Identification and Functional Characterization of Gene Components of Type VI Secretion System in Bacterial Genomes

A new secretion system, called the Type VI Secretion system (T6SS), was recently reported in Vibrio cholerae, Pseudomonas aeruginosa and Burkholderia mallei. A total of 18 genes have been identified to be belonging to this secretion system in V. cholerae. Here we attempt to identify presence of T6SS in other bacterial genomes. This includes identification of orthologous sequences, conserved motifs, domains, families, 3D folds, genomic islands containing T6SS components, phylogenetic profiles and protein-protein association of these components. Our analysis indicates presence of T6SS in 42 bacteria and its absence in most of their non-pathogenic species, suggesting the role of T6SS in imparting pathogenicity to an organism. Analysis of genomic regions containing T6SS components, phylogenetic profiles and protein-protein association of T6SS components indicate few additional genes which could be involved in this secretion system. Based on our studies, functional annotations were assigned to most of the components. Except one of the genes, we could group all the other genes of T6SS into those belonging to the puncturing device, and those located in the outer membrane, transmembrane and inner membrane. Based on our analysis, we have proposed a model of T6SS and have compared the same with the other bacterial secretion systems

Environmental Response and Genomic Regions Correlated with Rice Root Growth and Yield under Drought in the OryzaSNP Panel across Multiple Study Systems

Funding: This research was funded by the Generation Challenge Program (GCP) project G3008.06, “Targeting Drought-Avoidance Root Traits to Enhance Rice Productivity under Water-Limited Environments". The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Peer reviewedPublisher PD

Dynamic Changes in Protein Functional Linkage Networks Revealed by Integration with Gene Expression Data

Response of cells to changing environmental conditions is governed by the dynamics of intricate biomolecular interactions. It may be reasonable to assume, proteins being the dominant macromolecules that carry out routine cellular functions, that understanding the dynamics of protein∶protein interactions might yield useful insights into the cellular responses. The large-scale protein interaction data sets are, however, unable to capture the changes in the profile of protein∶protein interactions. In order to understand how these interactions change dynamically, we have constructed conditional protein linkages for Escherichia coli by integrating functional linkages and gene expression information. As a case study, we have chosen to analyze UV exposure in wild-type and SOS deficient E. coli at 20 minutes post irradiation. The conditional networks exhibit similar topological properties. Although the global topological properties of the networks are similar, many subtle local changes are observed, which are suggestive of the cellular response to the perturbations. Some such changes correspond to differences in the path lengths among the nodes of carbohydrate metabolism correlating with its loss in efficiency in the UV treated cells. Similarly, expression of hubs under unique conditions reflects the importance of these genes. Various centrality measures applied to the networks indicate increased importance for replication, repair, and other stress proteins for the cells under UV treatment, as anticipated. We thus propose a novel approach for studying an organism at the systems level by integrating genome-wide functional linkages and the gene expression data

Understanding Communication Signals during Mycobacterial Latency through Predicted Genome-Wide Protein Interactions and Boolean Modeling

About 90% of the people infected with Mycobacterium tuberculosis carry latent bacteria that are believed to get activated upon immune suppression. One of the fundamental challenges in the control of tuberculosis is therefore to understand molecular mechanisms involved in the onset of latency and/or reactivation. We have attempted to address this problem at the systems level by a combination of predicted functional protein∶protein interactions, integration of functional interactions with large scale gene expression studies, predicted transcription regulatory network and finally simulations with a Boolean model of the network. Initially a prediction for genome-wide protein functional linkages was obtained based on genome-context methods using a Support Vector Machine. This set of protein functional linkages along with gene expression data of the available models of latency was employed to identify proteins involved in mediating switch signals during dormancy. We show that genes that are up and down regulated during dormancy are not only coordinately regulated under dormancy-like conditions but also under a variety of other experimental conditions. Their synchronized regulation indicates that they form a tightly regulated gene cluster and might form a latency-regulon. Conservation of these genes across bacterial species suggests a unique evolutionary history that might be associated with M. tuberculosis dormancy. Finally, simulations with a Boolean model based on the regulatory network with logical relationships derived from gene expression data reveals a bistable switch suggesting alternating latent and actively growing states. Our analysis based on the interaction network therefore reveals a potential model of M. tuberculosis latency

Integrated genomic approaches implicate osteoglycin (Ogn) in the regulation of left ventricular mass

Left ventricular mass (LVM) and cardiac gene expression are complex traits regulated by factors both intrinsic and extrinsic to the heart. To dissect the major determinants of LVM, we combined expression quantitative trait locus1 and quantitative trait transcript (QTT) analyses of the cardiac transcriptome in the rat. Using these methods and in vitro functional assays, we identified osteoglycin (Ogn) as a major candidate regulator of rat LVM, with increased Ogn protein expression associated with elevated LVM. We also applied genome-wide QTT analysis to the human heart and observed that, out of 22,000 transcripts, OGN transcript abundance had the highest correlation with LVM. We further confirmed a role for Ogn in the in vivo regulation of LVM in Ogn knockout mice. Taken together, these data implicate Ogn as a key regulator of LVM in rats, mice and humans, and suggest that Ogn modifies the hypertrophic response to extrinsic factors such as hypertension and aortic stenosi

A Theoretical Analysis of the Geography of Schistosomiasis in Burkina Faso Highlights the Roles of Human Mobility and Water Resources Development in Disease Transmission

We study the geography of schistosomiasis across Burkina Faso by means of a spatially explicit model of water-based disease dynamics. The model quantitatively addresses the geographic stratification of disease burden in a novel framework by explicitly accounting for drivers and controls of the disease, including spatial information on the distributions of population and infrastructure, jointly with a general description of human mobility and climatic/ecological drivers. Spatial patterns of disease are analysed by the extraction and the mapping of suitable eigenvectors of the Jacobian matrix subsuming the stability of the disease-free equilibrium. The relevance of the work lies in the novel mapping of disease burden, a byproduct of the parametrization induced by regional upscaling, by model-guided field validations and in the predictive scenarios allowed by exploiting the range of possible parameters and processes. Human mobility is found to be a primary control at regional scales both for pathogen invasion success and the overall distribution of disease burden. The effects of water resources development highlighted by systematic reviews are accounted for by the average distances of human settlements from water bodies that are habitats for the parasite's intermediate host. Our results confirm the empirical findings about the role of water resources development on disease spread into regions previously nearly disease-free also by inspection of empirical prevalence patterns. We conclude that while the model still needs refinements based on field and epidemiological evidence, the proposed framework provides a powerful tool for large-scale public health planning and schistosomiasis management

A dataset of acoustic measurements from soundscapes collected worldwide during the COVID-19 pandemic

Political responses to the COVID-19 pandemic led to changes in city soundscapes around the globe. From March to October 2020, a consortium of 261 contributors from 35 countries brought together by the Silent Cities project built a unique soundscape recordings collection to report on local acoustic changes in urban areas. We present this collection here, along with metadata including observational descriptions of the local areas from the contributors, open-source environmental data, open-source confinement levels and calculation of acoustic descriptors. We performed a technical validation of the dataset using statistical models run on a subset of manually annotated soundscapes. Results confirmed the large-scale usability of ecoacoustic indices and automatic sound event recognition in the Silent Cities soundscape collection. We expect this dataset to be useful for research in the multidisciplinary field of environmental sciences