Rapid antigen testing for SARS-CoV-2 by lateral flow assay: A field evaluation of self- and professional testing at UK community testing sites

BACKGROUND

The advent of lateral flow devices (LFDs) for SARS-CoV-2 detection enabled widespread use of rapid self-tests during the pandemic. While self-testing using LFDs is now common, whether self-testing provides comparable performance to professional testing was a key question that remained important for pandemic planning.

METHODS

Three prospective multi-centre studies were conducted to compare the performance of self- and professional testing using LFDs. Participants tested themselves or were tested by trained (professional) testers at community testing sites in the UK. Corresponding qRT-PCR test results served as reference standard. The performance of Innova, Orient Gene and SureScreen LFDs by users (self) and professional testers was assessed in terms of sensitivity, specificity, and kit failure (void) rates. Impact of age, sex and symptom status was analysed using logistic regression modelling.

RESULTS

16,617 participants provided paired tests, of which 15,418 were included in the analysis. Self-testing with Innova, Orient Gene or SureScreen LFDs achieved sensitivities of 50 %, 53 % or 72 %, respectively, compared to qRT-PCR. Self and professional LFD testing showed no statistically different sensitivity with respect to corresponding qRT-PCR testing. Specificity was consistently equal to or higher than 99 %. Sex and age had no or only marginal impact on LFD performance while sensitivity was significantly higher for symptomatic individuals. Sensitivity of LFDs increased strongly to up to 90 % with higher levels of viral RNA measured by qRT-PCR.

CONCLUSIONS

Our results support SARS-CoV-2 self-testing with LFDs, especially for the detection of individuals whose qRT-PCR tests showed high viral concentrations.

Faster detection of asymptomatic COVID-19 cases among care home staff in England through the combination of SARS-CoV-2 testing technologies

To detect SARS-CoV-2 amongst asymptomatic care home staff in England, a dual-technology weekly testing regime was introduced on 23 December 2020. A lateral flow device (LFD) and quantitative reverse transcription polymerase chain reaction (qRT-PCR) test were taken on the same day (day 0) and a midweek LFD test was taken three to four days later. We evaluated the effectiveness of using dual-technology to detect SARS-CoV-2 between December 2020 to April 2021. Viral concentrations derived from qRT-PCR were used to determine the probable stage of infection and likely level of infectiousness. Day 0 PCR detected 1,493 cases of COVID-19, of which 53% were in the early stages of infection with little to no risk of transmission. Day 0 LFD detected 83% of cases that were highly likely to be infectious. On average, LFD results were received 46.3 h earlier than PCR, enabling removal of likely infectious staff from the workplace quicker than by weekly PCR alone. Demonstrating the rapidity of LFDs to detect highly infectious cases could be combined with the ability of PCR to detect cases in the very early stages of infection. In practice, asymptomatic care home staff were removed from the workplace earlier, breaking potential chains of transmission.

Ribogenesis boosts controlled by HEATR1-MYC interplay promote transition into brain tumour growth

Cell commitment to tumourigenesis and the onset of uncontrolled growth are critical determinants in cancer development but the early events directing tumour initiating cell (TIC) fate remain unclear. We reveal a single-cell transcriptome profile of brain TICs transitioning into tumour growth using the brain tumour (brat) neural stem cell-based Drosophila model. Prominent changes in metabolic and proteostasis-associated processes including ribogenesis are identified. Increased ribogenesis is a known cell adaptation in established tumours. Here we propose that brain TICs boost ribogenesis prior to tumour growth. In brat-deficient TICs, we show that this dramatic change is mediated by upregulated HEAT-Repeat Containing 1 (HEATR1) to promote ribosomal RNA generation, TIC enlargement and onset of overgrowth. High HEATR1 expression correlates with poor glioma patient survival and patient-derived glioblastoma stem cells rely on HEATR1 for enhanced ribogenesis and tumourigenic potential. Finally, we show that HEATR1 binds the master growth regulator MYC, promotes its nucleolar localisation and appears required for MYC-driven ribogenesis, suggesting a mechanism co-opted in ribogenesis reprogramming during early brain TIC development.

Swab pooling enables rapid expansion of high-throughput capacity for SARS-CoV-2 community testing

BACKGROUND

The challenges of rapid upscaling of testing capacity were a major lesson from the COVID-19 pandemic response. The need for process adjustments in high-throughput testing laboratories made sample pooling a challenging option to implement.

OBJECTIVE

This study aimed to evaluate whether pooling samples at source (swab pooling) was as effective as qRT-PCR testing of individuals in identifying cases of SARS-CoV-2 in real-world community testing conditions using the same high-throughput pipeline.

METHODS

Two cohorts of 10 (Pool10: 1,030 participants and 103 pools) and 6 (Pool6: 1,284 participants and 214 pools) samples per pool were tested for concordance, sensitivity, specificity, and Ct value differences with individual testing as reference.

RESULTS

Swab pooling allowed unmodified application of an existing high-throughput SARS-Cov-2 testing pipeline with only marginal loss of accuracy. For Pool10, concordance was 98.1% (95% Confidence interval: 93.3-99.8%), sensitivity was 95.7% (85.5-99.5%), and specificity was 100.0% (93.6-100.0%). For Pool6, concordance was 97.2% (94.0-99.0%), sensitivity was 97.5% (93.7-99.3%), and specificity was 96.4% (87.7-99.6%). Differences of outcomes measure between pool size were not significant. Most positive individual samples, which were not detected in pools, had very low viral concentration. If only individual samples with a viral concentration > 400 copies/ml (i.e. Ct value < 30) were considered positive, the overall sensitivity of pooling increased to 99.5%.

CONCLUSION

The study demonstrated high sensitivity and specificity by swab pooling and the immediate capability of high-throughput laboratories to implement this method making it an option in planning of rapid upscaling of laboratory capacity for future pandemics.

Loss of H3K9 trimethylation alters chromosome compaction and transcription factor retention during mitosis

Recent studies have shown that repressive chromatin machinery, including DNA methyltransferases and polycomb repressor complexes, binds to chromosomes throughout mitosis and their depletion results in increased chromosome size. In the present study, we show that enzymes that catalyze H3K9 methylation, such as Suv39h1, Suv39h2, G9a and Glp, are also retained on mitotic chromosomes. Surprisingly, however, mutants lacking histone 3 lysine 9 trimethylation (H3K9me3) have unusually small and compact mitotic chromosomes associated with increased histone H3 phospho Ser10 (H3S10ph) and H3K27me3 levels. Chromosome size and centromere compaction in these mutants were rescued by providing exogenous first protein lysine methyltransferase Suv39h1 or inhibiting Ezh2 activity. Quantitative proteomic comparisons of native mitotic chromosomes isolated from wild-type versus Suv39h1/Suv39h2 double-null mouse embryonic stem cells revealed that H3K9me3 was essential for the efficient retention of bookmarking factors such as Esrrb. These results highlight an unexpected role for repressive heterochromatin domains in preserving transcription factor binding through mitosis and underscore the importance of H3K9me3 for sustaining chromosome architecture and epigenetic memory during cell division.

Integration of Stemness Gene Signatures Reveals Core Functional Modules of Stem Cells and Potential Novel Stemness Genes

Stem cells encompass a variety of different cell types which converge on the dual capacity to self-renew and differentiate into one or more lineages. These characteristic features are key for the involvement of stem cells in crucial biological processes such as development and ageing. To decipher their underlying genetic substrate, it is important to identify so-called stemness genes that are common to different stem cell types and are consistently identified across different studies. In this meta-analysis, 21 individual stemness signatures for humans and another 21 for mice, obtained from a variety of stem cell types and experimental techniques, were compared. Although we observed biological and experimental variability, a highly significant overlap between gene signatures was identified. This enabled us to define integrated stemness signatures (ISSs) comprised of genes frequently occurring among individual stemness signatures. Such integrated signatures help to exclude false positives that can compromise individual studies and can provide a more robust basis for investigation. To gain further insights into the relevance of ISSs, their genes were functionally annotated and connected within a molecular interaction network. Most importantly, the present analysis points to the potential roles of several less well-studied genes in stemness and thus provides promising candidates for further experimental validation.

CCBE1 Is Essential for Epicardial Function during Myocardium Development

The epicardium is a single cell layer of mesothelial cells that plays a critical role during heart development contributing to different cardiac cell types of the developing heart through epithelial-to-mesenchymal transition (EMT). Moreover, the epicardium is a source of secreted growth factors that promote myocardial growth. CCBE1 is a secreted extracellular matrix protein expressed by epicardial cells that is required for the formation of the primitive coronary plexus. However, the role of CCBE1 during epicardial development was still unknown. Here, using a Ccbe1 knockout (KO) mouse model, we observed that loss of CCBE1 leads to congenital heart defects including thinner and hyper-trabeculated ventricular myocardium. In addition, Ccbe1 mutant hearts displayed reduced proliferation of cardiomyocyte and epicardial cells. Epicardial outgrowth culture assay to assess epicardial-derived cells (EPDC) migration showed reduced invasion of the collagen gel by EPDCs in Ccbe1 KO epicardial explants. Ccbe1 KO hearts also displayed fewer nonmyocyte/nonendothelial cells intramyocardially with a reduced proliferation rate. Additionally, RNA-seq data and experimental validation by qRT-PCR showed a marked deregulation of EMT-related genes in developing Ccbe1 mutant hearts. Together, these findings indicate that the myocardium defects in Ccbe1 KO mice arise from disruption of epicardial development and function.

The Gene Regulation Knowledge Commons: The action area of GREEKC

The COST Action Gene Regulation Ensemble Effort for the Knowledge Commons (GREEKC, CA15205, www.greekc.org) organized nine workshops in a four-year period, starting September 2016. The workshops brought together a wide range of experts from all over the world working on various parts of the knowledge cycle that is central to understanding gene regulatory mechanisms. The discussions between ontologists, curators, text miners, biologists, bioinformaticians, philosophers and computational scientists spawned a host of activities aimed to update and standardise existing knowledge management workflows, encourage new experimental approaches and thoroughly involve end-users in the process to design the Gene Regulation Knowledge Commons (GRKC). The GREEKC consortium describes its main achievements, contextualised in a state-of-the-art of current tools and resources that today represent the GRKC.

Genome-wide identification and characterization of Fur-binding sites in the cyanobacteria Synechocystis sp. PCC 6803 and PCC 6714

The Ferric uptake regulator (Fur) is crucial to both pathogenic and non-pathogenic bacteria for the maintenance of iron homeostasis as well as the defence against reactive oxygen species. Based on datasets from the genome-wide mapping of transcriptional start sites and transcriptome data, we identified a high confidence regulon controlled by Fur for the model cyanobacterium Synechocystis sp. PCC 6803 and its close relative, strain 6714, based on the conserved strong iron starvation response and Fur-binding site occurrence. This regulon comprises 33 protein-coding genes and the sRNA IsaR1 that are under the control of 16 or 14 individual promoters in strains 6803 and 6714, respectively. The associated gene functions are mostly restricted to transporters and enzymes involved in the uptake and storage of iron ions, with few exceptions or unknown functional relevance. Within the isiABC operon, we identified a previously neglected gene encoding a small cysteine-rich protein, which we suggest calling, IsiE. The regulation of iron uptake, storage, and utilization ultimately results from the interplay between the Fur regulon, several other transcription factors, the FtsH3 protease, and the sRNA IsaR1.

DAND5 Inactivation Enhances Cardiac Differentiation in Mouse Embryonic Stem Cells

Deciphering the clues of a regenerative mechanism for the mammalian adult heart would save millions of lives in the near future. Heart failure due to cardiomyocyte loss is still one of the significant health burdens worldwide. Here, we show the potential of a single molecule, DAND5, in mouse pluripotent stem cell-derived cardiomyocytes specification and proliferation. Dand5 loss-of-function generated the double of cardiac beating foci compared to the wild-type cells. The early formation of cardiac progenitor cells and the increased proliferative capacity of Dand5 KO mESC-derived cardiomyocytes contribute to the observed higher number of derived cardiac cells. Transcriptional profiling sequencing and quantitative RT-PCR assays showed an upregulation of early cardiac gene networks governing cardiomyocyte differentiation, cell cycling, and cardiac regenerative pathways but reduced levels of genes involved in cardiomyocyte maturation. These findings prompt DAND5 as a key driver for the generation and expansion of pluripotent stem cell-derived cardiomyocytes systems with further clinical application purposes.

Integration and Comparison of Transcriptomic and Proteomic Data for Meningioma

Meningioma are the most frequent primary intracranial tumour. Management of aggressive meningioma is complex, and development of effective biomarkers or pharmacological interventions is hampered by an incomplete knowledge of molecular landscape. Here, we present an integrated analysis of two complementary omics studies to investigate alterations in the "transcriptome-proteome" profile of high-grade (III) compared to low-grade (I) meningiomas. We identified 3598 common transcripts/proteins and revealed concordant up- and downregulation in grade III vs. grade I meningiomas. Concordantly upregulated genes included FABP7, a fatty acid binding protein and the monoamine oxidase MAOB, the latter of which we validated at the protein level and established an association with Food and Drug Administration (FDA)-approved drugs. Notably, we derived a plasma signature of 21 discordantly expressed genes showing positive changes in protein but negative in transcript levels of high-grade meningiomas, including the validated genes CST3, LAMP2, PACS1 and HTRA1, suggesting the acquisition of these proteins by tumour from plasma. Aggressive meningiomas were enriched in processes such as oxidative phosphorylation and RNA metabolism, whilst concordantly downregulated genes were related to reduced cellular adhesion. Overall, our study provides the first transcriptome-proteome characterisation of meningioma, identifying several novel and previously described transcripts/proteins with potential grade III biomarker and therapeutic significance.

Depletion of the FtsH1/3 Proteolytic Complex Suppresses the Nutrient Stress Response in the Cyanobacterium Synechocystis sp strain PCC 6803

The membrane-embedded FtsH proteases found in bacteria, chloroplasts, and mitochondria are involved in diverse cellular processes including protein quality control and regulation. The genome of the model cyanobacterium Synechocystis sp PCC 6803 encodes four FtsH homologs designated FtsH1 to FtsH4. The FtsH3 homolog is present in two hetero-oligomeric complexes: FtsH2/3, which is responsible for photosystem II quality control, and the essential FtsH1/3 complex, which helps maintain Fe homeostasis by regulating the level of the transcription factor Fur. To gain a more comprehensive insight into the physiological roles of FtsH hetero-complexes, we performed genome-wide expression profiling and global proteomic analyses of Synechocystis mutants conditionally depleted of FtsH3 or FtsH1 grown under various nutrient conditions. We show that the lack of FtsH1/3 leads to a drastic reduction in the transcriptional response to nutrient stress of not only Fur but also the Pho, NdhR, and NtcA regulons. In addition, this effect is accompanied by the accumulation of the respective transcription factors. Thus, the FtsH1/3 complex is of critical importance for acclimation to iron, phosphate, carbon, and nitrogen starvation in Synechocystis.plantcell;31/12/2912/FX1F1fx1.

StemMapper: a curated gene expression database for stem cell lineage analysis

Transcriptomic data have become a fundamental resource for stem cell (SC) biologists as well as for a wider research audience studying SC-related processes such as aging, embryonic development and prevalent diseases including cancer, diabetes and neurodegenerative diseases. Access and analysis of the growing amount of freely available transcriptomics datasets for SCs, however, are not trivial tasks. Here, we present StemMapper, a manually curated gene expression database and comprehensive resource for SC research, built on integrated data for different lineages of human and mouse SCs. It is based on careful selection, standardized processing and stringent quality control of relevant transcriptomics datasets to minimize artefacts, and includes currently over 960 transcriptomes covering a broad range of SC types. Each of the integrated datasets was individually inspected and manually curated. StemMapper's user-friendly interface enables fast querying, comparison, and interactive visualization of quality-controlled SC gene expression data in a comprehensive manner. A proof-of-principle analysis discovering novel putative astrocyte/neural SC lineage markers exemplifies the utility of the integrated data resource. We believe that StemMapper can open the way for new insights and advances in SC research by greatly simplifying the access and analysis of SC transcriptomic data. StemMapper is freely accessible at http://stemmapper.sysbiolab.eu.

Exogenous WNT5A and WNT11 proteins rescue CITED2 dysfunction in mouse embryonic stem cells and zebrafish morphants

Mutations and inadequate methylation profiles of CITED2 are associated with human congenital heart disease (CHD). In mouse, Cited2 is necessary for embryogenesis, particularly for heart development, and its depletion in embryonic stem cells (ESC) impairs cardiac differentiation. We have now determined that Cited2 depletion in ESC affects the expression of transcription factors and cardiopoietic genes involved in early mesoderm and cardiac specification. Interestingly, the supplementation of the secretome prepared from ESC overexpressing CITED2, during the onset of differentiation, rescued the cardiogenic defects of Cited2-depleted ESC. In addition, we demonstrate that the proteins WNT5A and WNT11 held the potential for rescue. We also validated the zebrafish as a model to investigate cited2 function during development. Indeed, the microinjection of morpholinos targeting cited2 transcripts caused developmental defects recapitulating those of mice knockout models, including the increased propensity for cardiac defects and severe death rate. Importantly, the co-injection of anti-cited2 morpholinos with either CITED2 or WNT5A and WNT11 recombinant proteins corrected the developmental defects of Cited2-morphants. This study argues that defects caused by the dysfunction of Cited2 at early stages of development, including heart anomalies, may be remediable by supplementation of exogenous molecules, offering the opportunity to develop novel therapeutic strategies aiming to prevent CHD.

ChIP-seq Experiment and Data Analysis in the Cyanobacterium Synechocystis sp. PCC 6803

Nitrogen is an essential nutrient for all living organisms. In cyanobacteria, a group of oxygenic photosynthetic bacteria, nitrogen homeostasis is maintained by an intricate regulatory network around the transcription factor NtcA. Although mechanisms controlling NtcA activity appear to be well understood, the sets of genes under its control (i.e., its regulon) remain poorly defined. In this protocol, we describe the procedure for chromatin immunoprecipitation using NtcA antibodies, followed by DNA sequencing analysis (ChIP-seq) during early acclimation to nitrogen starvation in the cyanobacterium Synechocystis sp. PCC 6803 (hereafter Synechocystis). This protocol can be extended to analyze any DNA-binding protein in cyanobacteria for which suitable antibodies exist.

Parallel Genome-wide Profiling of Coding and Non-coding RNAs to Identify Novel Regulatory Elements in Embryonic and Maturated Heart

Heart development is a complex process, tightly regulated by numerous molecular mechanisms. Key components of the regulatory network underlying heart development are transcription factors (TFs) and microRNAs (miRNAs), yet limited investigation of the role of miRNAs in heart development has taken place. Here, we report the first parallel genome-wide profiling of polyadenylated RNAs and miRNAs in a developing murine heart. These data enable us to identify dynamic activation or repression of numerous biological processes and signaling pathways. More than 200 miRNAs and 25 long non-coding RNAs were differentially expressed during embryonic heart development compared to the mature heart; most of these had not been previously associated with cardiogenesis. Integrative analysis of expression data and potential regulatory interactions suggested 28 miRNAs as novel regulators of embryonic heart development, representing a considerable expansion of the current repertoire of known cardiac miRNAs. To facilitate follow-up investigations, we constructed HeartMiR (http://heartmir.sysbiolab.eu), an open access database and interactive visualization tool for the study of gene regulation by miRNAs during heart development.

Identification of the direct regulon of NtcA during early acclimation to nitrogen starvation in the cyanobacterium Synechocystis sp. PCC 6803

In cyanobacteria, nitrogen homeostasis is maintained by an intricate regulatory network around transcription factor NtcA. Although mechanisms controlling NtcA activity appear to be well understood, its regulon remains poorly defined. To determine the NtcA regulon during the early stages of nitrogen starvation for the model cyanobacterium Synechocystis sp. PCC 6803, we performed chromatin immunoprecipitation, followed by sequencing (ChIP-seq), in parallel with transcriptome analysis (RNA-seq). Through combining these methods, we determined 51 genes activated and 28 repressed directly by NtcA. In addition to genes associated with nitrogen and carbon metabolism, a considerable number of genes without current functional annotation were among direct targets providing a rich reservoir for further studies. The NtcA regulon also included eight non-coding RNAs, of which Ncr1071, Syr6 and NsiR7 were experimentally validated, and their putative targets were computationally predicted. Surprisingly, we found substantial NtcA binding associated with delayed expression changes indicating that NtcA can reside in a poised state controlled by other factors. Indeed, a role of PipX as modulating factor in nitrogen regulation was confirmed for selected NtcA-targets. We suggest that the indicated poised state of NtcA enables a more differentiated response to nitrogen limitation and can be advantageous in native habitats of Synechocystis.

HDNetDB: A Molecular Interaction Database for Network-Oriented Investigations into Huntington's Disease

Huntington’s disease (HD) is a progressive and fatal neurodegenerative disorder caused by an expanded CAG repeat in the huntingtin gene. Although HD is monogenic, its molecular manifestation appears highly complex and involves multiple cellular processes. The recent application of high throughput platforms such as microarrays and mass-spectrometry has indicated multiple pathogenic routes. The massive data generated by these techniques together with the complexity of the pathogenesis, however, pose considerable challenges to researchers. Network-based methods can provide valuable tools to consolidate newly generated data with existing knowledge, and to decipher the interwoven molecular mechanisms underlying HD. To facilitate research on HD in a network-oriented manner, we have developed HDNetDB, a database that integrates molecular interactions with many HD-relevant datasets. It allows users to obtain, visualize and prioritize molecular interaction networks using HD-relevant gene expression, phenotypic and other types of data obtained from human samples or model organisms. We illustrated several HDNetDB functionalities through a case study and identified proteins that constitute potential cross-talk between HD and the unfolded protein response (UPR). HDNetDB is publicly accessible at http://hdnetdb.sysbiolab.eu.

Acclimation of Oxygenic Photosynthesis to Iron Starvation Is Controlled by the sRNA IsaR1

Oxygenic photosynthesis crucially depends on proteins that possess Fe²⁺ or Fe/S complexes as co-factors or prosthetic groups. Here, we show that the small regulatory RNA (sRNA) IsaR1 (Iron-Stress-Activated RNA 1) plays a pivotal role in acclimation to low-iron conditions. The IsaR1 regulon consists of more than 15 direct targets, including Fe²⁺-containing proteins involved in photosynthetic electron transfer, detoxification of anion radicals, citrate cycle, and tetrapyrrole biogenesis. IsaR1 is essential for maintaining physiological levels of Fe/S cluster biogenesis proteins during iron deprivation. Consequently, IsaR1 affects the acclimation of the photosynthetic apparatus to iron starvation at three levels: (1) directly, via posttranscriptional repression of gene expression; (2) indirectly, via suppression of pigment; and (3) Fe/S cluster biosynthesis. Homologs of IsaR1 are widely conserved throughout the cyanobacterial phylum. We conclude that IsaR1 is a critically important riboregulator. These findings provide a new perspective for understanding the regulation of iron homeostasis in photosynthetic organisms.

Membrane-enriched proteome changes and prion protein expression during neural differentiation and in neuroblastoma cells

Background

The function of the prion protein, involved in the so-called prion diseases, remains a subject of intense debate and the possibility that it works as a pleiotropic protein through the interaction with multiple membrane proteins is somehow supported by recent reports. Therefore, the use of proteomic and bioinformatics combined to uncover cellular processes occurring together with changes in the expression of the prion protein may provide further insight into the putative pleiotropic role of the prion protein.

Results

This study assessed the membrane-enriched proteome changes accompanying alterations in the expression of the prion protein. A 2D-DIGE approach was applied to two cell lines after prefractionation towards the membrane protein subset: an embryonic stem cell line and the PK1 subline of neuroblastoma cells which efficiently propagates prion infection. Several proteins were differentially abundant with the increased expression of the prion protein during neural differentiation of embryonic stem cells and with the knockdown of the prion protein in PK1 cells. The identity of around 20% of the differentially abundant proteins was obtained by tandem MS. The catalytic subunit A of succinate dehydrogenase, a key enzyme for the aerobic energy metabolism and redox homeostasis, showed a similar abundance trend as the prion protein in both proteomic experiments. A gene ontology analysis revealed “myelin sheath”, “organelle membrane” and “focal adhesion” associated proteins as the main cellular components, and “protein folding” and “ATPase activity” as the biological processes enriched in the first set of differentially abundant proteins. The known interactome of these differentially abundant proteins was customized to reveal four interactors with the prion protein, including two heat shock proteins and a protein disulfide isomerase.

Conclusions

Overall, our study shows that expression of the prion protein occurs concomitantly with changes in chaperone activity and cell-redox homeostasis, emphasizing the functional link between these cellular processes and the prion protein.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-3694-6) contains supplementary material, which is available to authorized users.

Extracellular Proteins: Novel Key Components of Metal Resistance in Cyanobacteria?

Metals are essential for all living organisms and required for fundamental biochemical processes. However, when in excess, metals can turn into highly-toxic agents able to disrupt cell membranes, alter enzymatic activities, and damage DNA. Metal concentrations are therefore tightly controlled inside cells, particularly in cyanobacteria. Cyanobacteria are ecologically relevant prokaryotes that perform oxygenic photosynthesis and can be found in many different marine and freshwater ecosystems, including environments contaminated with heavy metals. As their photosynthetic machinery imposes high demands for metals, homeostasis of these micronutrients has been widely studied in cyanobacteria. So far, most studies have focused on how cells are capable of controlling their internal metal pools, with a strong bias toward the analysis of intracellular processes. Ultrastructure, modulation of physiology, dynamic changes in transcription and protein levels have been studied, but what takes place in the extracellular environment when cells are exposed to an unbalanced metal availability remains largely unknown. The interest in studying the subset of proteins present in the extracellular space has only recently begun and the identification and functional analysis of the cyanobacterial exoproteomes are just emerging. Remarkably, metal-related proteins such as the copper-chaperone CopM or the iron-binding protein FutA2 have already been identified outside the cell. With this perspective, we aim to raise the awareness that metal-resistance mechanisms are not yet fully known and hope to motivate future studies assessing the role of extracellular proteins on bacterial metal homeostasis, with a special focus on cyanobacteria.

The Transcriptional Landscape of the Photosynthetic Model Cyanobacterium Synechocystis sp. PCC6803

Cyanobacteria exhibit a great capacity to adapt to different environmental conditions through changes in gene expression. Although this plasticity has been extensively studied in the model cyanobacterium Synechocystis sp. PCC 6803, a detailed analysis of the coordinated transcriptional adaption across varying conditions is lacking. Here, we report a meta-analysis of 756 individual microarray measurements conducted in 37 independent studies-the most comprehensive study of the Synechocystis transcriptome to date. Using stringent statistical evaluation, we characterized the coordinated adaptation of Synechocystis' gene expression on systems level. Evaluation of the data revealed that the photosynthetic apparatus is subjected to greater changes in expression than other cellular components. Nevertheless, network analyses indicated a significant degree of transcriptional coordination of photosynthesis and various metabolic processes, and revealed the tight co-regulation of components of photosystems I, II and phycobilisomes. Detailed inspection of the integrated data led to the discovery a variety of regulatory patterns and novel putative photosynthetic genes. Intriguingly, global clustering analyses suggested contrasting transcriptional response of metabolic and regulatory genes stress to conditions. The integrated Synechocystis transcriptome can be accessed and interactively analyzed via the CyanoEXpress website (http://cyanoexpress.sysbiolab.eu).

Systematic interaction network filtering identifies CRMP1 as a novel suppressor of huntingtin misfolding and neurotoxicity

Assemblies of huntingtin (HTT) fragments with expanded polyglutamine (polyQ) tracts are a pathological hallmark of Huntington's disease (HD). The molecular mechanisms by which these structures are formed and cause neuronal dysfunction and toxicity are poorly understood. Here, we utilized available gene expression data sets of selected brain regions of HD patients and controls for systematic interaction network filtering in order to predict disease-relevant, brain region-specific HTT interaction partners. Starting from a large protein-protein interaction (PPI) data set, a step-by-step computational filtering strategy facilitated the generation of a focused PPI network that directly or indirectly connects 13 proteins potentially dysregulated in HD with the disease protein HTT. This network enabled the discovery of the neuron-specific protein CRMP1 that targets aggregation-prone, N-terminal HTT fragments and suppresses their spontaneous self-assembly into proteotoxic structures in various models of HD. Experimental validation indicates that our network filtering procedure provides a simple but powerful strategy to identify disease-relevant proteins that influence misfolding and aggregation of polyQ disease proteins.

Identification of novel biomarkers in chronic immune thrombocytopenia (ITP) by microarray-based serum protein profiling

The pathological mechanisms underlying the development of immune thrombocytopenia (ITP) are unclear and its diagnosis remains a process of exclusion. Currently, there are no known specific biomarkers for ITP to support differential diagnosis and treatment decisions. Profiling of serum proteins may be valuable for identifying such biomarkers. Sera from 46 patients with primary chronic ITP and 34 healthy blood donors were analysed using a microarray of 755 antibodies. We identified 161 differentially expressed proteins. In addition to oncoproteins and tumour-suppressor proteins, including apoptosis regulator BCL2, breast cancer type 1 susceptibility protein (BRCA1), Fanconi anaemia complementation group C (FANCC) and vascular endothelial growth factor A (VEGFA), we detected six anti-nuclear autoantibodies in a subset of ITP patients: anti-PCNA, anti-SmD, anti-Ro/SSA60, anti-Ro/SSA52, anti-La/SSB and anti-RNPC antibodies. This finding may provide a rational explanation for the association of ITP with malignancies and other autoimmune diseases. While RUNX1mRNA expression in the peripheral blood mononuclear cells (PBMC) of patients was significantly downregulated, an accumulation of RUNX1 protein was observed in the platelets of ITP patients. This may indicate dysregulation of RUNX1 expression in PBMC and megakaryocytes and may lead to an imbalanced immune response and impaired thrombopoiesis. In conclusion, we provide novel insights into the pathogenic mechanisms of ITP that warrant further exploration.

Novel Human Embryonic Stem Cell Regulators Identified by Conserved and Distinct CpG Island Methylation State

Human embryonic stem cells (hESCs) undergo epigenetic changes in vitro which may compromise function, so an epigenetic pluripotency “signature” would be invaluable for line validation. We assessed Cytosine-phosphate-Guanine Island (CGI) methylation in hESCs by genomic DNA hybridisation to a CGI array, and saw substantial variation in CGI methylation between lines. Comparison of hESC CGI methylation profiles to corresponding somatic tissue data and hESC mRNA expression profiles identified a conserved hESC-specific methylation pattern associated with expressed genes. Transcriptional repressors and activators were over-represented amongst genes whose associated CGIs were methylated or unmethylated specifically in hESCs, respectively. Knockdown of candidate transcriptional regulators (HMGA1, GLIS2, PFDN5) induced differentiation in hESCs, whereas ectopic expression in fibroblasts modulated iPSC colony formation. Chromatin immunoprecipitation confirmed interaction between the candidates and the core pluripotency transcription factor network. We thus identify novel pluripotency genes on the basis of a conserved and distinct epigenetic configuration in human stem cells.

StemChecker: a web-based tool to discover and explore stemness signatures in gene sets

Stem cells present unique regenerative abilities, offering great potential for treatment of prevalent pathologies such as diabetes, neurodegenerative and heart diseases. Various research groups dedicated significant effort to identify sets of genes—so-called stemness signatures—considered essential to define stem cells. However, their usage has been hindered by the lack of comprehensive resources and easy-to-use tools. For this we developed StemChecker, a novel stemness analysis tool, based on the curation of nearly fifty published stemness signatures defined by gene expression, RNAi screens, Transcription Factor (TF) binding sites, literature reviews and computational approaches. StemChecker allows researchers to explore the presence of stemness signatures in user-defined gene sets, without carrying-out lengthy literature curation or data processing. To assist in exploring underlying regulatory mechanisms, we collected over 80 target gene sets of TFs associated with pluri- or multipotency. StemChecker presents an intuitive graphical display, as well as detailed statistical results in table format, which helps revealing transcriptionally regulatory programs, indicating the putative involvement of stemness-associated processes in diseases like cancer. Overall, StemChecker substantially expands the available repertoire of online tools, designed to assist the stem cell biology, developmental biology, regenerative medicine and human disease research community. StemChecker is freely accessible at http://stemchecker.sysbiolab.eu.

The unfolded protein response and its potential role in Huntington's disease elucidated by a systems biology approach

Huntington ´s disease (HD) is a progressive, neurodegenerative disease with a fatal outcome. Although the disease-causing gene (huntingtin) has been known for over 20 years, the exact mechanisms leading to neuronal cell death are still controversial. One potential mechanism contributing to the massive loss of neurons observed in the brain of HD patients could be the unfolded protein response (UPR) activated by accumulation of misfolded proteins in the endoplasmic reticulum (ER). As an adaptive response to counter-balance accumulation of un- or misfolded proteins, the UPR upregulates transcription of chaperones, temporarily attenuates new translation, and activates protein degradation via the proteasome. However, persistent ER stress and an activated UPR can also cause apoptotic cell death. Although different studies have indicated a role for the UPR in HD, the evidence remains inconclusive. Here, we present extensive bioinformatic analyses that revealed UPR activation in different experimental HD models based on transcriptomic data. Accordingly, we have identified 53 genes, including RAB5A, HMGB1, CTNNB1, DNM1, TUBB, TSG101, EEF2, DYNC1H1, SLC12A5, ATG5, AKT1, CASP7 and SYVN1 that provide a potential link between UPR and HD. To further elucidate the potential role of UPR as a disease-relevant process, we examined its connection to apoptosis based on molecular interaction data, and identified a set of 40 genes including ADD1, HSP90B1, IKBKB, IKBKG, RPS3A and LMNB1, which seem to be at the crossroads between these two important cellular processes. Remarkably, we also found strong correlation of UPR gene expression with the length of the polyglutamine tract of Huntingtin, which is a critical determinant of age of disease onset in human HD patients pointing to the UPR as a promising target for therapeutic intervention. The study is complemented by a newly developed web-portal called UPR-HD (http://uprhd.sysbiolab.eu) that enables visualization and interactive analysis of UPR-associated gene expression across various HD models.

The unfolded protein response and its potential role in Huntington's disease elucidated by a systems biology approach

Huntington ´s disease (HD) is a progressive, neurodegenerative disease with a fatal outcome. Although the disease-causing gene (huntingtin) has been known for over 20 years, the exact mechanisms leading to neuronal cell death are still controversial. One potential mechanism contributing to the massive loss of neurons observed in the brain of HD patients could be the unfolded protein response (UPR) activated by accumulation of misfolded proteins in the endoplasmic reticulum (ER). As an adaptive response to counter-balance accumulation of un- or misfolded proteins, the UPR upregulates transcription of chaperones, temporarily attenuates new translation, and activates protein degradation via the proteasome. However, persistent ER stress and an activated UPR can also cause apoptotic cell death. Although different studies have indicated a role for the UPR in HD, the evidence remains inconclusive. Here, we present extensive bioinformatic analyses that revealed UPR activation in different experimental HD models based on transcriptomic data. Accordingly, we have identified 53 genes, including RAB5A, HMGB1, CTNNB1, DNM1, TUBB, TSG101, EEF2, DYNC1H1, SLC12A5, ATG5, AKT1, CASP7 and SYVN1 that provide a potential link between UPR and HD. To further elucidate the potential role of UPR as a disease-relevant process, we examined its connection to apoptosis based on molecular interaction data, and identified a set of 40 genes including ADD1, HSP90B1, IKBKB, IKBKG, RPS3A and LMNB1, which seem to be at the crossroads between these two important cellular processes. Remarkably, we also found strong correlation of UPR gene expression with the length of the polyglutamine tract of Huntingtin, which is a critical determinant of age of disease onset in human HD patients pointing to the UPR as a promising target for therapeutic intervention. The study is complemented by a newly developed web-portal called UPR-HD (http://uprhd.sysbiolab.eu) that enables visualization and interactive analysis of UPR-associated gene expression across various HD models.

Toward a systems-level understanding of gene regulatory, protein interaction, and metabolic networks in cyanobacteria

Cyanobacteria are essential primary producers in marine ecosystems, playing an important role in both carbon and nitrogen cycles. In the last decade, various genome sequencing and metagenomic projects have generated large amounts of genetic data for cyanobacteria. This wealth of data provides researchers with a new basis for the study of molecular adaptation, ecology and evolution of cyanobacteria, as well as for developing biotechnological applications. It also facilitates the use of multiplex techniques, i.e., expression profiling by high-throughput technologies such as microarrays, RNA-seq, and proteomics. However, exploration and analysis of these data is challenging, and often requires advanced computational methods. Also, they need to be integrated into our existing framework of knowledge to use them to draw reliable biological conclusions. Here, systems biology provides important tools. Especially, the construction and analysis of molecular networks has emerged as a powerful systems-level framework, with which to integrate such data, and to better understand biological relevant processes in these organisms. In this review, we provide an overview of the advances and experimental approaches undertaken using multiplex data from genomic, transcriptomic, proteomic, and metabolomic studies in cyanobacteria. Furthermore, we summarize currently available web-based tools dedicated to cyanobacteria, i.e., CyanoBase, CyanoEXpress, ProPortal, Cyanorak, CyanoBIKE, and CINPER. Finally, we present a case study for the freshwater model cyanobacteria, Synechocystis sp. PCC6803, to show the power of meta-analysis, and the potential to extrapolate acquired knowledge to the ecologically important marine cyanobacteria genus, Prochlorococcus.

Targeting molecular networks for drug research

The study of molecular networks has recently moved into the limelight of biomedical research. While it has certainly provided us with plenty of new insights into cellular mechanisms, the challenge now is how to modify or even restructure these networks. This is especially true for human diseases, which can be regarded as manifestations of distorted states of molecular networks. Of the possible interventions for altering networks, the use of drugs is presently the most feasible. In this mini-review, we present and discuss some exemplary approaches of how analysis of molecular interaction networks can contribute to pharmacology (e.g., by identifying new drug targets or prediction of drug side effects), as well as list pointers to relevant resources and software to guide future research. We also outline recent progress in the use of drugs for in vitro reprogramming of cells, which constitutes an example par excellence for altering molecular interaction networks with drugs.

StemCellNet: an interactive platform for network-oriented investigations in stem cell biology

Stem cells are characterized by their potential for self-renewal and their capacity to differentiate into mature cells. These two key features emerge through the interplay of various factors within complex molecular networks. To provide researchers with a dedicated tool to investigate these networks, we have developed StemCellNet, a versatile web server for interactive network analysis and visualization. It rapidly generates focused networks based on a large collection of physical and regulatory interactions identified in human and murine stem cells. The StemCellNet web-interface has various easy-to-use tools for selection and prioritization of network components, as well as for integration of expression data provided by the user. As a unique feature, the networks generated can be screened against a compendium of stemness-associated genes. StemCellNet can also indicate novel candidate genes by evaluating their connectivity patterns. Finally, an optional dataset of generic interactions, which provides large coverage of the human and mouse proteome, extends the versatility of StemCellNet to other biomedical research areas in which stem cells play important roles, such as in degenerative diseases or cancer. The StemCellNet web server is freely accessible at http://stemcellnet.sysbiolab.eu.

UniHI 7: an enhanced database for retrieval and interactive analysis of human molecular interaction networks

Unified Human Interactome (UniHI) (http://www.unihi.org) is a database for retrieval, analysis and visualization of human molecular interaction networks. Its primary aim is to provide a comprehensive and easy-to-use platform for network-based investigations to a wide community of researchers in biology and medicine. Here, we describe a major update (version 7) of the database previously featured in NAR Database Issue. UniHI 7 currently includes almost 350 000 molecular interactions between genes, proteins and drugs, as well as numerous other types of data such as gene expression and functional annotation. Multiple options for interactive filtering and highlighting of proteins can be employed to obtain more reliable and specific network structures. Expression and other genomic data can be uploaded by the user to examine local network structures. Additional built-in tools enable ready identification of known drug targets, as well as of biological processes, phenotypes and pathways enriched with network proteins. A distinctive feature of UniHI 7 is its user-friendly interface designed to be utilized in an intuitive manner, enabling researchers less acquainted with network analysis to perform state-of-the-art network-based investigations.

Dynamic circadian protein-protein interaction networks predict temporal organization of cellular functions

Essentially all biological processes depend on protein-protein interactions (PPIs). Timing of such interactions is crucial for regulatory function. Although circadian (~24-hour) clocks constitute fundamental cellular timing mechanisms regulating important physiological processes, PPI dynamics on this timescale are largely unknown. Here, we identified 109 novel PPIs among circadian clock proteins via a yeast-two-hybrid approach. Among them, the interaction of protein phosphatase 1 and CLOCK/BMAL1 was found to result in BMAL1 destabilization. We constructed a dynamic circadian PPI network predicting the PPI timing using circadian expression data. Systematic circadian phenotyping (RNAi and overexpression) suggests a crucial role for components involved in dynamic interactions. Systems analysis of a global dynamic network in liver revealed that interacting proteins are expressed at similar times likely to restrict regulatory interactions to specific phases. Moreover, we predict that circadian PPIs dynamically connect many important cellular processes (signal transduction, cell cycle, etc.) contributing to temporal organization of cellular physiology in an unprecedented manner.

CyanoEXpress: A web database for exploration and visualisation of the integrated transcriptome of cyanobacterium Synechocystis sp. PCC6803

Synechocystis sp. PCC6803 is one of the best studied cyanobacteria and an important model organism for our understanding of photosynthesis. The early availability of its complete genome sequence initiated numerous transcriptome studies, which have generated a wealth of expression data. Analysis of the accumulated data can be a powerful tool to study transcription in a comprehensive manner and to reveal underlying regulatory mechanisms, as well as to annotate genes whose functions are yet unknown. However, use of divergent microarray platforms, as well as distributed data storage make meta-analyses of Synechocystis expression data highly challenging, especially for researchers with limited bioinformatic expertise and resources. To facilitate utilisation of the accumulated expression data for a wider research community, we have developed CyanoEXpress, a web database for interactive exploration and visualisation of transcriptional response patterns in Synechocystis. CyanoEXpress currently comprises expression data for 3073 genes and 178 environmental and genetic perturbations obtained in 31 independent studies. At present, CyanoEXpress constitutes the most comprehensive collection of expression data available for Synechocystis and can be freely accessed.

AVAILABILITY

The database is available for free at http://cyanoexpress.sysbiolab.eu.

Huntington's disease and its therapeutic target genes: a global functional profile based on the HD Research Crossroads database

Background

Huntington’s disease (HD) is a fatal progressive neurodegenerative disorder caused by the expansion of the polyglutamine repeat region in the huntingtin gene. Although the disease is triggered by the mutation of a single gene, intensive research has linked numerous other genes to its pathogenesis. To obtain a systematic overview of these genes, which may serve as therapeutic targets, CHDI Foundation has recently established the HD Research Crossroads database. With currently over 800 cataloged genes, this web-based resource constitutes the most extensive curation of genes relevant to HD. It provides us with an unprecedented opportunity to survey molecular mechanisms involved in HD in a holistic manner.

Methods

To gain a synoptic view of therapeutic targets for HD, we have carried out a variety of bioinformatical and statistical analyses to scrutinize the functional association of genes curated in the HD Research Crossroads database. In particular, enrichment analyses were performed with respect to Gene Ontology categories, KEGG signaling pathways, and Pfam protein families. For selected processes, we also analyzed differential expression, using published microarray data. Additionally, we generated a candidate set of novel genetic modifiers of HD by combining information from the HD Research Crossroads database with previous genome-wide linkage studies.

Results

Our analyses led to a comprehensive identification of molecular mechanisms associated with HD. Remarkably, we not only recovered processes and pathways, which have frequently been linked to HD (such as cytotoxicity, apoptosis, and calcium signaling), but also found strong indications for other potentially disease-relevant mechanisms that have been less intensively studied in the context of HD (such as the cell cycle and RNA splicing, as well as Wnt and ErbB signaling). For follow-up studies, we provide a regularly updated compendium of molecular mechanism, that are associated with HD, at http://hdtt.sysbiolab.eu Additionally, we derived a candidate set of 24 novel genetic modifiers, including histone deacetylase 3 (HDAC3), metabotropic glutamate receptor 1 (GRM1), CDK5 regulatory subunit 2 (CDK5R2), and coactivator 1ß of the peroxisome proliferator-activated receptor gamma (PPARGC1B).

Conclusions

The results of our study give us an intriguing picture of the molecular complexity of HD. Our analyses can be seen as a first step towards a comprehensive list of biological processes, molecular functions, and pathways involved in HD, and may provide a basis for the development of more holistic disease models and new therapeutics.

Comparison and consolidation of microarray data sets of human tissue expression

Background

Human tissue displays a remarkable diversity in structure and function. To understand how such diversity emerges from the same DNA, systematic measurements of gene expression across different tissues in the human body are essential. Several recent studies addressed this formidable task using microarray technologies. These large tissue expression data sets have provided us an important basis for biomedical research. However, it is well known that microarray data can be compromised by high noise level and various experimental artefacts. Critical comparison of different data sets can help to reveal such errors and to avoid pitfalls in their application.

Results

We present here the first comparison and integration of four freely available tissue expression data sets generated using three different microarray platforms and containing a total of 377 microarray hybridizations. When assessing the tissue expression of genes, we found that the results considerably depend on the chosen data set. Nevertheless, the comparison also revealed statistically significant similarity of gene expression profiles across different platforms. This enabled us to construct consolidated lists of platform-independent tissue-specific genes using a set of complementary measures. Follow-up analyses showed that results based on consolidated data tend to be more reliable.

Conclusions

Our study strongly indicates that the consolidation of the four different tissue expression data sets can increase data quality and can lead to biologically more meaningful results. The provided compendium of platform-independent gene lists should facilitate the identification of novel tissue-specific marker genes.

Choreography of the transcriptome, photophysiology, and cell cycle of a minimal photoautotroph, prochlorococcus

The marine cyanobacterium Prochlorococcus MED4 has the smallest genome and cell size of all known photosynthetic organisms. Like all phototrophs at temperate latitudes, it experiences predictable daily variation in available light energy which leads to temporal regulation and partitioning of key cellular processes. To better understand the tempo and choreography of this minimal phototroph, we studied the entire transcriptome of the cell over a simulated daily light-dark cycle, and placed it in the context of diagnostic physiological and cell cycle parameters. All cells in the culture progressed through their cell cycles in synchrony, thus ensuring that our measurements reflected the behavior of individual cells. Ninety percent of the annotated genes were expressed, and 80% had cyclic expression over the diel cycle. For most genes, expression peaked near sunrise or sunset, although more subtle phasing of gene expression was also evident. Periodicities of the transcripts of genes involved in physiological processes such as in cell cycle progression, photosynthesis, and phosphorus metabolism tracked the timing of these activities relative to the light-dark cycle. Furthermore, the transitions between photosynthesis during the day and catabolic consumption of energy reserves at night— metabolic processes that share some of the same enzymes — appear to be tightly choreographed at the level of RNA expression. In-depth investigation of these patterns identified potential regulatory proteins involved in balancing these opposing pathways. Finally, while this analysis has not helped resolve how a cell with so little regulatory capacity, and a ‘deficient’ circadian mechanism, aligns its cell cycle and metabolism so tightly to a light-dark cycle, it does provide us with a valuable framework upon which to build when the Prochlorococcus proteome and metabolome become available.

Tight regulation of unstructured proteins: from transcript synthesis to protein degradation

Altered abundance of several intrinsically unstructured proteins (IUPs) has been associated with perturbed cellular signaling that may lead to pathological conditions such as cancer. Therefore, it is important to understand how cells precisely regulate the availability of IUPs. We observed that regulation of transcript clearance, proteolytic degradation, and translational rate contribute to controlling the abundance of IUPs, some of which are present in low amounts and for short periods of time. Abundant phosphorylation and low stochasticity in transcription and translation indicate that the availability of IUPs can be finely tuned. Fidelity in signaling may require that most IUPs be available in appropriate amounts and not present longer than needed.

UniHI 4: new tools for query, analysis and visualization of the human protein-protein interactome

Human protein interaction maps have become important tools of biomedical research for the elucidation of molecular mechanisms and the identification of new modulators of disease processes. The Unified Human Interactome database (UniHI, http://www.unihi.org) provides researchers with a comprehensive platform to query and access human protein–protein interaction (PPI) data. Since its first release, UniHI has considerably increased in size. The latest update of UniHI includes over 250 000 interactions between ∼22 300 unique proteins collected from 14 major PPI sources. However, this wealth of data also poses new challenges for researchers due to the complexity of interaction networks retrieved from the database. We therefore developed several new tools to query, analyze and visualize human PPI networks. Most importantly, UniHI allows now the construction of tissue-specific interaction networks and focused querying of canonical pathways. This will enable researchers to target their analysis and to prioritize candidate proteins for follow-up studies.

The challenge of regulation in a minimal photoautotroph: non-coding RNAs in Prochlorococcus

Prochlorococcus, an extremely small cyanobacterium that is very abundant in the world's oceans, has a very streamlined genome. On average, these cells have about 2,000 genes and very few regulatory proteins. The limited capability of regulation is thought to be a result of selection imposed by a relatively stable environment in combination with a very small genome. Furthermore, only ten non-coding RNAs (ncRNAs), which play crucial regulatory roles in all forms of life, have been described in Prochlorococcus. Most strains also lack the RNA chaperone Hfq, raising the question of how important this mode of regulation is for these cells. To explore this question, we examined the transcription of intergenic regions of Prochlorococcus MED4 cells subjected to a number of different stress conditions: changes in light qualities and quantities, phage infection, or phosphorus starvation. Analysis of Affymetrix microarray expression data from intergenic regions revealed 276 novel transcriptional units. Among these were 12 new ncRNAs, 24 antisense RNAs (asRNAs), as well as 113 short mRNAs. Two additional ncRNAs were identified by homology, and all 14 new ncRNAs were independently verified by Northern hybridization and 5'RACE. Unlike its reduced suite of regulatory proteins, the number of ncRNAs relative to genome size in Prochlorococcus is comparable to that found in other bacteria, suggesting that RNA regulators likely play a major role in regulation in this group. Moreover, the ncRNAs are concentrated in previously identified genomic islands, which carry genes of significance to the ecology of this organism, many of which are not of cyanobacterial origin. Expression profiles of some of these ncRNAs suggest involvement in light stress adaptation and/or the response to phage infection consistent with their location in the hypervariable genomic islands.

Are we overestimating the number of cell-cycling genes? The impact of background models on time-series analysis

MOTIVATION

Periodic processes play fundamental roles in organisms. Prominent examples are the cell cycle and the circadian clock. Microarray array technology has enabled us to screen complete sets of transcripts for possible association with such fundamental periodic processes on a system-wide level. Frequently, quite large numbers of genes have been detected as periodically expressed. However, the small overlap between genes identified in different studies has cast some doubts on the reliability of the periodic expression detected.

RESULTS

In this study, comparative analysis suggests that the lacking agreement between different cell-cycle studies might be due to inadequate background models for the determination of significance. We demonstrate that the choice of background model has considerable impact on the statistical significance of periodic expression. For illustration, we reanalyzed two microarray studies of the yeast cell cycle. Our evaluation strongly indicates that the results of previous analyses might have been overoptimistic and that the use of more suitable background model promises to give more realistic results.

AVAILABILITY

R scripts are available on request from the corresponding author.

Functional and Transcriptional Coherency of Modules in the Human Protein Interaction Network

Modularity is a major design principle in interaction networks. Various studies have shown that protein interaction networks in prokaryotes and eukaryotes display a modular structure. A majority of the studies have been performed for the yeast interaction network, for which data have become abundant. The systematic examination of the human protein interaction network, however, is still in an early phase. To assess whether the human interaction network similarly displays a modular structure, we assembled a large protein network consisting of over 30,000 interactions. More than 670 modules were subsequently identified based on the detection of cliques. Inspection showed that these modules included numerous known protein complexes. The extracted modules were scrutinized for their coherency with respect to function, localization and expression, thereby allowing us to distinguish between stable and dynamic modules. Finally, the examination of the overlap between modules identified key proteins linking distinct molecular processes.

Genome-wide expression dynamics of a marine virus and host reveal features of co-evolution

Interactions between bacterial hosts and their viruses (phages) lead to reciprocal genome evolution through a dynamic co-evolutionary process. Phage-mediated transfer of host genes--often located in genome islands--has had a major impact on microbial evolution. Furthermore, phage genomes have clearly been shaped by the acquisition of genes from their hosts. Here we investigate whole-genome expression of a host and phage, the marine cyanobacterium Prochlorococcus MED4 and the T7-like cyanophage P-SSP7, during lytic infection, to gain insight into these co-evolutionary processes. Although most of the phage genome was linearly transcribed over the course of infection, four phage-encoded bacterial metabolism genes formed part of the same expression cluster, even though they are physically separated on the genome. These genes--encoding photosystem II D1 (psbA), high-light inducible protein (hli), transaldolase (talC) and ribonucleotide reductase (nrd)--are transcribed together with phage DNA replication genes and seem to make up a functional unit involved in energy and deoxynucleotide production for phage replication in resource-poor oceans. Also unique to this system was the upregulation of numerous genes in the host during infection. These may be host stress response genes and/or genes induced by the phage. Many of these host genes are located in genome islands and have homologues in cyanophage genomes. We hypothesize that phage have evolved to use upregulated host genes, leading to their stable incorporation into phage genomes and their subsequent transfer back to hosts in genome islands. Thus activation of host genes during infection may be directing the co-evolution of gene content in both host and phage genomes.

Mfuzz: a software package for soft clustering of microarray data

For the analysis of microarray data, clustering techniques are frequently used. Most of such methods are based on hard clustering of data wherein one gene (or sample) is assigned to exactly one cluster. Hard clustering, however, suffers from several drawbacks such as sensitivity to noise and information loss. In contrast, soft clustering methods can assign a gene to several clusters. They can overcome shortcomings of conventional hard clustering techniques and offer further advantages. Thus, we constructed an R package termed Mfuzz implementing soft clustering tools for microarray data analysis. The additional package Mfuzzgui provides a convenient TclTk based graphical user interface.

Flexible web-based integration of distributed large-scale human protein interaction maps

Protein-protein interactions constitute the backbone of many molecular processes. This has motivated the recent construction of several large-scale human protein-protein interaction maps [1-10]. Although these maps clearly offer a wealth of information, their use is challenging: complexity, rapid growth, and fragmentation of interaction data hamper their usability. To overcome these hurdles, we have developed a publicly accessible database termed UniHI (Unified Human Interactome) for integration of human protein-protein interaction data. This database is designed to provide biomedical researchers a common platform for exploring previously disconnected human interaction maps. UniHI offers researchers flexible integrated tools for accessing comprehensive information about the human interactome. Several features included in the UniHI allow users to perform various types of network-oriented and functional analysis. At present, UniHI contains over 160,000 distinct interactions between 17,000 unique proteins from ten major interaction maps derived by both computational and experimental approaches [1-10]. Here we describe the details of the implementation and maintenance of UniHI and discuss the challenges that have to be addressed for a successful integration of interaction data.

Comparison of human protein-protein interaction maps

MOTIVATION

Large-scale mappings of protein-protein interactions have started to give us new views of the complex molecular mechanisms inside a cell. After initial projects to systematically map protein interactions in model organisms such as yeast, worm and fly, researchers have begun to focus on the mapping of the human interactome. To tackle this enormous challenge, different approaches have been proposed and pursued. While several large-scale human protein interaction maps have recently been published, their quality remains to be critically assessed.

RESULTS

We present here a first comparative analysis of eight currently available large-scale maps with a total of over 10,000 unique proteins and 57,000 interactions included. They are based either on literature search, orthology or by yeast-two-hybrid assays. Comparison reveals only a small, but statistically significant overlap. More importantly, our analysis gives clear indications that all interaction maps imply considerable selection and detection biases. These results have to be taken into account for future assembly of the human interactome.

AVAILABILITY

An integrated human interaction network called Unified Human Interactome (UniHI) is made publicly accessible at http://www.mdc-berlin.de/unihi.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.