Consequences of recombination on traditional phylogenetic analysis

We investigate the shape of a phylogenetic tree reconstructed from sequences evolving under the coalescent with recombination. The motivation is that evolutionary inferences are often made from phylogenetic trees reconstructed from population data even though recombination may well occur (mtDNA or viral sequences) or does occur (nuclear sequences). We investigate the size and direction of biases when a single tree is reconstructed ignoring recombination. Standard software (PHYLIP) was used to construct the best phylogenetic tree from sequences simulated under the coalescent with recombination. With recombination present, the length of terminal branches and the total branch length are larger, and the time to the most recent common ancestor smaller, than for a tree reconstructed from sequences evolving with no recombination. The effects are pronounced even for small levels of recombination that may not be immediately detectable in a data set. The phylogenies when recombination is present superficially resemble phylogenies for sequences from an exponentially growing population. However, exponential growth has a different effect on statistics such as Tajima's D. Furthermore, ignoring recombination leads to a large overestimation of the substitution rate heterogeneity and the loss of the molecular clock. These results are discussed in relation to viral and mtDNA data sets.     

Assembly, secretion, and vacuolar delivery of a hybrid immunoglobulin in plants

Secretory immunoglobulin (Ig) A is a decameric Ig composed of four alpha-heavy chains, four light chains, a joining (J) chain, and a secretory component (SC). The heavy and light chains form two tetrameric Ig molecules that are joined by the J chain and associate with the SC. Expression of a secretory monoclonal antibody in tobacco (Nicotiana tabacum) has been described: this molecule (secretory IgA/G [SIgA/G]) was modified by having a hybrid heavy chain sequence consisting of IgG gamma-chain domains linked to constant region domains of an IgA alpha-chain. In tobacco, about 70% of the protein assembles to its final, decameric structure. We show here that SIgA/G assembly and secretion are slow, with only approximately 10% of the newly synthesized molecules being secreted after 24 h and the bulk probably remaining in the endoplasmic reticulum. In addition, a proportion of SIgA/G is delivered to the vacuole as at least partially assembled molecules by a process that is blocked by the membrane traffic inhibitor brefeldin A. Neither the SC nor the J chain are responsible for vacuolar delivery, because IgA/G tetramers have the same fate. The parent IgG tetrameric molecule, containing wild-type gamma-heavy chains, is instead secreted rapidly and efficiently. This strongly suggests that intracellular retention and vacuolar delivery of IgA/G is due to the alpha-domains present in the hybrid alpha/gamma-heavy chains and indicates that the plant secretory system may partially deliver to the vacuole recombinant proteins expected to be secreted.     

Comparison of [3H]tamsulosin and [3H]prazosin binding to wild-type and constitutively active alpha1B-adrenoceptors

We have tested the hypothesis that smaller alpha1B-adrenoceptor labeling by [3H]tamsulosin compared to [3H]prazosin is related to differential recognition of agonist low affinity states. Paired saturation binding experiments with [3H]prazosin and [3H]tamsulosin were performed in membrane preparations from rat liver and Rat- fibroblasts stably transfected with wild-type hamster alpha1B-adrenoceptors or a constitutively active mutant thereof. In all three settings [3H]tamsulosin labeled significantly fewer alpha1B-adrenoceptors than [3H]prazosin. In noradrenaline competition binding experiments, the percentage of agonist low affinity sites was smallest for the constitutively active alpha1B-adrenoceptor but the percentage of agonist low affinity sites recognized by [3H]tamsulosin and [3H]prazosin did not differ significantly. We conclude that [3H]tamsulosin labels fewer alpha1B-adrenoceptors than [3H]prazosin but this is not fully explained by a poorer labeling of agonist low affinity sites.     

Nucleolar Localization Elements of Xenopus laevis U3 Small Nucleolar RNA

The Nucleolar Localization Elements (NoLEs) of Xenopus laevis U3 small nucleolar RNA (snoRNA) have been defined. Fluorescein-labeled wild-type U3 snoRNA injected into Xenopus oocyte nuclei localized specifically to nucleoli as shown by fluorescence microscopy. Injection of mutated U3 snoRNA revealed that the 5′ region containing Boxes A and A′, known to be important for rRNA processing, is not essential for nucleolar localization. Nucleolar localization of U3 snoRNA was independent of the presence and nature of the 5′ cap and the terminal stem. In contrast, Boxes C and D, common to the Box C/D snoRNA family, are critical elements for U3 localization. Mutation of the hinge region, Box B, or Box C′ led to reduced U3 nucleolar localization. Results of competition experiments suggested that Boxes C and D act in a cooperative manner. It is proposed that Box B facilitates U3 snoRNA nucleolar localization by the primary NoLEs (Boxes C and D), with the hinge region of U3 subsequently base pairing to the external transcribed spacer of pre-rRNA, thus positioning U3 snoRNA for its roles in rRNA processing.     

Neural Control of Enhanced Filtering Demands in a Combined Flanker and Garner Conflict Task

Several studies demonstrated that visual filtering mechanisms might underlie both conflict resolution of the Flanker conflict and the control of the Garner effect. However, it remains unclear whether the mechanisms involved in the processing of both effects depend on similar filter mechanisms, such that especially the Garner effect is able to modulate filtering needs in the Flanker conflict. In the present experiment twenty-four subjects participated in a combined Garner and Flanker task during two runs of functional magnetic resonance imaging (fMRI) recordings. Behavioral data showed a significant Flanker but no Garner effect. A run-wise analysis, however, revealed a Flanker effect in the Garner filtering condition in the first experimental run, while we found a Flanker effect in the Garner baseline condition in the second experimental run. The fMRI data revealed a fronto-parietal network involved in the processing of both types of effects. Flanker interference was associated with activity in the inferior frontal gyrus, the anterior cingulate cortex, the precuneus as well as the inferior (IPL) and superior parietal lobule (SPL). Garner interference was associated with activation in middle frontal and middle temporal gyrus, the lingual gyrus as well as the IPL and SPL. Interaction analyses between the Garner and the Flanker effect additionally revealed differences between the two experimental runs. In the first experimental run, activity specifically related to the interaction of effects was found in frontal and parietal regions, while in the second run we found activity in the hippocampus, the parahippocampal cortex and the basal ganglia. This shift in activity for the interaction effects might be associated with a task-related learning process to control filtering demands. Especially perceptual learning mechanisms might play a crucial role in the present Flanker and Garner task design and, therefore, increased performance in the second experimental run could be the reason for the lack of behavioral Garner interference on the level of the whole experiment.     

Accurate Protein Complex Retrieval by Affinity Enrichment Mass Spectrometry (AE-MS) Rather than Affinity Purification Mass Spectrometry (AP-MS)

Protein–protein interactions are fundamental to the understanding of biological processes. Affinity purification coupled to mass spectrometry (AP-MS) is one of the most promising methods for their investigation. Previously, complexes were purified as much as possible, frequently followed by identification of individual gel bands. However, todays mass spectrometers are highly sensitive, and powerful quantitative proteomics strategies are available to distinguish true interactors from background binders. Here we describe a high performance affinity enrichment-mass spectrometry method for investigating protein–protein interactions, in which no attempt at purifying complexes to homogeneity is made. Instead, we developed analysis methods that take advantage of specific enrichment of interactors in the context of a large amount of unspecific background binders. We perform single-step affinity enrichment of endogenously expressed GFP-tagged proteins and their interactors in budding yeast, followed by single-run, intensity-based label-free quantitative LC-MS/MS analysis. Each pull-down contains around 2000 background binders, which are reinterpreted from troubling contaminants to crucial elements in a novel data analysis strategy. First the background serves for accurate normalization. Second, interacting proteins are not identified by comparison to a single untagged control strain, but instead to the other tagged strains. Third, potential interactors are further validated by their intensity profiles across all samples. We demonstrate the power of our AE-MS method using several well-known and challenging yeast complexes of various abundances. AE-MS is not only highly efficient and robust, but also cost effective, broadly applicable, and can be performed in any laboratory with access to high-resolution mass spectrometers.Protein–protein interactions are key to protein-mediated biological processes and influence all aspects of life. Therefore, considerable efforts have been dedicated to the mapping of protein–protein interactions. A classical experimental approach consists of co-immunoprecipitation of protein complexes combined with SDS-PAGE followed by Western blotting to identify complex members. More recently, high-throughput techniques have been introduced; among these affinity purification-mass spectrometry (AP-MS)¹ (1–3) and the yeast two-hybrid (Y2H) approach (4–6) are the most prominent. AP-MS, in particular, has great potential for detecting functional interactions under near-physiological conditions, and has already been employed for interactome mapping in several organisms (7–15). Various AP-MS approaches have evolved over time, that differ in expression, tagging, and affinity purification of the bait protein; fractionation, LC-MS measurement, and quantification of the sample; and in data analysis. Recent progress in the AP-MS field has been driven by two factors: A new generation of mass spectrometers (16) providing higher sequencing speed, sensitivity, and mass accuracy, and the development of quantitative MS strategies.In the early days of AP-MS, tagged bait proteins were mostly overexpressed, enhancing their recovery in the pull-down. However, overexpression comes at the cost of obscuring the true situation in the cell, potentially leading to the detection of false interactions (17). Today, increased MS instrument power helps in the detection of bait proteins and interactors expressed at endogenous levels, augmenting the chances to detect functional interactions. In some simple organisms like yeast, genes of interest can directly be tagged in their genetic loci and expressed under their native promoter. In higher organisms, tagging proteins in their endogenous locus is more challenging, but also for mammalian cells, methods for close to endogenous expression are available. For instance, in controlled inducible expression systems, the concentration of the tagged bait protein can be titrated to close to endogenous levels (18). A very powerful approach is BAC transgenomics (19), as used in our QUBIC protocol (20), where a bacterial artificial chromosome (BAC) containing a tagged version of the gene of interest including all regulatory sequences and the natural promoter is stably transfected into a host cell line.The affinity purification step has also been subject to substantial changes over time. Previously, AP has been combined with nonquantitative MS as the readout, meaning all proteins identified by MS were considered potential interactors. Therefore, to reduce co-purifying “contaminants,” stringent two-step AP protocols using dual affinity tags like the TAP-tag (21) had to be employed. However, such stringent and multistep protocols can result in the loss of weak or transient interactors (3), whereas laborious and partially subjective filtering still has to be applied to clean up the list of identified proteins. The introduction of quantitative mass spectrometry (22–25) to the interactomics field about ten years ago was a paradigm shift, as it offered a proper way of dealing with unspecific binding and true interactors could be directly distinguished from background binders (26, 27). Importantly, quantification enables the detection of true interactors even under low-stringent conditions (28). In turn, this allowed the return to single-step AP protocols, which are milder and faster, and hence more suitable for detecting weak and transient interactors.Despite these advances, nonquantitative methods—often in combination with the TAP-tagging approach—are still popular and widely used, presumably because of reagent expenses and labeling protocols used in label-based approaches. However, there are ways to determine relative protein abundances in a label-free format. A simple, semiquantitative label-free way to estimate protein abundance is spectral counting (29). Another relative label-free quantification strategy is based on peptide intensities (30). In recent years high resolution MS has become much more widely accessible and there has been great progress in intensity-based label-free quantification (LFQ) approaches. Together with development of sophisticated LFQ algorithms, this has boosted obtainable accuracy. Intensity-based LFQ now offers a viable and cost-effective alternative to label-based methods in most applications (31). The potential of intensity-based LFQ approaches as tools for investigating protein–protein interactions has already been demonstrated by us (20, 32, 33) and others (34, 35). We have further refined intensity-based LFQ in the context of the MaxQuant framework (36) using sophisticated normalization algorithms, achieving excellent accuracy and robustness of the measured “MaxLFQ” intensities (37).Another important advance in AP-MS, again enabled by increased MS instrument power, was the development of single-shot LC-MS methods with comprehensive coverage. Instead of extensive fractionation, which was previously needed to reduce sample complexity, nowadays even entire model proteomes can be measured in single LC-MS runs (38). The protein mixture resulting from pull-downs is naturally of lower complexity compared with the entire proteome. Therefore, modern MS obviates the need for gel-based (or other) fractionation and samples can be analyzed in single runs. Apart from avoiding selection of gel bands by visual examination, this has many advantages, including decreased sample preparation and measurement time, increased sensitivity, and higher quantitative accuracy in a label-free format.In this work, we build on many of the recent advances in the field to establish a state of the art LFQ AE-MS method. Based on our previous QUBIC pipeline (20), we developed an approach for investigating protein–protein interactions, which we exemplify in Saccharomyces cerevisiae. We extended the data analysis pipeline to extract the wealth of information contained in the LFQ data, by establishing a novel concept that specifically makes use of the signature of background binders instead of eliminating them from the data set. The large amount of unspecific binders detected in our experiments rendered the use of a classic untagged control strain unnecessary and enabled comparing to a control group consisting of many unrelated pull-downs instead. Our protocol is generic, practical, and fast, uses low input amounts, and identifies interactors with high confidence. We propose that single-step pull-down experiments, especially when coupled to high-sensitivity MS, should now be regarded as affinity enrichment rather than affinity purification methods.     

Genome-Based Identification of Active Prophage Regions by Next Generation Sequencing in Bacillus licheniformis DSM13

Prophages are viruses, which have integrated their genomes into the genome of a bacterial host. The status of the prophage genome can vary from fully intact with the potential to form infective particles to a remnant state where only a few phage genes persist. Prophages have impact on the properties of their host and are therefore of great interest for genomic research and strain design. Here we present a genome- and next generation sequencing (NGS)-based approach for identification and activity evaluation of prophage regions. Seven prophage or prophage-like regions were identified in the genome of Bacillus licheniformis DSM13. Six of these regions show similarity to members of the Siphoviridae phage family. The remaining region encodes the B. licheniformis orthologue of the PBSX prophage from Bacillus subtilis. Analysis of isolated phage particles (induced by mitomycin C) from the wild-type strain and prophage deletion mutant strains revealed activity of the prophage regions BLi_Pp2 (PBSX-like), BLi_Pp3 and BLi_Pp6. In contrast to BLi_Pp2 and BLi_Pp3, neither phage DNA nor phage particles of BLi_Pp6 could be visualized. However, the ability of prophage BLi_Pp6 to generate particles could be confirmed by sequencing of particle-protected DNA mapping to prophage locus BLi_Pp6. The introduced NGS-based approach allows the investigation of prophage regions and their ability to form particles. Our results show that this approach increases the sensitivity of prophage activity analysis and can complement more conventional approaches such as transmission electron microscopy (TEM).     

Beta-Lactamase Repressor BlaI Modulates Staphylococcus aureus Cathelicidin Antimicrobial Peptide Resistance and Virulence

BlaI is a repressor of BlaZ, the beta-lactamase responsible for penicillin resistance in Staphylococcus aureus. Through screening a transposon library in S. aureus Newman for susceptibility to cathelicidin antimicrobial peptide, we discovered BlaI as a novel cathelicidin resistance factor. Additionally, through integrational mutagenesis in S. aureus Newman and MRSA Sanger 252 strains, we confirmed the role of BlaI in resistance to human and murine cathelidicin and showed that it contributes to virulence in human whole blood and murine infection models. We further demonstrated that BlaI could be a target for innate immune-based antimicrobial therapies; by removing BlaI through subinhibitory concentrations of 6-aminopenicillanic acid, we were able to sensitize S. aureus to LL-37 killing.