Nature uses 64 codons to encode the synthesis of proteins from the genome, and chooses 1 sense codon-out of up to 6 synonyms-to encode each amino acid. Synonymous codon choice has diverse and important roles, and many synonymous substitutions are detrimental. Here we demonstrate that the number of codons used to encode the canonical amino acids can be reduced, *

Synthetic recoding of genomes, to remove targeted sense codons, may facilitate the encoded cellular synthesis of unnatural polymers by orthogonal translation systems. However, our limited understanding of allowed synonymous codon substitutions and the absence of methods that enable the stepwise replacement of the E. coli genome with long synthetic DNA, and provide feedback on allowed and disallowed design features in synthetic genomes, have restricted progress on this goal. Here we endow E. coli with a system for efficient, programmable replacement of genomic DNA with long (~100 kb) synthetic DNA, through the in vivo excision of double stranded DNA from an episomal replicon by CRISPR/Cas9, coupled to lambda red mediated recombination and simultaneous positive and negative selection. We iterate the approach, providing a basis for stepwise whole-genome replacement. We attempt systematic recoding in an essential operon using eight synonymous recoding schemes. Each scheme systematically replaces target codons with defined synonyms and is compatible with codon reassignment. Our results define allowed and disallowed synonymous recoding schemes, and enable the identification and repair of recoding at idiosyncratic positions in the genome.The design and synthesis of genomes provides a powerful approach for understanding and engineering biology1-6. Genome synthesis has the potential to elucidate synonymous codon function7, accelerate metabolic engineering8, and facilitate genetically encoded unnatural polymer synthesis9,10.Methods that i) replace the genome in sections6, ii) provide feedback on precisely where a given design fails and on how to repair it, and that iii) can be rapidly iterated for whole

Pentatricopeptide repeat (PPR) proteins control diverse aspects of RNA metabolism in eukaryotic cells. Although recent computational and structural studies have provided insights into RNA recognition by PPR proteins, their highly insoluble nature and inconsistencies between predicted and observed modes of RNA binding have restricted our understanding of their biological functions and their use as tools. Here we use a consensus design strategy to create artificial PPR domains that are structurally robust and can be programmed for sequence-specific RNA binding. The atomic structures of these artificial PPR domains elucidate the structural basis for their stability and modelling of RNA-protein interactions provides mechanistic insights into the importance of RNA-binding residues and suggests modes of PPR-RNA association. The modular mode of RNA binding by PPR proteins holds great promise for the engineering of new tools to target RNA and to understand the mechanisms of gene regulation by natural PPR proteins.

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Estrogens, in particular 17β-estradiol, are well-known regulators of essential cellular functions; however, discrepancies remain over the mechanisms by which they act on mitochondria. Here we propose a novel mechanism for the direct regulation of mitochondrial gene expression by estrogen under metabolic stress. We show that in serum-depleted medium, estrogen stimulates a rapid relocation of estrogen receptor-α to mitochondria, in which it elicits a cellular response, resulting in an increase in mitochondrial RNA abundance. Mitochondrial RNA levels are regulated through the association of estrogen receptor-α with 17β-hydroxysteroid dehydrogenase 10, a multifunctional protein involved in steroid metabolism that is also a core subunit of the mitochondrial ribonuclease P complex responsible for the cleavage of mitochondrial polycistronic transcripts. Processing of mitochondrial transcripts affects mitochondrial gene expression by controlling the levels of mature RNAs available for translation. This work provides the first mechanism linking RNA processing and estrogen activation in mitochondrial gene expression and underscores the coordinated response between the nucleus and mitochondria in response to stress.

DNA is typically found as a double helix, however it must be separated into single strands during all phases of DNA metabolism; including transcription, replication, recombination and repair. Although recent breakthroughs have enabled the design of modular RNA- and double-stranded DNA-binding proteins, there are currently no tools available to manipulate single-stranded DNA (ssDNA). Here we show that artificial pentatricopeptide repeat (PPR) proteins can be programmed for sequence-specific ssDNA binding. Interactions occur using the same code and specificity as for RNA binding. We solve the structures of DNA-bound and apo proteins revealing the basis for ssDNA binding and how hydrogen bond rearrangements enable the PPR structure to envelope its ssDNA target. Finally, we show that engineered PPRs can be designed to bind telomeric ssDNA and can block telomerase activity. The modular mode of ssDNA binding by PPR proteins provides tools to target ssDNA and to understand its importance in cells.

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Background and Aim Artificial intelligence has been extensively studied to assist clinicians in polyp detection, but such systems usually require expansive processing power, making them prohibitively expensive and hindering wide adaption. The current study used a fast object detection algorithm, known as the YOLOv3 algorithm, to achieve real‐time polyp detection on a laptop. In addition, we evaluated and classified the causes of false detections to further improve accuracy. Methods The YOLOv3 algorithm was trained and validated with 6038 and 2571 polyp images, respectively. Videos from live colonoscopies in a tertiary center and those obtained from public databases were used for the training and validation sets. The algorithm was tested on 10 unseen videos from the CVC‐Video ClinicDB dataset. Only bounding boxes with an intersection over union area of > 0.3 were considered positive predictions. Results Polyp detection rate in our study was 100%, with the algorithm able to detect every polyp in each video. Sensitivity, specificity, and F1 score were 74.1%, 85.1%, and 83.3, respectively. The algorithm achieved a speed of 61.2 frames per second (fps) on a desktop RTX2070 GPU and 27.2 fps on a laptop GTX2060 GPU. Nearly a quarter of false negatives happened when the polyps were at the corner of an image. Image blurriness accounted for approximately 3% and 9% of false positive and false negative detections, respectively. Conclusion The YOLOv3 algorithm can achieve real‐time poly detection with high accuracy and speed on a desktop GPU, making it low cost and accessible to most endoscopy centers worldwide.