Predicting and Interpreting Protein Developability Via Transfer of Convolutional Sequence Representation

Engineered proteins have emerged as novel diagnostics, therapeutics, and catalysts. Often, poor protein developability─quantified by expression, solubility, and stability─hinders utility. The ability to predict protein developability from amino acid sequence would reduce the experimental burden when selecting candidates. Recent advances in screening technologies enabled a high-throughput (HT) developability dataset for 105 of 1020 possible variants of protein ligand scaffold Gp2. In this work, we evaluate the ability of neural networks to learn a developability representation from a HT dataset and transfer this knowledge to predict recombinant expression beyond observed sequences. The model convolves learned amino acid properties to predict expression levels 44% closer to the experimental variance compared to a non-embedded control. Analysis of learned amino acid embeddings highlights the uniqueness of cysteine, the importance of hydrophobicity and charge, and the unimportance of aromaticity, when aiming to improve the developability of small proteins. We identify clusters of similar sequences with increased recombinant expression through nonlinear dimensionality reduction and we explore the inferred expression landscape via nested sampling. The analysis enables the first direct visualization of the fitness landscape and highlights the existence of evolutionary bottlenecks in sequence space giving rise to competing subpopulations of sequences with different developability. The work advances applied protein engineering efforts by predicting and interpreting protein scaffold expression from a limited dataset. Furthermore, our statistical mechanical treatment of the problem advances foundational efforts to characterize the structure of the protein fitness landscape and the amino acid characteristics that influence protein developability.

Seizures after epidural blood patch in a postpartum patient later diagnosed with hypertension and proteinuria: a diagnostic conundrum

Seizures are a rare, but documented, consequence of accidental dural puncture and epidural blood patch. They are also the cardinal feature of eclampsia. We present a postpartum patient who suffered a tonic-clonic seizure within 1 hour of an epidural blood patch procedure for a suspected post-dural puncture headache. Investigations also revealed hypertension, proteinuria and subdural collections. This case demonstrates the diagnostic dilemma associated with postpartum headache and late postpartum eclampsia. We illustrate the importance of a thorough clinical assessment of postpartum patients presenting with headache, highlighting the possibility of more than one underlying pathological cause. We also consider the role of epidural blood patch in both precipitating, and preventing, complications of accidental dural puncture.

Diaphragmatic hernia masquerading as a pulmonary metastasis

Iatrogenic injury accounts for the second most common cause of acquired diaphragmatic hernias after penetrating trauma. An increased incidence of these hernias has been observed with the widespread use of laparoscopic surgery. We present the case of a 65-year-old woman who initially underwent sigmoid resection for an adenocarcinoma and a subsequent liver resection for metastasis. She was noted to have a left lower lobe pulmonary nodule on surveillance computed tomography, for which she underwent a mini-thoracotomy for a planned resection. At the time of surgery, the pulmonary nodule was discovered to be a diaphragmatic hernia, most probably of iatrogenic origin. We discuss the difficulty in diagnosis given her history and the location of such a lesion.