The alphabet of building blocks for RNA molecules is much larger than the standard four nucleotides. The diversity is achieved by the post-transcriptional biochemical modification of these nucleotides into distinct chemical entities that are structurally and functionally different from their unmodified counterparts. Some of these modifications are constituent and critical for RNA functions, while others serve as dynamic markings to regulate the fate of specific RNA molecules. Together, these modifications form the epitranscriptome, an essential layer of cellular biochemistry. As of the time of writing this review, more than 300 distinct RNA modifications from all three life domains have been identified. However, only a few of the most well-established modifications are included in most reviews on this topic. To provide a complete overview of the current state of research on the epitranscriptome, we analyzed the extent of the available information for all known RNA modifications. We selected 25 modifications to describe in detail. Summarizing our findings, we describe the current status of research on most RNA modifications and identify further developments in this field.

Metabolomics uses advanced analytical chemistry methods to analyze metabolites in biological samples. The most intensively studied samples are blood and its liquid components: plasma and serum. Armed with advanced equipment and progressive software solutions, the scientific community has shown that small molecules’ roles in living systems are not limited to traditional “building blocks” or “just fuel” for cellular energy. As a result, the conclusions based on studying the metabolome are finding practical reflection in molecular medicine and a better understanding of fundamental biochemical processes in living systems. This review is not a detailed protocol of metabolomic analysis. However, it should support the reader with information about the achievements in the whole process of metabolic exploration of human plasma and serum using mass spectrometry combined with gas chromatography.

Both biological and technical variations can discredit the reliability of obtained data in omics studies. In this technical note, we investigated the effect of prolonged cultivation of the HepG2 hepatoma cell line on its metabolomic profile. Using the GC × GC-MS approach, we determined the degree of metabolic variability across HepG2 cells cultured in uniform conditions for 0, 5, 10, 15, and 20 days. Post-processing of obtained data revealed substantial changes in relative abundances of 110 metabolites among HepG2 samples under investigation. Our findings have implications for interpreting metabolomic results obtained from immortal cells, especially in longitudinal studies. There are still plenty of unanswered questions regarding metabolomics variability and many potential areas for future targeted and panoramic research. However, we suggest that the metabolome of cell lines is unstable and may undergo significant transformation over time, even if the culture conditions remain the same. Considering metabolomics variability on a relatively long-term basis, careful experimentation with particular attention to control samples is required to ensure reproducibility and relevance of the research results when testing both fundamentally and practically significant hypotheses.

Increasing attention has been focused on the study of protein–metabolite interactions (PMI), which play a key role in regulating protein functions and directing an orchestra of cellular processes. The investigation of PMIs is complicated by the fact that many such interactions are extremely short-lived, which requires very high resolution in order to detect them. As in the case of protein–protein interactions, protein–metabolite interactions are still not clearly defined. Existing assays for detecting protein–metabolite interactions have an additional limitation in the form of a limited capacity to identify interacting metabolites. Thus, although recent advances in mass spectrometry allow the routine identification and quantification of thousands of proteins and metabolites today, they still need to be improved to provide a complete inventory of biological molecules, as well as all interactions between them. Multiomic studies aimed at deciphering the implementation of genetic information often end with the analysis of changes in metabolic pathways, as they constitute one of the most informative phenotypic layers. In this approach, the quantity and quality of knowledge about PMIs become vital to establishing the full scope of crosstalk between the proteome and the metabolome in a biological object of interest. In this review, we analyze the current state of investigation into the detection and annotation of protein–metabolite interactions, describe the recent progress in developing associated research methods, and attempt to deconstruct the very term “interaction” to advance the field of interactomics further.