MiRNA Response to Folic Acid during Embryogenesis and Development of Caenhorabditis elegans
Abstract
Folic acid, a form of folate, is a common dietary supplement used in combination with other vitamins and minerals in prenatal vitamins during female human pregnancy. Folic acid has great importance in neurogenesis, epigenetic regulation, and DNA formation in many organisms, but can also be toxic at overly abundant levels [1]. Folic acid is metabolized into folate derivatives through the use of multiple enzymes in the folate cycle. Furthermore, the methionine cycle converges with the folate cycle due to the utilization of folate intermediates for DNA methylation and DNA formation [2]. Currently, many studies have been performed analyzing the effects of folic acid and folate on different organisms and for different purposes, with great focus into pathogenesis of neurodegenerative and cardiovascular disease [3]. Similarly to how DNA methylation regulates gene expression, RNA interference (RNAi) plays an important role as an epigenetic regulator for genetic and genomic expression, with current focus to use micro RNA (miRNA) as a potential vector for disease management and treatment [3]. Current studies have identified miRNA to interact with messenger RNA (mRNA) through binding and subsequent degradation, resulting in a regulated expression of proteins. Currently, 38,589 miRNAs have been identified across multiple organisms and recorded in miRBase [4][5][6][7][8][9]. After the initial discovery of miRNA regulation in C. elegans [10], the organism is actively being used in current research as an efficient and well-equipped model for studying RNAi pathways and worm development. Additionally, many miRNAs discovered have shown high conservation between homosapiens and C. elegans [11]. However, miRNAs are still not fully understood. As such, to further scientific knowledge and our understanding of RNAi pathways, studying the RNAi pathways and miRNAs involved during the development of C. elegans can provide insight into how the organism regulates the enzymes involved and the consequential effects of supplementation of vitamins on organismic health.
1. Koseki K, Maekawa Y, Bito T, Yabuta Y, Watanabe F. High-dose folic acid supplementation results in significant accumulation of unmetabolized homocysteine, leading to severe oxidative stress in Caenorhabditis elegans. Redox biology. 2020 Oct 1;37:101724.
2. Annibal A, Tharyan RG, Schonewolff MF, Tam H, Latza C, Auler MM, Grönke S, Partridge L, Antebi A. Regulation of the one carbon folate cycle as a shared metabolic signature of longevity. Nature communications. 2021 Jun 9;12(1):1-4.
3. Beckett EL, Veysey M, Lucock M. Folate and microRNA: bidirectional interactions. Clinica Chimica Acta. 2017 Nov 1;474:60-6.
4. Kozomara A, Birgaoanu M, Griffiths-Jones S. miRBase: from microRNA sequences to function. Nucleic acids research. 2019 Jan 8;47(D1):D155-62.
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11. Ibáñez-Ventoso C, Vora M, Driscoll M. Sequence relationships among C. elegans, D. melanogaster and human microRNAs highlight the extensive conservation of microRNAs in biology. PloS one. 2008 Jul 30;3(7):e2818
Variable Expression of Extracellular miRNA during Caenorhabditis elegans Pathogenic Infection
Abstract
Micro RNA (miRNA) has been identified as a critical component in gene regulation and has been actively studied in a transcriptional silencing. Caenorhabitis elegans has been distinguished as a powerful model for studying miRNA functionality and application due to its heavy utilization in the nematode’s epigenetic regulatory pathway [1]. Currently, extracellular miRNA has been increasingly studied as a potential biomarker for different pathogenic conditions and diseases, such as lung health [2]. These miRNA have currently been found either inside of extracellular vesicles (EVs) or existing free-floating in extracellular fluid [3]. However, evaluating extracellular miRNA responses as a result of different microbes involved with C. elegans is an active area of research. This project aims to identify the qualitative and quantitative expressions of extracellular miRNA as part of an infection-response to pathogenic microbes.
Lim LP, Lau NC, Weinstein EG, Abdelhakim A, Yekta S, Rhoades MW, Burge CB, Bartel DP. The microRNAs of Caenorhabditis elegans. Genes Dev. 2003 Apr 15;17(8):991-1008. doi: 10.1101/gad.1074403. Epub 2003 Apr 2. PMID: 12672692; PMCID: PMC196042.
Eckhardt CM, Gambazza S, Bloomquist TR, De Hoff P, Vuppala A, Vokonas PS, Litonjua AA, Sparrow D, Parvez F, Laurent LC, Schwartz J. Extracellular vesicle-encapsulated microRNAs as novel biomarkers of lung health. American Journal of Respiratory and Critical Care Medicine. 2023 Jan 1;207(1):50-9.
Turchinovich A, Weiz L, Langheinz A, Burwinkel B. Characterization of extracellular circulating microRNA. Nucleic acids research. 2011 Sep 1;39(16):7223-33.
Mutational Analysis of Intragenic and Intergenic Variants of Uterine Cancer and Super Enhancer Associations
Abstract
Mutational variants and changes in the genetic code serve as the foundational cause for many diseases and syndromes. Amongst the many diseases, cancer has been displayed to be often consequential due to mutational variants. However, the progression and penetrance of phenotypes consequential to uterine cancers are not well understood. This study focuses on addressing this through mutational analysis of uterine cancer data acquired from the NIH TCGA database and further evaluating the potential association between associated mutations and the relative theoretical and observed consequences through modelling and existing data [1]
Weinstein JN, Collisson EA, Mills GB, Shaw KR, Ozenberger BA, Ellrott K, Shmulevich I, Sander C, Stuart JM. The cancer genome atlas pan-cancer analysis project. Nature genetics. 2013 Oct;45(10):1113-20.
Evaluating the Efficiency of 2A Sequences Due to Gene Size Variability in Polycistronic Vectors
Abstract
Multi-peptide producing processes have been an emerging topic. Originating from viruses, two primary modalities of multi-peptide-producing vectors have been observed: IRES sequences and 2A sequences. The latter is of great interest due to the short sequence length, diversity, and plasmid transfection efficiency, and has been extensively studied to identify various modifiers to improve cleavage efficiency[1]. Furthermore, various combinations of 2A sequences have been observed to play different cleavage efficiencies when used together, posing a challenge in effective, functional polycistronic vector disease. Additionally, little is known regarding the effects of gene characteristics in effects on 2A peptide efficiency. This study focuses on identifying various gene characteristics and applying them via vector design to observe the differences in cleavage efficiency amongst various 2A peptides. This study will provide greater insight into the effects of gene content when designing polycistronic vectors and the potential application in transcript synthesis and relevant applications.
References:
Wang X, Marchisio MA. Synthetic polycistronic sequences in eukaryotes. Synthetic and Systems Biotechnology. 2021 Dec 1;6(4):254-61.
Liu Z, Chen O, Wall JB, Zheng M, Zhou Y, Wang L, Ruth Vaseghi H, Qian L, Liu J. Systematic comparison of 2A peptides for cloning multi-genes in a polycistronic vector. Scientific reports. 2017 May 19;7(1):2193.
Evaluating the Potential Application of Accessible LLMs in Simulation-based Patient-Physician Cases and Development of Virtual Patient Cases for Medical-Based Education
Abstract
AI models have become extremely popular as prospective tools for healthcare and potential involvement in medical interactions, and eventually diagnosis. Large language models (LLM), such as ChatGPT, are amongst the most popular, with a diverse set of functions and roles, including involvement in healthcare and medical education. Companies such as Google have begun implementation of medical diagnostic AI models such as AMIE (Articulate Medical Intelligence Performer), which has shown promising results to advance both aspects of diagnostic capabilities and patient-physician interactions. Other LLMs have been developed that attempt to target specific aspects of patient-physician relationship, such as HAILEY, an AI chatbot aimed at improving empathy for text-based patient-physician interactions.
Another area where LLM and machine learning can assist is through simulation-based and conversational learning for medical education. With progressive advancement in LLM and machine learning, there is great potential in applying these models towards medical teaching through implementation of virtual standardized patient (VSP) cases. Although the aforementioned AMIE infrastructure is being developed, current simulation-based practice may be utilized through other LLMs, such have been put into question their legitimacy in appropriate emotional and objective responses in patient-physician interactions. In this study, we look and observe how various LLMs develop and present clinical scenarios based on presentation to various specialties stipulated by a role-play between a VSP and a specialist. Furthermore, complex emotional factors, such as stated tonality associated with emotions that could be considered to be involved with a given specialty, will be taken into consideration. The scenario responses and patient-based responses will be applied into the current framework amongst various LLMs and observed for relative changes in empathetic responses and medical accuracy. The findings of this study will enhance our understanding of LLM and the potential for currently available LLM models to be applied in creating clinical scenarios, relative biases developed by specialities perceived within LLMs, as well as cautions to consider regarding application in medical education.
References:
1.Scherr R, Halaseh FF, Spina A, Andalib S, Rivera R. ChatGPT interactive medical simulations for early clinical education: case study. JMIR Medical Education. 2023 Nov 10;9:e49877.
2. McDuff D, Schaekermann M, Tu T, Palepu A, Wang A, Garrison J, Singhal K, Sharma Y, Azizi S, Kulkarni K, Hou L. Towards accurate differential diagnosis with large language models. arXiv preprint arXiv:2312.00164. 2023 Nov 30.
3. Sharma A, Lin IW, Miner AS, Atkins DC, Althoff T. Human–AI collaboration enables more empathic conversations in text-based peer-to-peer mental health support. Nature Machine Intelligence. 2023 Jan;5(1):46-57.
4.Gray M, Baird A, Sawyer T, James J, DeBroux T, Bartlett M, Krick J, Umoren R. Increasing Realism and Variety of Virtual Patient Dialogues for Prenatal Counseling Education Through a Novel Application of ChatGPT: Exploratory Observational Study. JMIR Medical Education. 2024 Feb 1;10:e50705.