Aminoacylated tRNAs are the substrates for ribosomal protein synthesis in all branches of life, implying an ancient origin for aminoacylation chemistry. In the 1970s, Orgel and colleagues reported potentially prebiotic routes to aminoacylated nucleotides and their RNA-templated condensation to form amino acid-bridged dinucleotides. However, it is unclear whether such reactions would have aided or impeded non-enzymatic RNA replication. Determining whether aminoacylated RNAs could have been advantageous in evolution prior to the emergence of protein synthesis remains a key challenge. We therefore tested the ability of aminoacylated RNA to participate in both templated primer extension and ligation reactions. We find that at low magnesium concentrations that favor fatty acid-based protocells, these reactions proceed orders of magnitude more rapidly than when initiated from the -diol of unmodified RNA. We further demonstrate that amino acid-bridged RNAs can act as templates in a subsequent round of copying. Our results suggest that aminoacylation facilitated non-enzymatic RNA replication, thus outlining a potentially primordial functional link between aminoacylation chemistry and RNA replication.
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http://dx.doi.org/10.1021/acs.biochem.0c00943 | DOI Listing |
J Control Release
December 2024
Department of Traumatology and Orthopaedic Surgery, Huizhou Central People's Hospital, Huizhou 516001, China; Hui Zhou-Hong Kong Bone Health Joint Research Center, Institute of Orthopaedics, Huizhou Central People's Hospital, Huizhou 516001, China. Electronic address:
Bacterial infections evoke considerable apprehension in orthopedics. Traditional antibiotic treatments exhibit cytotoxic effects and foster bacterial resistance, thereby presenting an ongoing and formidable obstacle in the realm of therapeutic interventions. Achieving bacterial eradication and osteogenesis are critical requirements for bone infection treatment.
View Article and Find Full Text PDFJ Med Virol
January 2025
Microbiology Department, University of Massachusetts, Amherst, Massachusetts, USA.
Kaposi's sarcoma-associated herpesvirus is an oncogenic gammaherpesvirus that plays a major role in several human malignancies, including Kaposi's sarcoma, primary effusion lymphoma, and multicentric Castleman's disease. The complexity of KSHV biology is reflected in the sophisticated regulation of its biphasic life cycle, consisting of a quiescent latent phase and virion-producing lytic replication. KSHV expresses coding and noncoding RNAs, including microRNAs and long noncoding RNAs, which play crucial roles in modulating viral gene expression, immune evasion, and intercellular communication.
View Article and Find Full Text PDFPLoS One
December 2024
Institute of Cell Biology, University of Bern, Bern, Switzerland.
Malaria caused by Plasmodium parasites remains a large health burden. One approach to combat this disease involves vaccinating individuals with whole sporozoites that have been genetically modified to arrest their development at a specific stage in the liver by targeted gene deletion, resulting in a genetically attenuated parasite (GAP). Through a comprehensive phenotyping screen, we identified the hscb gene, encoding a putative iron-sulfur protein assembly chaperone, as crucial for liver stage development, making it a suitable candidate gene for GAP generation.
View Article and Find Full Text PDFEMBO J
December 2024
Division of Structural Biology, University of Oxford, Oxford, UK.
Nipah virus is a highly virulent zoonotic paramyxovirus causing severe respiratory and neurological disease. Despite its lethality, there is no approved treatment for Nipah virus infection. The viral polymerase complex, composed of the polymerase (L) and phosphoprotein (P), replicates and transcribes the viral RNA genome.
View Article and Find Full Text PDFGeroscience
December 2024
Institute on the Biology of Aging and Metabolism, University of Minnesota, Twin Cities, Minneapolis, MN, 55455, USA.
Although cellular senescence has been recognized as a hallmark of aging, it is challenging to detect senescence cells (SnCs) due to their high level of heterogeneity at the molecular level. Machine learning (ML) is likely an ideal approach to address this challenge because of its ability to recognize complex patterns that cannot be characterized by one or a few features, from high-dimensional data. To test this, we evaluated the performance of four ML algorithms including support vector machines (SVM), random forest (RF), decision tree (DT), and Soft Independent Modelling of Class Analogy (SIMCA), in distinguishing SnCs from controls based on bulk RNA sequencing data.
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