Description and critical appraisal of principal components analysis (PCA) methodology applied to pulsed-field gel electrophoresis profiles of methicillin-resistant Staphylococcus aureus isolates

Principal components analysis (PCA) has been described for over 50 years; however, it is rarely applied to the analysis of epidemiological data. In this study PCA was critically appraised in its ability to reveal relationships between pulsed-field gel electrophoresis (PFGE) profiles of methicillin- resistant Staphylococcus aureus (MRSA) in comparison to the more commonly employed cluster analysis and representation by dendrograms. The PFGE type following SmaI chromosomal digest was determined for 44 multidrug-resistant hospital-acquired methicillin-resistant S. aureus (MR-HA-MRSA) isolates, two multidrug-resistant community-acquired MRSA (MR-CA-MRSA), 50 hospital-acquired MRSA (HA-MRSA) isolates (from the University Hospital Birmingham, NHS Trust, UK) and 34 community-acquired MRSA (CA-MRSA) isolates (from general practitioners in Birmingham, UK). Strain relatedness was determined using Dice band-matching with UPGMA clustering and PCA. The results indicated that PCA revealed relationships between MRSA strains, which were more strongly correlated with known epidemiology, most likely because, unlike cluster analysis, PCA does not have the constraint of generating a hierarchic classification. In addition, PCA provides the opportunity for further analysis to identify key polymorphic bands within complex genotypic profiles, which is not always possible with dendrograms. Here we provide a detailed description of a PCA method for the analysis of PFGE profiles to complement further the epidemiological study of infectious disease. © 2005 Elsevier B.V. All rights reserved.

AntigenDB:an immunoinformatics database of pathogen antigens

The continuing threat of infectious disease and future pandemics, coupled to the continuous increase of drug-resistant pathogens, makes the discovery of new and better vaccines imperative. For effective vaccine development, antigen discovery and validation is a prerequisite. The compilation of information concerning pathogens, virulence factors and antigenic epitopes has resulted in many useful databases. However, most such immunological databases focus almost exclusively on antigens where epitopes are known and ignore those for which epitope information was unavailable. We have compiled more than 500 antigens into the AntigenDB database, making use of the literature and other immunological resources. These antigens come from 44 important pathogenic species. In AntigenDB, a database entry contains information regarding the sequence, structure, origin, etc. of an antigen with additional information such as B and T-cell epitopes, MHC binding, function, gene-expression and post translational modifications, where available. AntigenDB also provides links to major internal and external databases. We shall update AntigenDB on a rolling basis, regularly adding antigens from other organisms and extra data analysis tools. AntigenDB is available freely at http://www.imtech.res.in/raghava/antigendb and its mirror site http://www.bic.uams.edu/raghava/antigendb.

Statnote 35: are the data log-normal?

In many of the Statnotes described in this series, the statistical tests assume the data are a random sample from a normal distribution These Statnotes include most of the familiar statistical tests such as the ‘t’ test, analysis of variance (ANOVA), and Pearson’s correlation coefficient (‘r’). Nevertheless, many variables exhibit a more or less ‘skewed’ distribution. A skewed distribution is asymmetrical and the mean is displaced either to the left (positive skew) or to the right (negative skew). If the mean of the distribution is low, the degree of variation large, and when values can only be positive, a positively skewed distribution is usually the result. Many distributions have potentially a low mean and high variance including that of the abundance of bacterial species on plants, the latent period of an infectious disease, and the sensitivity of certain fungi to fungicides. These positively skewed distributions are often fitted successfully by a variant of the normal distribution called the log-normal distribution. This statnote describes fitting the log-normal distribution with reference to two scenarios: (1) the frequency distribution of bacterial numbers isolated from cloths in a domestic environment and (2), the sizes of lichenised ‘areolae’ growing on the hypothalus of Rhizocarpon geographicum (L.) DC.

Vaginal microbicides for the prevention of HIV transmission

The human immunodeficiency virus (HIV) kills more people worldwide than any other infectious disease. Approximately 42 million people, mostly in Africa and Asia, are currently infected with HIV (Figure 3.1), and 5 million new infections occur every year (AIDS Epidemic Update, 2002). It is estimated that 22 milIion people have died since the first clinical evidence of AIDS (acquired immunodeficiency syndrome) emerged in 1981 ('Mobilization for Microbicides' ~ The Rockfeller Foundation). HIV is generally transmitted in one of three ways: through unprotected sexual intercourse, blood-to-blood contact, and mother-to-child transmission. Once the virus has entered the body, it invades the cells of the immune system and initiates the production of new virus particles with concomitant destruction of the immune cells. As the number of immune cells in the body slowly declines, weight loss, debilitation, and eventually death occur due to opportunistic infections or cancers. Although AIDS is presently incurable, highly active antiretroviral therapy (HAART), where a cocktail of potent antiretroviral drugs are administered daily to HIV-positive patients to control the viral load, has resulted in dramatic reductions in HIV-related morbidity and mortality in the developed world

Characterization of Acanthamoeba-microsphere association by multiparameter flow cytometry and confocal microscopy

Background: Acanthamoebae, in common with other protozoa, readily endocytose particulate material, which in turn may lead to the spread of infectious disease. Methods: Evaluation and quantification of plain and carboxylate FITC-microsphere association with acanthamoebal trophzoites was undertaken using a combination of flow cytometry and confocal microscopy. Trophozoites from strains and species of Acanthamoeba were exposed to plain and carboxylate FITC-microspheres. Microsphere size and aspects such as trophozoite starvation, maturity, and exposure to metabolic inhibitors were assessed. Results: All species and strains of Acanthamoeba readily endocytosed plain and carboxylate microspheres. Starving trophozoites significantly increased binding and potential ingestion of microspheres, whereas trophozoites of increasing maturity lost such abilities. Trophozoites showed a significant preference for 2.0- and 3.0-μm-diameter microspheres when compared with other sizes, which in turn could occupy much of the cytoplasm. The physiological inhibitors sodium azide, 2,4-clinitrophenol, and cytochalasin B reduced microsphere association with trophozoites; however, some microspheres still bound and associated with trophozoites after inhibitor exposure, a manifestation of both active and inactive agent involvement in microsphere endocytosis. Conclusions: Even though the origins of microsphere binding by acanthamoebal trophozoite remains shrouded, the combination of flow cytometry and confocal microscopy supported synergistic quantification and qualification of trophozoite-microsphere endocytosis. © 2006 International Society for Analytical Cytology.

Designing immunogenic peptides

Peptides fulfill many roles in immunology, yet none are more important than their role as immunogenic epitopes driving the adaptive immune response, our ultimate bulwark against infectious disease. Peptide epitopes are mediated primarily by their interaction with major histocompatibility complexes (T-cell epitopes) and antibodies (B-cell epitopes). As pathogen genomes continue to be revealed, both experimental and computational epitope mapping are becoming crucial tools in vaccine discovery1,2. Immunoinformatics offers many tools, techniques and approaches for in silico epitope characterization, which is capable of greatly accelerating epitope design. © 2013 Nature America, Inc. All rights reserved.

Quantifying short-term dynamics of Parkinson's disease using self-reported symptom data from an internet social network

Background: Parkinson’s disease (PD) is an incurable neurological disease with approximately 0.3% prevalence. The hallmark symptom is gradual movement deterioration. Current scientific consensus about disease progression holds that symptoms will worsen smoothly over time unless treated. Accurate information about symptom dynamics is of critical importance to patients, caregivers, and the scientific community for the design of new treatments, clinical decision making, and individual disease management. Long-term studies characterize the typical time course of the disease as an early linear progression gradually reaching a plateau in later stages. However, symptom dynamics over durations of days to weeks remains unquantified. Currently, there is a scarcity of objective clinical information about symptom dynamics at intervals shorter than 3 months stretching over several years, but Internet-based patient self-report platforms may change this. Objective: To assess the clinical value of online self-reported PD symptom data recorded by users of the health-focused Internet social research platform PatientsLikeMe (PLM), in which patients quantify their symptoms on a regular basis on a subset of the Unified Parkinson’s Disease Ratings Scale (UPDRS). By analyzing this data, we aim for a scientific window on the nature of symptom dynamics for assessment intervals shorter than 3 months over durations of several years. Methods: Online self-reported data was validated against the gold standard Parkinson’s Disease Data and Organizing Center (PD-DOC) database, containing clinical symptom data at intervals greater than 3 months. The data were compared visually using quantile-quantile plots, and numerically using the Kolmogorov-Smirnov test. By using a simple piecewise linear trend estimation algorithm, the PLM data was smoothed to separate random fluctuations from continuous symptom dynamics. Subtracting the trends from the original data revealed random fluctuations in symptom severity. The average magnitude of fluctuations versus time since diagnosis was modeled by using a gamma generalized linear model. Results: Distributions of ages at diagnosis and UPDRS in the PLM and PD-DOC databases were broadly consistent. The PLM patients were systematically younger than the PD-DOC patients and showed increased symptom severity in the PD off state. The average fluctuation in symptoms (UPDRS Parts I and II) was 2.6 points at the time of diagnosis, rising to 5.9 points 16 years after diagnosis. This fluctuation exceeds the estimated minimal and moderate clinically important differences, respectively. Not all patients conformed to the current clinical picture of gradual, smooth changes: many patients had regimes where symptom severity varied in an unpredictable manner, or underwent large rapid changes in an otherwise more stable progression. Conclusions: This information about short-term PD symptom dynamics contributes new scientific understanding about the disease progression, currently very costly to obtain without self-administered Internet-based reporting. This understanding should have implications for the optimization of clinical trials into new treatments and for the choice of treatment decision timescales.

Celiac disease-specific TG2-targeted autoantibodies inhibit angiogenesis ex vivo and in vivo in mice by interfering with endothelial cell dynamics

A characteristic feature of celiac disease is the presence of circulating autoantibodies targeted against transglutaminase 2 (TG2), reputed to have a function in angiogenesis. In this study we investigated whether TG2-specific autoantibodies derived from celiac patients inhibit angiogenesis in both ex vivo and in vivo models and sought to clarify the mechanism behind this phenomenon. We used the ex vivo murine aorta-ring and the in vivo mouse matrigel-plug assays to address aforementioned issues. We found angiogenesis to be impaired as a result of celiac disease antibody supplementation in both systems. Our results also showed the dynamics of endothelial cells was affected in the presence of celiac antibodies. In the in vivo angiogenesis assays, the vessels formed were able to transport blood despite impairment of functionality after treatment with celiac autoantibodies, as revealed by positron emission tomography. We conclude that celiac autoantibodies inhibit angiogenesis ex vivo and in vivo and impair vascular functionality. Our data suggest that the anti-angiogenic mechanism of the celiac disease-specific autoantibodies involves extracellular TG2 and inhibited endothelial cell mobility. © 2013 Kalliokoski et al.