Mutations induced by reactive nitrogen oxide species in the supF forward mutation assay

Nitric oxide is an important bioregulatory molecule with a range of physiological functions. Nitric oxide can also react with oxygen species to produce a range of reactive nitrogen oxides that can damage DNA and lead to mutations of the DNA base sequence. The mutagenicity of a variety of reactive nitrogen oxide species and related DNA damaging agents in the supF assay are reviewed here, in the context of recent reports that relate to the nature of the DNA lesions responsible for the induced mutations. Mutations induced by nitric oxide in the supF assay are compared to those induced by N₂O₃, nitrous acid, peroxynitrite and different reactive oxygen species. The effect of replication of the damaged pSP189 plasmid in human cells or Escherichia coli cells is also considered.     

1.70 A X-ray structure of human apo kallikrein 1: structural changes upon peptide inhibitor/substrate binding

Human kallikreins are serine proteases that comprise a recently identified large and closely related 15-member family. The kallikreins include both regulatory- and degradative-type proteases, impacting a variety of physiological processes including regulation of blood pressure, neuronal health, and the inflammatory response. While the function of the majority of the kallikreins remains to be elucidated, two members are useful biomarkers for prostate cancer and several others are potentially useful biomarkers for breast cancer, Alzheimer's, and Parkinson's disease. Human tissue kallikrein (human K1) is the best functionally characterized member of this family, and is known to play an important role in blood pressure regulation. As part of this function, human K1 exhibits unique dual-substrate specificity in hydrolyzing low molecular weight kininogen between both Arg-Ser and Met-Lys sequences. We report the X-ray crystal structure of mature, active recombinant human apo K1 at 1.70 A resolution. The active site exhibits structural features intermediate between that of apo and pro forms of known kallikrein structures. The S2 to S2' pockets demonstrate a variety of conformational changes in comparison to the porcine homolog of K1 in complex with peptide inhibitors, including the displacement of an extensive solvent network. These results indicate that the binding of a peptide substrate contributes to a structural rearrangement of the active-site Ser 195 resulting in a catalytically competent juxtaposition with the active-site His 57. The solvent networks within the S1 and S1' pockets suggest how the Arg-Ser and Met-Lys dual substrate specificity of human K1 is accommodated.     

Expression of epithelial antigens in primary cultures of normal human breast analysed with monoclonal antibodies

Abstract. Primary cultures of normal human breast were stained with monoclonal antibodies to see if antigens characteristic of luminal epithelial cells are retained in culture. Three monoclonal antibodies were used, LICR-LON-M8, LICR-LON-M18, and LICR-LON-M24, all specific for the cell surface of luminal epithelial as opposed to myoepithelial or stromal cells in the breast, and each staining a different subset of the epithelial cells in the intact tissue. Cultures were prepared from reduction mammoplasty samples by digestion with collagenase. The surface layer of cells was stained by immunofluorescence without fixation. (Cells underneath the surface layer were not accessible to this mode of staining). The antibodies stained patches of cells resembling flattened epithelium. These patches of cells cannot be distinguished by phase contrast microscopy without reference to the staining, in fact the boundaries of the cells are not usually resolved by phase contrast microscopy. Electron microscopy of sections through these cells show they are very flattened. They lie on top of the polygonal and elongated cells that dominate the phase contrast image. Two of the antibodies, M8 and M24, stain subsets of these epithelial-like cells at all stages of culture. The third antibody, Ml8, stains such cells initially, but after the first few days staining is predominantly found on the polygonal and elongated cells, then this also gradually disappears. It is possible that the cells stained by antibody Ml8 are converting from the epithelial-like morphology to the cuboidal and elongated morphology. Many cells are not stained by any of the antibodies, so appear either to by myoepithelial in origin or to have lost their luminal epithelial surface antigens at an early stage. This analysis draws attention to the variety of cell types in these cultures and the limitations of phase contrast microscopy as a means of analysing them.     

AgroLux: bioluminescent Agrobacterium to improve molecular pharming and study plant immunity

Agroinfiltration in Nicotiana benthamiana is widely used to transiently express heterologous proteins in plants. However, the state of Agrobacterium itself is not well studied in agroinfiltrated tissues, despite frequent studies of immunity genes conducted through agroinfiltration. Here, we generated a bioluminescent strain of Agrobacterium tumefaciens GV3101 to monitor the luminescence of Agrobacterium during agroinfiltration. By integrating a single copy of the lux operon into the genome, we generated a stable ‘AgroLux’ strain, which is bioluminescent without affecting Agrobacterium growth in vitro and in planta. To illustrate its versatility, we used AgroLux to demonstrate that high light intensity post infiltration suppresses both Agrobacterium luminescence and protein expression. We also discovered that AgroLux can detect Avr/Cf-induced immune responses before tissue collapse, establishing a robust and rapid quantitative assay for the hypersensitive response (HR). Thus, AgroLux provides a non-destructive, versatile and easy-to-use imaging tool to monitor both Agrobacterium and plant responses.     

Potential Biases in Estimating Absolute and Relative Case-Fatality Risks during Outbreaks

Estimating the case-fatality risk (CFR)—the probability that a person dies from an infection given that they are a case—is a high priority in epidemiologic investigation of newly emerging infectious diseases and sometimes in new outbreaks of known infectious diseases. The data available to estimate the overall CFR are often gathered for other purposes (e.g., surveillance) in challenging circumstances. We describe two forms of bias that may affect the estimation of the overall CFR—preferential ascertainment of severe cases and bias from reporting delays—and review solutions that have been proposed and implemented in past epidemics. Also of interest is the estimation of the causal impact of specific interventions (e.g., hospitalization, or hospitalization at a particular hospital) on survival, which can be estimated as a relative CFR for two or more groups. When observational data are used for this purpose, three more sources of bias may arise: confounding, survivorship bias, and selection due to preferential inclusion in surveillance datasets of those who are hospitalized and/or die. We illustrate these biases and caution against causal interpretation of differential CFR among those receiving different interventions in observational datasets. Again, we discuss ways to reduce these biases, particularly by estimating outcomes in smaller but more systematically defined cohorts ascertained before the onset of symptoms, such as those identified by forward contact tracing. Finally, we discuss the circumstances in which these biases may affect non-causal interpretation of risk factors for death among cases.The case-fatality risk (CFR) is a key quantity in characterizing new infectious agents and new outbreaks of known agents. The CFR can be defined as the probability that a case dies from the infection. Several variations of the definition of “case” are used for different infections, as discussed in Box 1. Under all these definitions, the CFR characterizes the severity of an infection and is useful for planning and determining the intensity of a response to an outbreak [1,2]. Moreover, the CFR may be compared between cases who do and do not receive particular treatments as a way of trying to estimate the causal impact of these treatments on survival. Such causal inference might ideally be done in a randomized trial in which individuals are randomly assigned to treatments, but this is often not possible during an outbreak for logistical, ethical, and other reasons [3]. Therefore, observational estimates of CFR under different treatment conditions may be the only available means to assess the impact of various treatments.

Box 1. Definition of the CFR.

The CFR itself is an ambiguous term, as its definition and value depend on what qualifies an individual to be a “case.” Several different precise definitions of CFR have been used in practice, as have several imprecise ones. The infection-fatality risk (sometimes written IFR) defines a case as a person who has shown evidence of infection, either by clinical detection of the pathogen or by seroconversion or other immune response. Such individuals may or may not be symptomatic, though asymptomatic ones may go undetected. The symptomatic case-fatality risk (sCFR) defines a case as someone who is infected and shows certain symptoms. Infection in many outbreaks is given several gradations, including confirmed (definitive laboratory confirmation), probable (high degree of suspicion, by various clinical and epidemiologic criteria, without laboratory confirmation), and possible or suspected (lower degree of suspicion). This paper describes issues in estimating any of these risks or comparing them across groups, but does not go into the details of each possible definition.Furthermore, unlike risks commonly used in epidemiologic research (e.g., the 5-year mortality risk), the length of the period during which deaths are counted for the CFR is rarely explicit, probably because it is considered to be short enough to avoid ambiguity in the definition of CFR. However, a precise definition of the CFR would need to include the risk period, e.g., the 1-month CFR of Ebola. Clearly, the definition of CFR for a particular investigation should be specified as precisely as possible.However, observational studies conducted in the early phases of an outbreak, when public health authorities are appropriately concentrating on crisis response and not on rigorous study design, are challenging. A common problem is that disease severity of the cases recorded in a surveillance database will differ, perhaps substantially, from that of all cases in the population. This issue has arisen in the present epidemic of Ebola virus disease in West Africa and in many previous outbreaks and epidemics [4–9] and will continue to arise in future ones.Here we outline two biases that may occur when estimating the CFR in a population from a surveillance database, and three more biases that may occur when comparing the CFR between subgroups to estimate the causal effect of medical interventions. We also briefly consider the applicability of these biases to a different application: comparing the CFR across different groups of people, for example, by geography, sex, age, comorbidities, and other “unchangeable” risk factors. Such factors are “unchangeable” in the sense that they are not candidates for intervention in the setting of the outbreak, though some could, of course, change over longer timescales. The goal of estimating the CFR in groups defined by such unchangeable factors is not to understand the causal role of these factors in mortality, but to develop a predictive model for mortality that might be used to improve prognostic accuracy or identify disparities. Such predictions may be affected by survivorship bias and selection bias, but not by confounding, as we discuss.     

Identification of OmpA,a Coxiella burnetii Protein Involved in Host Cell Invasion,by Multi-Phenotypic High-Content Screening

Coxiella burnetii is the agent of the emerging zoonosis Q fever. This pathogen invades phagocytic and non-phagocytic cells and uses a Dot/Icm secretion system to co-opt the endocytic pathway for the biogenesis of an acidic parasitophorous vacuole where Coxiella replicates in large numbers. The study of the cell biology of Coxiella infections has been severely hampered by the obligate intracellular nature of this microbe, and Coxiella factors involved in host/pathogen interactions remain to date largely uncharacterized. Here we focus on the large-scale identification of Coxiella virulence determinants using transposon mutagenesis coupled to high-content multi-phenotypic screening. We have isolated over 3000 Coxiella mutants, 1082 of which have been sequenced, annotated and screened. We have identified bacterial factors that regulate key steps of Coxiella infections: 1) internalization within host cells, 2) vacuole biogenesis/intracellular replication, and 3) protection of infected cells from apoptosis. Among these, we have investigated the role of Dot/Icm core proteins, determined the role of candidate Coxiella Dot/Icm substrates previously identified in silico and identified additional factors that play a relevant role in Coxiella pathogenesis. Importantly, we have identified CBU_1260 (OmpA) as the first Coxiella invasin. Mutations in ompA strongly decreased Coxiella internalization and replication within host cells; OmpA-coated beads adhered to and were internalized by non-phagocytic cells and the ectopic expression of OmpA in E. coli triggered its internalization within cells. Importantly, Coxiella internalization was efficiently inhibited by pretreating host cells with purified OmpA or by incubating Coxiella with a specific anti-OmpA antibody prior to host cell infection, suggesting the presence of a cognate receptor at the surface of host cells. In summary, we have developed multi-phenotypic assays for the study of host/pathogen interactions. By applying our methods to Coxiella burnetii, we have identified the first Coxiella protein involved in host cell invasion.     

Using Hawkes Processes to model imported and local malaria cases in near-elimination settings

Developing new methods for modelling infectious diseases outbreaks is important for monitoring transmission and developing policy. In this paper we propose using semi-mechanistic Hawkes Processes for modelling malaria transmission in near-elimination settings. Hawkes Processes are well founded mathematical methods that enable us to combine the benefits of both statistical and mechanistic models to recreate and forecast disease transmission beyond just malaria outbreak scenarios. These methods have been successfully used in numerous applications such as social media and earthquake modelling, but are not yet widespread in epidemiology. By using domain-specific knowledge, we can both recreate transmission curves for malaria in China and Eswatini and disentangle the proportion of cases which are imported from those that are community based.