Andreas Schroeder

Bio: Andreas Schroeder is an academic researcher from Agilent Technologies. The author has contributed to research in topics: Medicine & RNA integrity number. The author has an hindex of 4, co-authored 5 publications receiving 2743 citations.

The RIN: an RNA integrity number for assigning integrity values to RNA measurements

Abstract: The integrity of RNA molecules is of paramount importance for experiments that try to reflect the snapshot of gene expression at the moment of RNA extraction. Until recently, there has been no reliable standard for estimating the integrity of RNA samples and the ratio of 28S:18S ribosomal RNA, the common measure for this purpose, has been shown to be inconsistent. The advent of microcapillary electrophoretic RNA separation provides the basis for an automated high-throughput approach, in order to estimate the integrity of RNA samples in an unambiguous way. A method is introduced that automatically selects features from signal measurements and constructs regression models based on a Bayesian learning technique. Feature spaces of different dimensionality are compared in the Bayesian framework, which allows selecting a final feature combination corresponding to models with high posterior probability. This approach is applied to a large collection of electrophoretic RNA measurements recorded with an Agilent 2100 bioanalyzer to extract an algorithm that describes RNA integrity. The resulting algorithm is a user-independent, automated and reliable procedure for standardization of RNA quality control that allows the calculation of an RNA integrity number (RIN). Our results show the importance of taking characteristics of several regions of the recorded electropherogram into account in order to get a robust and reliable prediction of RNA integrity, especially if compared to traditional methods.

Towards standardization of RNA quality assessment using user-independent classifiers of microcapillary electrophoresis traces

Abstract: While it is universally accepted that intact RNA constitutes the best representation of the steady-state of transcription, there is no gold standard to define RNA quality prior to gene expression analysis. In this report, we evaluated the reliability of conventional methods for RNA quality assessment including UV spectroscopy and 28S:18S area ratios, and demonstrated their inconsistency. We then used two new freely available classifiers, the Degradometer and RIN systems, to produce user-independent RNA quality metrics, based on analysis of microcapillary electrophoresis traces. Both provided highly informative and valuable data and the results were found highly correlated, while the RIN system gave more reliable data. The relevance of the RNA quality metrics for assessment of gene expression differences was tested by Q-PCR, revealing a significant decline of the relative expression of genes in RNA samples of disparate quality, while samples of similar, even poor integrity were found highly comparable. We discuss the consequences of these observations to minimize artifactual detection of false positive and negative differential expression due to RNA integrity differences, and propose a scheme for the development of a standard operational procedure, with optional registration of RNA integrity metrics in public repositories of gene expression data.

Determining the quality of biomolecule samples

Abstract: Disclosed is determining the quality, expressed in terms of a quality value, of an biomolecule sample, based on measured data of the biomolecule sample, by extracting a number of prescribed features from the measured data using data analysis, and determining the quality value from the extracted features using a quality algorithm.

RNA integrity number (RIN) - towards standardization of RNA quality assessment

Abstract: 1649 RNA quality assessment has been identified as one of the most critical elements in order to obtain meaningful gene expression data via microarray or real-time PCR experiments. Current advances in microfluidics have improved RNA quality measurements tremendously by allowing a more detailed look at RNA degradation patterns by providing electrophoretic traces of RNA samples. However, the interpretation of such electropherograms still requires a certain level of experience and can vary from one researcher to the next. A so-called “RNA integrity number” (RIN) algorithm is introduced that assigns a user-independent integrity number to each RNA sample. The RIN has been developed using neural networks by “teaching” this algorithm with a large number of RNA integrity data. It was found that the RIN is more reliable than the ribosomal ratio, when assessing the integrity of RNA samples. The RIN is shown to be largely independent of RNA concentration, instrument (Agilent 2100 bioanalyzer), and most importantly, the origin of the RNA sample. Using the RIN, researchers can work towards standardization of the important RNA integrity measurement ensuring reproducibility and reliability of gene expression experiments.

Primary Graft Dysfunction: The Role of Aging in Lung Ischemia-Reperfusion Injury

Abstract: Transplant centers around the world have been using extended criteria donors to remedy the ongoing demand for lung transplantation. With a rapidly aging population, older donors are increasingly considered. Donor age, at the same time has been linked to higher rates of lung ischemia reperfusion injury (IRI). This process of acute, sterile inflammation occurring upon reperfusion is a key driver of primary graft dysfunction (PGD) leading to inferior short- and long-term survival. Understanding and improving the condition of older lungs is thus critical to optimize outcomes. Notably, ex vivo lung perfusion (EVLP) seems to have the potential of reconditioning ischemic lungs through ex-vivo perfusing and ventilation. Here, we aim to delineate mechanisms driving lung IRI and review both experimental and clinical data on the effects of aging in augmenting the consequences of IRI and PGD in lung transplantation.

The RIN: an RNA integrity number for assigning integrity values to RNA measurements

Abstract: The integrity of RNA molecules is of paramount importance for experiments that try to reflect the snapshot of gene expression at the moment of RNA extraction. Until recently, there has been no reliable standard for estimating the integrity of RNA samples and the ratio of 28S:18S ribosomal RNA, the common measure for this purpose, has been shown to be inconsistent. The advent of microcapillary electrophoretic RNA separation provides the basis for an automated high-throughput approach, in order to estimate the integrity of RNA samples in an unambiguous way. A method is introduced that automatically selects features from signal measurements and constructs regression models based on a Bayesian learning technique. Feature spaces of different dimensionality are compared in the Bayesian framework, which allows selecting a final feature combination corresponding to models with high posterior probability. This approach is applied to a large collection of electrophoretic RNA measurements recorded with an Agilent 2100 bioanalyzer to extract an algorithm that describes RNA integrity. The resulting algorithm is a user-independent, automated and reliable procedure for standardization of RNA quality control that allows the calculation of an RNA integrity number (RIN). Our results show the importance of taking characteristics of several regions of the recorded electropherogram into account in order to get a robust and reliable prediction of RNA integrity, especially if compared to traditional methods.

Quantification of mRNA using real-time RT-PCR

Abstract: The real-time reverse transcription polymerase chain reaction (RT-qPCR) addresses the evident requirement for quantitative data analysis in molecular medicine, biotechnology, microbiology and diagnostics and has become the method of choice for the quantification of mRNA. Although it is often described as a "gold" standard, it is far from being a standard assay. The significant problems caused by variability of RNA templates, assay designs and protocols, as well as inappropriate data normalization and inconsistent data analysis, are widely known but also widely disregarded. As a first step towards standardization, we describe a series of RT-qPCR protocols that illustrate the essential technical steps required to generate quantitative data that are reliable and reproducible. We would like to emphasize, however, that RT-qPCR data constitute only a snapshot of information regarding the quantity of a given transcript in a cell or tissue. Any assessment of the biological consequences of variable mRNA levels must include additional information regarding regulatory RNAs, protein levels and protein activity. The entire protocol described here, encompassing all stages from initial assay design to reliable qPCR data analysis, requires approximately 15 h.

Laser-capture microdissection

Abstract: Deciphering the cellular and molecular interactions that drive disease within the tissue microenvironment holds promise for discovering drug targets of the future. In order to recapitulate the in vivo interactions thorough molecular analysis, one must be able to analyze specific cell populations within the context of their heterogeneous tissue microecology. Laser-capture microdissection (LCM) is a method to procure subpopulations of tissue cells under direct microscopic visualization. LCM technology can harvest the cells of interest directly or can isolate specific cells by cutting away unwanted cells to give histologically pure enriched cell populations. A variety of downstream applications exist: DNA genotyping and loss-of-heterozygosity (LOH) analysis, RNA transcript profiling, cDNA library generation, proteomics discovery and signal-pathway profiling. Herein we provide a thorough description of LCM techniques, with an emphasis on tips and troubleshooting advice derived from LCM users. The total time required to carry out this protocol is typically 1-1.5 h.

Hereditary parkinsonism with dementia is caused by mutations in ATP13A2, encoding a lysosomal type 5 P-type ATPase.

Abstract: Neurodegenerative disorders such as Parkinson and Alzheimer disease cause motor and cognitive dysfunction and belong to a heterogeneous group of common and disabling disorders. Although the complex molecular pathophysiology of neurodegeneration is largely unknown, major advances have been achieved by elucidating the genetic defects underlying mendelian forms of these diseases. This has led to the discovery of common pathophysiological pathways such as enhanced oxidative stress, protein misfolding and aggregation and dysfunction of the ubiquitin-proteasome system. Here, we describe loss-of-function mutations in a previously uncharacterized, predominantly neuronal P-type ATPase gene, ATP13A2, underlying an autosomal recessive form of early-onset parkinsonism with pyramidal degeneration and dementia (PARK9, Kufor-Rakeb syndrome). Whereas the wild-type protein was located in the lysosome of transiently transfected cells, the unstable truncated mutants were retained in the endoplasmic reticulum and degraded by the proteasome. Our findings link a class of proteins with unknown function and substrate specificity to the protein networks implicated in neurodegeneration and parkinsonism.