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Johan Lindberg

Publications and source records attributed to Johan Lindberg.

9 recordsLinked to original sources
PubMed2006

Determination of binding specificities in highly multiplexed bead-based assays for antibody proteomics.

One of the major challenges of antibody-based proteomics is the quality assurance of the generated antibodies to ensure specificity to the target protein. Here we describe a single tube multiplex approach to simultaneously analyze the binding of antibodies to a large number of different antigens. This bead-based assay utilizes the full multiplexing capacity theoretically offered by the Luminex suspension array technology. A protocol for an increased coupling throughput for the immobilization of antigens was developed and used to set up complex and stabile 100-plex bead mixtures. The possibility of using a two-dimensional multiplexing, in terms of high numbers of both analytes and samples or as in this case antigens and antibodies, enables the specificity of 96 antibodies versus 100 different antigens to be determined in 2 h. This high throughput analysis will potentially have great impact on the possibility for the utilization of different antibody proteomics approaches where the quality assessment of antibodies is of the utmost importance.

Antibodies↗
PubMed2006

Variability in synovial inflammation in rheumatoid arthritis investigated by microarray technology.

In recent years microarray technology has been used increasingly to acquire knowledge about the pathogenic processes involved in rheumatoid arthritis. The present study investigated variations in gene expression in synovial tissues within and between patients with rheumatoid arthritis. This was done by applying microarray technology on multiple synovial biopsies obtained from the same knee joints. In this way the relative levels of intra-patient and inter-patient variation could be assessed. The biopsies were obtained from 13 different patients: 7 by orthopedic surgery and 6 by rheumatic arthroscopy. The data show that levels of heterogeneity varied substantially between the biopsies, because the number of genes found to be differentially expressed between pairs of biopsies from the same knee ranged from 6 to 2,133. Both arthroscopic and orthopedic biopsies were examined, allowing us to compare the two sampling methods. We found that the average number of differentially expressed genes between biopsies from the same patient was about three times larger in orthopedic than in arthroscopic biopsies. Using a parallel analysis of the tissues by immunohistochemistry, we also identified orthopedic biopsies that were unsuitable for gene expression analysis of synovial inflammation due to sampling of non-inflamed parts of the tissue. Removing these biopsies reduced the average number of differentially expressed genes between the orthopedic biopsies from 455 to 171, in comparison with 143 for the arthroscopic biopsies. Hierarchical clustering analysis showed that the remaining orthopedic and arthroscopic biopsies had gene expression signatures that were unique for each patient, apparently reflecting patient variation rather than tissue heterogeneity. Subsets of genes found to vary between biopsies were investigated for overrepresentation of biological processes by using gene ontology. This revealed representative 'themes' likely to vary between synovial biopsies affected by inflammatory disease.

Aged↗
PubMed2006

Second-order peak detection for multicomponent high-resolution LC/MS data.

The first step when analyzing multicomponent LC/MS data from complex samples such as biofluid metabolic profiles is to separate the data into information and noise via, for example, peak detection. Due to the complex nature of this type of data, with problems such as alternating backgrounds and differing peak shapes, this can be a very complex task. This paper presents and evaluates a two-dimensional peak detection algorithm based on raw vector-represented LC/MS data. The algorithm exploits the fact that in high-resolution centroid data chromatographic peaks emerge flanked with data voids in the corresponding mass axis. According to the proposed method, only 4 per thousand of the total amount of data from a urine sample is defined as chromatographic peaks; however, 94% of the raw data variance is captured within these peaks. Compared to bucketed data, results show that essentially the same features that an experienced analyst would define as peaks can automatically be extracted with a minimum of noise and background. The method is simple and requires a priori knowledge of only the minimum chromatographic peak width-a system-dependent parameter that is easily assessed. Additional meta parameters are estimated from the data themselves. The result is well-defined chromatographic peaks that are consistently arranged in a matrix at their corresponding m/z values. In the context of automated analysis, the method thus provides an alternative to the traditional approach of bucketing the data followed by denoising and/or one-dimensional peak detection. The software implementation of the proposed algorithm is available at http://www.anchem.su.se/peakd as compiled code for Matlab.

Algorithms↗
PubMed2006

Predictive metabolite profiling applying hierarchical multivariate curve resolution to GC-MS data--a potential tool for multi-parametric diagnosis.

A method for predictive metabolite profiling based on resolution of GC-MS data followed by multivariate data analysis is presented and applied to three different biofluid data sets (rat urine, aspen leaf extracts, and human blood plasma). Hierarchical multivariate curve resolution (H-MCR) was used to simultaneously resolve the GC-MS data into pure profiles, describing the relative metabolite concentrations between samples, for multivariate analysis. Here, we present an extension of the H-MCR method allowing treatment of independent samples according to processing parameters estimated from a set of training samples. Predictions or inclusion of the new samples, based on their metabolite profiles, into an existing model could then be carried out, which is a requirement for a working application within, e.g., clinical diagnosis. Apart from allowing treatment and prediction of independent samples the proposed method also reduces the time for the curve resolution process since only a subset of representative samples have to be processed while the remaining samples can be treated according to the obtained processing parameters. The time required for resolving the 30 training samples in the rat urine example was approximately 13 h, while the treatment of the 30 test samples according to the training parameters required only approximately 30 s per sample (approximately 15 min in total). In addition, the presented results show that the suggested approach works for describing metabolic changes in different biofluids, indicating that this is a general approach for high-throughput predictive metabolite profiling, which could have important applications in areas such as plant functional genomics, drug toxicity, treatment efficacy and early disease diagnosis.

Animals↗
PubMed2006

Effect of infliximab on mRNA expression profiles in synovial tissue of rheumatoid arthritis patients.

We examined the gene expression profiles in arthroscopic biopsies retrieved from 10 rheumatoid arthritis patients before and after anti-TNF treatment with infliximab to investigate whether such profiles can be used to predict responses to the therapy, and to study effects of the therapy on the profiles. Responses to treatment were assessed using European League Against Rheumatism response criteria. Three patients were found to be good responders, five patients to be moderate responders and two patients to be nonresponders. The TNF-alpha status of the biopsies from each of the patients before treatment was also investigated immunohistochemically, and it was detected in biopsies from four of the patients, including all three of the good responders. The gene expression data demonstrate that all patients had unique gene expression signatures, with low intrapatient variability between biopsies. The data also revealed significant differences between the good responding and nonresponding patients (279 differentially expressed genes were detected, with a false discovery rate < 0.025). Among the identified genes we found that MMP-3 was significantly upregulated in good responders (log2 fold change, 2.95) compared with nonresponders, providing further support for the potential of MMP-3 as a marker for good responses to therapy. An even more extensive list of 685 significantly differentially expressed genes was found between patients in whom TNF-alpha was found and nonresponders, indicating that TNF-alpha could be an important biomarker for successful infliximab treatment. Significant differences were also observed between biopsies taken before and after anti-TNF treatment, including 115 differentially expressed genes in the good responding group. Interestingly, the effect was even stronger in the group in which TNF-alpha was immunohistochemically detected before therapy. Here, 1,058 genes were differentially expressed, including many that were novel in this context (for example, CXCL3 and CXCL14). Subsequent Gene Ontology analysis revealed that several 'themes' were significantly over-represented that are known to be affected by anti-TNF treatment in inflammatory tissue; for example, immune response (GO:0006955), cell communication (GO:0007154), signal transduction (GO:0007165) and chemotaxis (GO:0006935). No genes reached statistical significance in the moderately responding or nonresponding groups. In conclusion, this pilot study suggests that further investigation is warranted on the usefulness of gene expression profiling of synovial tissue to predict and monitor the outcome of rheumatoid arthritis therapies.

Adult↗
PubMed2005

A comparison of methods for alignment of NMR peaks in the context of cluster analysis.

This paper compares the performance of two recently developed algorithms and methods for peak alignment of first-order NMR data of complex biological samples. The NMR spectra of such samples exhibit variations in peak position and peak shape due to variations in the sample matrix and to instrumental instabilities. The first method comprises an alignment of spectral segments with linear interpolation and shift correction to accommodate correspondence between a target and a test spectrum by a beam search or genetic algorithm. The second method is based on peak picking and needle vector representation of the NMR data with subsequent breadth-first search to establish shift corrections between the target and the test spectrum. The two proposed peak alignment methods and their respective merits are discussed for a real metabonomics application. Both alignment methods have been shown to enhance the interpretability of the resulting multivariate models, thereby increasing the prospect of detecting and following the onset of subtle biological changes reflected in the NMR data.

Algorithms↗
PubMed2003

Two distinct transport motifs in the adenovirus E3/10.4-14.5 proteins act in concert to down-modulate apoptosis receptors and the epidermal growth factor receptor.

The adenovirus (Ad) early transcription unit E3 encodes immunosubversive functions. The E3 transmembrane proteins 10.4 and 14.5 form a complex that down-regulates the epidermal growth factor receptor and apoptosis receptors from the cell surface by diverting them to endosomes/lysosomes for degradation. The latter process protects infected cells from ligand-induced apoptosis. The mechanism by which 10.4-14.5 mediate re-routing remains elusive. We examined the role of putative YXX Phi and dileucine (LL) transport motifs within Ad2 10.4-14.5 for target protein modulation. By generating stable E3 transfectants expressing 10.4-14.5 proteins with alanine substitutions in these motifs, we show that 3 of the 5 motifs are essential for functional activity. Whereas tyrosine 74 in 14.5 appears to be important for efficient 10.4-14.5 interaction, the 122YXX Phi motif in 14.5 and the dileucine motif Leu 87-Leu88 in 10.4 constitute genuine transport motifs: disruption of either motif abolished binding to the cellular adaptor proteins AP-1 and AP-2, as shown by surface plasmon resonance spectroscopy, and caused missorting, dramatically altering cell surface appearance and the intracellular location of viral proteins. Fluorescence-activated cell sorter analysis and immunofluorescence data provide evidence that Tyr122 in 14.5 is essential for rapid endocytosis of the 10.4-14.5 complex, whereas the 10.4LL motif acts down-stream and protects 10.4-14.5 from extensive degradation by rerouting it into a recycling pathway. Infection of primary cells with adenoviruses carrying the relevant point mutations confirmed the crucial role of these transport motifs for down-regulation of Fas, TRAIL-R1, TRAIL-R2, and epidermal growth factor receptor. Thus, two distinct transport motifs present in two proteins synergize for efficient target removal and immune evasion.

Adaptor Protein Complex 1↗