Dem IPB wird erneut ein beispielhaftes Handeln im Sinne einer chancengleichheitsorientierten Personal- und Organisationspolitik bescheinigt. Das Institut erhält zum 6. Mal in Folge das TOTAL E-QUALITY…
Die Plant Science Student Conference (PSSC) wird seit 20 Jahren im jährlichen Wechsel von Studierenden der beiden Leibniz-Institute IPK und IPB organisiert. Im Interview erläutern Christina Wäsch…
Type 2 diabetes mellitus (T2DM) is a complex group of disorders, characterized by hyperglycemia, insulin resistance and insulin deficiency. In human blood, hyperglycemia ultimately results in the enhancement of glycation – a posttranslational modification formed by the interaction of protein amino groups with glucose. The resulting fructosamines (Amadori compounds) readily undergo further degradation resulting in advanced glycation end products (AGEs), known to be pro-inflammatory in humans. These compounds are highly heterogeneous and characteristic of advanced stages of the disease, whereas fructosamines are recognized markers of early diabetes stages (HbA1C, glycated albumin). Recently, individual plasma protein glycation sites were proposed as promising T2DM biomarkers sensitive to short-term fluctuations of plasma glucose. However, corresponding absolute quantification strategies, applicable in regular clinical practice, are still not established. Therefore, here we propose a new analytical approach aiming at reproducible and precise quantification of multiple glycated peptides in human plasma tryptic digests. Thereby, the standard peptides comprised a 13C,15N-labeled lysyl residue, a dabsyl moiety for determination of standard amounts, and a cleavable linker. Known amounts of these peptides were spiked to plasma samples prior to tryptic digestion, quantification relying on stable isotope dilution. The method was demonstrated to be applicable for quantification of individual glycated sites in T2DM patients and non-diabetic controls.
Publikation
Nettling, M.; Treutler, H.; Cerquides, J.; Grosse, I.;Combining phylogenetic footprinting with motif models incorporating intra-motif dependenciesBMC Bioinformatics18141(2017)DOI: 10.1186/s12859-017-1495-1
BackgroundTranscriptional gene regulation is a fundamental process in nature, and the experimental and computational investigation of DNA binding motifs and their binding sites is a prerequisite for elucidating this process. Approaches for de-novo motif discovery can be subdivided in phylogenetic footprinting that takes into account phylogenetic dependencies in aligned sequences of more than one species and non-phylogenetic approaches based on sequences from only one species that typically take into account intra-motif dependencies. It has been shown that modeling (i) phylogenetic dependencies as well as (ii) intra-motif dependencies separately improves de-novo motif discovery, but there is no approach capable of modeling both (i) and (ii) simultaneously.ResultsHere, we present an approach for de-novo motif discovery that combines phylogenetic footprinting with motif models capable of taking into account intra-motif dependencies. We study the degree of intra-motif dependencies inferred by this approach from ChIP-seq data of 35 transcription factors. We find that significant intra-motif dependencies of orders 1 and 2 are present in all 35 datasets and that intra-motif dependencies of order 2 are typically stronger than those of order 1. We also find that the presented approach improves the classification performance of phylogenetic footprinting in all 35 datasets and that incorporating intra-motif dependencies of order 2 yields a higher classification performance than incorporating such dependencies of only order 1.ConclusionCombining phylogenetic footprinting with motif models incorporating intra-motif dependencies leads to an improved performance in the classification of transcription factor binding sites. This may advance our understanding of transcriptional gene regulation and its evolution.