4DXpress: a database for cross-species expression pattern comparisons

In the major animal model species like mouse, fish or fly, detailed spatial information on gene expression over time can be acquired through whole mount in situ hybridization experiments. In these species, expression patterns of many genes have been studied and data has been integrated into dedicated model organism databases like ZFIN for zebrafish, MEPD for medaka, BDGP for Drosophila or GXD for mouse. However, a central repository that allows users to query and compare gene expression patterns across different species has not yet been established. Therefore, we have integrated expression patterns for zebrafish, Drosophila, medaka and mouse into a central public repository called 4DXpress (expression database in four dimensions). Users can query anatomy ontology-based expression annotations across species and quickly jump from one gene to the orthologues in other species. Genes are linked to public microarray data in ArrayExpress. We have mapped developmental stages between the species to be able to compare developmental time phases. We store the largest collection of gene expression patterns available to date in an individual resource, reflecting 16 505 annotated genes. 4DXpress will be an invaluable tool for developmental as well as for computational biologists interested in gene regulation and evolution. 4DXpress is available at http://ani.embl.de/4DXpress

Complex networks theory for analyzing metabolic networks

One of the main tasks of post-genomic informatics is to systematically investigate all molecules and their interactions within a living cell so as to understand how these molecules and the interactions between them relate to the function of the organism, while networks are appropriate abstract description of all kinds of interactions. In the past few years, great achievement has been made in developing theory of complex networks for revealing the organizing principles that govern the formation and evolution of various complex biological, technological and social networks. This paper reviews the accomplishments in constructing genome-based metabolic networks and describes how the theory of complex networks is applied to analyze metabolic networks.Comment: 13 pages, 2 figure

Technical design of the phase I Mu3e experiment

The Mu3e experiment aims to find or exclude the lepton flavour violating decay at branching fractions above . A first phase of the experiment using an existing beamline at the Paul Scherrer Institute (PSI) is designed to reach a single event sensitivity of . We present an overview of all aspects of the technical design and expected performance of the phase I Mu3e detector. The high rate of up to muon decays per second and the low momenta of the decay electrons and positrons pose a unique set of challenges, which we tackle using an ultra thin tracking detector based on high-voltage monolithic active pixel sensors combined with scintillating fibres and tiles for precise timing measurements

Accelerated search for biomolecular network models to interpret high-throughput experimental data

<p>Abstract</p> <p>Background</p> <p>The functions of human cells are carried out by biomolecular networks, which include proteins, genes, and regulatory sites within DNA that encode and control protein expression. Models of biomolecular network structure and dynamics can be inferred from high-throughput measurements of gene and protein expression. We build on our previously developed fuzzy logic method for bridging quantitative and qualitative biological data to address the challenges of noisy, low resolution high-throughput measurements, i.e., from gene expression microarrays. We employ an evolutionary search algorithm to accelerate the search for hypothetical fuzzy biomolecular network models consistent with a biological data set. We also develop a method to estimate the probability of a potential network model fitting a set of data by chance. The resulting metric provides an estimate of both model quality and dataset quality, identifying data that are too noisy to identify meaningful correlations between the measured variables.</p> <p>Results</p> <p>Optimal parameters for the evolutionary search were identified based on artificial data, and the algorithm showed scalable and consistent performance for as many as 150 variables. The method was tested on previously published human cell cycle gene expression microarray data sets. The evolutionary search method was found to converge to the results of exhaustive search. The randomized evolutionary search was able to converge on a set of similar best-fitting network models on different training data sets after 30 generations running 30 models per generation. Consistent results were found regardless of which of the published data sets were used to train or verify the quantitative predictions of the best-fitting models for cell cycle gene dynamics.</p> <p>Conclusion</p> <p>Our results demonstrate the capability of scalable evolutionary search for fuzzy network models to address the problem of inferring models based on complex, noisy biomolecular data sets. This approach yields multiple alternative models that are consistent with the data, yielding a constrained set of hypotheses that can be used to optimally design subsequent experiments.</p

The response of perennial and temporary headwater stream invertebrate communities to hydrological extremes

The headwaters of karst rivers experience considerable hydrological variability, including spates and streambed drying. Extreme summer flooding on the River Lathkill (Derbyshire, UK) provided the opportunity to examine the invertebrate community response to unseasonal spate flows, flow recession and, at temporary sites, streambed drying. Invertebrates were sampled at sites with differing flow permanence regimes during and after the spates. Following streambed drying at temporary sites, dewatered surface sediments were investigated as a refugium for aquatic invertebrates. Experimental rehydration of these dewatered sediments was conducted to promote development of desiccation-tolerant life stages. At perennial sites, spate flows reduced invertebrate abundance and diversity, whilst at temporary sites, flow reactivation facilitated rapid colonisation of the surface channel by a limited number of invertebrate taxa. Following streambed drying, 38 taxa were recorded from the dewatered and rehydrated sediments, with Oligochaeta being the most abundant taxon and Chironomidae (Diptera) the most diverse. Experimental rehydration of dewatered sediments revealed the presence of additional taxa, including Stenophylax sp. (Trichoptera: Limnephilidae) and Nemoura sp. (Plecoptera: Nemouridae). The influence of flow permanence on invertebrate community composition was apparent despite the aseasonal high-magnitude flood events

Leigh syndrome is the main clinical characteristic of PTCD3 deficiency

Mitochondrial translation defects are a continuously growing group of disorders showing a large variety of clinical symptoms including a wide range of neurological abnormalities. To date, mutations in PTCD3, encoding a component of the mitochondrial ribosome, have only been reported in a single individual with clinical evidence of Leigh syndrome. Here, we describe three additional PTCD3 individuals from two unrelated families, broadening the genetic and phenotypic spectrum of this disorder, and provide definitive evidence that PTCD3 deficiency is associated with Leigh syndrome. The patients presented in the first months of life with psychomotor delay, respiratory insufficiency and feeding difficulties. The neurologic phenotype included dystonia, optic atrophy, nystagmus and tonic-clonic seizures. Brain MRI showed optic nerve atrophy and thalamic changes, consistent with Leigh syndrome. WES and RNA-seq identified compound heterozygous variants in PTCD3 in both families: c.[1453-1G>C];[1918C>G] and c.[710del];[902C>T]. The functional consequences of the identified variants were determined by a comprehensive characterization of the mitochondrial function. PTCD3 protein levels were significantly reduced in patient fibroblasts and, consistent with a mitochondrial translation defect, a severe reduction in the steady state levels of complexes I and IV subunits was detected. Accordingly, the activity of these complexes was also low, and high-resolution respirometry showed a significant decrease in the mitochondrial respiratory capacity. Functional complementation studies demonstrated the pathogenic effect of the identified variants since the expression of wild-type PTCD3 in immortalized fibroblasts restored the steady-state levels of complexes I and IV subunits as well as the mitochondrial respiratory capacity. Additionally, minigene assays demonstrated that three of the identified variants were pathogenic by altering PTCD3 mRNA processing. The fourth variant was a frameshift leading to a truncated protein. In summary, we provide evidence of PTCD3 involvement in human disease confirming that PTCD3 deficiency is definitively associated with Leigh syndrome.© 2022 The Authors. Brain Pathology published by John Wiley & Sons Ltd on behalf of International Society of Neuropathology

Exploiting the pathway structure of metabolism to reveal high-order epistasis

<p>Abstract</p> <p>Background</p> <p>Biological robustness results from redundant pathways that achieve an essential objective, e.g. the production of biomass. As a consequence, the biological roles of many genes can only be revealed through multiple knockouts that identify a <it>set </it>of genes as essential for a given function. The identification of such "epistatic" essential relationships between network components is critical for the understanding and eventual manipulation of robust systems-level phenotypes.</p> <p>Results</p> <p>We introduce and apply a network-based approach for genome-scale metabolic knockout design. We apply this method to uncover over 11,000 minimal knockouts for biomass production in an <it>in silico </it>genome-scale model of <it>E. coli</it>. A large majority of these "essential sets" contain 5 or more reactions, and thus represent complex epistatic relationships between components of the <it>E. coli </it>metabolic network.</p> <p>Conclusion</p> <p>The complex minimal biomass knockouts discovered with our approach illuminate robust essential systems-level roles for reactions in the <it>E. coli </it>metabolic network. Unlike previous approaches, our method yields results regarding high-order epistatic relationships and is applicable at the genome-scale.</p

Exhaustive identification of steady state cycles in large stoichiometric networks

BACKGROUND: Identifying cyclic pathways in chemical reaction networks is important, because such cycles may indicate in silico violation of energy conservation, or the existence of feedback in vivo. Unfortunately, our ability to identify cycles in stoichiometric networks, such as signal transduction and genome-scale metabolic networks, has been hampered by the computational complexity of the methods currently used. RESULTS: We describe a new algorithm for the identification of cycles in stoichiometric networks, and we compare its performance to two others by exhaustively identifying the cycles contained in the genome-scale metabolic networks of H. pylori, M. barkeri, E. coli, and S. cerevisiae. Our algorithm can substantially decrease both the execution time and maximum memory usage in comparison to the two previous algorithms. CONCLUSION: The algorithm we describe improves our ability to study large, real-world, biochemical reaction networks, although additional methodological improvements are desirable

A systems approach to identifying correlated gene targets for the loss of colour pigmentation in plants

<p>Abstract</p> <p>Background</p> <p>The numerous diverse metabolic pathways by which plant compounds can be produced make it difficult to predict how colour pigmentation is lost for different tissues and plants. This study employs mathematical and <it>in silico </it>methods to identify correlated gene targets for the loss of colour pigmentation in plants from a whole cell perspective based on the full metabolic network of <it>Arabidopsis</it>. This involves extracting a self-contained flavonoid subnetwork from the AraCyc database and calculating feasible metabolic routes or elementary modes (EMs) for it. Those EMs leading to anthocyanin compounds are taken to constitute the anthocyanin biosynthetic pathway (ABP) and their interplay with the rest of the EMs is used to study the minimal cut sets (MCSs), which are different combinations of reactions to block for eliminating colour pigmentation. By relating the reactions to their corresponding genes, the MCSs are used to explore the phenotypic roles of the ABP genes, their relevance to the ABP and the impact their eliminations would have on other processes in the cell.</p> <p>Results</p> <p>Simulation and prediction results of the effect of different MCSs for eliminating colour pigmentation correspond with existing experimental observations. Two examples are: i) two MCSs which require the simultaneous suppression of genes DFR and ANS to eliminate colour pigmentation, correspond to observational results of the same genes being co-regulated for eliminating floral pigmentation in <it>Aquilegia </it>and; ii) the impact of another MCS requiring CHS suppression, corresponds to findings where the suppression of the early gene CHS eliminated nearly all flavonoids but did not affect the production of volatile benzenoids responsible for floral scent.</p> <p>Conclusions</p> <p>From the various MCSs identified for eliminating colour pigmentation, several correlate to existing experimental observations, indicating that different MCSs are suitable for different plants, different cells, and different conditions and could also be related to regulatory genes. Being able to correlate the predictions with experimental results gives credence to the use of these mathematical and <it>in silico </it>analyses methods in the design of experiments. The methods could be used to prioritize target enzymes for different objectives to achieve desired outcomes, especially for less understood pathways.</p

A novel pancoronavirus RT-PCR assay: frequent detection of human coronavirus NL63 in children hospitalized with respiratory tract infections in Belgium

BACKGROUND: Four human coronaviruses are currently known to infect the respiratory tract: human coronaviruses OC43 (HCoV-OC43) and 229E (HCoV-229E), SARS associated coronavirus (SARS-CoV) and the recently identified human coronavirus NL63 (HCoV-NL63). In this study we explored the incidence of HCoV-NL63 infection in children diagnosed with respiratory tract infections in Belgium. METHODS: Samples from children hospitalized with respiratory diseases during the winter seasons of 2003 and 2004 were evaluated for the presence of HCoV-NL63 using a optimized pancoronavirus RT-PCR assay. RESULTS: Seven HCoV-NL63 positive samples were identified, six were collected during January/February 2003 and one at the end of February 2004. CONCLUSIONS: Our results support the notation that HCoV-NL63 can cause serious respiratory symptoms in children. Sequence analysis of the S gene showed that our isolates could be classified into two subtypes corresponding to the two prototype HCoV-NL63 sequences isolated in The Netherlands in 1988 and 2003, indicating that these two subtypes may currently be cocirculating