Biology subjects

Kimchi-Sarfaty, C.

Publications and source records attributed to Kimchi-Sarfaty, C..

3 recordsLinked to original sources

bioRxiv2026

Splice-Aware Optimization Prevents Pervasive Missplicing of Natural and Synthetic cDNAs

Heterologous gene expression is widely used across biology and medicine, and often relies on codon optimization to increase protein yields. Here we uncover missplicing as a common and largely unrecognized failure mode of heterologous expression. Using systematically designed libraries comprising over 5,000 synthetic reporter genes and natural human cDNAs, we find that the majority of gene variants expressed in a human cell line are at least partially spliced, and in many variants the spliced isoform dominates, reducing protein output or ablating expression entirely. By analysing sequence determinants of expression across multiple human cell lines, we uncover a hierarchical architecture of regulatory control, where GC content establishes baseline mRNA levels, local sequence features influence splicing, and tissue-specific codon adaptation to tRNA pools fine-tunes translation efficiency. These findings enable us to develop predictive models of expression and splicing, benchmark current optimization strategies, and design a splice-aware optimization algorithm that substantially improves transgene performance.

synthetic biology↗

bioRxiv2020

Potential impact on coagulopathy of gene variants of coagulation related proteins that interact with SARS-CoV-2

Thrombosis has been one of the complications of the Coronavirus disease of 2019 (COVID-19), often associated with poor prognosis. There is a well-recognized link between coagulation and inflammation, however, the extent of thrombotic events associated with COVID-19 warrants further investigation. Poly(A) Binding Protein Cytoplasmic 4 (PABPC4), Serine/Cysteine Proteinase Inhibitor Clade G Member 1 (SERPING1) and Vitamin K epOxide Reductase Complex subunit 1 (VKORC1), which are all proteins linked to coagulation, have been shown to interact with SARS proteins. We computationally examined the interaction of these with SARS-CoV-2 proteins and, in the case of VKORC1, we describe its binding to ORF7a in detail. We examined the occurrence of variants of each of these proteins across populations and interrogated their potential contribution to COVID-19 severity. Potential mechanisms by which some of these variants may contribute to disease are proposed. Some of these variants are prevalent in minority groups that are disproportionally affected by severe COVID-19. Therefore, we are proposing that further investigation around these variants may lead to better understanding of disease pathogenesis in minority groups and more informed therapeutic approaches. Author summaryIncreased blood clotting, especially in the lungs, is a common complication of COVID-19. Infectious diseases cause inflammation which in turn can contribute to increased blood clotting. However, the extent of clot formation that is seen in the lungs of COVID-19 patients suggests that there may be a more direct link. We identified three human proteins that are involved indirectly in the blood clotting cascade and have been shown to interact with proteins of SARS virus, which is closely related to the novel coronavirus. We examined computationally the interaction of these human proteins with the viral proteins. We looked for genetic variants of these proteins and examined how these variants are distributed across populations. We investigated whether variants of these genes could impact severity of COVID-19. Further investigation around these variants may provide clues for the pathogenesis of COVID-19 particularly in minority groups.

bioinformatics↗

bioRxiv2020

Sequence analysis of SARS-CoV-2 genome reveals features important for vaccine design

As the SARS-CoV-2 pandemic is rapidly progressing, the need for the development of an effective vaccine is critical. A promising approach for vaccine development is to generate, through codon pair deoptimization, an attenuated virus. This approach carries the advantage that it only requires limited knowledge specific to the virus in question, other than its genome sequence. Therefore, it is well suited for emerging viruses for which we may not have extensive data. We performed comprehensive in silico analyses of several features of SARS-CoV-2 genomic sequence (e.g., codon usage, codon pair usage, dinucleotide/junction dinucleotide usage, RNA structure around the frameshift region) in comparison with other members of the coronaviridae family of viruses, the overall human genome, and the transcriptome of specific human tissues such as lung, which are primarily targeted by the virus. Our analysis identified the spike (S) and nucleocapsid (N) proteins as promising targets for deoptimization and suggests a roadmap for SARS-CoV-2 vaccine development, which can be generalizable to other viruses.

bioinformatics↗