via a 10 amino acid ser-gly linker. SpAP residues 1–540 (full-length sans signal peptide, original numbering with signal sequence = 20–559) were subcloned into the manufacturer-supplied plasmid from the PURExpress In Vitro Protein Synthesis Kit (New England Biolabs, Ipswich, MA, USA) using the Gibson assembly method with synthetic E. coli codon-optimized SpAP DNA (IDT, Coralville, IA, USA). The full plasmid map (Figure S10), DNA sequence (Figure S11), and the SpAP-eGFP fusion protein sequence (Figure S12) are provided in the Supplemental Information.

Design of Mutagenic Oligo Arrays

Oligo arrays were designed using the Agilent Technologies (Santa Clara, CA, USA) eArray web program (https://earray.chem.agilent.com/earray/). The full sequence of the PURExpress-SpAP-eGFP was provided as input to the eArray software (Figure S11), and mutational regions were manually adjusted until primer sequences for all sublibrary mutational windows (13 total) passed thermodynamic thresholds calculated by this software. Oligos were selected to mutate all non-valine residues from positions 2–326 to valine; all valine residues from positions 2–326 to alanine; all non-alanine residues from positions 327–542 to alanine; and all alanine residues from positions 327–542 to synonymous alanine codons, corresponding to 541 total mutants (Table S2). Each mutagenic oligo was synthesized in duplicate within a 7500 oligo capacity high-fidelity array (Agilent Technologies, see Table S10 for array sizes and sample pricing). The forward and reverse primer sequences (Table S2) required to amplify each mutational window from the pooled array were also obtained from the eArray design output and were purchased from IDT. The full array sequence is provided in an accompanying data repository (https://osf.io/k3rjy/).

Preparation of Sublibrary Mutagenic Primer Pools and PCR Mutagenesis

Lyophilized oligo arrays were resuspended in 200 μL of 10 mM Tris–HCl, pH 8.5 (EB) and then further diluted 1:100 with EB. Sublibrary oligo pools were amplified individually using window-specific primer pairs and KAPA HiFi HotStart ReadyMix (Roche, Indianapolis, IN, USA) with a final template concentration of 1:2000 resuspended oligo array and annealing temperatures of either 60 or 65 °C (depending on performance of individual primer pairs) for 25 PCR cycles. Resulting PCR products (“sublibrary mutagenic primers”) were purified using the StrataPrep PCR Purification Kit (Agilent Technologies) and analyzed for quality and concentration using TapeStation electrophoresis with HSD1000 ScreenTapes (Agilent Technologies). For initial mutagenesis reactions, primer stocks were normalized to a uniform concentration, measured by UV absorbance, of 15 nM, that of the lowest concentration sublibrary pool (Table S3). PCR mutagenesis was performed using the QuikChange Lightning enzyme (Agilent Technologies) at an annealing temperature of 60 °C for 18 cycles with the following components: 2.5 μL of 10× manufacturer-supplied buffer, 1 μL of supplied dNTP mix, 0.75 μL of QuikSolution additive, 1 μL of 25 ng/μL PURExpress-SpAP-eGFP template plasmid, 15 μL of 15 nM sublibrary pool, 1 μL of QuikChange Lightning enzyme, and 3.75 μL of H2O. Following PCR, the template WT plasmid was digested by the addition of 1 μL of DpnI (Agilent Technologies) for 5 min at 37 °C. For sublibraries that provided an insufficient number of transformants, mutagenesis was repeated using the undiluted purified sublibrary primer pools.

Transformation, Plating, Colony Picking & Growth

DpnI-digested PCR mutagenesis reactions were transformed into chemically competent NEB 5-alpha E. coli. Transformations were plated on 15 cm LB agar plates containing 100 μg/mL ampicillin and grown overnight at 37 °C. Transformation ratios of 1:20–1:3.33 PCR product:cells were used to obtain a desired yield of ∼400–500 colonies per 15 cm plate. Colonies were picked manually (sublibraries 1 and 5 only) or using a PIXL robotic colony picker (Singer Instrument Company, Somerset, UK) at the Stanford University School of Medicine Genome Technology Center (Palo Alto, CA, USA). Single colonies were picked from source LB agar plates into 384 well (120 μL) destination microwell plates containing 60 μL of LB containing ampicillin. At least 384 colonies were picked and grown from each sublibrary window (Figure 2). Microwell plates were sealed with gas-permeable AeraSeal film (MilliporeSigma, Burlington, MA, USA) and grown to saturation with shaking at 37 °C.

qPCR Detection of E. Coli Genomic DNA

E. coli cultures from clonal mutants were pooled and diluted from 101 to 104-fold to assay for genomic DNA concentration using qPCR with the commercial NEB Luna 2X MasterMix. A previously reported primer set to the rodA gene was used (forward: 5’-GCAAACCACCTTTGGTCG-3′; reverse: 5’-CTGTGGGTGTGGATTGACAT-3′). (41) Library samples were quantified using a standard curve of purified E. coli O157:H7 genomic DNA (Zeptometrix, Buffalo, NY, USA) at concentrations of 0.0001–1 ng/μL.

Preparation of Enzyme ORF Amplicons

Saturated clonal E. coli cultures in 384 well plates were diluted 1:1000 with H2O, by serial dilution using a 96-well Rainin Liquidator (Mettler-Toledo, Columbus, OH, USA). Dilutions and additional amplicon preparation steps were performed in 384 well Bio-Rad HSP3801 plates (Bio-Rad, Hercules, CA, USA). Primers were designed to amplify a 2525 bp region including the SpAP-eGFP ORF and 5′- and 3’-UTR segments (Figure S10). Forward (5′- gatctacactctttccctacacgacgctcttccgatctCCCGCGAAATTAATACGACTCACTATAGG-3′) and reverse (5’-gtctcgtgggctcggagatgtgtataagagacagGCACCACCTTAATTAAAGGCCTCC-3′) primers also contained Illumina Read 1 and Read 2 overhangs, respectively, shown in lowercase. Note: the underlined nucleotides in the Read 1 overhang were included inadvertently but did not affect downstream steps. Diluted cultures were used as PCR templates and amplified with KAPA HiFi HotStart polymerase at a scale of 4 μL:0.8 μL 1:1000 dilute culture template, 2 μL of KAPA HiFi HotStart ReadyMix (Roche), 0.96 μL of H2O, 0.12 μL of 10 μM forward primer, 0.12 μL of 10 μM reverse primer (see sequences above). Thermal cycling conditions were as follows: 95 °C, 5 min; 25 × [98 °C, 20 s; 60 °C, 15 s; 72 °C, 2 min]; 72 °C, 2 min.

Fluorescence Quantification of Amplicon DNA

Amplicon DNA concentrations after PCR were determined using the Quant-iT PicoGreen dsDNA assay (Thermo-Fisher Scientific, Waltham, MA, USA). In brief, a master mix containing 1:200 PicoGreen reagent (from stock concentration as supplied) in 10 mM Tris–HCl, pH 8.5 was prepared immediately before use and kept from light. Amplicon samples were prepared by the addition of 1.5 μL of 1:5 PCR reaction:H2O to 34 μL of the master mix. Standards were prepared by the addition of 1.5 μL of λ phage DNA ranging in concentration from 0 to 100 ng/μL to 34 μL of the master mix. Standard curves were included, in duplicate, on each sample plate. Samples were incubated ∼5 min at room temperature and read by fluorescence (λex = 480 nm, λem = 520 nm) using a Synergy H1 plate reader (BioTek, Winooski, VT, USA).

Tn5 Tagmentation

A library preparation procedure adapted from Picelli et al., (18,26) with modifications, was used to generate barcoded, sequencing-ready libraries. Commercial pA-Tn5 (protein A-Tn5) was purchased pre-loaded with sequence adapters from Diagenode (Denville, NJ, USA) and diluted to a working concentration of 1:50 with dilution buffer (40 mM Tris–HCl, pH 7.5, 40 mM MgCl2). Amplicons in 384 well plates were diluted 1:100 in H2O to provide template concentrations suitable for tagmentation. For Tn5 reactions, 1.2 μL of master mix (0.2 μL 1:50 pA-Tn5; 1 μL 1.6× buffer containing 16 mM Tris–HCl, pH 8.0, 8 mM MgCl2, and 16% (v/v) dimethylformamide, sparged with N2 and added immediately prior to use) was added to each well of a new 384 well plate using a Mantis microfluidics liquid handler robot (Formulatrix, Bedford, MA, USA). Amplicon templates were added to Tn5 reaction mixtures (0.4 μL 1:100 template each) using a Mosquito LV pipetting robot (SPT Labtech, Boston, MA, USA). Reaction plates were sealed, briefly vortexed, collected by centrifugation, and incubated for 7 min at 55 °C. Tn5 reactions were stopped by the addition of 0.4 μL of 0.1% (w/v) sodium dodecyl sulfate, using the Mantis liquid handler.

i7/i5 Barcoding PCR and Library Cleanup

Tagmented libraries were barcoded and amplified using KAPA HiFI polymerase and a collection of Nextera XT 12mer dual unique index sequencing primers (purchased from IDT and supplied by CZ-Biohub). First, 1.2 μL of a master mix containing 0.08 μL of KAPA HiFi (1 U/μL), 0.8 μL of 5× buffer (manufacturer supplied), 0.12 μL of 10 mM dNTP mix (2.5 mM each), and 0.2 μL of H2O was added to each 2 μL SDS-halted Tn5 reaction using the Mantis liquid handler. Next, 0.8 μL of unique i5/i7 primer mix (2.5 μM each) was transferred from source plates to sample using the Mosquito instrument. Reaction plates were sealed, briefly vortexed, collected by centrifugation, and amplified with the following thermal cycler conditions: 72 °C, 3 min; 95 °C, 30 s; 12 × [98 °C, 10 s; 55 °C, 15 s; 72 °C, 1 min]; 72 °C, 5 min. Resulting libraries were pooled (with the Mosquito) and treated with AMPure XP magnetic beads at a ratio of 0.8:1 beads:sample volume to purify DNA (Beckman Coulter, Brea, CA, USA). Library yield and quality were determined by TapeStation electrophoresis with an HSD1000 ScreenTapes (Agilent Technologies).

Next-Generation Sequencing

Sequencing was performed by SeqMatic (Fremont, CA, USA). Libraries were sequenced using Miseq v3 2x300 bp, with the addition of 1% PhiX control DNA. Samples were submitted with i7/i5 barcodes corresponding to each tagmented mutant and demultiplexed by the instrument.

Picking Simulations

Pools of mutants were simulated as numeric lists containing unique elements equal in number to desired simulated mutant pool. The random module (Python 3 (42)) was used to sample from this pool pseudo-randomly, thereby simulating a large (compared to sampling events) mutant pool with identical distributions of each unique mutant (https://github.com/FordyceLab/uPICM). Simulation of sampling from a variant pool containing additional non-single mutants was accomplished by the above strategy with the addition of a preceding step. This step introduced a pseudo-random draw from a pool containing specified fractions of single mutants (0.1–1.0) and non-single mutants (0–0.9), with only draws picking among the single mutant fraction carried forward.

NGS Data Processing, and Analysis

NGS data were processed using open source software tools, executed with the Snakemake workflow tool. (43) First, sequences of Illumina adapters were trimmed and redundant (read-through) read mates were disposed from demultiplexed fastq read files using the Trimmomatic package. (30) Trimmed reads were aligned to the PURExpress-SpAP-eGFP plasmid, and separately, the full E. coli genome (NCBI Reference Sequence: NC_000913.3) using BWA-MEM, (31) with the output mapped, sorted, and indexed with SAMtools. (32) Variant base calls were identified against the PURExpress-SpAP-eGFP plasmid genome using the BCFtools utility of the SAMtools package. (33) Alignments were visualized using Integrative Genomics Viewer. (44) Subsequent analyses were performed with custom code using Python 3, available at (https://github.com/FordyceLab/uPICM). Raw sequencing files are provided in our data repository (https://osf.io/k3rjy/).

Supporting Information

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The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acsomega.1c04180.

  • Timeline of uPIC–M library generation, amplification of window-specific sublibrary pools from an oligo array, quantification of E. coli genomic DNA in diluted mutant culture templates, selection of PCR conditions for SpAP mutant amplicons, quantification of amplicon DNA concentrations per sublibrary plate, Tn5 tagmentation reaction conditions, electropherograms of tagmented and amplified mutant sublibraries, histogram of variant:WT read ratios among single, double, and triple and greater mutants, comparison of observed and simulated single mutant frequency distributions, time and cost calculations for uPIC–M and conventional mutagenesis, Plasmid map of PURExpress-SpAP-eGFP, complete DNA sequence of PURExpress-SpAP-eGFP plasmid, protein sequence of SpAP-(10mer linker)-eGFP, oligo array and window design details for SpAP scanning mutant library, concentration of purified sublibrary mutagenic primer pools, expected mutant yields from simulations of mutant sampling, variant composition of small-scale QuikChange-HT reactions, sublibrary transformation and colony picking results, amplicon DNA and library concentration statistics, unique single mutant yields for the SpAP scanning library, comparison of uPIC–M performance with simulated picking experiments, per sublibrary, and oligo array price summary (PDF)

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Author Information

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  • Corresponding Authors
    • Daniel Herschlag - Department of Biochemistry, Stanford University, Stanford, California 94305, United States;  Orcidhttps://orcid.org/0000-0002-4685-1973;  Email: [email protected]
    • Polly M. Fordyce - Department of Bioengineering, Stanford University, Stanford, California 94305, United States;  Chan Zuckerberg Biohub, San Francisco, California 94110, United States;  Department of Genetics, Stanford University, Stanford, California 94305, United States;  ChEM-H Institute, Stanford University, Stanford, California 94305, United States;  Orcidhttps://orcid.org/0000-0002-9505-0638;  Email: [email protected]
  • Authors
    • Mason J. Appel - Department of Biochemistry, Stanford University, Stanford, California 94305, United States;  Orcidhttps://orcid.org/0000-0001-7501-8115
    • Scott A. Longwell - Department of Bioengineering, Stanford University, Stanford, California 94305, United States
    • Maurizio Morri - Chan Zuckerberg Biohub, San Francisco, California 94110, United States
    • Norma Neff - Chan Zuckerberg Biohub, San Francisco, California 94110, United States
  • Notes
    The authors declare no competing financial interest.

Acknowledgments

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We thank Daniel Mokhtari for assistance with data analysis, Agilent Technologies for generously providing oligo arrays, Dr. Robert St. Onge and the Stanford Genome Technology Center for assistance with robotic colony picking, and members of the Herschlag and Fordyce research groups for critical discussions and reviewing the manuscript. This work was supported by the NIH grant R01 (GM064798) awarded to D.H. and P.M.F., an Ono Pharma Foundation Breakthrough Innovation Prize, and the Gordon and Betty Moore Foundation (grant number 8415). P.M.F. is a Chan Zuckerberg Biohub Investigator.

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    Markin, C. J.; Mokhtari, D. A.; Sunden, F.; Appel, M. J.; Akiva, E.; Longwell, S. A.; Sabatti, C.; Herschlag, D.; Fordyce, P. M. Revealing Enzyme Functional Architecture via High-Throughput Microfluidic Enzyme Kinetics. Science 2021, 373, eabf8761,  DOI: 10.1126/science.abf8761
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  6. 6
    Liang, S.; Mort, M.; Stenson, P. D.; Cooper, D. N.; Yu, H. PIVOTAL: Prioritizing Variants of Uncertain Significance with Spatial Genomic Patterns in the 3D Proteome. Genomics 2020.  DOI: 10.1101/2020.06.04.135103 .
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  7. 7
    Starita, L. M.; Ahituv, N.; Dunham, M. J.; Kitzman, J. O.; Roth, F. P.; Seelig, G.; Shendure, J.; Fowler, D. M. Variant Interpretation: Functional Assays to the Rescue. Am. J. Hum. Genet. 2017, 101, 315– 325,  DOI: 10.1016/j.ajhg.2017.07.014
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    Variant Interpretation: Functional Assays to the Rescue
    Starita, Lea M.; Ahituv, Nadav; Dunham, Maitreya J.; Kitzman, Jacob O.; Roth, Frederick P.; Seelig, Georg; Shendure, Jay; Fowler, Douglas M.
    American Journal of Human Genetics (2017), 101 (3), 315-325CODEN: AJHGAG; ISSN:0002-9297. (Cell Press)
    Classical genetic approaches for interpreting variants, such as case-control or co-segregation studies, require finding many individuals with each variant. Because the overwhelming majority of variants are present in only a few living humans, this strategy has clear limits. Fully realizing the clin. potential of genetics requires that we accurately infer pathogenicity even for rare or private variation. Many computational approaches to predicting variant effects have been developed, but they can identify only a small fraction of pathogenic variants with the high confidence that is required in the clinic. Exptl. measuring a variant's functional consequences can provide clearer guidance, but individual assays performed only after the discovery of the variant are both time and resource intensive. Here, we discuss how multiplex assays of variant effect (MAVEs) can be used to measure the functional consequences of all possible variants in disease-relevant loci for a variety of mol. and cellular phenotypes. The resulting large-scale functional data can be combined with machine learning and clin. knowledge for the development of "lookup tables" of accurate pathogenicity predictions. A coordinated effort to produce, analyze, and disseminate large-scale functional data generated by multiplex assays could be essential to addressing the variant-interpretation crisis.
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  8. 8
    Hochberg, G. K. A.; Thornton, J. W. Reconstructing Ancient Proteins to Understand the Causes of Structure and Function. Annu. Rev. Biophys. 2017, 46, 247– 269,  DOI: 10.1146/annurev-biophys-070816-033631
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    8
    Reconstructing Ancient Proteins to Understand the Causes of Structure and Function
    Hochberg, Georg K. A.; Thornton, Joseph W.
    Annual Review of Biophysics (2017), 46 (), 247-269CODEN: ARBNCV; ISSN:1936-122X. (Annual Reviews)
    A review. A central goal in biochem. is to explain the causes of protein sequence, structure, and function. Mainstream approaches seek to rationalize sequence and structure in terms of their effects on function and to identify function's underlying determinants by comparing related proteins to each other. Although productive, both strategies suffer from intrinsic limitations that have left important aspects of many proteins unexplained. These limits can be overcome by reconstructing ancient proteins, exptl. characterizing their properties, and retracing their evolution through time. This approach has proven to be a powerful means for discovering how historical changes in sequence produced the functions, structures, and other phys./chem. characteristics of modern proteins. It has also illuminated whether protein features evolved because of functional optimization, historical constraint, or blind chance. Here this review recent studies employing ancestral protein reconstruction and show how they have produced new knowledge not only of mol. evolutionary processes but also of the underlying determinants of modern proteins' phys., chem., and biol. properties.
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  9. 9
    Lim, S. A.; Bolin, E. R.; Marqusee, S. Tracing a Protein’s Folding Pathway over Evolutionary Time Using Ancestral Sequence Reconstruction and Hydrogen Exchange. eLife 2018, 7, e38369  DOI: 10.7554/eLife.38369
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    9
    Tracing a protein's folding pathway over evolutionary time using ancestral sequence reconstruction and hydrogen exchange
    Lim, Shion An; Bolin, Eric Richard; Marqusee, Susan
    eLife (2018), 7 (), e38369/1-e38369/19CODEN: ELIFA8; ISSN:2050-084X. (eLife Sciences Publications Ltd.)
    The conformations populated during protein folding have been studied for decades; yet, their evolutionary importance remains largely unexplored. Ancestral sequence reconstruction allows access to proteins across evolutionary time, and new methods such as pulsed-labeling hydrogen exchange coupled with mass spectrometry allow detn. of folding intermediate structures at near amino-acid resoln. Here, we combine these techniques to monitor the folding of the RNase H family along the evolutionary lineages of T. thermophilus and E. coli RNase H. All homologs and ancestral proteins studied populate a similar folding intermediate despite being sepd. by billions of years of evolution. Even though this conformation is conserved, the pathway leading to it has diverged over evolutionary time, and rational mutations can alter this trajectory. Our results demonstrate that evolutionary processes can affect the energy landscape to preserve or alter specific features of a protein's folding pathway.
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  10. 10
    Flamholz, A. I.; Prywes, N.; Moran, U.; Davidi, D.; Bar-On, Y. M.; Oltrogge, L. M.; Alves, R.; Savage, D.; Milo, R. Revisiting Trade-Offs between Rubisco Kinetic Parameters. Biochemistry 2019, 58, 3365– 3376,  DOI: 10.1021/acs.biochem.9b00237
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    10
    Revisiting Trade-offs between Rubisco Kinetic Parameters
    Flamholz, Avi I.; Prywes, Noam; Moran, Uri; Davidi, Dan; Bar-On, Yinon M.; Oltrogge, Luke M.; Alves, Rui; Savage, David; Milo, Ron
    Biochemistry (2019), 58 (31), 3365-3376CODEN: BICHAW; ISSN:0006-2960. (American Chemical Society)
    Rubisco is the primary carboxylase of the Calvin cycle, the most abundant enzyme in the biosphere, and one of the best-characterized enzymes. On the basis of correlations between Rubisco kinetic parameters, it is widely posited that constraints embedded in the catalytic mechanism enforce trade-offs between CO2 specificity, SC/O, and max. carboxylation rate, kcat,C. However, the reasoning that established this view was based on data from ≈20 organisms. Here, we re-examine models of trade-offs in Rubisco catalysis using a data set from ≈300 organisms. Correlations between kinetic parameters are substantially attenuated in this larger data set, with the inverse relationship between kcat,C and SC/O being a key example. Nonetheless, measured kinetic parameters display extremely limited variation, consistent with a view of Rubisco as a highly constrained enzyme. More than 95% of kcat,C values are between 1 and 10 s-1, and no measured kcat,C exceeds 15 s-1. Similarly, SC/O varies by only 30% among Form I Rubiscos and <10% among C3 plant enzymes. Limited variation in SC/O forces a strong pos. correlation between the catalytic efficiencies (kcat/KM) for carboxylation and oxygenation, consistent with a model of Rubisco catalysis in which increasing the rate of addn. of CO2 to the enzyme-substrate complex requires an equal increase in the O2 addn. rate. Altogether, these data suggest that Rubisco evolution is tightly constrained by the physicochem. limits of CO2/O2 discrimination.
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  11. 11
    Furukawa, R.; Toma, W.; Yamazaki, K.; Akanuma, S. Ancestral Sequence Reconstruction Produces Thermally Stable Enzymes with Mesophilic Enzyme-like Catalytic Properties. Sci. Rep. 2020, 10, 15493,  DOI: 10.1038/s41598-020-72418-4
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    11
    Ancestral sequence reconstruction produces thermally stable enzymes with mesophilic enzyme-like catalytic properties
    Furukawa, Ryutaro; Toma, Wakako; Yamazaki, Koji; Akanuma, Satoshi
    Scientific Reports (2020), 10 (1), 15493CODEN: SRCEC3; ISSN:2045-2322. (Nature Research)
    Abstr.: Enzymes have high catalytic efficiency and low environmental impact, and are therefore potentially useful tools for various industrial processes. Crucially, however, natural enzymes do not always have the properties required for specific processes. It may be necessary, therefore, to design, engineer, and evolve enzymes with properties that are not found in natural enzymes. In particular, the creation of enzymes that are thermally stable and catalytically active at low temp. is desirable for processes involving both high and low temps. In the current study, we designed two ancestral sequences of 3-isopropylmalate dehydrogenase by an ancestral sequence reconstruction technique based on a phylogenetic anal. of extant homologous amino acid sequences. Genes encoding the designed sequences were artificially synthesized and expressed in Escherichia coli. The reconstructed enzymes were found to be slightly more thermally stable than the extant thermophilic homolog from Thermus thermophilus. Moreover, they had considerably higher low-temp. catalytic activity as compared with the T. thermophilus enzyme. Detailed analyses of their temp.-dependent specific activities and kinetic properties showed that the reconstructed enzymes have catalytic properties similar to those of mesophilic homologues. Collectively, our study demonstrates that ancestral sequence reconstruction can produce a thermally stable enzyme with catalytic properties adapted to low-temp. reactions.
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  12. 12
    Alejaldre, L.; Pelletier, J. N.; Quaglia, D. Methods for Enzyme Library Creation: Which One Will You Choose?: A Guide for Novices and Experts to Introduce Genetic Diversity. BioEssays 2021, 43, 2100052,  DOI: 10.1002/bies.202100052
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  13. 13
    Cirino, P., Mayer, K. M., Umeno, D. C.; Mayer, K. M.; Umeno, D. Generating Mutant Libraries Using Error-Prone PCR. In Directed Evolution Library Creation; Humana Press: New Jersey, 2003; Vol. 231, pp. 3– 10.  DOI: 10.1385/1-59259-395-X:3 .
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  14. 14
    Hanson-Manful, P.; Patrick, W. M. Construction and Analysis of Randomized Protein-Encoding Libraries Using Error-Prone PCR. In Protein Nanotechnology; Gerrard, J. A., Ed.; Methods in Molecular Biology; Humana Press: Totowa, NJ, 2013; Vol. 996, pp 251–267.  DOI: 10.1007/978-1-62703-354-1_15 .
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    Firth, A. E.; Patrick, W. M. Statistics of Protein Library Construction. Bioinformatics 2005, 21, 3314– 3315,  DOI: 10.1093/bioinformatics/bti516
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    15
    Statistics of protein library construction
    Firth, Andrew E.; Patrick, Wayne M.
    Bioinformatics (2005), 21 (15), 3314-3315CODEN: BOINFP; ISSN:1367-4803. (Oxford University Press)
    Review. We have investigated the statistics assocd. with constructing and sampling large protein-encoding libraries. Using fairly simple statistics we have written algorithms for estg. the diversity in libraries generated by the most commonly used protocols, including error-prone PCR, DNA shuffling, StEP PCR, oligonucleotide-directed randomization, MAX randomization, synthetic shuffling, DHR, ADO and SISDC.
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  16. 16
    Steffens, D. L.; Williams, J. G. Efficient Site-Directed Saturation Mutagenesis Using Degenerate Oligonucleotides. J. Biomol. Tech. 2007, 18, 147– 149
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    16
    Efficient site-directed saturation mutagenesis using degenerate oligonucleotides
    Steffens David L; Williams John G K
    Journal of biomolecular techniques : JBT (2007), 18 (3), 147-9 ISSN:1524-0215.
    We describe a reliable protocol for constructing single-site saturation mutagenesis libraries consisting of all 20 naturally occurring amino acids at a specific site within a protein. Such libraries are useful for structure-function studies and directed evolution. This protocol extends the utility of Stratagene's QuikChange Site-Directed Mutagenesis Kit, which is primarily recommended for single amino acid substitutions. Two complementary primers are synthesized, containing a degenerate mixture of the four bases at the three positions of the selected codon. These primers are added to starting plasmid template and thermal cycled to produce mutant DNA molecules, which are subsequently transformed into competent bacteria. The protocol does not require purification of mutagenic oligonucleotides or PCR products. This reduces both the cost and turnaround time in high-throughput directed evolution applications. We have utilized this protocol to generate over 200 site-saturation libraries in a DNA polymerase, with a success rate of greater than 95%.
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  17. 17
    Shimko, T. C.; Fordyce, P. M.; Orenstein, Y. DeCoDe: Degenerate Codon Design for Complete Protein-Coding DNA Libraries. Bioinformatics 2020, 36, 3357– 3364,  DOI: 10.1093/bioinformatics/btaa162
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    17
    DeCoDe: degenerate codon design for complete protein-coding DNA libraries
    Shimko, Tyler C.; Fordyce, Polly M.; Orenstein, Yaron
    Bioinformatics (2020), 36 (11), 3357-3364CODEN: BOINFP; ISSN:1367-4811. (Oxford University Press)
    High-throughput protein screening is a crit. technique for dissecting and designing protein function. Libraries for these assays can be created through a no. of means, including targeted or random mutagenesis of a template protein sequence or direct DNA synthesis. However, mutagenic library construction methods often yield vastly more nonfunctional than functional variants and, despite advances in large-scale DNA synthesis, individual synthesis of each desired DNA template is often prohibitively expensive. Consequently, many protein-screening libraries rely on the use of degenerate codons (DCs), mixts. of DNA bases incorporated at specific positions during DNA synthesis, to generate highly diverse protein-variant pools from only a few low-cost synthesis reactions. However, selecting DCs for sets of sequences that covary at multiple positions dramatically increases the difficulty of designing a DC library and leads to the creation of many undesired variants that can quickly outstrip screening capacity. We introduce a novel algorithm for total DC library optimization, degenerate codon design (DeCoDe), based on integer linear programming. DeCoDe significantly outperforms state-of-the-art DC optimization algorithms and scales well to more than a hundred proteins sharing complex patterns of covariation (e.g. the lab-derived avGFP lineage).
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  18. 18
    Picelli, S.; Faridani, O. R.; Björklund, Å. K.; Winberg, G.; Sagasser, S.; Sandberg, R. Full-Length RNA-Seq from Single Cells Using Smart-Seq2. Nat. Protoc. 2014, 9, 171– 181,  DOI: 10.1038/nprot.2014.006
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    18
    Full-length RNA-seq from single cells using Smart-seq2
    Picelli, Simone; Faridani, Omid R.; Bjorklund, Aasa K.; Winberg, Goesta; Sagasser, Sven; Sandberg, Rickard
    Nature Protocols (2014), 9 (1), 171-181CODEN: NPARDW; ISSN:1750-2799. (Nature Publishing Group)
    Emerging methods for the accurate quantification of gene expression in individual cells hold promise for revealing the extent, function and origins of cell-to-cell variability. Different high-throughput methods for single-cell RNA-seq have been introduced that vary in coverage, sensitivity and multiplexing ability. We recently introduced Smart-seq for transcriptome anal. from single cells, and we subsequently optimized the method for improved sensitivity, accuracy and full-length coverage across transcripts. Here we present a detailed protocol for Smart-seq2 that allows the generation of full-length cDNA and sequencing libraries by using std. reagents. The entire protocol takes ∼2 d from cell picking to having a final library ready for sequencing; sequencing will require an addnl. 1-3 d depending on the strategy and sequencer. The current limitations are the lack of strand specificity and the inability to detect nonpolyadenylated (polyA-) RNA.
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  19. 19
    Tee, K. L.; Wong, T. S. Back to Basics: Creating Genetic Diversity. In Directed Enzyme Evolution: Advances and Applications; Alcalde, M., Ed.; Springer International Publishing: Cham, CH, 2017; pp. 201– 227.  DOI: 10.1007/978-3-319-50413-1_8 .
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    Firnberg, E.; Ostermeier, M. PFunkel: Efficient, Expansive, User-Defined Mutagenesis. PLoS One 2012, 7, e52031,  DOI: 10.1371/journal.pone.0052031
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    20
    PFunkel: efficient, expansive, user-defined mutagenesis
    Firnberg, Elad; Ostermeier, Marc
    PLoS One (2012), 7 (12), e52031CODEN: POLNCL; ISSN:1932-6203. (Public Library of Science)
    We introduce PFunkel, a versatile method for extensive, researcher-defined DNA mutagenesis using a ssDNA or dsDNA template. Once the template DNA is prepd., the method can be completed in a single day in a single tube, and requires no intermediate DNA purifn. or sub-cloning. PFunkel can be used for site-directed mutagenesis at an efficiency approaching 100%. More importantly, PFunkel allows researchers the unparalleled ability to efficiently construct user-defined libraries. We demonstrate the creation of a library with site-satn. at four distal sites simultaneously at 70% efficiency. We also employ PFunkel to create a comprehensive codon mutagenesis library of the TEM-1 β-lactamase gene. We designed this library to contain 18,081 members, one for each possible codon substitution in the gene (287 positions in TEM-1 × 63 possible codon substitutions). Deep sequencing revealed that ∼97% of the designed single codon substitutions are present in the library. From such a library we identified 18 previously unreported adaptive mutations that each confer resistance to the β-lactamase inhibitor tazobactam. Three of these mutations confer resistance equal to or higher than that of the most resistant reported TEM-1 allele and have the potential to emerge clin.
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  21. 21
    Wrenbeck, E. E.; Klesmith, J. R.; Stapleton, J. A.; Adeniran, A.; Tyo, K. E. J.; Whitehead, T. A. Plasmid-Based One-Pot Saturation Mutagenesis. Nat. Methods 2016, 13, 928– 930,  DOI: 10.1038/nmeth.4029
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    21
    Plasmid-based one-pot saturation mutagenesis
    Wrenbeck, Emily E.; Klesmith, Justin R.; Stapleton, James A.; Adeniran, Adebola; Tyo, Keith E. J.; Whitehead, Timothy A.
    Nature Methods (2016), 13 (11), 928-930CODEN: NMAEA3; ISSN:1548-7091. (Nature Publishing Group)
    Deep mutational scanning is a foundational tool for addressing the functional consequences of large nos. of mutants, but a more efficient and accessible method for construction of user-defined mutagenesis libraries is needed. Here we present nicking mutagenesis, a robust, single-day, one-pot satn. mutagenesis method performed on routinely prepped plasmid dsDNA. The method can be used to produce comprehensive or single- or multi-site satn. mutagenesis libraries.
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  22. 22
    Bihani, S. C.; Das, A.; Nilgiriwala, K. S.; Prashar, V.; Pirocchi, M.; Apte, S. K.; Ferrer, J.-L.; Hosur, M. V. X-Ray Structure Reveals a New Class and Provides Insight into Evolution of Alkaline Phosphatases. PLoS One 2011, 6, e22767  DOI: 10.1371/journal.pone.0022767
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    22
    X-ray structure reveals a new class and provides insight into evolution of alkaline phosphatases
    Bihani, Subhash C.; Das, Amit; Nilgiriwala, Kayzad S.; Prashar, Vishal; Pirocchi, Michel; Apte, Shree Kumar; Ferrer, Jean-Luc; Hosur, Madhusoodan V.
    PLoS One (2011), 6 (7), e22767CODEN: POLNCL; ISSN:1932-6203. (Public Library of Science)
    The alk. phosphatase (AP) is a bi-metalloenzyme of potential applications in biotechnol. and bioremediation, in which phosphate monoesters are nonspecifically hydrolyzed under alk. conditions to yield inorg. phosphate. The hydrolysis occurs through an enzyme intermediate in which the catalytic residue is phosphorylated. The reaction, which also requires a third metal ion, is proposed to proceed through a mechanism of in-line displacement involving a trigonal bipyramidal transition state. Stabilizing the transition state by bidentate hydrogen bonding has been suggested to be the reason for conservation of an arginine residue in the active site. We report here the first crystal structure of alk. phosphatase purified from the bacterium Sphingomonas sp. Strain BSAR-1 (SPAP). The crystal structure reveals many differences from other APs: (1) the catalytic residue is a threonine instead of serine, (2) there is no third metal ion binding pocket, and (3) the arginine residue forming bidentate hydrogen bonding is deleted in SPAP. A lysine and an aspargine residue, recruited together for the first time into the active site, bind the substrate phosphoryl group in a manner not obsd. before in any other AP. These and other structural features suggest that SPAP represents a new class of APs. Because of its direct contact with the substrate phosphoryl group, the lysine residue is proposed to play a significant role in catalysis. The structure is consistent with a mechanism of in-line displacement via a trigonal bipyramidal transition state. The structure provides important insights into evolutionary relationships between members of AP superfamily.
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  23. 23
    Rinke, C.; Lee, J.; Nath, N.; Goudeau, D.; Thompson, B.; Poulton, N.; Dmitrieff, E.; Malmstrom, R.; Stepanauskas, R.; Woyke, T. Obtaining Genomes from Uncultivated Environmental Microorganisms Using FACS–Based Single-Cell Genomics. Nat. Protoc. 2014, 9, 1038– 1048,  DOI: 10.1038/nprot.2014.067
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    23
    Obtaining genomes from uncultivated environmental microorganisms using FACS-based single-cell genomics
    Rinke, Christian; Lee, Janey; Nath, Nandita; Goudeau, Danielle; Thompson, Brian; Poulton, Nicole; Dmitrieff, Elizabeth; Malmstrom, Rex; Stepanauskas, Ramunas; Woyke, Tanja
    Nature Protocols (2014), 9 (5), 1038-1048CODEN: NPARDW; ISSN:1750-2799. (Nature Publishing Group)
    A review. Single-cell genomics is a powerful tool for exploring the genetic makeup of environmental microorganisms, the vast majority of which are difficult, if not impossible, to cultivate with current approaches. Here we present a comprehensive protocol for obtaining genomes from uncultivated environmental microbes via high-throughput single-cell isolation by FACS. The protocol encompasses the preservation and pretreatment of differing environmental samples, followed by the phys. sepn., lysis, whole-genome amplification and 16S rRNA-based identification of individual bacterial and archaeal cells. The described procedure can be performed with std. mol. biol. equipment and a FACS machine. It takes <12 h of bench time over a 4-d time period, and it generates up to 1 mg of genomic DNA from an individual microbial cell, which is suitable for downstream applications such as PCR amplification and shotgun sequencing. The completeness of the recovered genomes varies, with an av. of ∼50%.
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  24. 24
    Brower, K. K.; Carswell-Crumpton, C.; Klemm, S.; Cruz, B.; Kim, G.; Calhoun, S. G. K.; Nichols, L.; Fordyce, P. M. Double Emulsion Flow Cytometry with High-Throughput Single Droplet Isolation and Nucleic Acid Recovery. Lab Chip 2020, 20, 2062– 2074,  DOI: 10.1039/D0LC00261E
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    24
    Double emulsion flow cytometry with high-throughput single droplet isolation and nucleic acid recovery
    Brower, Kara K.; Carswell-Crumpton, Catherine; Klemm, Sandy; Cruz, Bianca; Kim, Gaeun; Calhoun, Suzanne G. K.; Nichols, Lisa; Fordyce, Polly M.
    Lab on a Chip (2020), 20 (12), 2062-2074CODEN: LCAHAM; ISSN:1473-0189. (Royal Society of Chemistry)
    Droplet microfluidics has made large impacts in diverse areas such as enzyme evolution, chem. product screening, polymer engineering, and single-cell anal. However, while droplet reactions have become increasingly sophisticated, phenotyping droplets by a fluorescent signal and sorting them to isolate individual variants-of-interest at high-throughput remains challenging. Here, we present sdDE-FACS (single droplet Double Emulsion-FACS), a new method that uses a std. flow cytometer to phenotype, select, and isolate individual double emulsion droplets of interest. Using a 130μm nozzle at high sort frequency (12-14 kHz), we demonstrate detection of droplet fluorescence signals with a dynamic range spanning 5 orders of magnitude and robust post-sort recovery of intact double emulsion (DE) droplets using 2 com.-available FACS instruments. We report the first demonstration of single double emulsion droplet isolation with post-sort recovery efficiencies >70%, equiv. to the capabilities of single-cell FACS. Finally, we establish complete downstream recovery of nucleic acids from single, sorted double emulsion droplets via qPCR with little to no cross-contamination. sdDE-FACS marries the full power of droplet microfluidics with flow cytometry to enable a variety of new droplet assays, including rare variant isolation and multiparameter single-cell anal.
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    Bronner, I. F.; Quail, M. A. Best Practices for Illumina Library Preparation. Curr. Protoc. Hum. Genet. 2019, 102, e86,  DOI: 10.1002/cphg.86
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    Picelli, S.; Björklund, Å. K.; Reinius, B.; Sagasser, S.; Winberg, G.; Sandberg, R. Tn5 Transposase and Tagmentation Procedures for Massively Scaled Sequencing Projects. Genome Res. 2014, 24, 2033– 2040,  DOI: 10.1101/gr.177881.114
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    26
    Tn5 transposase and tagmentation procedures for massively scaled sequencing projects
    Picelli, Simone; Bjoerklund, Aasa K.; Reinius, Bjoern; Sagasser, Sven; Winberg, Goesta; Sandberg, Rickard
    Genome Research (2014), 24 (12), 2033-2040CODEN: GEREFS; ISSN:1088-9051. (Cold Spring Harbor Laboratory Press)
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    Figure 1. Overview of the uPIC–M pipeline to generate user-defined clonal mutant libraries. (A) Examples of clonal libraries from uPIC–M and potential high-throughput biochemistry applications. Applications are listed along with examples of the types of variants involved. (B) Comparison of cost (including materials and labor) of conventional mutagenesis vs uPIC–M for libraries of 50–20,000 mutants. A uPIC–M clone sampling rate of 384 per 50 desired mutants (7.68-fold excess) was used for these calculations. uPIC–M (modified) represents a lower cost version of uPIC–M with the addition of pipet tip washing for plate liquid transfer steps. See Table S1 for full time and cost calculations. (C) Workflow for generating uPIC–M libraries in three phases: (1) Mutagenic oligos are synthesized for ∼50 residue windows on a pooled array and selective PCR amplification of each window generates a primer pool used for QuikChange; (2) pooled QuikChange reactions are transformed and plated, with each plate containing a mixture of ∼50 possible single mutants, facilitating colony picking into multiwell plates to isolate clonal libraries of unidentified variants; (3) clonal libraries are prepared and sequenced by NGS to reveal the genotype and location of each variant.

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    Figure 2

    Figure 2. Tiling window strategy for uPIC–M mutagenic oligo array design. (A) Tiling window strategy (see Figure 1C) divides the ORF from the protein of interest into mutagenic sublibrary regions, with sublibrary oligo length constrained by DNA synthesis limits. Each window contains unique forward and reverse priming sites (dark shading, here ∼25 nt each) at the 5′- and 3′-termini surrounding a mutational region (light shading, here ∼150 nt). For a scanning library, each codon along the length of a sublibrary mutational region is substituted via an individual mutagenic oligo. (B) Selective amplification of oligos from a single window (sublibrary 11). Forward and reverse primers specific to a single sublibrary are used to amplify oligos from the resuspended array material, yielding an oligo pool containing ∼50 codon substitutions from the same mutagenic window.

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    Figure 3

    Figure 3. Simulated sampling of pooled single mutant libraries. (A, B) Simulation of the number of unique mutants obtained as a function of the number of clones sampled for pooled libraries containing 50 (A) or 541 (B) unique single mutants with single mutant frequencies from 0.1 to 1.0. The remaining fraction of each pool represents all other variants (e.g., WT, indels, double, and higher-order mutants). Each curve represents the average of 103 simulations; shaded bands represent the 95% confidence interval; horizontal dashed lines (A, B) indicate the total possible number of unique mutants; vertical line (B) indicates the number of colonies picked for the SpAP library constructed herein (for legend, see A). (C–E) Simulated picking results for a sublibrary containing 50 single mutants at equal relative abundances sampled 384 times with a single mutant frequency of 0.5. (C) Simulated positional frequencies of single mutants; the results of five sampling simulations were chosen at random. (D) Histogram of expected mutant yields and (E) histogram of expected yields per sublibrary position (from 103 sampling events).

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    Figure 4

    Figure 4. Schematic of uPIC–M sequencing library preparation. Preparation of sequencing libraries takes place in multiwell plate format (96 or 384) via the following steps: (i) ORF regions of target plasmids are amplified from each clone using universal primers to obtain enriched amplicon DNA (A); (iia) For amplicons ≤600 bp, universal Illumina adapters may be ligated directed to amplicons or added by amplification in a second PCR step; (iib) for amplicons >600 bp, DNA is fragmented and tagged using adapter-loaded Tn5 transposase, i.e., tagmented; (iii) amplicons or fragments are further amplified with Nextera primers that incorporate dual-unique i7 and i5 index barcodes; (iv–vii) amplified and barcoded clonal libraries are pooled for NGS, purified, sequenced, and barcodes are used to report the plate-well location and genotype of each variant (B). Mutant amplicons generated at (i) can be used directly for high-throughput biochemistry applications (shown here: cell-free expression and fluorogenic assay of an enzyme library using a microfluidic platform to obtain kinetic parameters) (C).

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    Figure 5

    Figure 5. Sequencing library quality control results. (A) Plot of fluorescence (arbitrary units) vs fragment length for sublibary 1 following tagmentation and barcoding amplification. See Figure S7 for analogous data for the other sublibraries. (B) Electropherograms of sublibraries 1–13 (see Table S6 for integrated peak concentrations).

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    Figure 6

    Figure 6. NGS data processing and read mapping pipeline and results for the SpAP scanning library. (A) Data processing steps and observed statistics. Raw FASTQ files (demultiplexed and unpaired) are filtered for barcodes containing 1 or more reads followed by adapter sequence trimming and pairing with read mates (if both reads are present and meet length/quality thresholds). Sequence-redundant readthrough read pairs are flagged at this stage and redundant read mates are discarded. (B) Trimmed and paired reads are mapped to the SpAP-eGFP amplicon, E. coli, and full plasmid genomes. (C) Histogram of total reads per barcode across all sublibraries following read trimming and pairing (n = 4645). (D) Barcode counts for each sublibrary plate at several read depth thresholds for the SpAP-eGFP ORF (>0 represents barcodes containing any mapped reads and remaining thresholds represent the minimum number of mapped reads at all positions; only barcodes containing at least one mapped read are included). The horizontal dashed line at 384 barcodes represents the maximum possible number of barcodes.

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    Figure 7

    Figure 7. Characterization of the SpAP alkaline phosphatase scanning mutant library created with uPIC–M. (A) Overview of variant detection analyses and calculated yields (red) for the SpAP mutant library. (B) Overall distribution of single mutants, WT, double mutants, triple and greater mutants, and indels across all mutational sublibraries (indel count reflects variants containing one or more indels). (C) Location and frequency of intended single mutants across the entire SpAP-eGFP ORF. (D) Scatter plot and histograms of variant reads vs WT reads for all intended single mutants. (E) Comparison of simulated and observed single mutant frequency distributions for three sublibraries. The legend specifies the observed yield of unique single mutants and simulated 95% confidence interval from 1000 events; “n” indicates the total number of observed intended single mutants. Results for all sublibraries are shown in Figure S9.

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  • References

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      Gene expression is regulated in part by protein transcription factors that bind target regulatory DNA sequences. Predicting DNA binding sites and affinities from transcription factor sequence or structure is difficult; therefore, exptl. data are required to link transcription factors to target sequences. We present a microfluidics-based approach for de novo discovery and quant. biophys. characterization of DNA target sequences. We validated our technique by measuring sequence preferences for 28 Saccharomyces cerevisiae transcription factors with a variety of DNA-binding domains, including several that have proven difficult to study by other techniques. For each transcription factor, we measured relative binding affinities to oligonucleotides covering all possible 8-bp DNA sequences to create a comprehensive map of sequence preferences; for four transcription factors, we also detd. abs. affinities. We expect that these data and future use of this technique will provide information essential for understanding transcription factor specificity, improving identification of regulatory sites and reconstructing regulatory interactions.
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      Transcription factors (TFs) bind regulatory DNA to control gene expression, and mutations to either TFs or DNA can alter binding affinities to rewire regulatory networks and drive phenotypic variation. While studies have profiled energetic effects of DNA mutations extensively, we lack similar information for TF variants. Here, we present STAMMP (simultaneous transcription factor affinity measurements via microfluidic protein arrays), a high-throughput microfluidic platform enabling quant. characterization of hundreds of TF variants simultaneously. Measured affinities for ∼210 mutants of a model yeast TF (Pho4) interacting with 9 oligonucleotides (>1,800 Kds) reveal that many combinations of mutations to poorly conserved TF residues and nucleotides flanking the core binding site alter but preserve physiol. binding, providing a mechanism by which combinations of mutations in cis and trans could modulate TF binding to tune occupancies during evolution. Moreover, biochem. double-mutant cycles across the TF-DNA interface reveal mol. mechanisms driving recognition, linking sequence to function. A record of this paper's Transparent Peer Review process is included in the Supplemental Information.
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      Starita, L. M.; Ahituv, N.; Dunham, M. J.; Kitzman, J. O.; Roth, F. P.; Seelig, G.; Shendure, J.; Fowler, D. M. Variant Interpretation: Functional Assays to the Rescue. Am. J. Hum. Genet. 2017, 101, 315– 325,  DOI: 10.1016/j.ajhg.2017.07.014
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      Classical genetic approaches for interpreting variants, such as case-control or co-segregation studies, require finding many individuals with each variant. Because the overwhelming majority of variants are present in only a few living humans, this strategy has clear limits. Fully realizing the clin. potential of genetics requires that we accurately infer pathogenicity even for rare or private variation. Many computational approaches to predicting variant effects have been developed, but they can identify only a small fraction of pathogenic variants with the high confidence that is required in the clinic. Exptl. measuring a variant's functional consequences can provide clearer guidance, but individual assays performed only after the discovery of the variant are both time and resource intensive. Here, we discuss how multiplex assays of variant effect (MAVEs) can be used to measure the functional consequences of all possible variants in disease-relevant loci for a variety of mol. and cellular phenotypes. The resulting large-scale functional data can be combined with machine learning and clin. knowledge for the development of "lookup tables" of accurate pathogenicity predictions. A coordinated effort to produce, analyze, and disseminate large-scale functional data generated by multiplex assays could be essential to addressing the variant-interpretation crisis.
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      A review. A central goal in biochem. is to explain the causes of protein sequence, structure, and function. Mainstream approaches seek to rationalize sequence and structure in terms of their effects on function and to identify function's underlying determinants by comparing related proteins to each other. Although productive, both strategies suffer from intrinsic limitations that have left important aspects of many proteins unexplained. These limits can be overcome by reconstructing ancient proteins, exptl. characterizing their properties, and retracing their evolution through time. This approach has proven to be a powerful means for discovering how historical changes in sequence produced the functions, structures, and other phys./chem. characteristics of modern proteins. It has also illuminated whether protein features evolved because of functional optimization, historical constraint, or blind chance. Here this review recent studies employing ancestral protein reconstruction and show how they have produced new knowledge not only of mol. evolutionary processes but also of the underlying determinants of modern proteins' phys., chem., and biol. properties.
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      The conformations populated during protein folding have been studied for decades; yet, their evolutionary importance remains largely unexplored. Ancestral sequence reconstruction allows access to proteins across evolutionary time, and new methods such as pulsed-labeling hydrogen exchange coupled with mass spectrometry allow detn. of folding intermediate structures at near amino-acid resoln. Here, we combine these techniques to monitor the folding of the RNase H family along the evolutionary lineages of T. thermophilus and E. coli RNase H. All homologs and ancestral proteins studied populate a similar folding intermediate despite being sepd. by billions of years of evolution. Even though this conformation is conserved, the pathway leading to it has diverged over evolutionary time, and rational mutations can alter this trajectory. Our results demonstrate that evolutionary processes can affect the energy landscape to preserve or alter specific features of a protein's folding pathway.
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      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1MXitlyrurzJ&md5=9a82831cc2e19b9fb662ce0842abf3a1
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      Flamholz, A. I.; Prywes, N.; Moran, U.; Davidi, D.; Bar-On, Y. M.; Oltrogge, L. M.; Alves, R.; Savage, D.; Milo, R. Revisiting Trade-Offs between Rubisco Kinetic Parameters. Biochemistry 2019, 58, 3365– 3376,  DOI: 10.1021/acs.biochem.9b00237
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      Revisiting Trade-offs between Rubisco Kinetic Parameters
      Flamholz, Avi I.; Prywes, Noam; Moran, Uri; Davidi, Dan; Bar-On, Yinon M.; Oltrogge, Luke M.; Alves, Rui; Savage, David; Milo, Ron
      Biochemistry (2019), 58 (31), 3365-3376CODEN: BICHAW; ISSN:0006-2960. (American Chemical Society)
      Rubisco is the primary carboxylase of the Calvin cycle, the most abundant enzyme in the biosphere, and one of the best-characterized enzymes. On the basis of correlations between Rubisco kinetic parameters, it is widely posited that constraints embedded in the catalytic mechanism enforce trade-offs between CO2 specificity, SC/O, and max. carboxylation rate, kcat,C. However, the reasoning that established this view was based on data from ≈20 organisms. Here, we re-examine models of trade-offs in Rubisco catalysis using a data set from ≈300 organisms. Correlations between kinetic parameters are substantially attenuated in this larger data set, with the inverse relationship between kcat,C and SC/O being a key example. Nonetheless, measured kinetic parameters display extremely limited variation, consistent with a view of Rubisco as a highly constrained enzyme. More than 95% of kcat,C values are between 1 and 10 s-1, and no measured kcat,C exceeds 15 s-1. Similarly, SC/O varies by only 30% among Form I Rubiscos and <10% among C3 plant enzymes. Limited variation in SC/O forces a strong pos. correlation between the catalytic efficiencies (kcat/KM) for carboxylation and oxygenation, consistent with a model of Rubisco catalysis in which increasing the rate of addn. of CO2 to the enzyme-substrate complex requires an equal increase in the O2 addn. rate. Altogether, these data suggest that Rubisco evolution is tightly constrained by the physicochem. limits of CO2/O2 discrimination.
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      Ancestral sequence reconstruction produces thermally stable enzymes with mesophilic enzyme-like catalytic properties
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      Abstr.: Enzymes have high catalytic efficiency and low environmental impact, and are therefore potentially useful tools for various industrial processes. Crucially, however, natural enzymes do not always have the properties required for specific processes. It may be necessary, therefore, to design, engineer, and evolve enzymes with properties that are not found in natural enzymes. In particular, the creation of enzymes that are thermally stable and catalytically active at low temp. is desirable for processes involving both high and low temps. In the current study, we designed two ancestral sequences of 3-isopropylmalate dehydrogenase by an ancestral sequence reconstruction technique based on a phylogenetic anal. of extant homologous amino acid sequences. Genes encoding the designed sequences were artificially synthesized and expressed in Escherichia coli. The reconstructed enzymes were found to be slightly more thermally stable than the extant thermophilic homolog from Thermus thermophilus. Moreover, they had considerably higher low-temp. catalytic activity as compared with the T. thermophilus enzyme. Detailed analyses of their temp.-dependent specific activities and kinetic properties showed that the reconstructed enzymes have catalytic properties similar to those of mesophilic homologues. Collectively, our study demonstrates that ancestral sequence reconstruction can produce a thermally stable enzyme with catalytic properties adapted to low-temp. reactions.
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      Review. We have investigated the statistics assocd. with constructing and sampling large protein-encoding libraries. Using fairly simple statistics we have written algorithms for estg. the diversity in libraries generated by the most commonly used protocols, including error-prone PCR, DNA shuffling, StEP PCR, oligonucleotide-directed randomization, MAX randomization, synthetic shuffling, DHR, ADO and SISDC.
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      We describe a reliable protocol for constructing single-site saturation mutagenesis libraries consisting of all 20 naturally occurring amino acids at a specific site within a protein. Such libraries are useful for structure-function studies and directed evolution. This protocol extends the utility of Stratagene's QuikChange Site-Directed Mutagenesis Kit, which is primarily recommended for single amino acid substitutions. Two complementary primers are synthesized, containing a degenerate mixture of the four bases at the three positions of the selected codon. These primers are added to starting plasmid template and thermal cycled to produce mutant DNA molecules, which are subsequently transformed into competent bacteria. The protocol does not require purification of mutagenic oligonucleotides or PCR products. This reduces both the cost and turnaround time in high-throughput directed evolution applications. We have utilized this protocol to generate over 200 site-saturation libraries in a DNA polymerase, with a success rate of greater than 95%.
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      DeCoDe: degenerate codon design for complete protein-coding DNA libraries
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      Bioinformatics (2020), 36 (11), 3357-3364CODEN: BOINFP; ISSN:1367-4811. (Oxford University Press)
      High-throughput protein screening is a crit. technique for dissecting and designing protein function. Libraries for these assays can be created through a no. of means, including targeted or random mutagenesis of a template protein sequence or direct DNA synthesis. However, mutagenic library construction methods often yield vastly more nonfunctional than functional variants and, despite advances in large-scale DNA synthesis, individual synthesis of each desired DNA template is often prohibitively expensive. Consequently, many protein-screening libraries rely on the use of degenerate codons (DCs), mixts. of DNA bases incorporated at specific positions during DNA synthesis, to generate highly diverse protein-variant pools from only a few low-cost synthesis reactions. However, selecting DCs for sets of sequences that covary at multiple positions dramatically increases the difficulty of designing a DC library and leads to the creation of many undesired variants that can quickly outstrip screening capacity. We introduce a novel algorithm for total DC library optimization, degenerate codon design (DeCoDe), based on integer linear programming. DeCoDe significantly outperforms state-of-the-art DC optimization algorithms and scales well to more than a hundred proteins sharing complex patterns of covariation (e.g. the lab-derived avGFP lineage).
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      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXhvF2htbbE&md5=28244a325db665e60a24e45499eb4e2f
    18. 18
      Picelli, S.; Faridani, O. R.; Björklund, Å. K.; Winberg, G.; Sagasser, S.; Sandberg, R. Full-Length RNA-Seq from Single Cells Using Smart-Seq2. Nat. Protoc. 2014, 9, 171– 181,  DOI: 10.1038/nprot.2014.006
      18
      Full-length RNA-seq from single cells using Smart-seq2
      Picelli, Simone; Faridani, Omid R.; Bjorklund, Aasa K.; Winberg, Goesta; Sagasser, Sven; Sandberg, Rickard
      Nature Protocols (2014), 9 (1), 171-181CODEN: NPARDW; ISSN:1750-2799. (Nature Publishing Group)
      Emerging methods for the accurate quantification of gene expression in individual cells hold promise for revealing the extent, function and origins of cell-to-cell variability. Different high-throughput methods for single-cell RNA-seq have been introduced that vary in coverage, sensitivity and multiplexing ability. We recently introduced Smart-seq for transcriptome anal. from single cells, and we subsequently optimized the method for improved sensitivity, accuracy and full-length coverage across transcripts. Here we present a detailed protocol for Smart-seq2 that allows the generation of full-length cDNA and sequencing libraries by using std. reagents. The entire protocol takes ∼2 d from cell picking to having a final library ready for sequencing; sequencing will require an addnl. 1-3 d depending on the strategy and sequencer. The current limitations are the lack of strand specificity and the inability to detect nonpolyadenylated (polyA-) RNA.
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      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXls1ejtrc%253D&md5=152c5b7d140d866952bd1e211fefd280
    19. 19
      Tee, K. L.; Wong, T. S. Back to Basics: Creating Genetic Diversity. In Directed Enzyme Evolution: Advances and Applications; Alcalde, M., Ed.; Springer International Publishing: Cham, CH, 2017; pp. 201– 227.  DOI: 10.1007/978-3-319-50413-1_8 .
      There is no corresponding record for this reference.
    20. 20
      Firnberg, E.; Ostermeier, M. PFunkel: Efficient, Expansive, User-Defined Mutagenesis. PLoS One 2012, 7, e52031,  DOI: 10.1371/journal.pone.0052031
      20
      PFunkel: efficient, expansive, user-defined mutagenesis
      Firnberg, Elad; Ostermeier, Marc
      PLoS One (2012), 7 (12), e52031CODEN: POLNCL; ISSN:1932-6203. (Public Library of Science)
      We introduce PFunkel, a versatile method for extensive, researcher-defined DNA mutagenesis using a ssDNA or dsDNA template. Once the template DNA is prepd., the method can be completed in a single day in a single tube, and requires no intermediate DNA purifn. or sub-cloning. PFunkel can be used for site-directed mutagenesis at an efficiency approaching 100%. More importantly, PFunkel allows researchers the unparalleled ability to efficiently construct user-defined libraries. We demonstrate the creation of a library with site-satn. at four distal sites simultaneously at 70% efficiency. We also employ PFunkel to create a comprehensive codon mutagenesis library of the TEM-1 β-lactamase gene. We designed this library to contain 18,081 members, one for each possible codon substitution in the gene (287 positions in TEM-1 × 63 possible codon substitutions). Deep sequencing revealed that ∼97% of the designed single codon substitutions are present in the library. From such a library we identified 18 previously unreported adaptive mutations that each confer resistance to the β-lactamase inhibitor tazobactam. Three of these mutations confer resistance equal to or higher than that of the most resistant reported TEM-1 allele and have the potential to emerge clin.
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    21. 21
      Wrenbeck, E. E.; Klesmith, J. R.; Stapleton, J. A.; Adeniran, A.; Tyo, K. E. J.; Whitehead, T. A. Plasmid-Based One-Pot Saturation Mutagenesis. Nat. Methods 2016, 13, 928– 930,  DOI: 10.1038/nmeth.4029
      21
      Plasmid-based one-pot saturation mutagenesis
      Wrenbeck, Emily E.; Klesmith, Justin R.; Stapleton, James A.; Adeniran, Adebola; Tyo, Keith E. J.; Whitehead, Timothy A.
      Nature Methods (2016), 13 (11), 928-930CODEN: NMAEA3; ISSN:1548-7091. (Nature Publishing Group)
      Deep mutational scanning is a foundational tool for addressing the functional consequences of large nos. of mutants, but a more efficient and accessible method for construction of user-defined mutagenesis libraries is needed. Here we present nicking mutagenesis, a robust, single-day, one-pot satn. mutagenesis method performed on routinely prepped plasmid dsDNA. The method can be used to produce comprehensive or single- or multi-site satn. mutagenesis libraries.
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      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28Xhs1CnsrjF&md5=b571c246fb8f2c6bd97016e12a5d2302
    22. 22
      Bihani, S. C.; Das, A.; Nilgiriwala, K. S.; Prashar, V.; Pirocchi, M.; Apte, S. K.; Ferrer, J.-L.; Hosur, M. V. X-Ray Structure Reveals a New Class and Provides Insight into Evolution of Alkaline Phosphatases. PLoS One 2011, 6, e22767  DOI: 10.1371/journal.pone.0022767
      22
      X-ray structure reveals a new class and provides insight into evolution of alkaline phosphatases
      Bihani, Subhash C.; Das, Amit; Nilgiriwala, Kayzad S.; Prashar, Vishal; Pirocchi, Michel; Apte, Shree Kumar; Ferrer, Jean-Luc; Hosur, Madhusoodan V.
      PLoS One (2011), 6 (7), e22767CODEN: POLNCL; ISSN:1932-6203. (Public Library of Science)
      The alk. phosphatase (AP) is a bi-metalloenzyme of potential applications in biotechnol. and bioremediation, in which phosphate monoesters are nonspecifically hydrolyzed under alk. conditions to yield inorg. phosphate. The hydrolysis occurs through an enzyme intermediate in which the catalytic residue is phosphorylated. The reaction, which also requires a third metal ion, is proposed to proceed through a mechanism of in-line displacement involving a trigonal bipyramidal transition state. Stabilizing the transition state by bidentate hydrogen bonding has been suggested to be the reason for conservation of an arginine residue in the active site. We report here the first crystal structure of alk. phosphatase purified from the bacterium Sphingomonas sp. Strain BSAR-1 (SPAP). The crystal structure reveals many differences from other APs: (1) the catalytic residue is a threonine instead of serine, (2) there is no third metal ion binding pocket, and (3) the arginine residue forming bidentate hydrogen bonding is deleted in SPAP. A lysine and an aspargine residue, recruited together for the first time into the active site, bind the substrate phosphoryl group in a manner not obsd. before in any other AP. These and other structural features suggest that SPAP represents a new class of APs. Because of its direct contact with the substrate phosphoryl group, the lysine residue is proposed to play a significant role in catalysis. The structure is consistent with a mechanism of in-line displacement via a trigonal bipyramidal transition state. The structure provides important insights into evolutionary relationships between members of AP superfamily.
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    23. 23
      Rinke, C.; Lee, J.; Nath, N.; Goudeau, D.; Thompson, B.; Poulton, N.; Dmitrieff, E.; Malmstrom, R.; Stepanauskas, R.; Woyke, T. Obtaining Genomes from Uncultivated Environmental Microorganisms Using FACS–Based Single-Cell Genomics. Nat. Protoc. 2014, 9, 1038– 1048,  DOI: 10.1038/nprot.2014.067
      23
      Obtaining genomes from uncultivated environmental microorganisms using FACS-based single-cell genomics
      Rinke, Christian; Lee, Janey; Nath, Nandita; Goudeau, Danielle; Thompson, Brian; Poulton, Nicole; Dmitrieff, Elizabeth; Malmstrom, Rex; Stepanauskas, Ramunas; Woyke, Tanja
      Nature Protocols (2014), 9 (5), 1038-1048CODEN: NPARDW; ISSN:1750-2799. (Nature Publishing Group)
      A review. Single-cell genomics is a powerful tool for exploring the genetic makeup of environmental microorganisms, the vast majority of which are difficult, if not impossible, to cultivate with current approaches. Here we present a comprehensive protocol for obtaining genomes from uncultivated environmental microbes via high-throughput single-cell isolation by FACS. The protocol encompasses the preservation and pretreatment of differing environmental samples, followed by the phys. sepn., lysis, whole-genome amplification and 16S rRNA-based identification of individual bacterial and archaeal cells. The described procedure can be performed with std. mol. biol. equipment and a FACS machine. It takes <12 h of bench time over a 4-d time period, and it generates up to 1 mg of genomic DNA from an individual microbial cell, which is suitable for downstream applications such as PCR amplification and shotgun sequencing. The completeness of the recovered genomes varies, with an av. of ∼50%.
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    24. 24
      Brower, K. K.; Carswell-Crumpton, C.; Klemm, S.; Cruz, B.; Kim, G.; Calhoun, S. G. K.; Nichols, L.; Fordyce, P. M. Double Emulsion Flow Cytometry with High-Throughput Single Droplet Isolation and Nucleic Acid Recovery. Lab Chip 2020, 20, 2062– 2074,  DOI: 10.1039/D0LC00261E
      24
      Double emulsion flow cytometry with high-throughput single droplet isolation and nucleic acid recovery
      Brower, Kara K.; Carswell-Crumpton, Catherine; Klemm, Sandy; Cruz, Bianca; Kim, Gaeun; Calhoun, Suzanne G. K.; Nichols, Lisa; Fordyce, Polly M.
      Lab on a Chip (2020), 20 (12), 2062-2074CODEN: LCAHAM; ISSN:1473-0189. (Royal Society of Chemistry)
      Droplet microfluidics has made large impacts in diverse areas such as enzyme evolution, chem. product screening, polymer engineering, and single-cell anal. However, while droplet reactions have become increasingly sophisticated, phenotyping droplets by a fluorescent signal and sorting them to isolate individual variants-of-interest at high-throughput remains challenging. Here, we present sdDE-FACS (single droplet Double Emulsion-FACS), a new method that uses a std. flow cytometer to phenotype, select, and isolate individual double emulsion droplets of interest. Using a 130μm nozzle at high sort frequency (12-14 kHz), we demonstrate detection of droplet fluorescence signals with a dynamic range spanning 5 orders of magnitude and robust post-sort recovery of intact double emulsion (DE) droplets using 2 com.-available FACS instruments. We report the first demonstration of single double emulsion droplet isolation with post-sort recovery efficiencies >70%, equiv. to the capabilities of single-cell FACS. Finally, we establish complete downstream recovery of nucleic acids from single, sorted double emulsion droplets via qPCR with little to no cross-contamination. sdDE-FACS marries the full power of droplet microfluidics with flow cytometry to enable a variety of new droplet assays, including rare variant isolation and multiparameter single-cell anal.
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    25. 25
      Bronner, I. F.; Quail, M. A. Best Practices for Illumina Library Preparation. Curr. Protoc. Hum. Genet. 2019, 102, e86,  DOI: 10.1002/cphg.86
      There is no corresponding record for this reference.
    26. 26
      Picelli, S.; Björklund, Å. K.; Reinius, B.; Sagasser, S.; Winberg, G.; Sandberg, R. Tn5 Transposase and Tagmentation Procedures for Massively Scaled Sequencing Projects. Genome Res. 2014, 24, 2033– 2040,  DOI: 10.1101/gr.177881.114
      26
      Tn5 transposase and tagmentation procedures for massively scaled sequencing projects
      Picelli, Simone; Bjoerklund, Aasa K.; Reinius, Bjoern; Sagasser, Sven; Winberg, Goesta; Sandberg, Rickard
      Genome Research (2014), 24 (12), 2033-2040CODEN: GEREFS; ISSN:1088-9051. (Cold Spring Harbor Laboratory Press)
      Massively parallel DNA sequencing of thousands of samples in a single machine-run is now possible, but the prepn. of the individual sequencing libraries is expensive and time-consuming. Tagmentation-based library construction, using the Tn5 transposase, is efficient for generating sequencing libraries but currently relies on undisclosed reagents, which severely limits development of novel applications and the execution of large-scale projects. Here, we present simple and robust procedures for Tn5 transposase prodn. and optimized reaction conditions for tagmentation-based sequencing library construction. We further show how mol. crowding agents both modulate library lengths and enable efficient tagmentation from subpicogram amts. of cDNA. The comparison of single-cell RNA-sequencing libraries generated using produced and com. Tn5 demonstrated equal performances in terms of gene detection and library characteristics. Finally, because naked Tn5 can be annealed to any oligonucleotide of choice, for example, mol. barcodes in single-cell assays or methylated oligonucleotides for bisulfite sequencing, custom Tn5 prodn. and tagmentation enable innovation in sequencing-based applications.
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      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXitVOls7%252FF&md5=a79bbd4c329ebfb8690eb89ea04f2380
    27. 27
      Adey, A.; Morrison, H. G.; Xun, X.; Kitzman, J. O.; Turner, E. H.; Stackhouse, B.; MacKenzie, A. P.; Caruccio, N. C.; Zhang, X.; Shendure, J. Rapid, Low-Input, Low-Bias Construction of Shotgun Fragment Libraries by High-Density in Vitro Transposition. Genome Biol. 2010, 11, R119,  DOI: 10.1186/gb-2010-11-12-r119
      27
      Rapid, low-input, low-bias construction of shotgun fragment libraries by high-density in vitro transposition
      Adey, Andrew; Morrison, Hilary G.; Asan; Xun, Xu; Kitzman, Jacob O.; Turner, Emily H.; Stackhouse, Bethany; MacKenzie, Alexandra P.; Caruccio, Nicholas C.; Zhang, Xiuqing; Shendure, Jay
      Genome Biology (2010), 11 (12), R119CODEN: GNBLFW; ISSN:1474-760X. (BioMed Central Ltd.)
      We characterize and extend a highly efficient method for constructing shotgun fragment libraries in which transposase catalyzes in vitro DNA fragmentation and adaptor incorporation simultaneously. We apply this method towards sequencing a human genome, and find that coverage biases are comparable with conventional protocols. We also extend its capabilities by developing protocols for sub-nanogram library construction, exome capture from 50 ng of input DNA, PCR-free and colony PCR library construction, and 96-plex sample indexing.
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      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXltVegsA%253D%253D&md5=99c96db11994c37386dfdfd9947e80b5
    28. 28
      Glenn, T. C.; Nilsen, R. A.; Kieran, T. J.; Sanders, J. G.; Bayona-Vásquez, N. J.; Finger, J. W.; Pierson, T. W.; Bentley, K. E.; Hoffberg, S. L.; Louha, S.; Garcia-De Leon, F. J.; Del Rio Portilla, M. A.; Reed, K. D.; Anderson, J. L.; Meece, J. K.; Aggrey, S. E.; Rekaya, R.; Alabady, M.; Belanger, M.; Winker, K.; Faircloth, B. C. Adapterama I: Universal Stubs and Primers for 384 Unique Dual-Indexed or 147,456 Combinatorially-Indexed Illumina Libraries (ITru & INext). PeerJ 2019, 7, e7755,  DOI: 10.7717/peerj.7755
      There is no corresponding record for this reference.
    29. 29
      Tegally, H.; San, J. E.; Giandhari, J.; de Oliveira, T. Unlocking the Efficiency of Genomics Laboratories with Robotic Liquid-Handling. BMC Genomics 2020, 21, 729,  DOI: 10.1186/s12864-020-07137-1
      29
      Unlocking the efficiency of genomics laboratories with robotic liquid-handling
      Tegally Houriiyah; San James Emmanuel; Giandhari Jennifer; de Oliveira Tulio; de Oliveira Tulio
      BMC genomics (2020), 21 (1), 729 ISSN:.
      In research and clinical genomics laboratories today, sample preparation is the bottleneck of experiments, particularly when it comes to high-throughput next generation sequencing (NGS). More genomics laboratories are now considering liquid-handling automation to make the sequencing workflow more efficient and cost effective. The question remains as to its suitability and return on investment. A number of points need to be carefully considered before introducing robots into biological laboratories. Here, we describe the state-of-the-art technology of both sophisticated and do-it-yourself (DIY) robotic liquid-handlers and provide a practical review of the motivation, implications and requirements of laboratory automation for genome sequencing experiments.
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      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BB3s7jvFyitg%253D%253D&md5=4d99e01dfd76d80ead2ec8ad63d97087
    30. 30
      Bolger, A. M.; Lohse, M.; Usadel, B. Trimmomatic: A Flexible Trimmer for Illumina Sequence Data. Bioinformatics 2014, 30, 2114– 2120,  DOI: 10.1093/bioinformatics/btu170
      30
      Trimmomatic: a flexible trimmer for Illumina sequence data
      Bolger, Anthony M.; Lohse, Marc; Usadel, Bjoern
      Bioinformatics (2014), 30 (15), 2114-2120CODEN: BOINFP; ISSN:1367-4803. (Oxford University Press)
      Motivation: Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data. Results: The value of NGS read preprocessing is demonstrated for both ref.-based and ref.-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested. Availability and implementation: Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.phppage=trimmomatic Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics online.
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    31. 31
      Li, H. Aligning Sequence Reads, Clone Sequences and Assembly Contigs with BWA-MEM. arXiv:1303.3997 [q-bio] 2013.
      There is no corresponding record for this reference.
    32. 32
      Li, H.; Handsaker, B.; Wysoker, A.; Fennell, T.; Ruan, J.; Homer, N.; Marth, G.; Abecasis, G.; Durbin, R.; 1000 Genome Project Data Processing Subgroup The Sequence Alignment/Map Format and SAMtools. Bioinformatics 2009, 25, 2078– 2079,  DOI: 10.1093/bioinformatics/btp352
      32
      The Sequence Alignment/Map format and SAMtools
      Li, Heng; Handsaker, Bob; Wysoker, Alec; Fennell, Tim; Ruan, Jue; Homer, Nils; Marth, Gabor; Abecasis, Goncalo; Durbin, Richard
      Bioinformatics (2009), 25 (16), 2078-2079CODEN: BOINFP; ISSN:1367-4803. (Oxford University Press)
      Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against ref. sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: [email protected].
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    33. 33
      Li, H. A Statistical Framework for SNP Calling, Mutation Discovery, Association Mapping and Population Genetical Parameter Estimation from Sequencing Data. Bioinformatics 2011, 27, 2987– 2993,  DOI: 10.1093/bioinformatics/btr509
      33
      A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing data
      Li, Heng
      Bioinformatics (2011), 27 (21), 2987-2993CODEN: BOINFP; ISSN:1367-4803. (Oxford University Press)
      Motivation: Most existing methods for DNA sequence anal. rely on accurate sequences or genotypes. However, in applications of the next-generation sequencing (NGS), accurate genotypes may not be easily obtained (e.g. multi-sample low-coverage sequencing or somatic mutation discovery). These applications press for the development of new methods for analyzing sequence data with uncertainty. Results: We present a statistical framework for calling SNPs, discovering somatic mutations, inferring population genetical parameters and performing assocn. tests directly based on sequencing data without explicit genotyping or linkage-based imputation. On real data, we demonstrate that our method achieves comparable accuracy to alternative methods for estg. site allele count, for inferring allele frequency spectrum and for assocn. mapping. We also highlight the necessity of using sym. datasets for finding somatic mutations and confirm that for discovering rare events, mismapping is frequently the leading source of errors. Availability: http://samtools.sourceforge.net Contact: [email protected].
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      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXhtlGkur7L&md5=778fc839fbbce2b0fc82aa2d9295652b
    34. 34
      Kirsch, R. D.; Joly, E. An Improved PCR-Mutagenesis Strategy for Two-Site Mutagenesis or Sequence Swapping between Related Genes. Nucleic Acids Res. 1998, 26, 1848– 1850,  DOI: 10.1093/nar/26.7.1848
      34
      An improved PCR-mutagenesis strategy for two-site mutagenesis or sequence swapping between related genes
      Kirsch, Ralf D.; Joly, Etienne
      Nucleic Acids Research (1998), 26 (7), 1848-1850CODEN: NARHAD; ISSN:0305-1048. (Oxford University Press)
      The QuikChange protocol is one of the simplest and fastest methods for site-directed mutagenesis, but introduces mutations at only one site at a time, and requires two HPLC-purified complementary oligonucleotides. Here, we describe that this method can be used with non-overlapping oligonucleotides. By doing this, two sep. sites can be mutagenized simultaneously, or money can be saved by using a second "std." oligonucleotide. By a further modification, we have also used the QuikChange approach to exchange DNA sequences between closely related genes.
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      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK1cXis1Oju7Y%253D&md5=31423b2c27f6d183e7dc1b49d4d982c5
    35. 35
      Wang, W.; Malcolm, B. A. Two-Stage PCR Protocol Allowing Introduction of Multiple Mutations, Deletions and Insertions Using QuikChange TM Site-Directed Mutagenesis. BioTechniques 1999, 26, 680– 682,  DOI: 10.2144/99264st03
      35
      Two-stage PCR protocol allowing introduction of multiple mutations, deletions and insertions using QuikChange Site-Directed Mutagenesis
      Wang, Wenyan; Malcolm, Bruce A.
      BioTechniques (1999), 26 (4), 680-682CODEN: BTNQDO; ISSN:0736-6205. (Eaton Publishing Co.)
      We developed a two-stage procedure, based on the QuikChange Site-Directed Mutagenesis Protocol, that significantly expands its application to a variety of gene modification expts. A pre-PCR, single-primer extension stage before the std. protocol allows the efficient introduction of not only point mutation but also multiple mutations and deletions and insertions to a sequence of interest.
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      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK1MXislGmtrk%253D&md5=96add1e80ac3ed042f88de046997a848
    36. 36
      Li, M. Z.; Elledge, S. J. Harnessing Homologous Recombination in Vitro to Generate Recombinant DNA via SLIC. Nat. Methods 2007, 4, 251– 256,  DOI: 10.1038/nmeth1010
      36
      Harnessing homologous recombination in vitro to generate recombinant DNA via SLIC
      Li, Mamie Z.; Elledge, Stephen J.
      Nature Methods (2007), 4 (3), 251-256CODEN: NMAEA3; ISSN:1548-7091. (Nature Publishing Group)
      We describe a new cloning method, sequence and ligation-independent cloning (SLIC), which allows the assembly of multiple DNA fragments in a single reaction using in vitro homologous recombination and single-strand annealing. SLIC mimics in vivo homologous recombination by relying on exonuclease-generated ssDNA overhangs in insert and vector fragments, and the assembly of these fragments by recombination in vitro. SLIC inserts can also be prepd. by incomplete PCR (iPCR) or mixed PCR. SLIC allows efficient and reproducible assembly of recombinant DNA with as many as 5 and 10 fragments simultaneously. SLIC circumvents the sequence requirements of traditional methods and functions much more efficiently at very low DNA concns. when combined with RecA to catalyze homologous recombination. This flexibility allows much greater versatility in the generation of recombinant DNA for the purposes of synthetic biol.
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      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2sXitFChsbY%253D&md5=daf627b0eb2b744aa33a7e109f6df6b6
    37. 37
      Gibson, D. G.; Young, L.; Chuang, R.-Y.; Venter, J. C.; Hutchison, C. A., III; Smith, H. O. Enzymatic Assembly of DNA Molecules up to Several Hundred Kilobases. Nat. Methods 2009, 6, 343– 345,  DOI: 10.1038/nmeth.1318
      37
      Enzymatic assembly of DNA molecules up to several hundred kilobases
      Gibson, Daniel G.; Young, Lei; Chuang, Ray-Yuan; Venter, J. Craig; Hutchison, Clyde A.; Smith, Hamilton O.
      Nature Methods (2009), 6 (5), 343-345CODEN: NMAEA3; ISSN:1548-7091. (Nature Publishing Group)
      The authors describe an isothermal, single-reaction method for assembling multiple overlapping DNA mols. by the concerted action of a 5' exonuclease, a DNA polymerase and a DNA ligase. First they recessed DNA fragments, yielding single-stranded DNA overhangs that specifically annealed, and then covalently joined them. This assembly method can be used to seamlessly construct synthetic and natural genes, genetic pathways and entire genomes, and could be a useful mol. engineering tool.
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      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXksVemsbw%253D&md5=46284924c7d73c47cfb490983338e480
    38. 38
      Longwell, S. A.; Appel, M. J.; Orenstein, Y.; Fordyce, P. M. OpTile: An Optimized Method for Creating Overlapping Tiled Oligonucleotide Libraries. In preparation .
      There is no corresponding record for this reference.
    39. 39
      Logsdon, G. A.; Vollger, M. R.; Eichler, E. E. Long-Read Human Genome Sequencing and Its Applications. Nat. Rev. Genet. 2020, 21, 597– 614,  DOI: 10.1038/s41576-020-0236-x
      39
      Long-read human genome sequencing and its applications
      Logsdon, Glennis A.; Vollger, Mitchell R.; Eichler, Evan E.
      Nature Reviews Genetics (2020), 21 (10), 597-614CODEN: NRGAAM; ISSN:1471-0056. (Nature Research)
      A review. Over the past decade, long-read, single-mol. DNA sequencing technologies have emerged as powerful players in genomics. With the ability to generate reads tens to thousands of kilobases in length with an accuracy approaching that of short-read sequencing technologies, these platforms have proven their ability to resolve some of the most challenging regions of the human genome, detect previously inaccessible structural variants and generate some of the first telomere-to-telomere assemblies of whole chromosomes. Long-read sequencing technologies will soon permit the routine assembly of diploid genomes, which will revolutionize genomics by revealing the full spectrum of human genetic variation, resolving some of the missing heritability and leading to the discovery of novel mechanisms of disease.
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    40. 40
      Nilgiriwala, K. S.; Alahari, A.; Rao, A. S.; Apte, S. K. Cloning and Overexpression of Alkaline Phosphatase PhoK from Sphingomonas Sp. Strain BSAR-1 for Bioprecipitation of Uranium from Alkaline Solutions. Appl. Environ. Microbiol. 2008, 74, 5516– 5523,  DOI: 10.1128/aem.00107-08
      40
      Cloning and overexpression of alkaline phosphatase phoK from Sphingomonas sp. strain BSAR-1 for bioprecipitation of uranium from alkaline solutions
      Nilgiriwala, Kayzad S.; Alahari, Anuradha; Rao, Amara Sambasiva; Apte, Shree Kumar
      Applied and Environmental Microbiology (2008), 74 (17), 5516-5523CODEN: AEMIDF; ISSN:0099-2240. (American Society for Microbiology)
      Cells of Sphingomonas sp. strain BSAR-1 constitutively expressed an alk. phosphatase, which was also secreted in the extracellular medium. A null mutant lacking this alk. phosphatase activity was isolated by Tn5 random mutagenesis. The corresponding gene, designated phoK, was cloned and overexpressed in Escherichia coli strain BL21(DE3). The resultant E. coli strain EK4 overexpressed cellular activity 55 times higher and secreted extracellular PhoK activity 13 times higher than did BSAR-1. The recombinant strain very rapidly pptd. >90% of input uranium in less than 2 h from alk. solns. (pH, 9) contg. 0.5 to 5 mM of uranyl carbonate, compared to BSAR-1, which pptd. uranium in >7 h. In both strains BSAR-1 and EK4, pptd. uranium remained cell bound. The EK4 cells exhibited a much higher loading capacity of 3.8 g U/g dry wt. in <2 h compared to only 1.5 g U/g dry wt. in >7 h in BSAR-1. The data demonstrate the potential utility of genetically engineering PhoK for the biopptn. of uranium from alk. solns.
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    41. 41
      Chern, E. C.; Siefring, S.; Paar, J.; Doolittle, M.; Haugland, R. A. Comparison of Quantitative PCR Assays for Escherichia Coli Targeting Ribosomal RNA and Single Copy Genes. Lett. Appl. Microbiol. 2011, 52, 298– 306,  DOI: 10.1111/j.1472-765X.2010.03001.x
      41
      Comparison of quantitative PCR assays for Escherichia coli targeting ribosomal RNA and single copy genes
      Chern, E. C.; Siefring, S.; Paar, J.; Doolittle, M.; Haugland, R. A.
      Letters in Applied Microbiology (2011), 52 (3), 298-306CODEN: LAMIE7; ISSN:0266-8254. (Wiley-Blackwell)
      Aims: Compare specificity and sensitivity of quant. PCR (qPCR) assays targeting single and multi-copy gene regions of Escherichia coli. Methods and Results: A previously reported assay targeting the uidA gene (uidA405) was used as the basis for comparing the taxonomic specificity and sensitivity of qPCR assays targeting the rodA gene (rodA984) and two regions of the multi-copy 23S rRNA gene (EC23S and EC23S857). Exptl. analyses of 28 culture collection strains representing E. coli and 21 related non-target species indicated that the uidA405 and rodA984 assays were both 100% specific for E. coli while the EC23S assay was only 29% specific. The EC23S857 assay was only 95% specific due to detection of E. fergusonii. The uidA405, rodA984, EC23S and EC23S857 assays were 85%, 85%, 100% and 86% sensitive, resp., in detecting 175 presumptive E. coli culture isolates from fresh, marine and waste water samples. In analyses of DNA exts. from 32 fresh, marine and waste water samples, the rodA984, EC23S and EC23S857 assays detected mean densities of target sequences at ratios of approx. 1:1, 243:1 and 6:1 compared with the mean densities detected by the uidA405 assay. Conclusions: The EC23S assay was less specific for E. coli, whereas the rodA984 and EC23S857 assay taxonomic specificities and sensitivities were similar to those of the uidA405 gene assay. Significance and Impact: The EC23S857 assay has a lower limit of detection for E. coli cells than the uidA405 and rodA984 assays due to its multi-copy gene target and therefore provides greater anal. sensitivity in monitoring for these fecal pollution indicators in environmental waters by qPCR methods.
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    42. 42
      van Rossum, G.; Drake, F. L.; Van Rossum, G. The Python Language Reference, Release 3.0.1 [Repr.].; Python documentation manual; Python Software Foundation: Hampton, NH, 2010.
      There is no corresponding record for this reference.
    43. 43
      Mölder, F.; Jablonski, K. P.; Letcher, B.; Hall, M. B.; Tomkins-Tinch, C. H.; Sochat, V.; Forster, J.; Lee, S.; Twardziok, S. O.; Kanitz, A.; Wilm, A.; Holtgrewe, M.; Rahmann, S.; Nahnsen, S.; Köster, J. Sustainable Data Analysis with Snakemake. F1000Res 2021, 10, 33,  DOI: 10.12688/f1000research.29032.1
      43
      Sustainable data analysis with Snakemake
      Molder Felix; Forster Jan; Koster Johannes; Molder Felix; Jablonski Kim Philipp; Jablonski Kim Philipp; Letcher Brice; Hall Michael B; Tomkins-Tinch Christopher H; Tomkins-Tinch Christopher H; Sochat Vanessa; Forster Jan; Lee Soohyun; Twardziok Sven O; Holtgrewe Manuel; Kanitz Alexander; Kanitz Alexander; Wilm Andreas; Holtgrewe Manuel; Rahmann Sven; Nahnsen Sven; Koster Johannes
      F1000Research (2021), 10 (), 33 ISSN:.
      Data analysis often entails a multitude of heterogeneous steps, from the application of various command line tools to the usage of scripting languages like R or Python for the generation of plots and tables. It is widely recognized that data analyses should ideally be conducted in a reproducible way. Reproducibility enables technical validation and regeneration of results on the original or even new data. However, reproducibility alone is by no means sufficient to deliver an analysis that is of lasting impact (i.e., sustainable) for the field, or even just one research group. We postulate that it is equally important to ensure adaptability and transparency. The former describes the ability to modify the analysis to answer extended or slightly different research questions. The latter describes the ability to understand the analysis in order to judge whether it is not only technically, but methodologically valid. Here, we analyze the properties needed for a data analysis to become reproducible, adaptable, and transparent. We show how the popular workflow management system Snakemake can be used to guarantee this, and how it enables an ergonomic, combined, unified representation of all steps involved in data analysis, ranging from raw data processing, to quality control and fine-grained, interactive exploration and plotting of final results.
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    44. 44
      Robinson, J. T.; Thorvaldsdóttir, H.; Winckler, W.; Guttman, M.; Lander, E. S.; Getz, G.; Mesirov, J. P. Integrative Genomics Viewer. Nat. Biotechnol. 2011, 29, 24– 26,  DOI: 10.1038/nbt.1754
      44
      Integrative genomics viewer
      Robinson, James T.; Thorvaldsdottir, Helga; Winckler, Wendy; Guttman, Mitchell; Lander, Eric S.; Getz, Gad; Mesirov, Jill P.
      Nature Biotechnology (2011), 29 (1), 24-26CODEN: NABIF9; ISSN:1087-0156. (Nature Publishing Group)
      There is no expanded citation for this reference.
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  • Supporting Information

    Supporting Information

    The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acsomega.1c04180.

    • Timeline of uPIC–M library generation, amplification of window-specific sublibrary pools from an oligo array, quantification of E. coli genomic DNA in diluted mutant culture templates, selection of PCR conditions for SpAP mutant amplicons, quantification of amplicon DNA concentrations per sublibrary plate, Tn5 tagmentation reaction conditions, electropherograms of tagmented and amplified mutant sublibraries, histogram of variant:WT read ratios among single, double, and triple and greater mutants, comparison of observed and simulated single mutant frequency distributions, time and cost calculations for uPIC–M and conventional mutagenesis, Plasmid map of PURExpress-SpAP-eGFP, complete DNA sequence of PURExpress-SpAP-eGFP plasmid, protein sequence of SpAP-(10mer linker)-eGFP, oligo array and window design details for SpAP scanning mutant library, concentration of purified sublibrary mutagenic primer pools, expected mutant yields from simulations of mutant sampling, variant composition of small-scale QuikChange-HT reactions, sublibrary transformation and colony picking results, amplicon DNA and library concentration statistics, unique single mutant yields for the SpAP scanning library, comparison of uPIC–M performance with simulated picking experiments, per sublibrary, and oligo array price summary (PDF)


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