Quantifying water quality improvements through use of precision herbicide application technologies in a dry-tropical, furrow-irrigated cropping system

This study compared water quality effects of using precision herbicide application technologies and traditional spraying approaches across several regulated 'priority' and alternative preand post-emergent herbicides in a northern Australian cane farming system. Use of herbicide banding spray technologies resulted in pre-emergent herbicide load reductions, extending substantially beyond simple proportionate decreases in the amount of herbicide ingredient applied to paddocks. Aquatic risk assessment from resultant chemical mixtures leaving paddocks, and upscaled to local catchment concentrations, highlighted that precision application technologies could markedly reduce the ecological risk of pre-emergent herbicides. These risk reductions were, however, often complicated by the additional toxicity of post-emergent herbicides in mixtures, some associated with the adoption of band-spraying weed treatments. While the currently regulated priority herbicide, diuron, posed the greatest risk to the environment, alternative herbicides could still pose significant environmental risks, although these relative risks were lower at more ecologically relevant concentrations, typically found in the local freshwater ecosystems. Results underline the need for a carefully considered approach to integrating alternative herbicides and precision application technologies into improved weed management by irrigating cane farmers. Recent government changes to the appraisal of water quality improvement progress, from load-based to ecosystem-based targets, involving a much broader suite of herbicides, also appear likely to complicate assessment of the environmental impacts of practice change adoption for the industry

Database of RNA binding protein expression and disease dynamics (READ DB)

RNA Binding Protein (RBP) Expression and Disease Dynamics database (READ DB) is a non-redundant, curated database of human RBPs. RBPs curated from different experimental studies are reported with their annotation, tissue-wide RNA and protein expression levels, evolutionary conservation, disease associations, protein-protein interactions, microRNA predictions, their known RNA recognition sequence motifs as well as predicted binding targets and associated functional themes, providing a one stop portal for understanding the expression, evolutionary trajectories and disease dynamics of RBPs in the context of post-transcriptional regulatory networks

Go-Kit: A Tool To Enable Energy Landscape Exploration of Proteins.

Coarse-grained Go̅-like models, based on the principle of minimal frustration, provide valuable insight into fundamental questions in the field of protein folding and dynamics. In conjunction with commonly used molecular dynamics (MD) simulations, energy landscape exploration methods like discrete path sampling (DPS) with Go̅-like models can provide quantitative details of the thermodynamics and kinetics of proteins. Here we present Go-kit, a software that facilitates the setup of MD and DPS simulations of several flavors of Go̅-like models. Go-kit is designed for use with MD (GROMACS) and DPS (PATHSAMPLE) simulation engines that are open source. The Go-kit code is written in python2.7 and is also open source. A case study for the ribosomal protein S6 is discussed to illustrate the utility of the software, which is available at https://github.com/gokit1/gokit .epsr

Energy Landscape of the Designed Protein Top7.

To fold on biologically relevant time scales, proteins have evolved funnelled energy landscapes with minimal energetic trapping. However, the polymeric nature of proteins and the spatial arrangement of secondary structural elements can create topological traps and slow folding. It is challenging to identify, visualize, and quantify such topological trapping. Designed proteins have not had the benefit of evolution, and it has been hypothesized that de novo designed protein topologies may therefore feature more topological trapping. Structure-based models (SBMs) are inherently funnelled, removing most energetic trapping, and can thus be used to isolate the effect of protein topology on the landscape. Here, we compare Top7, a designed protein with a topology unknown in nature, to S6, a naturally occurring ribosomal protein of similar size and topology. Possible kinetic traps and the energetic barriers separating them from the native state are elucidated. We find that, even with an SBM, the potential energy landscape (PEL) of the designed protein is more frustrated than that of the natural protein. We then quantify the effect of adding non-native hydrophobic interactions and coarse-grained side-chains through a frustration density parameter. A clear increase in frustration is observed including side-chains, whereas adding hydrophobic interactions leads to a narrowing of the funnel and a decrease in complexity. The most likely (un)folding routes for all models are derived through the construction of probability contact maps. The ability to quantitatively understand and optimize the organization of the PEL for designed proteins may enable us to design structure-seeking landscapes, mimicking the effect of evolution.epsr

Dissecting the expression relationships between RNA-binding proteins and their cognate targets in eukaryotic post-transcriptional regulatory networks

RNA-binding proteins (RBPs) are pivotal in orchestrating several steps in the metabolism of RNA in eukaryotes thereby controlling an extensive network of RBP-RNA interactions. Here, we employed CLIP (cross-linking immunoprecipitation)-seq datasets for 60 human RBPs and RIP-ChIP (RNP immunoprecipitation-microarray) data for 69 yeast RBPs to construct a network of genome-wide RBP- target RNA interactions for each RBP. We show in humans that majority (~78%) of the RBPs are strongly associated with their target transcripts at transcript level while ~95% of the studied RBPs were also found to be strongly associated with expression levels of target transcripts when protein expression levels of RBPs were employed. At transcript level, RBP - RNA interaction data for the yeast genome, exhibited a strong association for 63% of the RBPs, confirming the association to be conserved across large phylogenetic distances. Analysis to uncover the features contributing to these associations revealed the number of target transcripts and length of the selected protein-coding transcript of an RBP at the transcript level while intensity of the CLIP signal, number of RNA-Binding domains, location of the binding site on the transcript, to be significant at the protein level. Our analysis will contribute to improved modelling and prediction of post-transcriptional network

The human RBPome: From genes and proteins to human disease

RNA binding proteins (RBPs) play a central role in mediating post transcriptional regulation of genes. However less is understood about them and their regulatory mechanisms. In this study, we construct a catalogue of 1344 experimentally confirmed RBPs. The domain architecture of RBPs enabled us to classify them into three groups — Classical (29%), Non-classical (19%) and unclassified (52%). A higher percentage of proteins with unclassified domains reveals the presence of various uncharacterised motifs that can potentially bind RNA. RBPs were found to be highly disordered compared to Non-RBPs (p < 2.2e-16, Fisher's exact test), suggestive of a dynamic regulatory role of RBPs in cellular signalling and homeostasis. Evolutionary analysis in 62 different species showed that RBPs are highly conserved compared to Non-RBPs (p < 2.2e-16, Wilcox-test), reflecting the conservation of various biological processes like mRNA splicing and ribosome biogenesis. The expression patterns of RBPs from human proteome map revealed that ~ 40% of them are ubiquitously expressed and ~ 60% are tissue-specific. RBPs were also seen to be highly associated with several neurological disorders, cancer and inflammatory diseases. Anatomical contexts like B cells, T-cells, foetal liver and foetal brain were found to be strongly enriched for RBPs, implying a prominent role of RBPs in immune responses and different developmental stages. The catalogue and meta-analysis presented here should form a foundation for furthering our understanding of RBPs and the cellular networks they control, in years to come. This article is part of a Special Issue entitled: Proteomics in India

Uncovering RNA binding proteins associated with age and gender during liver maturation

In the present study, we perform an association analysis focusing on the expression changes of 1344 RNA Binding proteins (RBPs) as a function of age and gender in human liver. We identify 88 and 45 RBPs to be significantly associated with age and gender respectively. Experimental verification of several of the predicted associations in mice confirmed our findings. Our results suggest that a small fraction of the gender-associated RBPs (~40%) are expressed higher in males than females. Altogether, these observations show that several of these RBPs are important and conserved regulators in maintaining liver function. Further analysis of the protein interaction network of RBPs associated with age and gender based on the centrality measures like degree, betweenness and closeness revealed that several of these RBPs might be prominent players in aging liver and impart gender specific alterations in gene expression via the formation of protein complexes. Indeed, both age and gender-associated RBPs in liver were found to show significantly higher clustering coefficients and network centrality measures compared to non-associated RBPs. The compendium of RBPs and this study will help us gain insight into the role of post-transcriptional regulatory molecules in aging and gender specific expression of genes

Mutational landscape of RNA-binding proteins in human cancers

RNA Binding Proteins (RBPs) are a class of post-transcriptional regulatory molecules which are increasingly documented to be dysfunctional in cancer genomes. However, our current understanding of these alterations is limited. Here, we delineate the mutational landscape of ∼1300 RBPs in ∼6000 cancer genomes. Our analysis revealed that RBPs have an average of ∼3 mutations per Mb across 26 cancer types. We identified 281 RBPs to be enriched for mutations (GEMs) in at least one cancer type. GEM RBPs were found to undergo frequent frameshift and inframe deletions as well as missense, nonsense and silent mutations when compared to those that are not enriched for mutations. Functional analysis of these RBPs revealed the enrichment of pathways associated with apoptosis, splicing and translation. Using the OncodriveFM framework, we also identified more than 200 candidate driver RBPs that were found to accumulate functionally impactful mutations in at least one cancer. Expression levels of 15% of these driver RBPs exhibited significant difference, when transcriptome groups with and without deleterious mutations were compared. Functional interaction network of the driver RBPs revealed the enrichment of spliceosomal machinery, suggesting a plausible mechanism for tumorogenesis while network analysis of the protein interactions between RBPs unambiguously revealed the higher degree, betweenness and closeness centrality for driver RBPs compared to non-drivers. Analysis to reveal cancer-specific Ribonucleoprotein (RNP) mutational hotspots showed extensive rewiring even among common drivers between cancer types. Knockdown experiments on pan-cancer drivers such as SF3B1 and PRPF8 in breast cancer cell lines, revealed cancer subtype specific functions like selective stem cell features, indicating a plausible means for RBPs to mediate cancer-specific phenotypes. Hence, this study would form a foundation to uncover the contribution of the mutational spectrum of RBPs in dysregulating the post-transcriptional regulatory networks in different cancer types

Splicing factor ESRP1 controls ER-positive breast cancer by altering metabolic pathways

The epithelial splicing regulatory proteins 1 and 2 (ESRP1 and ESRP2) control the epithelial-to-mesenchymal transition (EMT) splicing program in cancer. However, their role in breast cancer recurrence is unclear. In this study, we report that high levels of ESRP1, but not ESRP2, are associated with poor prognosis in estrogen receptor positive (ER+) breast tumors. Knockdown of ESRP1 in endocrine-resistant breast cancer models decreases growth significantly and alters the EMT splicing signature, which we confirm using TCGA SpliceSeq data of ER+ BRCA tumors. However, these changes are not accompanied by the development of a mesenchymal phenotype or a change in key EMT-transcription factors. In tamoxifen-resistant cells, knockdown of ESRP1 affects lipid metabolism and oxidoreductase processes, resulting in the decreased expression of fatty acid synthase (FASN), stearoyl-CoA desaturase 1 (SCD1), and phosphoglycerate dehydrogenase (PHGDH) at both the mRNA and protein levels. Furthermore, ESRP1 knockdown increases the basal respiration and spare respiration capacity. This study reports a novel role for ESRP1 that could form the basis for the prevention of tamoxifen resistance in ER+ breast cancer