Composite functional module inference: detecting cooperation between transcriptional regulation and protein interaction by mantel test

Background  

Functional modules are basic units of cell function, and exploring them is important for understanding the organization, regulation and execution of cell processes. Functional modules in single biological networks (e.g., the protein-protein interaction network), have been the focus of recent studies. Functional modules in the integrated network are composite functional modules, which imply the complex relationships involving multiple biological interaction types, and detect them will help us understand the complexity of cell processes.     

Section-level relationships of North American <Emphasis Type="Italic">Agalinis</Emphasis> (Orobanchaceae) based on DNA sequence analysis of three chloroplast gene regions

Background  

The North American Agalinis are representatives of a taxonomically difficult group that has been subject to extensive taxonomic revision from species level through higher sub-generic designations (e.g., subsections and sections). Previous presentations of relationships have been ambiguous and have not conformed to modern phylogenetic standards (e.g., were not presented as phylogenetic trees). Agalinis contains a large number of putatively rare taxa that have some degree of taxonomic uncertainty. We used DNA sequence data from three chloroplast genes to examine phylogenetic relationships among sections within the genus Agalinis Raf. (= Gerardia), and between Agalinis and closely related genera within Orobanchaceae.     

Cost-Effectiveness of Chagas Disease Vector Control Strategies in Northwestern Argentina

Background

Control and prevention of Chagas disease rely mostly on residual spraying of insecticides. In Argentina, vector control shifted from a vertical to a fully horizontal strategy based on community participation between 1992 and 2004. The effects of such strategy on Triatoma infestans, the main domestic vector, and on disease transmission have not been assessed.

Methods and Findings

Based on retrospective (1993–2004) records from the Argentinean Ministry of Health for the Moreno Department, Northwestern Argentina, we performed a cost-effectiveness (CE) analysis and compared the observed CE of the fully horizontal vector control strategy with the expected CE for a vertical or a mixed (i.e., vertical attack phase followed by horizontal surveillance) strategy. Total direct costs (in 2004 US$) of the horizontal and mixed strategies were, respectively, 3.3 and 1.7 times lower than the costs of the vertical strategy, due to reductions in personnel costs. The estimated CE ratios for the vertical, mixed and horizontal strategies were US$132, US$82 and US$45 per averted human case, respectively. When per diems were excluded from the costs (i.e., simulating the decentralization of control activities), the CE of vertical, mixed and horizontal strategies was reduced to US$60, US$42 and US$32 per averted case, respectively.

Conclusions and Significance

The mixed strategy would have averted between 1.6 and 4.0 times more human cases than the fully horizontal strategy, and would have been the most cost-effective option to interrupt parasite transmission in the Department. In rural and dispersed areas where waning vertical vector programs cannot accomplish full insecticide coverage, alternative strategies need to be developed. If properly implemented, community participation represents not only the most appealing but also the most cost-effective alternative to accomplish such objectives.     

Streamlining scenario analysis and optimization of key choices in value chains using a modular LCA approach

Purpose

The environmental performance of products or services is often a result of a number of key decisions that shape their life cycles (e.g., techology choices). This paper introduces a modular LCA approach that is capable of reducing the effort involved in performing scenario analyses and optimization when several key choices along a product’s value chain lead to many alternative life cycles.

Methods

The main idea is that the value chain of a product can be divided into interconnected but exchangeable modules, which together represent a full life cycle. A module is comprised of unit processes from the practitioner’s LCI database. The inputs, outputs, and system boundaries of each module can be tailored to the context of the studied system. Alternatives arise whenever multiple modules produce substitutable products. Unlike in conventional LCI databases, no copies are necessary to represent the same process with different inputs. A module-product matrix is used to store this information. It can be used as a basis for an automated scenario analysis of all alternatives or as an input to an optimization model.

Results and discussion

Our approach is illustrated in two case studies: (1) Passenger car fuel choices are modeled by 15 modules representing 33 alternative value chains for diesel, petrol, natural gas and electric cars. The automated comparison of LCA results indicates that electric mobility is often the preferable option from a climate perspective, but impacts depend strongly on the electricity source. (2) A dynamic optimization model including stocks is built from eight modules to analyze the optimal use of wood for material and energy applications. Results indicate that although direct substitution benefits are higher for energy applications, cascading use of wood can maximize environmental performance over the entire life cycle.

Conclusions

The modular LCA approach permits an efficient modeling and comparison of alternative product life cycles, enabling practitioners to focus on key decisions. It can be applied to exploit a potential that is hidden in LCI databases, which is that they contain many specific inventories but not all useful combinations in the context of scenario analyses. The user-defined level of abstraction that is introduced through modules can be helpful in the communication of LCA results. The modular approach also facilitates the integration of LCA and optimization as well as other industrial ecology methods. An open source software is provided to enable others to apply and further develop our implementation of a modular LCA approach.

     

Identification of responsive gene modules by network-based gene clustering and extending: application to inflammation and angiogenesis

Background  

Cell responses to environmental stimuli are usually organized as relatively separate responsive gene modules at the molecular level. Identification of responsive gene modules rather than individual differentially expressed (DE) genes will provide important information about the underlying molecular mechanisms. Most of current methods formulate module identification as an optimization problem: find the active sub-networks in the genome-wide gene network by maximizing the objective function considering the gene differential expression and/or the gene-gene co-expression information. Here we presented a new formulation of this task: a group of closely-connected and co-expressed DE genes in the gene network are regarded as the signatures of the underlying responsive gene modules; the modules can be identified by finding the signatures and then recovering the "missing parts" by adding the intermediate genes that connect the DE genes in the gene network.     

Tests for finding complex patterns of differential expression in cancers: towards individualized medicine

Background  

Microarray studies in cancer compare expression levels between two or more sample groups on thousands of genes. Data analysis follows a population-level approach (e.g., comparison of sample means) to identify differentially expressed genes. This leads to the discovery of 'population-level' markers, i.e., genes with the expression patterns A > B and B > A. We introduce the PPST test that identifies genes where a significantly large subset of cases exhibit expression values beyond upper and lower thresholds observed in the control samples.     

RRW: repeated random walks on genome-scale protein networks for local cluster discovery

Background  

We propose an efficient and biologically sensitive algorithm based on repeated random walks (RRW) for discovering functional modules, e.g., complexes and pathways, within large-scale protein networks. Compared to existing cluster identification techniques, RRW implicitly makes use of network topology, edge weights, and long range interactions between proteins.     

Comparisons of gene coexpression network modules in breast cancer and ovarian cancer

Background

Breast cancer and ovarian cancer are hormone driven and are known to have some predisposition genes in common such as the two well known cancer genes BRCA1 and BRCA2. The objective of this study is to compare the coexpression network modules of both cancers, so as to infer the potential cancer-related modules.

Methods

We applied the eigen-decomposition to the matrix that integrates the gene coexpression networks of both breast cancer and ovarian cancer. With hierarchical clustering of the related eigenvectors, we obtained the network modules of both cancers simultaneously. Enrichment analysis on Gene Ontology (GO), KEGG pathway, Disease Ontology (DO), and Gene Set Enrichment Analysis (GSEA) in the identified modules was performed.

Results

We identified 43 modules that are enriched by at least one of the four types of enrichments. 31, 25, and 18 modules are enriched by GO terms, KEGG pathways, and DO terms, respectively. The structure of 29 modules in both cancers is significantly different with p-values less than 0.05, of which 25 modules have larger densities in ovarian cancer. One module was found to be significantly enriched by the terms related to breast cancer from GO, KEGG and DO enrichment. One module was found to be significantly enriched by ovarian cancer related terms.

Conclusion

Breast cancer and ovarian cancer share some common properties on the module level. Integration of both cancers helps identifying the potential cancer associated modules.

     

Characterization and Comparison of the Tissue-Related Modules in Human and Mouse

Background

Due to the advances of high throughput technology and data-collection approaches, we are now in an unprecedented position to understand the evolution of organisms. Great efforts have characterized many individual genes responsible for the interspecies divergence, yet little is known about the genome-wide divergence at a higher level. Modules, serving as the building blocks and operational units of biological systems, provide more information than individual genes. Hence, the comparative analysis between species at the module level would shed more light on the mechanisms underlying the evolution of organisms than the traditional comparative genomics approaches.

Results

We systematically identified the tissue-related modules using the iterative signature algorithm (ISA), and we detected 52 and 65 modules in the human and mouse genomes, respectively. The gene expression patterns indicate that all of these predicted modules have a high possibility of serving as real biological modules. In addition, we defined a novel quantity, “total constraint intensity,” a proxy of multiple constraints (of co-regulated genes and tissues where the co-regulation occurs) on the evolution of genes in module context. We demonstrate that the evolutionary rate of a gene is negatively correlated with its total constraint intensity. Furthermore, there are modules coding the same essential biological processes, while their gene contents have diverged extensively between human and mouse.

Conclusions

Our results suggest that unlike the composition of module, which exhibits a great difference between human and mouse, the functional organization of the corresponding modules may evolve in a more conservative manner. Most importantly, our findings imply that similar biological processes can be carried out by different sets of genes from human and mouse, therefore, the functional data of individual genes from mouse may not apply to human in certain occasions.     

Identifying Thresholds for Ecosystem-Based Management

Background

One of the greatest obstacles to moving ecosystem-based management (EBM) from concept to practice is the lack of a systematic approach to defining ecosystem-level decision criteria, or reference points that trigger management action.

Methodology/Principal Findings

To assist resource managers and policymakers in developing EBM decision criteria, we introduce a quantitative, transferable method for identifying utility thresholds. A utility threshold is the level of human-induced pressure (e.g., pollution) at which small changes produce substantial improvements toward the EBM goal of protecting an ecosystem''s structural (e.g., diversity) and functional (e.g., resilience) attributes. The analytical approach is based on the detection of nonlinearities in relationships between ecosystem attributes and pressures. We illustrate the method with a hypothetical case study of (1) fishing and (2) nearshore habitat pressure using an empirically-validated marine ecosystem model for British Columbia, Canada, and derive numerical threshold values in terms of the density of two empirically-tractable indicator groups, sablefish and jellyfish. We also describe how to incorporate uncertainty into the estimation of utility thresholds and highlight their value in the context of understanding EBM trade-offs.

Conclusions/Significance

For any policy scenario, an understanding of utility thresholds provides insight into the amount and type of management intervention required to make significant progress toward improved ecosystem structure and function. The approach outlined in this paper can be applied in the context of single or multiple human-induced pressures, to any marine, freshwater, or terrestrial ecosystem, and should facilitate more effective management.     

eGender—from e-Learning to e-Research: a web-based interactive knowledge-sharing platform for sex- and gender-specific medical education

Background

Sex and Gender Medicine is a novel discipline that provides equitable medical care for society and improves outcomes for both male and female patients. The integration of sex- and gender-specific knowledge into medical curricula is limited due to adequate learning material, systematic teacher training and an innovative communication strategy. We aimed at initiating an e-learning and knowledge-sharing platform for Sex and Gender Medicine, the eGender platform (http://egender.charite.de), to ensure that future doctors and health professionals will have adequate knowledge and communication skills on sex and gender differences in order to make informed decisions for their patients.

Methods

The web-based eGender knowledge-sharing platform was designed to support the blended learning pedagogical teaching concept and follows the didactic concept of constructivism. Learning materials developed by Sex and Gender Medicine experts of seven universities have been used as the basis for the new learning tools. The content of these tools is patient-centered and provides add-on information on gender-sensitive aspects of diseases. The structural part of eGender was designed and developed using the open source e-learning platform Moodle. The eGender platform comprises an English and a German version of e-learning modules: one focusing on basic knowledge and seven on specific medical disciplines. Each module consists of several courses corresponding to a disease or symptom complex. Self-organized learning has to be managed by using different learning tools, e.g., texts and audiovisual material, tools for online communication and collaborative work.

Results

More than 90 users from Europe registered for the eGender Medicine learning modules. The most frequently accessed module was “Gender Medicine—Basics” and the users favored discussion forums. These e-learning modules fulfill the quality criteria for higher education and are used within the elective Master Module “Gender Medicine—Basics” implemented into the accredited Master of Public Health at Charité—Berlin.

Conclusions

The eGender platform is a flexible and user-friendly electronical knowledge-sharing platform providing evidence-based high-quality learning material used by a growing number of registered users. The eGender Medicine learning modules could be key in the reform of medical curricula to integrate Sex and Gender Medicine into the education of health professionals.

     

Interactions among Stalk Modules of Thrombospondin-1

Thrombospondin-1 is a trimeric, modular calcium-binding glycoprotein. The subunit is composed of an N-terminal module; oligomerization domain; stalk modules including a von Willebrand factor type C module, three properdin or thrombospondin type 1 repeat (TSR) modules, and two thrombospondin-type EGF-like modules; and a C-terminal signature domain comprising single copies of the epidermal growth factor (EGF)-like, wire, and lectin-like modules. Conformational changes in the signature domain influence ligand binding to the N-terminal modules. Interactions have been demonstrated among the modules of the signature domain and the thrombospondin-type EGF-like modules. We have extended this analysis to the rest of the stalk modules. Differential scanning calorimetry revealed interactions between the most C-terminal TSR module and the EGF-like modules. Calorimetry and differences in expression levels of single versus tandem modules indicated that the three TSRs interact with each other as well. No evidence of interactions between the von Willebrand factor type C and TSR modules were detected by differential scanning calorimetry, circular dichroism, or intrinsic fluorescence. These results indicate that the TSR and thrombospondin-type EGF-like stalk modules act as a unit that may relay conformational information between the N-terminal and C-terminal parts of the protein.Thrombospondin-1 (TSP-1)² is a major secreted protein of platelets that plays multiple roles after vascular injury (1, 2). TSPs are a family of multimodular, calcium-binding, extracellular glycoproteins. There are five family members in tetropods, each of which has a specific pattern of expression in embryonic and adult tissues (3). TSPs have two unique features, a signature domain comprising single copies of EGF-like, Ca²⁺-binding wire, and lectin-like modules and the TSP-type EGF-like module in which Cys⁴ and Cys⁵ are separated by two rather than one residue (3, 4). The family falls into two groups: A or trimeric TSPs, TSP-1 and TSP-2; and B or pentameric TSPs, TSP-3, TSP-4, and TSP-5. As depicted in Fig. 1, a subunit of the group A TSPs is composed of an N-terminal module tethered to an oligomerization domain, a von Willebrand Factor type C (vWF-C) module, three properdin or TSP type 1 repeat (TSR) modules, two TSP-type EGF-like modules, and the signature domain (3, 4). Subunits of group B TSPs lack vWF-C and TSR modules and have an extra TSP-type EGF-like module (4). Multiple interactions have been demonstrated among the modules of the signature domain of Ca²⁺-replete TSP-2 and TSP-5 (5, 6) and between the signature domain wire and second TSP-type EGF-like module of Ca²⁺-replete TSP-2 (5, 7).Open in a separate windowFIGURE 1.Schematics of (A) TSP-1 stalk modules studied in this paper, (B) TSP-1 in its Ca²⁺-depleted conformation, and (C) TSP-1 in its Ca²⁺-replete formation. Parts of TSP-1 in panels A and B are labeled as follows: N, N-terminal module; T, tether; C, vWF-C module; P, properdin or TSR module, E, EGF-like module; wire, Ca²⁺-binding repeats with 26 Ca²⁺-binding sites; and L, lectin-like module. The TSP-type EGF-like modules, E1 and E2, contain central shading. Sites of binding to heparin sulfate proteoglycan (HSPG), latent transforming growth factor-β (TGF), and CD36 are indicated in panel C. The schematics have been drawn based on structures described in the text. Sites of fucosylation of TSRs are indicated by open diamonds, and inter-module CPIXG sequences between P2 and P3 and between P3 and E1 are indicated with dots. As per the “Discussion,” changes in conformation and charge density of the signature domain due to gain or loss of Ca²⁺ are proposed to be propagated throughout trimeric TSP-1 by the stalk modules.TSP-1 has a distinctive appearance when examined by rotary shadowing electron microscopy: three bunched globules, which are thought to be the N-terminal modules, are connected by three stalks to three larger globules thought to be the C-terminal signature domains (4). Rotary shadowing electron microscopy demonstrates a striking conformational change upon removal of Ca²⁺ from the C-terminal signature domain with apparent lengthening of the stalk and loss of size of the C-terminal globules (8–10). Considerations of structures of the parts of TSP-1 indicate that the vWF-C, TSR, and TSP-type EGF-like modules form the stalk in Ca²⁺-replete TSP-1 (4), as depicted in Fig. 1. Immunochemical studies suggest that lengthening of the stalk is due, at least in part, to unraveling of two of the 13 Ca²⁺-binding repeats of the wire module (11).Removal of Ca²⁺ from binding sites on the C-terminal signature domain impacts binding of ligands or antibodies to the N-terminal modules of TSP-1 (12). The N700S polymorphism in TSP-1 that alters coordination of Ca²⁺ by the first Ca²⁺-binding wire repeat (13) also impacts interactions of the N-terminal modules with ligands (14). These observations indicate that TSP-1 possesses an allosteric mechanism whereby changes in the C-terminal signature domain are transmitted to the N-terminal modules. We have reported that the two TSP-type EGF-like modules and the signature domain EGF-like module interact with each other, suggesting a mechanism by which conformational changes in the signature domain can be propagated N-terminal as far as the first TSP-type EGF-like module (15). We have now explored the potential of EGF-like modules to work with TSR and vWF-C modules to transmit conformational information between the two ends of TSP-1.     

Social Network Analysis Reveals the Negative Effects of Attention-Deficit/Hyperactivity Disorder (ADHD) Symptoms on Friend-Based Student Networks

Introduction

Social network analysis has emerged as a promising tool in modern social psychology. This method can be used to examine friend-based social relationships in terms of network theory, with nodes representing individual students and ties representing relationships between students (e.g., friendships and kinships). Using social network analysis, we investigated whether greater severity of ADHD symptoms is correlated with weaker peer relationships among elementary school students.

Methods

A total of 562 sixth-graders from two elementary schools (300 males) provided the names of their best friends (maximum 10 names). Their teachers rated each student’s ADHD symptoms using an ADHD rating scale.

Results

The results showed that 10.2% of the students were at high risk for ADHD. Significant group differences were observed between the high-risk students and other students in two of the three network parameters (degree, centrality and closeness) used to assess friendship quality, with the high-risk group showing significantly lower values of degree and closeness compared to the other students. Moreover, negative correlations were found between the ADHD rating and two social network analysis parameters.

Conclusion

Our findings suggest that the severity of ADHD symptoms is strongly correlated with the quality of social and interpersonal relationships in students with ADHD symptoms.     

Pesticide exposure and risk of Parkinson's disease: A family-based case-control study

Background  

Pesticides and correlated lifestyle factors (e.g., exposure to well-water and farming) are repeatedly reported risk factors for Parkinson's disease (PD), but few family-based studies have examined these relationships.