Ferredoxin containing bacteriocins suggest a novel mechanism of iron uptake in <i>Pectobacterium spp</i>

In order to kill competing strains of the same or closely related bacterial species, many bacteria produce potent narrow-spectrum protein antibiotics known as bacteriocins. Two sequenced strains of the phytopathogenic bacterium &lt;i&gt;Pectobacterium carotovorum&lt;/i&gt; carry genes encoding putative bacteriocins which have seemingly evolved through a recombination event to encode proteins containing an N-terminal domain with extensive similarity to a [2Fe-2S] plant ferredoxin and a C-terminal colicin M-like catalytic domain. In this work, we show that these genes encode active bacteriocins, pectocin M1 and M2, which target strains of &lt;i&gt;Pectobacterium carotovorum&lt;/i&gt; and &lt;i&gt;Pectobacterium atrosepticum&lt;/i&gt; with increased potency under iron limiting conditions. The activity of pectocin M1 and M2 can be inhibited by the addition of spinach ferredoxin, indicating that the ferredoxin domain of these proteins acts as a receptor binding domain. This effect is not observed with the mammalian ferredoxin protein adrenodoxin, indicating that &lt;i&gt;Pectobacterium spp.&lt;/i&gt; carries a specific receptor for plant ferredoxins and that these plant pathogens may acquire iron from the host through the uptake of ferredoxin. In further support of this hypothesis we show that the growth of strains of &lt;i&gt;Pectobacterium carotovorum&lt;/i&gt; and &lt;i&gt;atrosepticum&lt;/i&gt; that are not sensitive to the cytotoxic effects of pectocin M1 is enhanced in the presence of pectocin M1 and M2 under iron limiting conditions. A similar growth enhancement under iron limiting conditions is observed with spinach ferrodoxin, but not with adrenodoxin. Our data indicate that pectocin M1 and M2 have evolved to parasitise an existing iron uptake pathway by using a ferredoxin-containing receptor binding domain as a Trojan horse to gain entry into susceptible cells

Novel computational methods for increasing PCR primer design effectiveness in directed sequencing

<p>Abstract</p> <p>Background</p> <p>Polymerase chain reaction (PCR) is used in directed sequencing for the discovery of novel polymorphisms. As the first step in PCR directed sequencing, effective PCR primer design is crucial for obtaining high-quality sequence data for target regions. Since current computational primer design tools are not fully tuned with stable underlying laboratory protocols, researchers may still be forced to iteratively optimize protocols for failed amplifications after the primers have been ordered. Furthermore, potentially identifiable factors which contribute to PCR failures have yet to be elucidated. This inefficient approach to primer design is further intensified in a high-throughput laboratory, where hundreds of genes may be targeted in one experiment.</p> <p>Results</p> <p>We have developed a fully integrated computational PCR primer design pipeline that plays a key role in our high-throughput directed sequencing pipeline. Investigators may specify target regions defined through a rich set of descriptors, such as Ensembl accessions and arbitrary genomic coordinates. Primer pairs are then selected computationally to produce a minimal amplicon set capable of tiling across the specified target regions. As part of the tiling process, primer pairs are computationally screened to meet the criteria for success with one of two PCR amplification protocols. In the process of improving our sequencing success rate, which currently exceeds 95% for exons, we have discovered novel and accurate computational methods capable of identifying primers that may lead to PCR failures. We reveal the laboratory protocols and their associated, empirically determined computational parameters, as well as describe the novel computational methods which may benefit others in future primer design research.</p> <p>Conclusion</p> <p>The high-throughput PCR primer design pipeline has been very successful in providing the basis for high-quality directed sequencing results and for minimizing costs associated with labor and reprocessing. The modular architecture of the primer design software has made it possible to readily integrate additional primer critique tests based on iterative feedback from the laboratory. As a result, the primer design software, coupled with the laboratory protocols, serves as a powerful tool for low and high-throughput primer design to enable successful directed sequencing.</p

Fear causes tears - Perineal injuries in home birth settings. A Swedish interview study

<p>Abstract</p> <p>Background</p> <p>Perineal injury is a serious complication of vaginal delivery that has a severe impact on the quality of life of healthy women. The prevalence of perineal injuries among women who give birth in hospital has increased over the last decade, while it is lower among women who give birth at home. The aim of this study was to describe the practice of midwives in home birth settings with the focus on the occurrence of perineal injuries.</p> <p>Methods</p> <p>Twenty midwives who had assisted home births for between one and 29 years were interviewed using an interview guide. The midwives also had experience of working in a hospital delivery ward. All the interviews were tape-recorded and transcribed. Content analysis was used.</p> <p>Results</p> <p>The overall theme was "No rushing and tearing about", describing the midwives' focus on the natural process taking its time. The subcategories 1) preparing for the birth; 2) going along with the physiological process; 3) creating a sense of security; 4) the critical moment and 5) midwifery skills illuminate the management of labor as experienced by the midwives when assisting births at home.</p> <p>Conclusions</p> <p>Midwives who assist women who give birth at home take many things into account in order to minimize the risk of complications during birth. Protection of the woman's perineum is an act of awareness that is not limited to the actual moment of the pushing phase but starts earlier, along with the communication between the midwife and the woman.</p

PETALS: Proteomic Evaluation and Topological Analysis of a mutated Locus' Signaling

<p>Abstract</p> <p>Background</p> <p>Colon cancer is driven by mutations in a number of genes, the most notorious of which is <it>Apc</it>. Though much of <it>Apc</it>'s signaling has been mechanistically identified over the years, it is not always clear which functions or interactions are operative in a particular tumor. This is confounded by the presence of mutations in a number of other putative cancer driver (CAN) genes, which often synergize with mutations in <it>Apc</it>.</p> <p>Computational methods are, thus, required to predict which pathways are likely to be operative when a particular mutation in <it>Apc </it>is observed.</p> <p>Results</p> <p>We developed a pipeline, PETALS, to predict and test likely signaling pathways connecting <it>Apc </it>to other CAN-genes, where the interaction network originating at <it>Apc </it>is defined as a "blossom," with each <it>Apc</it>-CAN-gene subnetwork referred to as a "petal." Known and predicted protein interactions are used to identify an Apc blossom with 24 petals. Then, using a novel measure of bimodality, the coexpression of each petal is evaluated against proteomic (2 D differential In Gel Electrophoresis, 2D-DIGE) measurements from the <it>Apc</it>^{<it>1638N</it>+/-}mouse to test the network-based hypotheses.</p> <p>Conclusions</p> <p>The predicted pathways linking <it>Apc </it>and <it>Hapln1 </it>exhibited the highest amount of bimodal coexpression with the proteomic targets, prioritizing the <it>Apc-Hapln1 </it>petal over other CAN-gene pairs and suggesting that this petal may be involved in regulating the observed proteome-level effects. These results not only demonstrate how functional 'omics data can be employed to test in <it>silico </it>predictions of CAN-gene pathways, but also reveal an approach to integrate models of upstream genetic interference with measured, downstream effects.</p

High DNA Methylation Pattern Intratumoral Diversity Implies Weak Selection in Many Human Colorectal Cancers

It is possible to infer the past of populations by comparing genomes between individuals. In general, older populations have more genomic diversity than younger populations. The force of selection can also be inferred from population diversity. If selection is strong and frequently eliminates less fit variants, diversity will be limited because new, initially homogeneous populations constantly emerge.Here we translate a population genetics approach to human somatic cancer cell populations by measuring genomic diversity within and between small colorectal cancer (CRC) glands. Control tissue culture and xenograft experiments demonstrate that the population diversity of certain passenger DNA methylation patterns is reduced after cloning but subsequently increases with time. When measured in CRC gland populations, passenger methylation diversity from different parts of nine CRCs was relatively high and uniform, consistent with older, stable lineages rather than mixtures of younger homogeneous populations arising from frequent cycles of selection. The diversity of six metastases was also high, suggesting dissemination early after transformation. Diversity was lower in DNA mismatch repair deficient CRC glands, possibly suggesting more selection and the elimination of less fit variants when mutation rates are elevated.The many hitchhiking passenger variants observed in primary and metastatic CRC cell populations are consistent with relatively old populations, suggesting that clonal evolution leading to selective sweeps may be rare after transformation. Selection in human cancers appears to be a weaker than presumed force after transformation, consistent with the observed rarity of driver mutations in cancer genomes. Phenotypic plasticity rather than the stepwise acquisition of new driver mutations may better account for the many different phenotypes within human tumors

wKinMut: An integrated tool for the analysis and interpretation of mutations in human protein kinases

BACKGROUND: Protein kinases are involved in relevant physiological functions and a broad number of mutations in this superfamily have been reported in the literature to affect protein function and stability. Unfortunately, the exploration of the consequences on the phenotypes of each individual mutation remains a considerable challenge. RESULTS: The wKinMut web-server offers direct prediction of the potential pathogenicity of the mutations from a number of methods, including our recently developed prediction method based on the combination of information from a range of diverse sources, including physicochemical properties and functional annotations from FireDB and Swissprot and kinase-specific characteristics such as the membership to specific kinase groups, the annotation with disease-associated GO terms or the occurrence of the mutation in PFAM domains, and the relevance of the residues in determining kinase subfamily specificity from S3Det. This predictor yields interesting results that compare favourably with other methods in the field when applied to protein kinases. Together with the predictions, wKinMut offers a number of integrated services for the analysis of mutations. These include: the classification of the kinase, information about associations of the kinase with other proteins extracted from iHop, the mapping of the mutations onto PDB structures, pathogenicity records from a number of databases and the classification of mutations in large-scale cancer studies. Importantly, wKinMut is connected with the SNP2L system that extracts mentions of mutations directly from the literature, and therefore increases the possibilities of finding interesting functional information associated to the studied mutations. CONCLUSIONS: wKinMut facilitates the exploration of the information available about individual mutations by integrating prediction approaches with the automatic extraction of information from the literature (text mining) and several state-of-the-art databases. wKinMut has been used during the last year for the analysis of the consequences of mutations in the context of a number of cancer genome projects, including the recent analysis of Chronic Lymphocytic Leukemia cases and is publicly available at http://wkinmut.bioinfo.cnio.es

Classification of tumours

Tumours are classified according to the most differentiated cells with the exception of carcinomas where a few tumour cells show neuroendocrine differentiation. In this case these cells are regarded as redifferentiated tumour cells, and the tumour is not classified as neuroendocrine. However, it is now clear that normal neuroendocrine cells can divide, and that continuous stimulation of such cells results in tumour formation, which during time becomes increasingly malignant. To understand tumourigenesis, it is of utmost importance to recognize the cell of origin of the tumour since knowledge of the growth regulation of that cell may give information about development and thus possible prevention and prophylaxis of the tumour. It may also have implications for the treatment. The successful treatment of gastrointestinal stromal tumours by a tyrosine kinase inhibitor is an example of the importance of a correct cellular classification of a tumour. In the future tumours should not just be classified as for instance adenocarcinomas of an organ, but more precisely as a carcinoma originating from a certain cell type of that organ

CA8 Mutations Cause a Novel Syndrome Characterized by Ataxia and Mild Mental Retardation with Predisposition to Quadrupedal Gait

We describe a consanguineous Iraqi family in which affected siblings had mild mental retardation and congenital ataxia characterized by quadrupedal gait. Genome-wide linkage analysis identified a 5.8 Mb interval on chromosome 8q with shared homozygosity among the affected persons. Sequencing of genes contained in the interval revealed a homozygous mutation, S100P, in carbonic anhydrase related protein 8 (CA8), which is highly expressed in cerebellar Purkinje cells and influences inositol triphosphate (ITP) binding to its receptor ITPR1 on the endoplasmatic reticulum and thereby modulates calcium signaling. We demonstrate that the mutation S100P is associated with proteasome-mediated degradation, and thus presumably represents a null mutation comparable to the Ca8 mutation underlying the previously described waddles mouse, which exhibits ataxia and appendicular dystonia. CA8 thus represents the third locus that has been associated with quadrupedal gait in humans, in addition to the VLDLR locus and a locus at chromosome 17p. Our findings underline the importance of ITP-mediated signaling in cerebellar function and provide suggestive evidence that congenital ataxia paired with cerebral dysfunction may, together with unknown contextual factors during development, predispose to quadrupedal gait in humans

Statistical method on nonrandom clustering with application to somatic mutations in cancer

<p>Abstract</p> <p>Background</p> <p>Human cancer is caused by the accumulation of tumor-specific mutations in oncogenes and tumor suppressors that confer a selective growth advantage to cells. As a consequence of genomic instability and high levels of proliferation, many passenger mutations that do not contribute to the cancer phenotype arise alongside mutations that drive oncogenesis. While several approaches have been developed to separate driver mutations from passengers, few approaches can specifically identify activating driver mutations in oncogenes, which are more amenable for pharmacological intervention.</p> <p>Results</p> <p>We propose a new statistical method for detecting activating mutations in cancer by identifying nonrandom clusters of amino acid mutations in protein sequences. A probability model is derived using order statistics assuming that the location of amino acid mutations on a protein follows a uniform distribution. Our statistical measure is the differences between pair-wise order statistics, which is equivalent to the size of an amino acid mutation cluster, and the probabilities are derived from exact and approximate distributions of the statistical measure. Using data in the Catalog of Somatic Mutations in Cancer (COSMIC) database, we have demonstrated that our method detects well-known clusters of activating mutations in KRAS, BRAF, PI3K, and <it>β</it>-catenin. The method can also identify new cancer targets as well as gain-of-function mutations in tumor suppressors.</p> <p>Conclusions</p> <p>Our proposed method is useful to discover activating driver mutations in cancer by identifying nonrandom clusters of somatic amino acid mutations in protein sequences.</p