Carsten Wiuf

Estimating the size of the human interactome.

After the completion of the human and other genome projects it emerged that the number of genes in organisms as diverse as fruit flies, nematodes, and humans does not reflect our perception of their relative complexity. Here, we provide reliable evidence that the size of protein interaction networks in different organisms appears to correlate much better with their apparent biological complexity. We develop a stable and powerful, yet simple, statistical procedure to estimate the size of the whole network from subnet data. This approach is then applied to a range of eukaryotic organisms for which extensive protein interaction data have been collected and we estimate the number of interactions in humans to be ≈650,000. We find that the human interaction network is one order of magnitude bigger than the Drosophila melanogaster interactome and ≈3 times bigger than in Caenorhabditis elegans.

Diagnostic and Prognostic MicroRNAs in Stage II Colon Cancer

MicroRNAs (miRNA) are a class of small noncoding RNAs with important posttranscriptional regulatory functions. Recent data suggest that miRNAs are aberrantly expressed in many human cancers and that they may play significant roles in carcinogenesis. Here, we used microarrays to profile the expression of 315 human miRNAs in 10 normal mucosa samples and 49 stage II colon cancers differing with regard to microsatellite status and recurrence of disease. Several miRNAs were differentially expressed between normal tissue and tumor microsatellite subtypes, with miR-145 showing the lowest expression in cancer relative to normal tissue. Microsatellite status for the majority of cancers could be correctly predicted based on miRNA expression profiles. Furthermore, a biomarker based on miRNA expression profiles could predict recurrence of disease with an overall performance accuracy of 81%, indicating a potential role of miRNAs in determining tumor aggressiveness. The expression levels of miR-320 and miR-498, both included in the predictive biomarker, correlated with the probability of recurrence-free survival by multivariate analysis. We successfully verified the expression of selected miRNAs using real-time reverse transcription-PCR assays for mature miRNAs, whereas in situ hybridization was used to detect the accumulation of miR-145 and miR-320 in normal epithelial cells and adenocarcinoma cells. Functional studies showed that miR-145 potently suppressed growth of three different colon carcinoma cell lines. In conclusion, our results suggest that perturbed expression of numerous miRNAs in colon cancer may have a functional effect on tumor cell behavior, and, furthermore, that some miRNAs with prognostic potential could be of clinical importance.

Monitoring endangered freshwater biodiversity using environmental DNA

Freshwater ecosystems are among the most endangered habitats on Earth, with thousands of animal species known to be threatened or already extinct. Reliable monitoring of threatened organisms is crucial for data-driven conservation actions but remains a challenge owing to nonstandardized methods that depend on practical and taxonomic expertise, which is rapidly declining. Here, we show that a diversity of rare and threatened freshwater animals--representing amphibians, fish, mammals, insects and crustaceans--can be detected and quantified based on DNA obtained directly from small water samples of lakes, ponds and streams. We successfully validate our findings in a controlled mesocosm experiment and show that DNA becomes undetectable within 2 weeks after removal of animals, indicating that DNA traces are near contemporary with presence of the species. We further demonstrate that entire faunas of amphibians and fish can be detected by high-throughput sequencing of DNA extracted from pond water. Our findings underpin the ubiquitous nature of DNA traces in the environment and establish environmental DNA as a tool for monitoring rare and threatened species across a wide range of taxonomic groups.

Long-term persistence of bacterial DNA

The persistence of bacterial DNA over geological timespans remains a contentious issue. In direct contrast to in vitro based predictions, bacterial DNA and even culturable cells have been reported from various ancient specimens many million years (Ma) old [1–8]. As both ancient DNA studies and the revival of microorganisms are known to be susceptible to contamination [8–10], it is concerning that these results have not been independently replicated to confirm their authenticity. Furthermore, they show no obvious relationship between sample age, and either bacterial composition or DNA persistence, although bacteria are known to differ markedly in hardiness and resistance to DNA degradation [11]. We present the first study of DNA durability and degradation of a broad variety of bacteria preserved under optimal frozen conditions, using rigorous ancient DNA methods [8–10]. The results demonstrate that nonspore-forming gram-positive (GP) Actinobacteria are by far the most durable, out-surviving endosporeformers such as Bacillaceae and Clostridiaceae. The observed DNA degradation rates are close to theoretical calculations [9], indicating a limit of ca. 400 thousand years (kyr) beyond which PCR amplifications are prevented by the formation of DNA interstrand crosslinks (ICLs). The twelve permafrost samples (0-8.1 Ma) investigated were obtained from northeast Siberia and Beacon Valley, Antarctica. DNA preservation at these sites is exceptional due to constant subzero temperatures, largely neutral pH, and anaerobic conditions. Epifluorescence microscopy revealed ~107cells/gram wetweight in the bacterial size range. The cell counts are in agreement with previous results obtained on permafrost [2,3]. 16S rDNA sequences of 120 bp and 600 bp could be reproducibly amplified from samples up to 400–600 kyr, and show an inverse relationship between PCR amplification efficiency and fragment length that is typical of ancient DNA [8–10,12]. Controls for surface contamination during sampling were negative. Chimeric sequences were excluded from analysis, along with sequences that failed a bootstrap test for independent reproducibility [13]. DNA concentrations and taxonomic diversity were found to decrease with age until 400–600 kyr, at which point the percentage of templates with ICLs reached 100% (Figure 1A–C). Sequences from the older samples appear to be a subset of those from younger material, and all identified bacterial taxa are known soil inhabitants, indicating that permafrost is a nonextremophile environment. There were clear age-related patterns in taxon survival across geographically widespread samples (separated up to 1400 km). Sequences of non-sporeforming GP Actinobacteria, affiliated largely to the genus Arthrobacter (99–100% similarity), consistently persisted for the longest time, followed by GP endospore-forming Bacillaceae and Clostridiaceae and finally gram-negative (GN) bacteria, mostly Proteobacteria (Figure 1D).

Common Variants at VRK2 and TCF4 Conferring Risk of Schizophrenia

Common sequence variants have recently joined rare structural polymorphisms as genetic factors with strong evidence for association with schizophrenia. Here we extend our previous genome-wide association study and meta-analysis (totalling 7 946 cases and 19 036 controls) by examining an expanded set of variants using an enlarged follow-up sample (up to 10 260 cases and 23 500 controls). In addition to previously reported alleles in the major histocompatibility complex region, near neurogranin (NRGN) and in an intron of transcription factor 4 (TCF4), we find two novel variants showing genome-wide significant association: rs2312147[C], upstream of vaccinia-related kinase 2 (VRK2) [odds ratio (OR) = 1.09, P = 1.9 × 10(-9)] and rs4309482[A], between coiled-coiled domain containing 68 (CCDC68) and TCF4, about 400 kb from the previously described risk allele, but not accounted for by its association (OR = 1.09, P = 7.8 × 10(-9)).

SOX4 expression in bladder carcinoma: clinical aspects and in vitro functional characterization.

The human transcription factor SOX4 was 5-fold up-regulated in bladder tumors compared with normal tissue based on whole-genome expression profiling of 166 clinical bladder tumor samples and 27 normal urothelium samples. Using a SOX4-specific antibody, we found that the cancer cells expressed the SOX4 protein and, thus, did an evaluation of SOX4 protein expression in 2,360 bladder tumors using a tissue microarray with clinical annotation. We found a correlation (P < 0.05) between strong SOX4 expression and increased patient survival. When overexpressed in the bladder cell line HU609, SOX4 strongly impaired cell viability and promoted apoptosis. To characterize downstream target genes and SOX4-induced pathways, we used a time-course global expression study of the overexpressed SOX4. Analysis of the microarray data showed 130 novel SOX4-related genes, some involved in signal transduction (MAP2K5), angiogenesis (NRP2), and cell cycle arrest (PIK3R3) and others with unknown functions (CGI-62). Among the genes regulated by SOX4, 25 contained at least one SOX4-binding motif in the promoter sequence, suggesting a direct binding of SOX4. The gene set identified in vitro was analyzed in the clinical bladder material and a small subset of the genes showed a high correlation to SOX4 expression. The present data suggest a role of SOX4 in the bladder cancer disease.

Comprehensive Genome Methylation Analysis in Bladder Cancer: Identification and Validation of Novel Methylated Genes and Application of These as Urinary Tumor Markers

Purpose: Epigenetic alterations are common and can now be addressed in a parallel fashion. We investigated the methylation in bladder cancer with respect to location in genome, consistency, variation in metachronous tumors, impact on transcripts, chromosomal location, and usefulness as urinary markers. Experimental Design: A microarray assay was utilized to analyze methylation in 56 samples. Independent validation was conducted in 63 samples by a PCR-based method and bisulfite sequencing. The methylation levels in 174 urine specimens were quantified. Transcript levels were analyzed using expression microarrays and pathways were analyzed using dedicated software. Results: Global methylation patterns were established within and outside CpG islands. We validated methylation of the eight tumor markers genes ZNF154 (P < 0.0001), HOXA9 (P < 0.0001), POU4F2 (P < 0.0001), EOMES (P = 0.0005), ACOT11 (P = 0.0001), PCDHGA12 (P = 0.0001), CA3 (P = 0.0002), and PTGDR (P = 0.0110), the candidate marker of disease progression TBX4 (P < 0.04), and other genes with stage-specific methylation. The methylation of metachronous tumors was stable and targeted to certain pathways. The correlation to expression was not stringent. Chromosome 21 showed most differential methylation (P < 0.0001) and specifically hypomethylation of keratins, which together with keratin-like proteins were epigenetically regulated. In DNA from voided urine, we detected differential methylation of ZNF154 (P < 0.0001), POU4F2 (P < 0.0001), HOXA9 (P < 0.0001), and EOMES (P < 0.0001), achieving 84% sensitivity and 96% specificity. Conclusions: We initiated a detailed mapping of the methylome in metachronous bladder cancer. Novel genes with tumor, chromosome, as well as pathway-specific differential methylation in bladder cancer were identified. The methylated genes were promising cancer markers for early detection of bladder cancer. Clin Cancer Res; 17(17); 5582–92. ©2011 AACR.

Challenges in microbial ecology: building predictive understanding of community function and dynamics

The importance of microbial communities (MCs) cannot be overstated. MCs underpin the biogeochemical cycles of the earth’s soil, oceans and the atmosphere, and perform ecosystem functions that impact plants, animals and humans. Yet our ability to predict and manage the function of these highly complex, dynamically changing communities is limited. Building predictive models that link MC composition to function is a key emerging challenge in microbial ecology. Here, we argue that addressing this challenge requires close coordination of experimental data collection and method development with mathematical model building. We discuss specific examples where model–experiment integration has already resulted in important insights into MC function and structure. We also highlight key research questions that still demand better integration of experiments and models. We argue that such integration is needed to achieve significant progress in our understanding of MC dynamics and function, and we make specific practical suggestions as to how this could be achieved.

Identification of endogenous retroviral reading frames in the human genome

BackgroundHuman endogenous retroviruses (HERVs) comprise a large class of repetitive retroelements. Most HERVs are ancient and invaded our genome at least 25 million years ago, except for the evolutionary young HERV-K group. The far majority of the encoded genes are degenerate due to mutational decay and only a few non-HERV-K loci are known to retain intact reading frames. Additional intact HERV genes may exist, since retroviral reading frames have not been systematically annotated on a genome-wide scale.ResultsBy clustering of hits from multiple BLAST searches using known retroviral sequences we have mapped 1.1% of the human genome as retrovirus related. The coding potential of all identified HERV regions were analyzed by annotating viral open reading frames (vORFs) and we report 7836 loci as verified by protein homology criteria. Among 59 intact or almost-intact viral polyproteins scattered around the human genome we have found 29 envelope genes including two novel gammaretroviral types. One encodes a protein similar to a recently discovered zebrafish retrovirus (ZFERV) while another shows partial, C-terminal, homology to Syncytin (HERV-W/FRD).ConclusionsThis compilation of HERV sequences and their coding potential provide a useful tool for pursuing functional analysis such as RNA expression profiling and effects of viral proteins, which may, in turn, reveal a role for HERVs in human health and disease. All data are publicly available through a database at http://www.retrosearch.dk.

Development of a Hypoxia Gene Expression Classifier with Predictive Impact for Hypoxic Modification of Radiotherapy in Head and Neck Cancer

Hypoxia, a common feature of the microenvironment in solid tumors, is associated with resistance to radiotherapy, reduced therapeutic response, and a poorer clinical outcome. In head and neck squamous cell carcinomas (HNSCC), the negative effect of hypoxia on radiotherapy can be counteracted via addition of hypoxic modification to the radiotherapy. To predict which patients harbor hypoxic tumors and would therefore benefit from hypoxic modification, clinically applicable methods for pretherapeutic hypoxic evaluation and categorization are needed. In this study, we developed a hypoxia classifier based on gene expression. Through study of xenograft tumors from human squamous cell carcinoma cell lines, we verified the in vivo relevance of previously identified in vitro derived hypoxia-induced genes. We then evaluated a training set of 58 hypoxia-evaluated HNSCCs to generate a gene expression classifier containing 15 genes. This 15-gene hypoxia classifier was validated in 323 patients with HNSCC randomized for hypoxic modification or placebo in combination with radiotherapy. Tumors categorized as hypoxic on the basis of the classifier were associated with a significantly poorer clinical outcome than nonhypoxic tumors. This outcome was improved and equalized to the nonhypoxic tumors by addition of hypoxic modification. Thus, findings show that the classifier attained both prognostic and predictive impact, and its pretherapeutic use may provide a method to identify those patients who will benefit from hypoxic modification of radiotherapy.