The PathOlogist: an automated tool for pathway-centric analysis

<p>Abstract</p> <p>Background</p> <p>The PathOlogist is a new tool designed to transform large sets of gene expression data into quantitative descriptors of pathway-level behavior. The tool aims to provide a robust alternative to the search for single-gene-to-phenotype associations by accounting for the complexity of molecular interactions.</p> <p>Results</p> <p>Molecular abundance data is used to calculate two metrics - 'activity' and 'consistency' - for each pathway in a set of more than 500 canonical molecular pathways (source: Pathway Interaction Database, <url>http://pid.nci.nih.gov</url>). The tool then allows a detailed exploration of these metrics through integrated visualization of pathway components and structure, hierarchical clustering of pathways and samples, and statistical analyses designed to detect associations between pathway behavior and clinical features.</p> <p>Conclusions</p> <p>The PathOlogist provides a straightforward means to identify the functional processes, rather than individual molecules, that are altered in disease. The statistical power and biologic significance of this approach are made easily accessible to laboratory researchers and informatics analysts alike. Here we show as an example, how the PathOlogist can be used to establish pathway signatures that robustly differentiate breast cancer cell lines based on response to treatment.</p

Confidence from uncertainty - A multi-target drug screening method from robust control theory

<p>Abstract</p> <p>Background</p> <p>Robustness is a recognized feature of biological systems that evolved as a defence to environmental variability. Complex diseases such as diabetes, cancer, bacterial and viral infections, exploit the same mechanisms that allow for robust behaviour in healthy conditions to ensure their own continuance. Single drug therapies, while generally potent regulators of their specific protein/gene targets, often fail to counter the robustness of the disease in question. Multi-drug therapies offer a powerful means to restore disrupted biological networks, by targeting the subsystem of interest while preventing the diseased network from reconciling through available, redundant mechanisms. Modelling techniques are needed to manage the high number of combinatorial possibilities arising in multi-drug therapeutic design, and identify synergistic targets that are robust to system uncertainty.</p> <p>Results</p> <p>We present the application of a method from robust control theory, Structured Singular Value or μ- analysis, to identify highly effective multi-drug therapies by using robustness in the face of uncertainty as a new means of target discrimination. We illustrate the method by means of a case study of a negative feedback network motif subject to parametric uncertainty.</p> <p>Conclusions</p> <p>The paper contributes to the development of effective methods for drug screening in the context of network modelling affected by parametric uncertainty. The results have wide applicability for the analysis of different sources of uncertainty like noise experienced in the data, neglected dynamics, or intrinsic biological variability.</p

Anion gap, anion gap corrected for albumin, base deficit and unmeasured anions in critically ill patients: implications on the assessment of metabolic acidosis and the diagnosis of hyperlactatemia

Abstract Background Base deficit (BD), anion gap (AG), and albumin corrected anion gap (ACAG) are used by clinicians to assess the presence or absence of hyperlactatemia (HL). We set out to determine if these tools can diagnose the presence of HL using cotemporaneous samples. Methods We conducted a chart review of ICU patients who had cotemporaneous arterial blood gas, serum chemistry, serum albumin (Alb) and lactate(Lac) levels measured from the same sample. We assessed the capacity of AG, BD, and ACAG to diagnose HL and severe hyperlactatemia (SHL). HL was defined as Lac > 2.5 mmol/L. SHL was defined as a Lac of > 4.0 mmol/L. Results From 143 patients we identified 497 series of lab values that met our study criteria. Mean age was 62.2 ± 15.7 years. Mean Lac was 2.11 ± 2.6 mmol/L, mean AG was 9.0 ± 5.1, mean ACAG was 14.1 ± 3.8, mean BD was 1.50 ± 5.4. The area under the curve for the ROC for BD, AG, and ACAG to diagnose HL were 0.79, 0.70, and 0.72, respectively. Conclusion AG and BD failed to reliably detect the presence of clinically significant hyperlactatemia. Under idealized conditions, ACAG has the capacity to rule out the presence of hyperlactatemia. Lac levels should be obtained routinely in all patients admitted to the ICU in whom the possibility of shock/hypoperfusion is being considered. If an AG assessment is required in the ICU, it must be corrected for albumin for there to be sufficient diagnostic utility.</p

The Aspartate-Semialdehyde Dehydrogenase of Edwardsiella ictaluri and Its Use as Balanced-Lethal System in Fish Vaccinology

asdA mutants of Gram-negative bacteria have an obligate requirement for diaminopimelic acid (DAP), which is an essential constituent of the peptidoglycan layer of the cell wall of these organisms. In environments deprived of DAP, i.e., animal tissues, they will undergo lysis. Deletion of the asdA gene has previously been exploited to develop antibiotic-sensitive strains of live attenuated recombinant bacterial vaccines. Introduction of an Asd+ plasmid into a ΔasdA mutant makes the bacterial strain plasmid-dependent. This dependence on the Asd+ plasmid vector creates a balanced-lethal complementation between the bacterial strain and the recombinant plasmid. E. ictaluri is an enteric Gram-negative fish pathogen that causes enteric septicemia in catfish. Because E. ictaluri is a nasal/oral invasive intracellular pathogen, this bacterium is a candidate to develop a bath/oral live recombinant attenuated Edwardsiella vaccine (RAEV) for the catfish aquaculture industry. As a first step to develop an antibiotic-sensitive RAEV strain, we characterized and deleted the E. ictaluri asdA gene. E. ictaluri ΔasdA01 mutants exhibit an absolute requirement for DAP to grow. The asdA gene of E. ictaluri was complemented by the asdA gene from Salmonella. Several Asd+ expression vectors with different origins of replication were transformed into E. ictaluri ΔasdA01. Asd+ vectors were compatible with the pEI1 and pEI2 E. ictaluri native plasmids. The balanced-lethal system was satisfactorily evaluated in vivo. Recombinant GFP, PspA, and LcrV proteins were synthesized by E. ictaluri ΔasdA01 harboring Asd+ plasmids. Here we constructed a balanced-lethal system, which is the first step to develop an antibiotic-sensitive RAEV for the aquaculture industry

Quantitative global studies of reactomes and metabolomes using a vectorial representation of reactions and chemical compounds

<p>Abstract</p> <p>Background</p> <p>Global studies of the protein repertories of organisms are providing important information on the characteristics of the protein space. Many of these studies entail classification of the protein repertory on the basis of structure and/or sequence similarities. The situation is different for metabolism. Because there is no good way of measuring similarities between chemical reactions, there is a barrier to the development of global classifications of "metabolic space" and subsequent studies comparable to those done for protein sequences and structures.</p> <p>Results</p> <p>In this work, we propose a vectorial representation of chemical reactions, which allows them to be compared and classified. In this representation, chemical compounds, reactions and pathways may be represented in the same vectorial space. We show that the representation of chemical compounds reflects their physicochemical properties and can be used for predictive purposes. We use the vectorial representations of reactions to perform a global classification of the reactome of the model organism <it>E. coli</it>.</p> <p>Conclusions</p> <p>We show that this unsupervised clustering results in groups of enzymes more coherent in biological terms than equivalent groupings obtained from the EC hierarchy. This hierarchical clustering produces an optimal set of 21 groups which we analyzed for their biological meaning.</p

Search for Gravitational Waves from Primordial Black Hole Binary Coalescences in the Galactic Halo

We use data from the second science run of the LIGO gravitational-wave detectors to search for the gravitational waves from primordial black hole (PBH) binary coalescence with component masses in the range 0.2--$1.0 M_\odot$. The analysis requires a signal to be found in the data from both LIGO observatories, according to a set of coincidence criteria. No inspiral signals were found. Assuming a spherical halo with core radius 5 kpc extending to 50 kpc containing non-spinning black holes with masses in the range 0.2--$1.0 M_\odot$, we place an observational upper limit on the rate of PBH coalescence of 63 per year per Milky Way halo (MWH) with 90% confidence.Comment: 7 pages, 4 figures, to be submitted to Phys. Rev.

Calculation of the Free Energy and Cooperativity of Protein Folding

Calculation of the free energy of protein folding and delineation of its pre-organization are of foremost importance for understanding, predicting and designing biological macromolecules. Here, we introduce an energy smoothing variant of parallel tempering replica exchange Monte Carlo (REMS) that allows for efficient configurational sampling of flexible solutes under the conditions of molecular hydration. Its usage to calculate the thermal stability of a model globular protein, Trp cage TC5b, achieves excellent agreement with experimental measurements. We find that the stability of TC5b is attained through the coupled formation of local and non-local interactions. Remarkably, many of these structures persist at high temperature, concomitant with the origin of native-like configurations and mesostates in an otherwise macroscopically disordered unfolded state. Graph manifold learning reveals that the conversion of these mesostates to the native state is structurally heterogeneous, and that the cooperativity of their formation is encoded largely by the unfolded state ensemble. In all, these studies establish the extent of thermodynamic and structural pre-organization of folding of this model globular protein, and achieve the calculation of macromolecular stability ab initio, as required for ab initio structure prediction, genome annotation, and drug design

Mass Homozygotes Accumulation in the NCI-60 Cancer Cell Lines As Compared to HapMap Trios, and Relation to Fragile Site Location

Runs of homozygosity (ROH) represents extended length of homozygotes on a long genomic distance. In oncology, it is known as loss of heterozygosity (LOH) if identified exclusively in cancer cell rather than in matched control cell. Studies have identified several genomic regions which show consistent ROH in different kinds of carcinoma. To query whether this consistency can be observed on broader spectrum, both in more cancer types and in wider genomic regions, we investigated ROH patterns in the National Cancer Institute 60 cancer cell line panel (NCI-60) and HapMap Caucasian healthy trio families. Using results from Affymetrix 500 K SNP arrays, we report a genome wide significant association of ROH regions between the NCI-60 and HapMap samples, with much a higher level of ROH (11 fold) in the cancer cell lines. Analysis shows that more severe ROH found in cancer cells appears to be the extension of existing ROH in healthy state. In the HapMap trios, the adult subgroup had a slightly but significantly higher level (1.02 fold) of ROH than did the young subgroup. For several ROH regions we observed the co-occurrence of fragile sites (FRAs). However, FRA on the genome wide level does not show a clear relationship with ROH regions

Phase I Hydroxylated Metabolites of the K2 Synthetic Cannabinoid JWH-018 Retain In Vitro and In Vivo Cannabinoid 1 Receptor Affinity and Activity

K2 products are synthetic cannabinoid-laced, marijuana-like drugs of abuse, use of which is often associated with clinical symptoms atypical of marijuana use, including hypertension, agitation, hallucinations, psychosis, seizures and panic attacks. JWH-018, a prevalent K2 synthetic cannabinoid, is structurally distinct from Δ(9)-THC, the main psychoactive ingredient in marijuana. Since even subtle structural differences can lead to differential metabolism, formation of novel, biologically active metabolites may be responsible for the distinct effects associated with K2 use. The present study proposes that K2's high adverse effect occurrence is due, at least in part, to distinct JWH-018 metabolite activity at the cannabinoid 1 receptor (CB1R).JWH-018, five potential monohydroxylated metabolites (M1-M5), and one carboxy metabolite (M6) were examined in mouse brain homogenates containing CB1Rs, first for CB1R affinity using a competition binding assay employing the cannabinoid receptor radioligand [(3)H]CP-55,940, and then for CB1R intrinsic efficacy using an [(35)S]GTPγS binding assay. JWH-018 and M1-M5 bound CB1Rs with high affinity, exhibiting K(i) values that were lower than or equivalent to Δ(9)-THC. These molecules also stimulated G-proteins with equal or greater efficacy relative to Δ(9)-THC, a CB1R partial agonist. Most importantly, JWH-018, M2, M3, and M5 produced full CB1R agonist levels of activation. CB1R-mediated activation was demonstrated by blockade with O-2050, a CB1R-selective neutral antagonist. Similar to Δ(9)-THC, JWH-018 and M1 produced a marked depression of locomotor activity and core body temperature in mice that were both blocked by the CB1R-preferring antagonist/inverse agonist AM251.Unlike metabolites of most drugs, the studied JWH-018 monohydroxylated compounds, but not the carboxy metabolite, retain in vitro and in vivo activity at CB1Rs. These observations, combined with higher CB1R affinity and activity relative to Δ(9)-THC, may contribute to the greater prevalence of adverse effects observed with JWH-018-containing products relative to cannabis