Computational and biochemical analysis of the Xanthomonas effector AvrBs2 and its role in the modulation of Xanthomonas type three effector delivery

Effectors of the bacterial type III secretion system provide invaluable molecular probes to elucidate the molecular mechanisms of plant immunity and pathogen virulence. In this report, we focus on the AvrBs2 effector protein from the bacterial pathogen Xanthomonas euvesicatoria (Xe), the causal agent of bacterial spot disease of tomato and pepper. Employing homology-based structural analysis, we generate a three-dimensional structural model for the AvrBs2 protein and identify catalytic sites in its putative glycerolphosphodiesterase domain (GDE). We demonstrate that the identified catalytic region of AvrBs2 was able to functionally replace the GDE catalytic site of the bacterial glycerophosphodiesterase BhGlpQ cloned from Borrelia hermsii and is required for AvrBs2 virulence. Mutations in the GDE catalytic domain did not disrupt the recognition of AvrBs2 by the cognate plant resistance gene Bs2. In addition, AvrBs2 activation of Bs2 suppressed subsequent delivery of other Xanthomonas type III effectors into the host plant cells. Investigation of the mechanism underlying this modulation of the type III secretion system may offer new strategies to generate broad-spectrum resistance to bacterial pathogens.     

Subtelomeric regions in mammalian cells are deficient in DNA double-strand break repair

We have previously demonstrated that double-strand breaks (DSBs) in regions near telomeres are much more likely to result in large deletions, gross chromosome rearrangements, and chromosome instability than DSBs at interstitial sites within chromosomes. In the present study, we investigated whether this response of subtelomeric regions to DSBs is a result of a deficiency in DSB repair by comparing the frequency of homologous recombination repair (HRR) and nonhomologous end joining (NHEJ) at interstitial and telomeric sites following the introduction of DSBs by I-SceI endonuclease. We also monitored the frequency of small deletions, which have been shown to be the most common mutation at I-SceI-induced DSBs at interstitial sites. We observed no difference in the frequency of small deletions or HRR at interstitial and subtelomeric DSBs. However, the frequency of NHEJ was significantly lower at DSBs near telomeres compared to interstitial sites. The frequency of NHEJ was also lower at DSBs occurring at interstitial sites containing telomeric repeat sequences. We propose that regions near telomeres are deficient in classical NHEJ as a result of the presence of cis-acting telomere-binding proteins that cause DSBs to be processed as though they were telomeres, resulting in excessive resection, telomere loss, and eventual chromosome rearrangements by alternative NHEJ.     

Neonatal mortality levels for 193 countries in 2009 with trends since 1990: a systematic analysis of progress, projections, and priorities

Background

Historically, the main focus of studies of childhood mortality has been the infant and under-five mortality rates. Neonatal mortality (deaths <28 days of age) has received limited attention, although such deaths account for about 41% of all child deaths. To better assess progress, we developed annual estimates for neonatal mortality rates (NMRs) and neonatal deaths for 193 countries for the period 1990–2009 with forecasts into the future.

Methods and Findings

We compiled a database of mortality in neonates and children (<5 years) comprising 3,551 country-years of information. Reliable civil registration data from 1990 to 2009 were available for 38 countries. A statistical model was developed to estimate NMRs for the remaining 155 countries, 17 of which had no national data. Country consultation was undertaken to identify data inputs and review estimates. In 2009, an estimated 3.3 million babies died in the first month of life—compared with 4.6 million neonatal deaths in 1990—and more than half of all neonatal deaths occurred in five countries of the world (44% of global livebirths): India 27.8% (19.6% of global livebirths), Nigeria 7.2% (4.5%), Pakistan 6.9% (4.0%), China 6.4% (13.4%), and Democratic Republic of the Congo 4.6% (2.1%). Between 1990 and 2009, the global NMR declined by 28% from 33.2 deaths per 1,000 livebirths to 23.9. The proportion of child deaths that are in the neonatal period increased in all regions of the world, and globally is now 41%. While NMRs were halved in some regions of the world, Africa''s NMR only dropped 17.6% (43.6 to 35.9).

Conclusions

Neonatal mortality has declined in all world regions. Progress has been slowest in the regions with high NMRs. Global health programs need to address neonatal deaths more effectively if Millennium Development Goal 4 (two-thirds reduction in child mortality) is to be achieved. Please see later in the article for the Editors'' Summary     

A genetic optimization approach for isolating translational efficiency bias

The study of codon usage bias is an important research area that contributes to our understanding of molecular evolution, phylogenetic relationships, respiratory lifestyle, and other characteristics. Translational efficiency bias is perhaps the most well-studied codon usage bias, as it is frequently utilized to predict relative protein expression levels. We present a novel approach to isolating translational efficiency bias in microbial genomes. There are several existent methods for isolating translational efficiency bias. Previous approaches are susceptible to the confounding influences of other potentially dominant biases. Additionally, existing approaches to identifying translational efficiency bias generally require both genomic sequence information and prior knowledge of a set of highly expressed genes. This novel approach provides more accurate results from sequence information alone by resisting the confounding effects of other biases. We validate this increase in accuracy in isolating translational efficiency bias on 10 microbial genomes, five of which have proven particularly difficult for existing approaches due to the presence of strong confounding biases.     

MCAM: multiple clustering analysis methodology for deriving hypotheses and insights from high-throughput proteomic datasets

Advances in proteomic technologies continue to substantially accelerate capability for generating experimental data on protein levels, states, and activities in biological samples. For example, studies on receptor tyrosine kinase signaling networks can now capture the phosphorylation state of hundreds to thousands of proteins across multiple conditions. However, little is known about the function of many of these protein modifications, or the enzymes responsible for modifying them. To address this challenge, we have developed an approach that enhances the power of clustering techniques to infer functional and regulatory meaning of protein states in cell signaling networks. We have created a new computational framework for applying clustering to biological data in order to overcome the typical dependence on specific a priori assumptions and expert knowledge concerning the technical aspects of clustering. Multiple clustering analysis methodology ('MCAM') employs an array of diverse data transformations, distance metrics, set sizes, and clustering algorithms, in a combinatorial fashion, to create a suite of clustering sets. These sets are then evaluated based on their ability to produce biological insights through statistical enrichment of metadata relating to knowledge concerning protein functions, kinase substrates, and sequence motifs. We applied MCAM to a set of dynamic phosphorylation measurements of the ERRB network to explore the relationships between algorithmic parameters and the biological meaning that could be inferred and report on interesting biological predictions. Further, we applied MCAM to multiple phosphoproteomic datasets for the ERBB network, which allowed us to compare independent and incomplete overlapping measurements of phosphorylation sites in the network. We report specific and global differences of the ERBB network stimulated with different ligands and with changes in HER2 expression. Overall, we offer MCAM as a broadly-applicable approach for analysis of proteomic data which may help increase the current understanding of molecular networks in a variety of biological problems.     

Illustration of SSMD, z score, SSMD*, z* score, and t statistic for hit selection in RNAi high-throughput screens

Hit selection is the ultimate goal in many high-throughput screens. Various analytic methods are available for this purpose. Some commonly used ones are z score, z* score, strictly standardized mean difference (SSMD), SSMD*, and t statistic. It is critical to know how to use them correctly because the misusage of them can readily produce misleading results. Here, the author presents basic concepts, elaborates their commonality and difference, describes some common misusage that people should avoid, and uses simulated simple examples to illustrate how to use them correctly.     

Effect of lipids on avian satellite cell proliferation, differentiation and heparan sulfate proteoglycan expression

The objective of this study was to determine the effects of fatty acids on the proliferation, differentiation, and expression of syndecan-4 and glypican-1 in avian myogenic satellite cells (SC). SC derived from the pectoralis major (PM) and biceps femoris (BF) muscles of the turkey and chicken were individually administered 8 different fatty acids in defined medium during proliferation. A parallel set of turkey SC was induced to differentiate. Highest levels of proliferation of turkey PM and BF SC occurred in cultures containing oleate. Linoleate and oleate were equipotent in supporting proliferation of chicken SC. Microscopic examination revealed that inclusion of docosahexaenoate or eicosapentaenoate was toxic towards both PM and BF SC from both species. Linolenate and arachidonate diminished levels of differentiation. Expression of glypican-1 varied between treatments to a greater extent with turkey BF than with PM SC. Expression in chicken PM and BF SC demonstrated a similar pattern in response to treatments. Turkey PM syndecan-4 expression varied between treatments, whereas expression in turkey BF SC was similar between treatments. Expression in chicken SC varied little between treatments. The results demonstrate species and muscle-specific differences in the parameters examined. It is proposed that changes in lipid raft receptor interactions may contribute to these observed differences.