Search bioRxiv⌕ Search

SEARCH · Search bioRxiv

Results for “Molecular Biology”

Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,207 records · Page 67Linked to original sources
bioRxiv2017

mixOmics: an R package for ‘omics feature selection and multiple data integration

The advent of high throughput technologies has led to a wealth of publicly available omics data coming from different sources, such as transcriptomics, proteomics, metabolomics. Combining such large-scale biological data sets can lead to the discovery of important biological insights, provided that relevant information can be extracted in a holistic manner. Current statistical approaches have been focusing on identifying small subsets of molecules (a molecular signature) to explain or predict biological conditions, but mainly for a single type of omics. In addition, commonly used methods are univariate and consider each biological feature independently.\n\nWe introduce mixOmics, an R package dedicated to the multivariate analysis of biological data sets with a specific focus on data exploration, dimension reduction and visualisation. By adopting a system biology approach, the toolkit provides a wide range of methods that statistically integrate several data sets at once to probe relationships between heterogeneous omics data sets. Our recent methods extend Projection to Latent Structure (PLS) models for discriminant analysis, for data integration across multiple omics data or across independent studies, and for the identification of molecular signatures. We illustrate our latest mixOmics integrative frameworks for the multivariate analyses of omics data available from the package.

bioinformatics↗
bioRxiv2017

The Cryptococcus neoformans Titan cell is an inducible and regulated morphotype underlying pathogenesis

Fungi undergo changes in cell shape in response to environmental stimuli that drive pathogenesis and niche adaptation, such as the yeast-to-hyphal transition of dimorphic fungi in response to changing temperature. The basidiomycete Cryptococcus neoformans undergoes an unusual morphogenetic transition in the host lung from haploid yeast to large, highly polyploid cells termed Titan cells. Titan cells influence fungal interaction with host cells, including through increased drug resistance, altered cell size, and altered Pathogen Associated Molecular Pattern exposure. Despite the important role these cells play in pathogenesis, understanding the environmental stimuli that drive the morphological transition, and the molecular mechanisms underlying their unique biology, has been hampered by the lack of a reproducible in vitro induction system. Here we demonstrate reproducible in vitro Titan cell induction in response to environmental stimuli consistent with the host lung. In vitro Titan cells exhibit all the properties of in vivo generated Titan cells, the current gold standard, including altered capsule, cell wall, size, high mother cell ploidy, and aneuploid progeny. We identify bacterial peptidoglycan as a serum compound associated with shift in cell size and ploidy, and demonstrate the capacity of bronchial lavage fluid and E. coli co-culture to induce Titanisation. Additionally, we demonstrate the capacity of our assay to identify established and previously undescribed regulators of Titanisation in vitro and investigate the Titanisation capacity of clinical isolates and their impact on disease outcome. Together, these findings provide new insight into the environmental stimuli and molecular mechanisms underlying the yeast-to-titan transition and establish an essential in vitro model for the future characterization of this important morphotype.\n\nAuthor SummaryChanges in cell shape underlie fungal pathogenesis by allowing immune evasion and dissemination. Aspergillus and Candida albicans hyphae drive tissue penetration. Histoplasma capsulatum and C. albicans yeast growth allows evasion and dissemination. As major virulence determinates, morphogenic transitions are extensively studied in animal models and in vitro. The pathogenic fungus Cryptococcus neoformans is a budding yeast that, in the host lung, switches to an unusual morphotype termed the Titan cell. Titans are large, polyploid, have altered cell wall and capsule, and produce haploid daughters. Their size prevents engulfment by phagocytes, yet they are linked to dissemination and altered immune response. Despite their important influence on disease, replicating the yeast-to-Titan switch in vitro has proved challenging. Here we show that Titans are induced by host-relevant stimuli, including serum and bronchio-alveolar lavage fluid. We identify bacterial peptidoglycan as a relevant inducing compound and predict an in vivo Titan defect for a clinical isolate. Genes regulating in vivo Titanisation also influence in vitro formation. Titanisation is a conserved morphogenic switch across the C. neoformans species complex. Together, we show that Titan cells are a regulated morphotype analogous to the yeast-to-hyphal transition and establish new ways to study Titans outside the host lung.

microbiology↗
bioRxiv2017

Interpretation of biological experiments changes with evolution of Gene Ontology and its annotations

Gene Ontology (GO) enrichment analysis is ubiquitously used for interpreting high throughput molecular data and generating hypotheses about underlying biological phenomena of experiments. However, the two building blocks of this analysis -- the ontology and the annotations -- evolve rapidly. We used gene signatures derived from 104 disease analyses to systematically evaluate how enrichment analysis results were affected by evolution of the GO over a decade. We found low consistency between enrichment analyses results obtained with early and more recent GO versions. Furthermore, there continues to be strong annotation bias in the GO annotations where 58% of the annotations are for 16% of the human genes. Our analysis suggests that GO evolution may have affected the interpretation and possibly reproducibility of experiments over time. Hence, researchers must exercise caution when interpreting GO enrichment analyses and should reexamine previous analyses with the most recent GO version.

bioinformatics↗
bioRxiv2018

Comparative Proteogenomic Analysis of Right-sided Colon Cancer, Left-sided Colon Cancer and Rectal Cancers Reveal Distinct Mutational Profiles.

To understand the molecular differences between right-sided colon cancer (RCC), left-sided colon cancer (LCC) and rectal cancer, we analyzed colorectal tumors at the DNA, RNA, miRNA and protein levels using previously sequenced data from The Cancer Genome Atlas and Memorial Sloan Kettering Cancer Center. Clonal evolution analysis identified the same tumor-initiating events involving APC, KRAS and TP53 genes in RCC, LCC and rectal cancers. However, the individual role-played by each event, their order in tumor dynamics and selection of downstream mutations were distinct in all three anatomical locations, with some similarities noted between LCC and rectal cancer. We found a potentially targetable alteration APC R1450* specific to RCC that has not been previously described. Differential gene expression analysis revealed multiple genes within the homeobox, G-protein coupled receptor binding and transcription regulation families were dysregulated in RCC, LCC, and rectal cancers and may have a pathological role in these cancers. Further, using a novel in silico proteomic analytic tool developed by our research group, we found distinct central or hub proteins with unique interactomes in each location. Protein expression signatures were not necessarily concordant with the tumor profiles obtained at the DNA and RNA levels, underscoring the relevance of post-transcriptional events in defining the biology of these cancers beyond molecular changes at the DNA and/or RNA level. Ultimately, not only tumor location and the respective genomic profile but also protein-protein interactions will need to be taken into account to improve treatment outcomes of colorectal cancers. Further studies that take into account the alterations found in this study may help in developing more tailored, and perhaps more effective, treatment strategies.\n\nAuthor summaryPatients with right-sided colon cancer (RCC) has a worse prognosis compared to left-sided colon cancer (LCC). Recent data has also shown that wild-type RAS metastatic RCCs have poor outcomes when treated with the combination of chemotherapy and anti-EGFR therapy compared to LCC and rectal cancers. Therefore, There is an urgent unmet need to understand the molecular differences between RCC, LCC, and rectal cancers. In this study, we demonstrate clonal evolutionary trajectory and the order of mutations in RCC, LCC, and rectal cancers are distinct with some similarities between LCC and rectal cancers. The order of the mutations that lead to the acquisition of crucial driver alterations may have prognostic and therapeutic implications. We also discovered a novel targetable alteration, APC R1450* to be significantly enriched in early, late and metastatic RCC but not in LCC and rectal cancers. Amazingly, proteomic signatures were discordant with DNA and RNA levels. These distinct differences in DNA, RNA and post-transcriptional events may contribute to their unique clinicopathological features.\n\nConflict of Interest StatementAshiq Masood Advisory board and speaker Bureau Bristol-Myers Squibb and Boehringer Ingelheim\n\nJanakiraman Subramanian Advisory board - Astra Zeneca, Pfizer, Boehringer Ingelheim, Alexion, Paradigm, Bristol-Myers Squibb Speakers Bureau - Astra Zeneca, Boehringer Ingelheim, Lilly Research Support - Biocept and Paradigm\n\nArif Hussain Advisory board - Novartis, Bayer, Astra Zeneca Consultant - Bristol-Myers-Squibb All other authors have no conflict of interest.

genomics↗
bioRxiv2017

Bayesian divergence-time estimation with genome-wide SNP data of sea catfishes (Ariidae) supports Miocene closure of the Panamanian Isthmus

The closure of the Isthmus of Panama has long been considered to be one of the best defined biogeographic calibration points for molecular divergence-time estimation. However, geological and biological evidence has recently cast doubt on the presumed timing of the initial isthmus closure around 3 Ma but has instead suggested the existence of temporary land bridges as early as the Middle or Late Miocene. The biological evidence supporting these earlier land bridges was based either on only few molecular markers or on concatenation of genome-wide sequence data, an approach that is known to result in potentially misleading branch lengths and divergence times, which could compromise the reliability of this evidence. To allow divergence-time estimation with genomic data using the more appropriate multi-species coalescent model, we here develop a new method combining the SNP-based Bayesian species-tree inference of the software SNAPP with a molecular clock model that can be calibrated with fossil or biogeographic constraints. We validate our approach with simulations and use our method to reanalyze genomic data of Neotropical army ants (Dorylinae) that previously supported divergence times of Central and South American populations before the isthmus closure around 3 Ma. Our reanalysis with the multi-species coalescent model shifts all of these divergence times to ages younger than 3 Ma, suggesting that the older estimates supporting the earlier existence of temporary land bridges were artifacts resulting at least partially from the use of concatenation. We then apply our method to a new RAD-sequencing data set of Neotropical sea catfishes (Ariidae) and calibrate their species tree with extensive information from the fossil record. We identify a series of divergences between groups of Caribbean and Pacific sea catfishes around 10 Ma, indicating that processes related to the emergence of the isthmus led to vicariant speciation already in the Late Miocene, millions of years before the final isthmus closure.

evolutionary biology↗
bioRxiv2017

CellNetVis: a web tool for visualization of biological networks using force-directed layout constrained by cellular components

BackgroundThe advent of \"omics\" science has brought new perspectives in contemporary biology through the high-throughput analyses of molecular interactions, providing new clues in protein/gene function and in the organization of biological pathways. Biomolecular interaction networks, or graphs, are simple abstract representations where the components of a cell (e.g. proteins, metabolites etc.) are represented by nodes and their interactions are represented by edges. An appropriate visualization of data is crucial for understanding such networks, since pathways are related to functions that occur in specific regions of the cell. The force-directed layout is an important and widely used technique to draw networks according to their topologies. Placing the networks into cellular compartments helps to quickly identify where network elements are located and, more specifically, concentrated. Currently, only a few tools provide the capability of visually organizing networks by cellular compartments. Most of them cannot handle large and dense networks. Even for small networks with hundreds of nodes the available tools are not able to reposition the network while the user is interacting, limiting the visual exploration capability.\n\nResultsHere we propose CellNetVis, a web tool to easily display biological networks in a cell diagram employing a constrained force-directed layout algorithm. The tool is freely available and open-source. It was originally designed for networks generated by the Integrated Interactome System and can be used with networks from others databases, like InnateDB.\n\nConclusionsCellNetVis has demonstrated to be applicable for dynamic investigation of complex networks over a consistent representation of a cell on the Web, with capabilities not matched elsewhere.

systems biology↗
bioRxiv2016

Fundamental principles governing sporulation efficiency: A network theory approach

Integrating network theory approaches over longitudinal genome-wide gene expression data is a robust approach to understand the molecular underpinnings of a dynamic biological process. Here, we performed a network-based investigation of longitudinal gene expression changes during sporulation of a yeast strain, SK1. Using global network attributes, viz. clustering coefficient, degree distribution of a node, degree-degree mixing of the connected nodes and disassortativity, we observed dynamic changes in these parameters indicating a highly connected network with inter-module crosstalk. Analysis of local attributes, such as clustering coefficient, hierarchy, betweenness centrality and Granovetters weak ties showed that there was an inherent hierarchy under regulatory control that was determined by specific nodes. Biological annotation of these nodes indicated the role of specifically linked pairs of genes in meiosis. These genes act as crucial regulators of sporulation in the highly sporulating SK1 strain. An independent analysis of these network properties in a less efficient sporulating strain helped to understand the heterogeneity of network profiles. We show that comparison of network properties has the potential to identify candidate nodes contributing to the phenotypic diversity of developmental processes in natural populations. Therefore, studying these network parameters as described in this work for dynamic developmental processes, such as sporulation in yeast and eventually in disease progression in humans, can help in identifying candidate factors which are potential regulators of differences between normal and perturbed processes and can be causal targets for intervention.

Systems Biology↗
bioRxiv2017

Three-dimensional actin-based protrusions of migrating neutrophils are intrinsically lamellar and facilitate direction changes

Leukocytes and other amoeboid cells change shape as they move, forming highly dynamic, actin-filled pseudopods. Although we understand much about the architecture and dynamics of thin lamellipodia made by slow-moving cells on flat surfaces, conventional light microscopy lacks the spatial and temporal resolution required to track complex pseudopods of cells moving in three dimensions. We therefore employed lattice light sheet microscopy to perform three-dimensional, time-lapse imaging of neutrophil-like HL-60 cells crawling through collagen matrices. To analyze three-dimensional pseudopods we: (i) developed fluorescent probe combinations that distinguish cortical actin from dynamic, pseudopod-forming actin networks, and (ii) adapted molecular visualization tools from structural biology to render and analyze complex cell surfaces. Surprisingly, three-dimensional pseudopods turn out to be composed of thin (<0.75 m), flat sheets that sometimes interleave to form rosettes. Their laminar nature is not templated by an external surface, but likely reflects a linear arrangement of regulatory molecules. Although we find that pseudopods are dispensable for three-dimensional locomotion, their elimination dramatically decreases the frequency of cell turning, and pseudopod dynamics increase when cells change direction, highlighting the important role pseudopods play in pathfinding.

cell biology↗
bioRxiv2017

Altered Expression Of A Unique Set Of Genes Reveals Complex Etiology Of Schizophrenia

PurposeThe etiology of schizophrenia is extensively debated, and multiple factors have been contended to be involved. A panoramic view of the contributing factors in a genome-wide study can be an effective strategy to provide a comprehensive understanding of its causality.\n\nMaterials and MethodsGSE53987 dataset downloaded from GEO-database, which comprised mRNA expression data of post-mortem brain tissue across three regions from control and age-matched subjects of schizophrenia (N= Hippocampus (HIP): C-15, T-18, Prefrontal cortex (PFC): C-15, T-19, Associative striatum (STR): C-18, T-18). Bio-conductor-affy-package used to compute mRNA expression, and further t-test applied to investigate differential gene expression. The analysis of the derived genes performed using PANTHER Classification System and NCBI database.\n\nResultsA set of 40 genes showed significantly altered (p<0.01) expression across all three brain regions. The analyses unraveled genes implicated in biological processes and events, and molecular pathways relating basic neuronal functions.\n\nConclusionsThe deviant expression of genes maintaining basic cell machinery explains compromised neuronal processing in SCZ.\n\nAbbreviationsSchizophrenia (SCZ), Hippocampus (HIP), Associative striatum (STR), Prefrontal cortex (PFC)

neuroscience↗
bioRxiv2017

Glucose limitation in Lactococcus shapes a single-peaked fitness landscape exposing membrane occupancy as a constraint

A central theme in biology is to understand the molecular basis of fitness: which strategies succeed under which conditions; how are they mechanistically implemented; and which constraints shape trade-offs between alternative strategies. We approached these questions with parallel bacterial evolution experiments in chemostats. Chemostats provide a constant environment with a defined resource limitation (glucose), in which the growth rate can be controlled. Using Lactococcus lactis, we found a single mutation in a global regulator of carbon metabolism, CcpA, to confer predictable fitness improvements across multiple growth rates. In silico protein structural analysis complemented with biochemical and phenotypic assays, show that the mutation reprograms the CcpA regulon, specifically targeting transporters. This supports that membrane occupancy, rather than biosynthetic capacity, is the dominant constraint for the observed fitness enhancement. It also demonstrates that cells can modulate a pleiotropic regulator to work around limiting constraints.

genomics↗
bioRxiv2018

Genome-wide Methylation Patterns Under Caloric Restriction in Daphnia magna.

The degradation of epigenetic control with age is associated with progressive diseases of ageing, including cancers, immunodeficiency and diabetes. Reduced caloric intake slows the effects of aging and age-related diseases, a process likely to be mediated by the impact of caloric restriction on epigenetic factors such as DNA methylation. We used whole genome bisulphite sequencing to study how DNA methylation patterns change with diet in a small invertebrate, the crustacean Daphnia magna. Daphnia show the classic response of longer life under CR, and they reproduce clonally, which permits the study of epigenetic changes in the absence of genetic variation. Global CpG methylation was 0.7-0.9%, and there was no difference in overall methylation levels between normal and calorie restricted replicates. However, 453 regions were differentially methylated (DMRs) between the normally fed and calorie restricted (CR) replicates. Of these 61% were hypomethylated in the CR group, and 39% were hypermethylated in the CR group. Gene Ontogeny (GO) term enrichment of hyper and hypo-methylated genes showed significant over- and under-representation in three molecular function terms and four biological process GO terms. Notable among these were kinase and phosphorylation activity, which have a well-known functional link to cancers.

genomics↗
bioRxiv2018

Conformational flexibility of collagen molecules: composition and environmental effects

The predominant structural protein in vertebrates is collagen, which plays a key role in extracellular matrix and connective tissue mechanics. Despite its prevalence and physical importance in biology, the mechanical properties of molecular collagen are far from established. The flexibility of its triple helix is unresolved, with descriptions from different experimental techniques ranging from flexible to semirigid. Furthermore, it is unknown how collagen type (homo-vs. heterotrimeric) and source (tissue-derived vs. recombinant) influence flexibility. Using SmarTrace, a chain tracing algorithm we devised, we performed statistical analysis of collagen conformations collected with atomic force microscopy (AFM) to determine the proteins mechanical properties. Our results show that types I, II and III collagens - the key fibrillar varieties - exhibit molecular flexibilities that are very similar. However, collagen conformations are strongly modulated by salt, transitioning from compact to extended as KCl concentration increases, in both neutral and acidic pH. While analysis with a standard worm-like chain model suggests that the persistence length of collagen can attain almost any value within the literature range, closer inspection reveals that this modulation of collagens conformational behaviour is not due to changes in flexibility, but rather arises from the induction of curvature (either intrinsic or induced by interactions with the mica surface). By modifying standard polymer theory to include innate curvature, we show that collagen behaves as an equilibrated curved worm-like chain (cWLC) in two dimensions. Analysis within the cWLC model shows that collagens curvature depends strongly on pH and salt, while its persistence length does not. Thus, we find that triple-helical collagen is well described as semiflexible, irrespective of source, type, pH and salt environment. These results demonstrate that collagen is more flexible than its conventional description as a rigid rod, which may have implications for its cellular processing and secretion.

biophysics↗
bioRxiv2018

Structure of the herpes-simplex virus portal-vertex

Herpesviruses include many important human pathogens such as herpes simplex virus, cytomegalovirus, varicella-zoster virus and the oncogenic Epstein-Barr virus and Kaposi-sarcoma associated herpesvirus. Herpes virions contains large icosahedral capsids that have a portal at a unique five-fold vertex, similar to that seen in the tailed bacteriophages. The portal is a molecular motor through which the viral genome enters the capsid during virion morphogenesis. The genome also exits the capsid through the portal-vertex when it is injected through the nuclear-pore into the nucleus of a new host cell to initiate infection. Structural investigations of the herpesvirus portal-vertex have proven challenging, owing to the small size of the tail-like portal-vertex associated tegument (PVAT), and the dense tegument layer that lays between the nucleocapsid and the viral envelope, obscuring the view of the portal-vertex. Here we show the structure of the herpes simplex virus portal-vertex at sub-nanometer resolution, solved by electron cryomicroscopy (cryoEM) and single-particle 3D reconstruction. This led to a number of new discoveries including the presence of two previously unknown portal associated structures that occupy the sites normally taken by the penton and the Ta triplex. Our data revealed that the PVAT is composed of ten copies of the C-terminal domain of pUL25, which are uniquely arranged as two tiers of star-shaped density. Our 3D reconstruction of the portal-vertex also shows that one end of the viral genome extends outside the portal in the manner described for some bacteriophage but not previously seen in any eukaryote viruses. Finally, we show that the viral genome is consistently packed in a highly-ordered left-handed spool to form concentric shells of DNA. Our data provide new insights into the structure of a molecular machine critical to the biology of an important class of human pathogens.

microbiology↗
bioRxiv2018

Toward machine-guided design of proteins

Proteins--molecular machines that underpin all biological life--are of significant therapeutic and industrial value. Directed evolution is a high-throughput experimental approach for improving protein function, but has difficulty escaping local maxima in the fitness landscape. Here, we investigate how supervised learning in a closed loop with DNA synthesis and high-throughput screening can be used to improve protein design. Using the green fluorescent protein (GFP) as an illustrative example, we demonstrate the opportunities and challenges of generating training datasets conducive to selecting strongly generalizing models. With prospectively designed wet lab experiments, we then validate that these models can generalize to unseen regions of the fitness landscape, even when constrained to explore combinations of non-trivial mutations. Taken together, this suggests a hybrid optimization strategy for protein design in which a predictive model is used to explore difficult-to-access but promising regions of the fitness landscape that directed evolution can then exploit at scale.

synthetic biology↗
bioRxiv2018

Strength in numbers: collaborative science for new experimental model systems

Our current understanding of biology is heavily based on the contributions from a small number of genetically tractable model organisms. Most eukaryotic phyla lack such experimental models, and this limits our ability to explore the molecular mechanisms that ultimately define their biology, ecology, and diversity. In particular, marine protists suffer from a paucity of model organisms despite playing critical roles in global nutrient cycles, food webs, and climate. To address this deficit, an initiative was launched in 2015 to foster development of ecologically and taxonomically diverse marine protist genetic models. This multifaceted, complex but important challenge required a highly collaborative community-based approach. Herein we describe this approach, the advances achieved, and the lessons learned by participants in this novel community-based model for research.

microbiology↗
bioRxiv2018

CausalTab: PSI-MITAB 2.8 updated format for signaling data representation and dissemination

Combining multiple layers of information underlying biological complexity into a structured framework, and in particular deciphering the molecular mechanisms behind cellular phenotypes, represent two challenges in systems biology. A key task is the formalisation of such information in models describing how biological entities interact to mediate the response to external and internal signals. Several databases with signaling information, such as SIGNOR, SignaLink and IntAct, focus on capturing, organising and displaying signaling interactions by representing them as binary, causal relationships between biological entities. The curation efforts that build these individual databases demand a concerted effort to ensure interoperability among resources, through the development of a standardized exchange format, ontologies and controlled vocabularies supporting the domain of causal interactions. Aware of the enormous benefits of standardization efforts in the molecular interaction research field, representatives of the signalling network community agreed to extend the PSI-MI controlled vocabulary to include additional terms representing aspects of causal interactions. Here, we present a common standard for the representation and dissemination of signaling information: the PSI Causal Interaction tabular format (CausalTAB) which is an extension of the existing PSI-MI tab-delimited format, now designated MITAB2.8. We define the new term \"causal interaction\", and related child terms, which are children of the PSI-MI \"molecular interaction\" term. The new vocabulary terms in this extended PSI-MI format will enable systems biologists to model large-scale signaling networks more precisely and with higher coverage than before.

systems biology↗
bioRxiv2017

Symmetry broken and rebroken during the ATP hydrolysis cycle of the mitochondrial Hsp90 TRAP1

Hsp90 is a homodimeric ATP-dependent molecular chaperone that remodels its substrate \"client\" proteins, facilitating their folding and activating them for biological function. Despite decades of research, the mechanism connecting ATP hydrolysis and chaperone function remains elusive. Particularly puzzling has been the apparent lack of cooperativity in hydrolysis of the ATP in each protomer. A crystal structure of the mitochondrial Hsp90, TRAP1, revealed that the catalytically active state is closed in a highly-strained asymmetric conformation. This asymmetry, unobserved in other Hsp90 homologs, is due to buckling of one of the protomers and is most pronounced at the broadly conserved client-binding region. Here, we show that rather than being cooperative or independent, ATP hydrolysis on the two protomers is sequential and deterministic. Moreover, dimer asymmetry sets up differential hydrolysis rates for each protomer, such that the buckled conformation favors ATP hydrolysis. Remarkably, after the first hydrolysis, the dimer undergoes a flip in the asymmetry while remaining in a closed state for the second hydrolysis. From these results, we propose a model where direct coupling of ATP hydrolysis and conformational flipping rearranges client-binding sites, providing a paradigm of how energy from ATP hydrolysis can be used for client remodeling.

molecular biology↗
bioRxiv2016

DynOmics to identify delays and co-expression patterns across time course experiments

Dynamic changes in biological systems can be captured by measuring molecular expression from different levels (e.g., genes and proteins) across time. Integration of such data aims to identify molecules that show similar expression changes over time; such molecules may be co-regulated and thus involved in similar biological processes. Combining data sources presents a systematic approach to study molecular behaviour. It can compensate for missing data in one source, and can reduce false positives when multiple sources highlight the same pathways. However, integrative approaches must accommodate the challenges inherent in omics data, including high-dimensionality, noise, and timing differences in expression. As current methods for identification of co-expression cannot cope with this level of complexity, we developed a novel algorithm called DynOmics. DynOmics is based on the fast Fourier transform, from which the difference in expression initiation between trajectories can be estimated. This delay can then be used to realign the trajectories and identify those which show a high degree of correlation. Through extensive simulations, we demonstrate that DynOmics is efficient and accurate compared to existing approaches. We consider two case studies highlighting its application, identifying regulatory relationships across omics data within an organism and for comparative gene expression analysis across organisms.

Bioinformatics↗