Robust and scalable single-molecule protein sequencing with fluorosequencing.

The need to accurately survey proteins and their modifications with ever higher sensitivities, particularly in clinical settings with limited samples, is spurring development of new single molecule proteomics technologies. Fluorosequencing is one such highly parallelized single molecule peptide sequencing platform, based on determining the sequence positions of select amino acid types within peptides to enable their identification and quantification from a reference database. Here, we describe substantial improvements to fluorosequencing, including identifying fluorophores compatible with the sequencing chemistry, mitigating dye-dye interactions through the use of extended polyproline linkers, and developing an end-to-end workflow for sample preparation and sequencing. We demonstrate by fluorosequencing peptides in mixtures and identifying a target neoantigen from a database of decoy MHC peptides, highlighting the potential of the technology for high sensitivity clinical applications.

Estimating error rates for single molecule protein sequencing experiments.

The practical application of new single molecule protein sequencing (SMPS) technologies requires accurate estimates of their associated sequencing error rates. Here, we describe the development and application of two distinct parameter estimation methods for analyzing SMPS reads produced by fluorosequencing. A Hidden Markov Model (HMM) based approach, extends whatprot, where we previously used HMMs for SMPS peptide-read matching. This extension offers a principled approach for estimating key parameters for fluorosequencing experiments, including missed amino acid cleavages, dye loss, and peptide detachment. Specifically, we adapted the Baum-Welch algorithm, a standard technique to estimate transition probabilities for an HMM using expectation maximization, but modified here to estimate a small number of parameter values directly rather than estimating every transition probability independently, which should help prevent overfitting. We demonstrate a high degree of accuracy on simulated data, but on experimental datasets, we observed that the model needed to be augmented with an additional error type, N-terminal blocking. This, in combination with data pre-processing, results in reasonable parameterizations of experimental datasets that agree with controlled experimental perturbations. A second independent implementation using a hybrid of DIRECT and Powell's method to reduce the root mean squared error (RMSE) between simulations and the real dataset was also developed. We compare these methods on both simulated and real data, finding that our Baum-Welch based approach outperforms DIRECT and Powell's method by most, but not all, criteria. Although some discrepancies between the results exist, we also find that both approaches provide similar error rate estimates from experimental single molecule fluorosequencing datasets.

Cryo-EM structure of OSCA1.2 from Oryza sativa elucidates the mechanical basis of potential membrane hyperosmolality gating.

Sensing and responding to environmental water deficiency and osmotic stresses are essential for the growth, development, and survival of plants. Recently, an osmolality-sensing ion channel called OSCA1 was discovered that functions in sensing hyperosmolality in Arabidopsis Here, we report the cryo-electron microscopy (cryo-EM) structure and function of an OSCA1 homolog from rice (Oryza sativa; OsOSCA1.2), leading to a model of how it could mediate hyperosmolality sensing and transport pathway gating. The structure reveals a dimer; the molecular architecture of each subunit consists of 11 transmembrane (TM) helices and a cytosolic soluble domain that has homology to RNA recognition proteins. The TM domain is structurally related to the TMEM16 family of calcium-dependent ion channels and lipid scramblases. The cytosolic soluble domain possesses a distinct structural feature in the form of extended intracellular helical arms that are parallel to the plasma membrane. These helical arms are well positioned to potentially sense lateral tension on the inner leaflet of the lipid bilayer caused by changes in turgor pressure. Computational dynamic analysis suggests how this domain couples to the TM portion of the molecule to open a transport pathway. Hydrogen/deuterium exchange mass spectrometry (HDXMS) experimentally confirms the conformational dynamics of these coupled domains. These studies provide a framework to understand the structural basis of proposed hyperosmolality sensing in a staple crop plant, extend our knowledge of the anoctamin superfamily important for plants and fungi, and provide a structural mechanism for potentially translating membrane stress to transport regulation.