Terminology of bioanalytical methods (IUPAC Recommendations 2018)

Recommendations are given concerning the terminology of methods of bioanalytical chemistry. With respect to dynamic development particularly in the analysis and investigation of biomacromolecules, terms related to bioanalytical samples, enzymatic methods, immunoanalytical methods, methods used in genomics and nucleic acid analysis, proteomics, metabolomics, glycomics, lipidomics, and biomolecules interaction studies are introduced

Terminology of bioanalytical methods (IUPAC Recommendations 2018)

free accessRecommendations are given concerning the terminology of methods of bioanalytical chemistry. With respect to dynamic development particularly in the analysis and investigation of biomacromolecules, terms related to bioanalytical samples, enzymatic methods, immunoanalytical methods, methods used in genomics and nucleic acid analysis, proteomics, metabolomics, glycomics, lipidomics, and biomolecules interaction studies are introduced.Peer reviewe

Additional file 1: of Individual CpG sites that are associated with age and life expectancy become hypomethylated upon aging

This file contains additional details on the methods, Additional file 1: Figures S1–S2, and Additional file 1: Tables S1–S6. (PDF 1054 kb

Zinc deficiency leads to reduced interleukin-2 production by active gene silencing due to enhanced CREMα expression in T cells

BACKGROUND & AIMS: The micronutrient zinc is essential for proper immune function. Consequently, zinc deficiency leads to impaired immune function, as seen in decreased secretion of interleukin (IL)-2 by T cells. Although this association has been known since the late 1980s, the underlying molecular mechanisms are still unknown. Zinc deficiency and reduced IL-2 levels are especially found in the elderly, which in turn are prone to chronic diseases. Here, we describe a new molecular link between zinc deficiency and reduced IL-2 expression in T cells. METHODS: The effects of zinc deficiency were first investigated in vitro in the human T cell lines Jurkat and Hut-78 and complemented by in vivo data from zinc-supplemented pigs. A short- and long-term model for zinc deficiency was established. Zinc levels were detected by flow cytometry and expression profiles were investigated on the mRNA and protein level. RESULTS: The expression of the transcription factor cAMP-responsive-element modulator α (CREMα) is increased during zinc deficiency in vitro, due to increased protein phosphatase 2A (PP2A) activity, resulting in decreased IL-2 production. Additionally, zinc supplementation in vivo reduced CREMα levels causing increased IL-2 expression. On epigenetic levels increased CREMα binding to the IL-2 promoter is mediated by histone deacetylase 1 (HDAC1). The HDAC1 activity is inhibited by zinc. Moreover, deacetylation of the activating histone mark H3K9 was increased under zinc deficiency, resulting in reduced IL-2 expression. CONCLUSIONS: With the transcription factor CREMα a molecular link was uncovered, connecting zinc deficiency with reduced IL-2 production due to enhanced PP2A and HDAC1 activity.status: Published onlin

Investigation of measurable residual disease in acute myeloid leukemia by DNA methylation patterns

Assessment of measurable residual disease (MRD) upon treatment of acute myeloid leukemia (AML) remains challenging. It is usually addressed by highly sensitive PCR- or sequencing-based screening of specific mutations, or by multiparametric flow cytometry. However, not all patients have suitable mutations and heterogeneity of surface markers hampers standardization in clinical routine. In this study, we propose an alternative approach to estimate MRD based on AML-associated DNA methylation (DNAm) patterns. We identified four CG dinucleotides (CpGs) that commonly reveal aberrant DNAm in AML and their combination could reliably discern healthy and AML samples. Interestingly, bisulfite amplicon sequencing demonstrated that aberrant DNAm patterns were symmetric on both alleles, indicating that there is epigenetic crosstalk between homologous chromosomes. We trained shallow-learning and deep-learning algorithms to identify anomalous DNAm patterns. The method was then tested on follow-up samples with and without MRD. Notably, even samples that were classified as MRD negative often revealed higher anomaly ratios than healthy controls, which may reflect clonal hematopoiesis. Our results demonstrate that targeted DNAm analysis facilitates reliable discrimination of malignant and healthy samples. However, since healthy samples also comprise few abnormal-classified DNAm reads the approach does not yet reliably discriminate MRD positive and negative samples

Bioanalytical Chemistry

This chapter provides a terminology of bioanalytical chemistry in general and analysis of biomacromolecules in particular. The vocabulary given in this chapter is largely taken from Labuda et al. “Terminology of bioanalytical methods (IUPAC Recommendations 2018)”,1 which becomes the immediate source reference for definitions of terms in this chapter that are not otherwise attributed. Reference to secondary sources follow the entry as “see also:” Terms are taken from the IUPAC Recommendations published in 1994 covering mostly the analytical terminology related to body fluids, enzymology, and immunology.2 Selected terms related to bioanalysis are included within recommendations and reports devoted to the unit “katal”,3 biotechnology,4 clinical chemistry,5 toxicology,6,7 medicinal chemistry,8,9 proteomics,10 electrochemical biosensors,11,12 and physical organic chemistry.13 Definitions of some terms have been updated here with respect to new reports and considerations, and a number of new terms has been introduced particularly on the topics of “–omics”, DNA analysis and studies of the interactions between biomolecules. Terms from earlier IUPAC Recommendations that are replaced by ref. 1 are not otherwise referenced but can be found as references in ref. 1