Recovery of Information Stored in Modified DNA with an Evolved Polymerase.

DNA is increasingly being explored as an alternative medium for digital information storage, but the potential information loss from degradation and associated issues with error during reading challenge its wide-scale implementation. To address this, we propose an atomic-scale encoding standard for DNA, where information is encoded in degradation-resistant analogues of natural nucleic acids (xNAs). To better enable this approach, we used directed evolution to create a polymerase capable of transforming 2'-O-methyl templates into double-stranded DNA. Starting from a thermophilic, error-correcting reverse transcriptase, RTX, we evolved an enzyme (RTX-Ome v6) that relies on a fully functional proofreading domain to correct mismatches on DNA, RNA, and 2'-O-methyl templates. In addition, we implemented a downstream analysis strategy that accommodates deletions that arise during phosphoramidite synthesis, the most common type of synthesis error. By coupling and integrating new chemistries, enzymes, and algorithms, we further enable the large-scale use of nucleic acids for information storage.

Next-Generation TLC: A Quantitative Platform for Parallel Spotting and Imaging.

A high-throughput screening approach for simultaneous analysis and quantification of the percent conversion of up to 48 reactions has been developed using a thin-layer chromatography (TLC) imaging method. As a test-bed reaction, we monitored 48 thiol conjugate additions to a Meldrum's acid derivative (1) in parallel using TLC. The TLC elutions were imaged using a cell phone and a LEGO brick-constructed UV/vis light box. Further, a spotting device was constructed from LEGO bricks that allows simple transfer of the samples from a well-plate to the TLC plate. Using software that was developed to detect "blobs" and report their intensity, we were able to quantitatively determine the extent of completion of the 48 reactions with one analysis.

Bringing Microscopy-By-Sequencing into View.

The spatial distribution of molecules and cells is fundamental to understanding biological systems. Traditionally, microscopies based on electromagnetic waves such as visible light have been used to localize cellular components by direct visualization. However, these techniques suffer from limitations of transmissibility and throughput. Complementary to optical approaches, biochemical techniques such as crosslinking can colocalize molecules without suffering the same limitations. However, biochemical approaches are often unable to combine individual colocalizations into a map across entire cells or tissues. Microscopy-by-sequencing techniques aim to biochemically colocalize DNA-barcoded molecules and, by tracking their thus unique identities, reconcile all colocalizations into a global spatial map. Here, we review this new field and discuss its enormous potential to answer a broad spectrum of questions.

A liquid-like organelle at the root of motile ciliopathy.

Motile ciliopathies are characterized by specific defects in cilia beating that result in chronic airway disease, subfertility, ectopic pregnancy, and hydrocephalus. While many patients harbor mutations in the dynein motors that drive cilia beating, the disease also results from mutations in so-called dynein axonemal assembly factors (DNAAFs) that act in the cytoplasm. The mechanisms of DNAAF action remain poorly defined. Here, we show that DNAAFs concentrate together with axonemal dyneins and chaperones into organelles that form specifically in multiciliated cells, which we term DynAPs, for dynein axonemal particles. These organelles display hallmarks of biomolecular condensates, and remarkably, DynAPs are enriched for the stress granule protein G3bp1, but not for other stress granule proteins or P-body proteins. Finally, we show that both the formation and the liquid-like behaviors of DynAPs are disrupted in a model of motile ciliopathy. These findings provide a unifying cell biological framework for a poorly understood class of human disease genes and add motile ciliopathy to the growing roster of human diseases associated with disrupted biological phase separation.

Highly parallel single-molecule identification of proteins in zeptomole-scale mixtures.

The identification and quantification of proteins lags behind DNA-sequencing methods in scale, sensitivity, and dynamic range. Here, we show that sparse amino acid-sequence information can be obtained for individual protein molecules for thousands to millions of molecules in parallel. We demonstrate selective fluorescence labeling of cysteine and lysine residues in peptide samples, immobilization of labeled peptides on a glass surface, and imaging by total internal reflection microscopy to monitor decreases in each molecule's fluorescence after consecutive rounds of Edman degradation. The obtained sparse fluorescent sequence of each molecule was then assigned to its parent protein in a reference database. We tested the method on synthetic and naturally derived peptide molecules in zeptomole-scale quantities. We also fluorescently labeled phosphoserines and achieved single-molecule positional readout of the phosphorylated sites. We measured >93% efficiencies for dye labeling, survival, and cleavage; further improvements should enable studies of increasingly complex proteomic mixtures, with the high sensitivity and digital quantification offered by single-molecule sequencing.

Photography Coupled with Self-Propagating Chemical Cascades: Differentiation and Quantitation of G- and V-Nerve Agent Mimics via Chromaticity.

Photography was employed for the quantitation and differentiation of G- and V-series nerve agent mimics with the use of self-propagating cascades. Fluoride anion and thiols, released from a G-nerve agent mimic (i.e., diisopropyl fluorophosphate) and a V-nerve agent mimic (i.e., demeton-S-methyl), respectively, were used to initiate self-propagating cascades that amplify fluorescence signals exponentially in a ratiometric manner. A homemade LEGO dark-box, a cell phone, and 96-well plates were employed to collect photographs of the fluorescence response to the analytes. The photographic images were digitally processed in the 1931 xyY color space using a watershed and morphological erosion algorithm to generate chromaticity vs concentration calibration curves. We show that the two different amplification routines are selective for their analyte class and thus successfully discriminated the G- and V-series nerve agent mimics. Further, accurate concentrations of the analytes are determined using the chromaticity and LEGO approach given herein, thus demonstrating a simple and on-site constructible/portable device for use in the field.

A theoretical justification for single molecule peptide sequencing.

The proteomes of cells, tissues, and organisms reflect active cellular processes and change continuously in response to intracellular and extracellular cues. Deep, quantitative profiling of the proteome, especially if combined with mRNA and metabolite measurements, should provide an unprecedented view of cell state, better revealing functions and interactions of cell components. Molecular diagnostics and biomarker discovery should benefit particularly from the accurate quantification of proteomes, since complex diseases like cancer change protein abundances and modifications. Currently, shotgun mass spectrometry is the primary technology for high-throughput protein identification and quantification; while powerful, it lacks high sensitivity and coverage. We draw parallels with next-generation DNA sequencing and propose a strategy, termed fluorosequencing, for sequencing peptides in a complex protein sample at the level of single molecules. In the proposed approach, millions of individual fluorescently labeled peptides are visualized in parallel, monitoring changing patterns of fluorescence intensity as N-terminal amino acids are sequentially removed, and using the resulting fluorescence signatures (fluorosequences) to uniquely identify individual peptides. We introduce a theoretical foundation for fluorosequencing and, by using Monte Carlo computer simulations, we explore its feasibility, anticipate the most likely experimental errors, quantify their potential impact, and discuss the broad potential utility offered by a high-throughput peptide sequencing technology.