Zhang, S. and Chen, J. Y. 2023. In Silico Design of Helicobacter pylori for Targeted Cancer Therapy. (pending review)
In this study, we propose an innovative bacterial-mediated cancer therapy (BMCT) using the 26695 Helicobacter pylori strain, linked to gastric cancer. Exploiting H. pylori's resilience in hostile gastric and tumor microenvironments, we propose targeted anticancer drug delivery. We suggest genetic adjustments to boost its anti-cancer abilities after evaluating pathogenic risks. This approach offers a novel paradigm for gastroenterological oncology. We dissect the survival strategies of the H. pylori 26695 strain, identifying 53 resilient genes and 58 chemotaxis-related genes. We propose the removal or modification of 50 potentially pathogenic genes, 43 genetic mobility elements, and 209 protein-coding genes, resulting in a toxin-free BMCT vector. We introduce eCIS (infrared-light lifestyle control) and therapeutic protein production through engineered plasmids. eCIS utilizes a safer T4SS drug injection system without CagA, and plasmids enhance BMCT capacities through H. pylori transformation. This blueprint, pending experimental validation, could revolutionize BMCT for precise targeting of gastroenterological cancers. The lead author, a high school scholar, thanks her teacher, the AlphaMind Club, and mentor Professor Chen for their support.
The sequencing data used in this study was extracted from Tomb et al. [1] and analyzed using Geneious Prime, a comprehensive bioinformatics software platform. The initial sequence dataset contained 1,632 identified genes across 3,241 genomic regions.
To refine the data for further analysis, we employed a two-step filtering process. First, we removed any coding regions classified as speculative, as these may not accurately represent functional gene products. This was achieved by cross-referencing the Geneious Prime annotations with the GenBank database to ensure that only well-annotated and experimentally confirmed genes were included subsequently.
Next, we manually assessed the remaining genes for their BMCT relevance to three key areas: environmental resistance, colonization capacity, and toxicity (Fig. 1). This assessment was based on the biological function of the encoded proteins as documented in the available literature and existing genomic databases. Each gene was scrutinized for any direct or indirect role it might play in these areas, thereby yielding a refined list of candidate genes.
The manual evaluation process was guided in part by the methodologies and findings of Doig et al. [2]. Furthermore, we utilized summaries generated by ChatGPT to augment our understanding and evaluation of the function of relevant genes. This innovative approach provided an additional layer of analysis, ensuring comprehensive consideration of the data. In parallel to the gene categorization process, we conducted a comprehensive literature review of over 100 scientific works related to protein function in H. pylori. This aided in associating identified genes with their potential roles in H. pylori's survival and pathogenicity.
The resultant categorization of genes, along with their associated references, is available as a supplemental file on our GitHub repository (https://github.com/alphamind-club/hpylori). We believe this result will serve as a valuable resource for future investigations into H. pylori's genomic characteristics and their implications for its pathogenicity and environmental adaptability.
The .rdf file contains the references used in this paper. Open using Zotero.