bioRxiv Science⌕ Search

Biology subjects

Soufi, M.

Publications and source records attributed to Soufi, M..

2 recordsLinked to original sources

Directed Evolution of Acoustic Reporter Genes Using High-Throughput Acoustic Screening

A major challenge in the fields of biological imaging and synthetic biology is noninvasively visualizing the functions of natural and engineered cells inside opaque samples such as living animals. One promising technology that addresses this limitation is ultrasound (US), with its penetration depth of several cm and spatial resolution on the order of 100 {micro}m.1 Within the past decade, reporter genes for US have been introduced2,3 and engineered4,5 to link cellular functions to US signals via heterologous expression in commensal bacteria and mammalian cells. These acoustic reporter genes (ARGs) represent a novel class of genetically encoded US contrast agent, and are based on air-filled protein nanostructures called gas vesicles (GVs).6 Just as the discovery of fluorescent proteins was followed by the improvement and diversification of their optical properties through directed evolution, here we describe the evolution of GVs as acoustic reporters. To accomplish this task, we establish high-throughput, semi-automated acoustic screening of ARGs in bacterial cultures and use it to screen mutant libraries for variants with increased nonlinear US scattering. Starting with scanning site saturation libraries for two homologs of the primary GV structural protein, GvpA/B, two rounds of evolution resulted in GV variants with 5- and 14-fold stronger acoustic signals than the parent proteins. We anticipate that this and similar approaches will help high-throughput protein engineering play as large a role in the development of acoustic biomolecules as it has for their fluorescent counterparts.

bioengineering↗

Translation of cellular protein localization by generative adversarial network

The protein localization in cells had been analyzed by the fluorescent labeling by indirect immunofluorescence and fluorescent protein tagging. However, the relationships between the localizations between different proteins had not been analyzed by artificial intelligence. In this study, we applied the generative adversarial network (GAN) to generate the protein localizations each other, in which the generation was dependent on the types of cells and the relationships between the proteins. Lamellipodia are one of the actin-dependent subcellular structures involved in cell migration and are mainly generated by the Wiskott-Aldrich syndrome protein (WASP)-family verprolin homologous protein 2 (WAVE2) and the membrane remodeling I-BAR domain protein IRSp53. Focal adhesions are another actin-based structure that contains vinculin protein and are essential for cell migration. In contrast, microtubules are not thought to be directly related to actin filaments. The GAN was trained using images of actin filaments paired with WAVE2, vinculin, IRSp53, and microtubules. Then, the generated images of WAVE2, vinculin, and IRSp53 by the GAN showed high similarity to the real images of WAVE2, vinculin, and IRSp53, respectively. However, the microtubule images generated from actin filament images were inferior, corroborating that the microscopic images of actin filaments provide more information about actin-related protein localization. Collectively, this study suggests that the image translation by the GAN can predict the localization of functionally related proteins.

cell biology↗