Biomedical subjects

Kay Nieselt

Publications and source records attributed to Kay Nieselt.

7 recordsLinked to original sources

PubMed2026

A new highly discriminatory typing scheme for Treponema pallidum reveals similar levels of genetic variability across lineages.

UNLABELLED: The global resurgence of treponematoses, particularly syphilis, poses a growing public health challenge. Despite advances in sequencing technologies, obtaining complete Treponema pallidum genome sequences for epidemiological studies remains challenging due to clinical sampling and methodological constraints. There is, therefore, a need for rapid, cost-effective, and accessible typing methods. Based on the analysis of 121 T. pallidum genomes spanning all three subspecies (TPA, TPE, and TEN) from diverse regions, we selected seven highly variable genes (tp0136, tp0326, tp0548, tp0705, tp0858, tp0865, and tp1031) to form a new typing system, combined with analysis of macrolide resistance mutations in the 23S rRNA gene. The scheme was validated on 542 global T. pallidum samples, using either Sanger reads or whole genome sequence data, obtaining 82 sequence types (STs) among the 415 fully typed samples. Macrolide resistance mutations were frequently detected, highlighting the need for ongoing epidemiological surveillance. Phylogenetic analyses based on concatenated multilocus typing (MLST) loci recovered the expected subspecies and lineage structure. Consistently, almost all sequence types formed monophyletic groups, indicating strong concordance between MLST-based classification and whole-genome phylogenies. In addition, population genetic analyses revealed comparable levels of within-lineage diversity across subspecies and lineages, despite pronounced differences in geographic distribution, and identified distinct regional genetic clusters consistent with localized transmission dynamics. Importantly, the scheme employs a single-step PCR for all seven targets, facilitating implementation in standard laboratories and is publicly accessible through PubMLST. Overall, our novel MLST scheme offers a rapid, cost-effective tool to advance molecular epidemiology of T. pallidum, facilitate transmission and resistance tracking, and support global surveillance to strengthen public health interventions for syphilis and endemic treponematoses control. IMPORTANCE: We have developed a new multilocus typing (MLST) scheme useful for all Treponema pallidum lineages after the analysis of 121 complete genome sequences of this species. The new scheme can be used directly with uncultured clinical samples, thus providing an excellent contribution to the molecular surveillance of syphilis and other treponematoses. The application of this MLST scheme to over 500 samples from all lineages and main geographical regions has revealed similar levels of genetic variation within them. Furthermore, the analyses show a complex pattern of spread, with global and local contributions to the observed distribution of genetic variation in the syphilis-producing sublineages. The new scheme represents a significant improvement over previous proposals and also reveals unsuspected levels of variability in T. pallidum lineages.

Treponema pallidum↗

PubMed2006

On the maximal cliques in c-max-tolerance graphs and their application in clustering molecular sequences.

Given a set S of n locally aligned sequences, it is a needed prerequisite to partition it into groups of very similar sequences to facilitate subsequent computations, such as the generation of a phylogenetic tree. This article introduces a new method of clustering which partitions S into subsets such that the overlap of each pair of sequences within a subset is at least a given percentage c of the lengths of the two sequences. We show that this problem can be reduced to finding all maximal cliques in a special kind of max-tolerance graph which we call a c-max-tolerance graph. Previously we have shown that finding all maximal cliques in general max-tolerance graphs can be done efficiently in O(n3 + out). Here, using a new kind of sweep-line algorithm, we show that the restriction to c-max-tolerance graphs yields a better runtime of O(n2 log n + out). Furthermore, we present another algorithm which is much easier to implement, and though theoretically slower than the first one, is still running in polynomial time. We then experimentally analyze the number and structure of all maximal cliques in a c-max-tolerance graph, depending on the chosen c-value. We apply our simple algorithm to artificial and biological data and we show that this implementation is much faster than the well-known application Cliquer. By introducing a new heuristic that uses the set of all maximal cliques to partition S, we finally show that the computed partition gives a reasonable clustering for biological data sets.

Journal Article↗

PubMed2006

Progression-specific genes identified by expression profiling of matched ductal carcinomas in situ and invasive breast tumors, combining laser capture microdissection and oligonucleotide microarray analysis.

Becoming invasive is a crucial step in breast cancer oncogenesis. At this point, a lesion carries the potential for spreading and metastasis--a process, whose molecular characteristics still remain poorly understood. In this article, we describe a matched-pair analysis of ductal carcinoma in situ (DCIS) and invasive ductal carcinoma (IDC) of nine breast ductal carcinomas to identify novel molecular markers characterizing the transition from DCIS to IDC. The purpose of this study was to better understand the molecular biology of this transition and to identify candidate genes whose products might serve as prognostic markers and/or as molecular targets for treatment. To obtain cellular-based gene expression profiles from epithelial tumor cells, we combined laser capture microdissection with a T7-based two-round RNA amplification and Affymetrix oligonucleotide microarray analysis. Altogether, a set of 24 tumor samples was analyzed, comprised of nine matched DCIS/IDC and replicate DCIS/IDC preparations from three of the nine tumors. Cluster analysis on expression data shows the robustness and reproducibility of the techniques we established. Using multiple statistical methods, 546 significantly differentially expressed probe sets were identified. Eighteen candidate genes were evaluated by RT-PCR. Examples of genes already known to be associated with breast cancer invasion are BPAG1, LRRC15, MMP11, and PLAU. The expression of BPAG1, DACT1, GREM1, MEF2C, SART2, and TNFAIP6 was localized to epithelial tumor cells by in situ hybridization and/or immunohistochemistry, confirming the accuracy of laser capture microdissection sampling and microarray analysis.

Breast Neoplasms↗

PubMed2006

Mayday--a microarray data analysis workbench.

UNLABELLED: Mayday is a workbench for visualization, analysis and storage of microarray data. It features a graphical user interface and supports the development and integration of existing and new analysis methods. Besides the infrastructural core functionality, Mayday offers a variety of plug-ins, such as various interactive viewers, a connection to the R statistical environment, a connection to SQL-based databases and different data mining methods, including WEKA-library based methods for classification and various clustering methods. In addition, so-called meta information objects are provided for annotation of the microarray data allowing integration of data from different sources, which is a feature that, for instance, is employed in the enhanced heatmap visualization. SUPPLEMENTARY INFORMATION: The software and more detailed information including screenshots and a user guide as well as test data can be found on the Mayday home page http://www.zbit.uni-tuebingen.de/pas/mayday. The core is published under the GPL (GNU Public License) and the associated plug-ins under the LGPL (Lesser GNU Public License).

Computer Graphics↗

PubMed2005

Open reading frames provide a rich pool of potential natural antisense transcripts in fungal genomes.

Natural antisense transcripts are reported from all kingdoms of life and several recent reports of genomewide screens indicate that they are widely distributed. These transcripts seem to be involved in various biological functions and may govern the expression of their respective sense partner. Very little, however, is known about the degree of evolutionary conservation of antisense transcripts. Furthermore, none of the earlier analyses has studied whether antisense relationships are solely dual or involved in more complex relationships. Here we present a systematic screen for cis- and trans-located antisense transcripts based on open reading frames (ORFs) from five fungal species. The relative number of ORFs involved in antisense relationships varies greatly between the five species. In addition, other significant differences are found between the species, such as the mean length of the antisense region. The majority of trans-located antisense transcripts is found to be involved in complex relationships, resulting in highly connected networks. The analysis of the degree of evolutionary conservation of antisense transcripts shows that most antisense transcripts have no ortholog in any other species. An annotation of antisense transcripts based on Gene Ontology directs to common terms and shows that proteins of genes involved in antisense relationships preferentially localize to the nucleus with common functions in the regulation or maintenance of nucleic acids.

Evolution, Molecular↗

PubMed2005

cDNA microarray analysis reveals novel candidate genes expressed in human peripheral blood following exhaustive exercise.

It is generally accepted that exhausting endurance exercise exhibits strong effects on the immune system. Such effects have been attributed to changes in the cellular composition of peripheral blood as well as to changes in the expression of plausible candidate genes. The list of candidate genes is far from being complete, since this issue has not yet been investigated in a systematic way. In this study, we used a custom-made cDNA microarray focused on inflammation as a screening approach to study gene expression in eight one-half marathon runners before, immediately after, and 24 h after exercise. Significant differential gene expression was verified by quantitative real-time PCR. Linear regression analysis showed that microarray expression analysis of cell type-specific surface molecules reflects the observed individual cellular shifts in peripheral blood cells with high statistical significance. In line with the results of former studies, we observed an upregulation of mitogen-activated protein kinase-activated protein kinase-2 (MAPKAP-K2), L-selectin, and IL-1 receptor antagonist (IL-1ra) after exhaustive exercise. The main results of this study report, for the first time, the downregulation of CD81; the upregulation of thioredoxin, which may play an important part in anti-oxidative defense; and, surprisingly, the downregulation of the anti-carcinogenic gene glutathione-S-transferase-3 (GSTM3) in peripheral blood. The study shows cDNA microarray expression analysis as a reliable systematic instrument to complete the list of candidate genes that may play a role in exhaustive exercise-induced modulation of the immune response.

Adult↗

PubMed2004

DIALIGN P: fast pair-wise and multiple sequence alignment using parallel processors.

BACKGROUND: Parallel computing is frequently used to speed up computationally expensive tasks in Bioinformatics. RESULTS: Herein, a parallel version of the multi-alignment program DIALIGN is introduced. We propose two ways of dividing the program into independent sub-routines that can be run on different processors: (a) pair-wise sequence alignments that are used as a first step to multiple alignment account for most of the CPU time in DIALIGN. Since alignments of different sequence pairs are completely independent of each other, they can be distributed to multiple processors without any effect on the resulting output alignments. (b) For alignments of large genomic sequences, we use a heuristics by splitting up sequences into sub-sequences based on a previously introduced anchored alignment procedure. For our test sequences, this combined approach reduces the program running time of DIALIGN by up to 97%. CONCLUSIONS: By distributing sub-routines to multiple processors, the running time of DIALIGN can be crucially improved. With these improvements, it is possible to apply the program in large-scale genomics and proteomics projects that were previously beyond its scope.

Computational Biology↗