Caging Targets for Destruction

Intracellular bacterial pathogens engage in a tug-of-war with innate host defenses. In this issue of Cell Host & Microbe, Mostowy et al. (2010) identify a role for the septin family of cytoskeletal proteins in targeting intracellular Shigella to the autophagy pathway

Systematic Overexpression of Genes Encoded By Mycobacteriophage Waterfoul Reveals Novel Inhibitors of Mycobacterial Growth

Bacteriophages represent an enormous reservoir of novel genes, many of which are unrelated to existing entries in public databases and cannot be assigned a predicted function. Characterization of these genes can provide important insights into the intricacies of phage–host interactions and may offer new strategies to manipulate bacterial growth and behavior. Overexpression is a useful tool in the study of gene-mediated effects, and we describe here the construction of a plasmid-based overexpression library of a complete set of genes for Waterfoul, a mycobacteriophage closely related to those infecting clinically important strains of Mycobacterium tuberculosis and/or Mycobacterium abscessus. The arrayed Waterfoul gene library was systematically screened in a plate-based cytotoxicity assay, identifying a diverse set of 32 Waterfoul gene products capable of inhibiting the growth of the host Mycobacterium smegmatis and providing a first look at the frequency and distribution of cytotoxic products encoded within a single mycobacteriophage genome. Several of these Waterfoul gene products were observed to confer potent anti-mycobacterial effects, making them interesting candidates for follow-up mechanistic studies

Validação da estrutura interna da Escala Brasileira de Vulnerabilidade Odontológica

OBJETIVO: Avaliar evidências de validade da estrutura interna da Escala Brasileira de Vulnerabilidade Odontológica (EVO-BR) quando aplicada no Brasil. MÉTODOS: Trata-se de um estudo de natureza psicométrica, que busca validar uma escala construída através de evidências de estrutura interna. A coleta de dados foi realizada em 18 unidades básicas de saúde que executam a metodologia da Planificação da Atenção à Saúde, distribuídas nas cinco regiões do Brasil. A versão inicial da EVO-BR continha 41 itens que mediam vulnerabilidade odontológica e foram aplicados por em usuários com 18 anos ou mais, usuários do Sistema Único de Saúde, que estivessem nas unidades básicas de saúde para consulta por profissionais de nível superior. Para avaliação das evidências foram utilizadas as seguintes análises estatísticas: análise fatorial exploratória, confirmatória e network analysis. RESULTADOS: Participaram do estudo 1.753 usuários. Para adequação da amostra considerou-se a fatorabilidade obtida de Kaiser-Meyer-Olkin (KMO) = 0,65, Bartlett sphericity = 8019,7 e determinante da matriz de 0,008. A análise paralela inicial indicou um modelo de 4 dimensões e teve os itens ajustados conforme cargas fatorais (variaram de 0,38 a 0,99), comunalidades (0,13 a 0,89) e Pratt’s measure até que o modelo tivesse congruência nos princípios estatístico e interpretativo simultaneamente. O modelo final apresentou 15 itens, manteve a indicação de quatro dimensões pela análise paralela e com uma variância explicada de 68,56%. CONCLUSÕES: A EVO-BR é uma escala validada para mensurar vulnerabilidade odontológica, e pode contribuir para organização do acesso a equipe de saúde bucal na atenção primária à saúde por meio da estratificação da população, como recomendado na planificação

Effect of Hypoglycemia on Inflammatory Responses and the Response to Low Dose Endotoxemia in Humans

Context: Hypoglycemia is emerging as a risk for cardiovascular events in diabetes. We hypothesized that hypoglycemia activates the innate immune system, which is known to increase cardiovascular risk. Objective: To determine whether hypoglycemia modifies subsequent innate immune system responses. Design and Setting: Single-blinded, prospective study of three independent parallel groups. Participants and Interventions: Twenty-four healthy participants underwent either a hyperinsulinemic-hypoglycemic (2.5 mmol/l), euglycemic (6.0 mmol/l) or sham-saline clamp (n=8 for each group). Forty-eight hours later, all participants received low-dose (0.3 ng/kg) intravenous endotoxin. Main outcome measures: We studied in-vivo monocyte mobilization and monocyte-platelet interactions. Results: Hypoglycemia increased total leucocytes (9.98±1.14 x109/l vs euglycemia: 4.38±0.53 x109/l; P<0.001 vs sham-saline: 4.76±0.36 x109/l; P<0.001) (mean±SEM), mobilized proinflammatory intermediate monocytes (42.20±7.52/μl vs euglycemia: 20.66±3.43/μl; P<0.01 vs sham-saline: 26.20±3.86/μl; P<0.05) and non-classical monocytes (36.16±4.66/μl vs euglycemia: 12.72±2.42/μl; P<0.001 vs sham-saline: 19.05±3.81/μl; P<0.001). Following hypoglycemia vs euglycemia, platelet aggregation to agonist (AUC) increased (73.87±7.30 vs 52.50±4.04; P<0.05) and formation of monocyte-platelet aggregates increased (96.05±14.51/μl vs 49.32±6.41/μl; P<0.05). Within monocyte subsets, hypoglycemia increased aggregation of intermediate monocytes (10.51±1.42/μl vs euglycemia: 4.19±1.08/μl; P<0.05 vs sham-saline: 3.81±1.42/μl; P<0.05) and non-classical monocytes (9.53±1.08/μl vs euglycemia: 2.86±0.72/μl; P<0.01 vs sham-saline: 3.08±1.01/μl; P<0.05) with platelets compared to controls. Hypoglycemia led to greater leucocyte mobilization in response to subsequent low-dose endotoxin challenge (10.96±0.97 vs euglycemia: 8.21±0.85 x109/l; P<0.05). Conclusions: Hypoglycemia mobilizes monocytes, increases platelet reactivity, promotes interaction between platelets and proinflammatory monocytes, and potentiates the subsequent immune response to endotoxin. These changes may contribute towards increased cardiovascular risk observed in people with diabetes

Defining Early-Onset Colon and Rectal Cancers

Background: Colorectal cancer (CRC) incidence is rising in the young, yet the age of those affected is not clearly defined. In this study, we identify such cohorts and define clinicopathological features of early-onset colon and rectal cancers.Methods: The Surveillance, Epidemiology and End Results Program (SEER) database was queried to compare clinicopathological characteristics of colon and rectal cancers diagnosed during 1973–1995 with those diagnosed during 1995–2014.Results: We identified 430,886 patients with colon and rectal cancers. From 1973–1995 to 1995–2014, colon cancer incidence increased in patients aged 20–44 years, while rectal cancer incidence increased in patients aged ≤54 years. The percent change of cancer incidence was greatest for rectal cancer with a 41.5% (95% confidence interval (CI): 37.4–45.8%) increase compared to a 9.8% (CI: 6.2–13.6%) increase in colon cancer. Colon cancer has increased in tumors located in ascending, sigmoid, and rectosigmoid locations. Adenocarcinoma histology has increased in both colon and rectal cancers (P &lt; 0.01), but mucinous and signet ring cell subtypes have not increased (P = 0.13 and 0.08, respectively). Incidence increases were race-specific, with rectal cancer seeing similar rises in white (38.4%, CI: 33.8–43.1%) and black populations (38.0%, CI: 26.2–51.2%), while colon cancer as a whole saw a rise in white (11.5%, CI: 7.2–15.9%) but not black populations (−6.8%, CI: −14.6–1.9%).Conclusions: Our study underscores the existence of key differences between early-onset colon (20–44 years) and rectal cancers (≤54 years) and provides evidence-based inclusion criteria for future investigations. We recommend that future research of CRC in the young should avoid investigating these cases as a single entity

Hypergraph models of biological networks to identify genes critical to pathogenic viral response

Background: Representing biological networks as graphs is a powerful approach to reveal underlying patterns, signatures, and critical components from high-throughput biomolecular data. However, graphs do not natively capture the multi-way relationships present among genes and proteins in biological systems. Hypergraphs are generalizations of graphs that naturally model multi-way relationships and have shown promise in modeling systems such as protein complexes and metabolic reactions. In this paper we seek to understand how hypergraphs can more faithfully identify, and potentially predict, important genes based on complex relationships inferred from genomic expression data sets. Results: We compiled a novel data set of transcriptional host response to pathogenic viral infections and formulated relationships between genes as a hypergraph where hyperedges represent significantly perturbed genes, and vertices represent individual biological samples with specific experimental conditions. We find that hypergraph betweenness centrality is a superior method for identification of genes important to viral response when compared with graph centrality. Conclusions: Our results demonstrate the utility of using hypergraphs to represent complex biological systems and highlight central important responses in common to a variety of highly pathogenic viruses

Seed amplification and neurodegeneration marker trajectories in individuals at risk of prion disease

Human prion diseases are remarkable for long incubation times followed typically by rapid clinical decline. Seed amplification assays and neurodegeneration biofluid biomarkers are remarkably useful in the clinical phase, but their potential to predict clinical onset in healthy people remains unclear. This is relevant not only to the design of preventive strategies in those at-risk of prion diseases, but more broadly, because prion-like mechanisms are thought to underpin many neurodegenerative disorders. Here, we report the accrual of a longitudinal biofluid resource in patients, controls and healthy people at risk of prion diseases, to which ultrasensitive techniques such as real-time quaking-induced conversion (RT-QuIC), and single molecule array (Simoa) digital immunoassays were applied for preclinical biomarker discovery. We studied 648 CSF and plasma samples, including 16 people who had samples taken when healthy but later developed inherited prion disease (IPD) ("converters"; range from 9.9 prior to, and 7.4 years after onset). Symptomatic IPD CSF samples were screened by RT-QuIC assay variations, before testing the entire collection of at-risk samples using the most sensitive assay. Glial fibrillary acidic protein (GFAP), neurofilament light (NfL), tau and ubiquitin carboxy-terminal hydrolase L1 (UCH-L1) levels were measured in plasma and CSF. Second generation (IQ-CSF) RT-QuIC proved 100% sensitive and specific for sporadic Creutzfeldt-Jakob disease (sCJD), iatrogenic (iCJD) and familial CJD phenotypes, and subsequently detected seeding activity in four presymptomatic CSF samples from three E200K carriers; one converted in under two months while two remain asymptomatic after at least three years' follow-up. A bespoke HuPrP P102L RT-QuIC showed partial sensitivity for P102L disease. No compatible RT-QuIC assay was discovered for classical 6-OPRI, A117V and D178N, and these at-risk samples tested negative with bank vole RT-QuIC. Plasma GFAP and NfL, and CSF NfL levels emerged as proximity markers of neurodegeneration in the typically slow IPDs (e.g. P102L), with significant differences in mean values segregating healthy control from IPD carriers (within 2 years to onset) and symptomatic IPD cohorts; plasma GFAP appears to change before NfL, and before clinical conversion. In conclusion, we show distinct biomarker trajectories in fast and slow IPDs. Specifically, we identify several years of presymptomatic seeding positivity in E200K, a new proximity marker (plasma GFAP) and sequential neurodegenerative marker evolution (plasma GFAP followed by NfL) in slow IPDs. We suggest a new preclinical staging system featuring clinical, seeding and neurodegeneration aspects, for validation with larger prion at-risk cohorts, and with potential application to other neurodegenerative proteopathies

Gene Characterization Index: Assessing the Depth of Gene Annotation

We introduce the Gene Characterization Index, a bioinformatics method for scoring the extent to which a protein-encoding gene is functionally described. Inherently a reflection of human perception, the Gene Characterization Index is applied for assessing the characterization status of individual genes, thus serving the advancement of both genome annotation and applied genomics research by rapid and unbiased identification of groups of uncharacterized genes for diverse applications such as directed functional studies and delineation of novel drug targets.The scoring procedure is based on a global survey of researchers, who assigned characterization scores from 1 (poor) to 10 (extensive) for a sample of genes based on major online resources. By evaluating the survey as training data, we developed a bioinformatics procedure to assign gene characterization scores to all genes in the human genome. We analyzed snapshots of functional genome annotation over a period of 6 years to assess temporal changes reflected by the increase of the average Gene Characterization Index. Applying the Gene Characterization Index to genes within pharmaceutically relevant classes, we confirmed known drug targets as high-scoring genes and revealed potentially interesting novel targets with low characterization indexes. Removing known drug targets and genes linked to sequence-related patent filings from the entirety of indexed genes, we identified sets of low-scoring genes particularly suited for further experimental investigation.The Gene Characterization Index is intended to serve as a tool to the scientific community and granting agencies for focusing resources and efforts on unexplored areas of the genome. The Gene Characterization Index is available from http://cisreg.ca/gci/