Prophage proteins alter long noncoding RNA and DNA of developing sperm to induce a paternal-effect lethality

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Abstract

The extent to which prophage proteins interact with eukaryotic macromolecules is largely unknown. In this work, we show that cytoplasmic incompatibility factor A (CifA) and B (CifB) proteins, encoded by prophage WO of the endosymbiont Wolbachia, alter long noncoding RNA (lncRNA) and DNA during Drosophila sperm development to establish a paternal-effect embryonic lethality known as cytoplasmic incompatibility (CI). CifA is a ribonuclease (RNase) that depletes a spermatocyte lncRNA important for the histone-to-protamine transition of spermiogenesis. Both CifA and CifB are deoxyribonucleases (DNases) that elevate DNA damage in late spermiogenesis. lncRNA knockdown enhances CI, and mutagenesis links lncRNA depletion and subsequent sperm chromatin integrity changes to embryonic DNA damage and CI. Hence, prophage proteins interact with eukaryotic macromolecules during gametogenesis to create a symbiosis that is fundamental to insect evolution and vector control.

Editor’s summary

Many arthropods carry symbiotic bacteria. Some, including Wolbachia strains, have the capacity to cause male sterility in a process called cytoplasmic incompatibility, and thereby have influenced the evolutionary trajectory of some insect lineages. One symbiont strain called w Mel has been successfully redeployed at scale for mosquito control. Kaur et al . delved into the mechanism that causes cytoplasmic incompatibility, finding that a combination of w Mel bacteriophage proteins enter sperm nuclei and act in a cascade of reactions to block embryo development. One protein is an RNase that depletes an insect long noncoding RNA that is required for the transformation of histone to protamine during sperm development. Both proteins can also nick DNA to compromise insect DNA integrity in late spermatids, which ultimately causes unrepairable embryo damage and sterility. —Caroline Ash

Abstract

Wolbachia prophage manipulates sperm noncoding RNA and DNA vital for chromatin integrity and offers potential leads for vector control.

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Geneious Basic: An integrated and extendable desktop software platform for the organization and analysis of sequence data

Matthew Kearse, Richard Moir, Amy Wilson … (2012)

Summary: The two main functions of bioinformatics are the organization and analysis of biological data using computational resources. Geneious Basic has been designed to be an easy-to-use and flexible desktop software application framework for the organization and analysis of biological data, with a focus on molecular sequences and related data types. It integrates numerous industry-standard discovery analysis tools, with interactive visualizations to generate publication-ready images. One key contribution to researchers in the life sciences is the Geneious public application programming interface (API) that affords the ability to leverage the existing framework of the Geneious Basic software platform for virtually unlimited extension and customization. The result is an increase in the speed and quality of development of computation tools for the life sciences, due to the functionality and graphical user interface available to the developer through the public API. Geneious Basic represents an ideal platform for the bioinformatics community to leverage existing components and to integrate their own specific requirements for the discovery, analysis and visualization of biological data. Availability and implementation: Binaries and public API freely available for download at http://www.geneious.com/basic, implemented in Java and supported on Linux, Apple OSX and MS Windows. The software is also available from the Bio-Linux package repository at http://nebc.nerc.ac.uk/news/geneiousonbl. Contact: peter@biomatters.com

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MUSCLE: a multiple sequence alignment method with reduced time and space complexity

Robert Edgar (2004)

Background In a previous paper, we introduced MUSCLE, a new program for creating multiple alignments of protein sequences, giving a brief summary of the algorithm and showing MUSCLE to achieve the highest scores reported to date on four alignment accuracy benchmarks. Here we present a more complete discussion of the algorithm, describing several previously unpublished techniques that improve biological accuracy and / or computational complexity. We introduce a new option, MUSCLE-fast, designed for high-throughput applications. We also describe a new protocol for evaluating objective functions that align two profiles. Results We compare the speed and accuracy of MUSCLE with CLUSTALW, Progressive POA and the MAFFT script FFTNS1, the fastest previously published program known to the author. Accuracy is measured using four benchmarks: BAliBASE, PREFAB, SABmark and SMART. We test three variants that offer highest accuracy (MUSCLE with default settings), highest speed (MUSCLE-fast), and a carefully chosen compromise between the two (MUSCLE-prog). We find MUSCLE-fast to be the fastest algorithm on all test sets, achieving average alignment accuracy similar to CLUSTALW in times that are typically two to three orders of magnitude less. MUSCLE-fast is able to align 1,000 sequences of average length 282 in 21 seconds on a current desktop computer. Conclusions MUSCLE offers a range of options that provide improved speed and / or alignment accuracy compared with currently available programs. MUSCLE is freely available at .

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Protein secondary structure prediction based on position-specific scoring matrices.

D. JONES (1999)

A two-stage neural network has been used to predict protein secondary structure based on the position specific scoring matrices generated by PSI-BLAST. Despite the simplicity and convenience of the approach used, the results are found to be superior to those produced by other methods, including the popular PHD method according to our own benchmarking results and the results from the recent Critical Assessment of Techniques for Protein Structure Prediction experiment (CASP3), where the method was evaluated by stringent blind testing. Using a new testing set based on a set of 187 unique folds, and three-way cross-validation based on structural similarity criteria rather than sequence similarity criteria used previously (no similar folds were present in both the testing and training sets) the method presented here (PSIPRED) achieved an average Q3 score of between 76.5% to 78.3% depending on the precise definition of observed secondary structure used, which is the highest published score for any method to date. Given the success of the method in CASP3, it is reasonable to be confident that the evaluation presented here gives a fair indication of the performance of the method in general. Copyright 1999 Academic Press.