Dirichlet multinomial mixtures: generative models for microbial metagenomics

We introduce Dirichlet multinomial mixtures (DMM) for the probabilistic modelling of microbial metagenomics data. This data can be represented as a frequency matrix giving the number of times each taxa is observed in each sample. The samples have different size, and the matrix is sparse, as communities are diverse and skewed to rare taxa. Most methods used previously to classify or cluster samples have ignored these features. We describe each community by a vector of taxa probabilities. These vectors are generated from one of a finite number of Dirichlet mixture components each with different hyperparameters. Observed samples are generated through multinomial sampling. The mixture components cluster communities into distinct 'metacommunities', and, hence, determine envirotypes or enterotypes, groups of communities with a similar composition. The model can also deduce the impact of a treatment and be used for classification. We wrote software for the fitting of DMM models using the 'evidence framework' (http://code.google.com/p/microbedmm/). This includes the Laplace approximation of the model evidence. We applied the DMM model to human gut microbe genera frequencies from Obese and Lean twins. From the model evidence four clusters fit this data best. Two clusters were dominated by Bacteroides and were homogenous; two had a more variable community composition. We could not find a significant impact of body mass on community structure. However, Obese twins were more likely to derive from the high variance clusters. We propose that obesity is not associated with a distinct microbiota but increases the chance that an individual derives from a disturbed enterotype. This is an example of the 'Anna Karenina principle (AKP)' applied to microbial communities: disturbed states having many more configurations than undisturbed. We verify this by showing that in a study of inflammatory bowel disease (IBD) phenotypes, ileal Crohn's disease (ICD) is associated with a more variable community.     

Using Stochastic modelling to identify unusual continuous glucose monitor measurements and behaviour, in newborn infants

ABSTRACT: BACKGROUND: : Abnormal blood glucose (BG) concentrations have been associated with increased morbidity and mortality in both critically ill adults and infants. Furthermore, hypoglycaemia and glycaemic variability have both been independently linked to mortality in these patients. Continuous Glucose Monitoring (CGM) devices have the potential to improve detection and diagnosis of these glycaemic abnormalities. However, sensor noise is a trade-off of the high measurement rate and must be managed effectively if CGMs are going to be used to monitor, diagnose and potentially help treat glycaemic abnormalities. AIM: To develop a tool that will aid clinicians in identifying unusual CGM behaviour and highlight CGM data that potentially need to be interpreted with care. METHOD: S: CGM data and BG measurements from 50 infants at risk of hypoglycaemia were used. Unusual CGM measurements were classified using a stochastic model based on the kernel density method and historical CGM measurements from the cohort. CGM traces were colour coded with very unusual measurements coloured red, highlighting areas to be interpreted with care. A 5-fold validation of the model was Monte Carlo simulated 25 times to ensure an adequate model fit. RESULTS: : The stochastic model was generated using ~67,000 CGM measurements, spread across the glycaemic range ~2-10mmol/L. A 5-fold validation showed a good model fit: the model 80% confidence interval (CI) captured 83% of clinical CGM data, the model 90% CI captured 91% of clinical CGM data, and the model 99% CI captured 99% of clinical CGM data. Three patient examples show the stochastic classification method in use with 1) A stable, low variability patient which shows no unusual CGM measurements, 2) A patient with a very sudden, short hypoglycaemic event (classified as unusual), and, 3) A patient with very high, potentially un-physiological, glycaemic variability after day 3 of monitoring (classified as very unusual). CONCLUSIONS: : This study has produced a stochastic model and classification method capable of highlighting unusual CGM behaviour. This method has the potential to classify important glycaemic events (e.g. hypoglycaemia) as true clinical events or sensor noise, and to help identify possible sensor degradation. Colour coded CGM traces convey the information quickly and efficiently, while remaining computationally light enough to be used retrospectively or in real-time.     

Generation of a conditional allele for the mouse endothelial nitric oxide synthase gene

Mice with endothelial nitric oxide synthase (eNOS) deletions have defined the crucial role of eNOS in vascular development, homeostasis, and pathology. However, cell specific eNOS function has not been determined, although an important role of eNOS has been suggested in multiple cell types. Here, we have generated a floxed eNOS allele in which exons 9–12, encoding the sites essential to eNOS activity, are flanked with loxP sites. Mice homozygous for the floxed allele showed normal eNOS protein levels and no overt phenotype. Conversely, homozygous mice with Cre‐deleted alleles displayed truncated eNOS protein, lack of vascular NO production, and exhibited similar phenotype to eNOS knockout mice, including hypertension, low heart rate, and focal renal scarring. These findings demonstrate that the floxed allele is normal and it can be converted to a non‐functional eNOS allele through Cre recombination. This mouse will allow time‐ and cell‐specific eNOS deletion. genesis 50:685–692, 2012. © 2012 Wiley Periodicals, Inc.     

Plasmodium falciparum produce lower infection intensities in local versus foreign Anopheles gambiae populations

Both Plasmodium falciparum and Anopheles gambiae show great diversity in Africa, in their own genetic makeup and population dynamics. The genetics of the individual mosquito and parasite are known to play a role in determining the outcome of infection in the vector, but whether differences in infection phenotype vary between populations remains to be investigated. Here we established two A. gambiae s.s. M molecular form colonies from Cameroon and Burkina Faso, representing a local and a foreign population for each of the geographical sites. Experimental infections of both colonies were conducted in Cameroon and Burkina Faso using local wild P. falciparum, giving a sympatric and allopatric vector-parasite combination in each site. Infection phenotype was determined in terms of oocyst prevalence and intensity for at least nine infections for each vector-parasite combination. Sympatric infections were found to produce 25% fewer oocysts per midgut than allopatric infections, while prevalence was not affected by local/foreign interactions. The reduction in oocyst numbers in sympatric couples may be the result of evolutionary processes where the mosquito populations have locally adapted to their parasite populations. Future research on vector-parasite interactions must take into account the geographic scale of adaptation revealed here by conducting experiments in natural sympatric populations to give epidemiologically meaningful results.     

Learning to use illumination gradients as an unambiguous cue to three dimensional shape

The luminance and colour gradients across an image are the result of complex interactions between object shape, material and illumination. Using such variations to infer object shape or surface colour is therefore a difficult problem for the visual system. We know that changes to the shape of an object can affect its perceived colour, and that shading gradients confer a sense of shape. Here we investigate if the visual system is able to effectively utilise these gradients as a cue to shape perception, even when additional cues are not available. We tested shape perception of a folded card object that contained illumination gradients in the form of shading and more subtle effects such as inter-reflections. Our results suggest that observers are able to use the gradients to make consistent shape judgements. In order to do this, observers must be given the opportunity to learn suitable assumptions about the lighting and scene. Using a variety of different training conditions, we demonstrate that learning can occur quickly and requires only coarse information. We also establish that learning does not deliver a trivial mapping between gradient and shape; rather learning leads to the acquisition of assumptions about lighting and scene parameters that subsequently allow for gradients to be used as a shape cue. The perceived shape is shown to be consistent for convex and concave versions of the object that exhibit very different shading, and also similar to that delivered by outline, a largely unrelated cue to shape. Overall our results indicate that, although gradients are less reliable than some other cues, the relationship between gradients and shape can be quickly assessed and the gradients therefore used effectively as a visual shape cue.     

Early clinical features of dengue virus infection in nicaraguan children: a longitudinal analysis

Background

Tens of millions of dengue cases and approximately 500,000 life-threatening complications occur annually. New tools are needed to distinguish dengue from other febrile illnesses. In addition, the natural history of pediatric dengue early in illness in a community-based setting has not been well-defined.

Methods

Data from the multi-year, ongoing Pediatric Dengue Cohort Study of approximately 3,800 children aged 2–14 years in Managua, Nicaragua, were used to examine the frequency of clinical signs and symptoms by day of illness and to generate models for the association of signs and symptoms during the early phase of illness and over the entire course of illness with testing dengue-positive. Odds ratios (ORs) and 95% confidence intervals were calculated using generalized estimating equations (GEE) for repeated measures, adjusting for age and gender.

Results

One-fourth of children who tested dengue-positive did not meet the WHO case definition for suspected dengue. The frequency of signs and symptoms varied by day of illness, dengue status, and disease severity. Multivariable GEE models showed increased odds of testing dengue-positive associated with fever, headache, retro-orbital pain, myalgia, arthralgia, rash, petechiae, positive tourniquet test, vomiting, leukopenia, platelets ≤150,000 cells/mL, poor capillary refill, cold extremities and hypotension. Estimated ORs tended to be higher for signs and symptoms over the course of illness compared to the early phase of illness.

Conclusions

Day-by-day analysis of clinical signs and symptoms together with longitudinal statistical analysis showed significant associations with testing dengue-positive and important differences during the early phase of illness compared to the entire course of illness. These findings stress the importance of considering day of illness when developing prediction algorithms for real-time clinical management.     

Adult human RPE can be activated into a multipotent stem cell that produces mesenchymal derivatives

The retinal pigment epithelium (RPE) is a monolayer of cells underlying and supporting the neural retina. It begins as a plastic tissue, capable, in some species, of generating lens and retina, but differentiates early in development and remains normally nonproliferative throughout life. Here we show that a subpopulation of adult human RPE cells can be activated in vitro to a self-renewing cell, the retinal pigment epithelial stem cell (RPESC) that loses RPE markers, proliferates extensively, and can redifferentiate into stable cobblestone RPE monolayers. Clonal studies demonstrate that RPESCs are multipotent and in defined conditions can generate both neural and mesenchymal progeny. This plasticity may explain human pathologies in which mesenchymal fates are seen in the eye, for example in proliferative vitroretinopathy (PVR) and phthisis bulbi. This study establishes the RPESC as an accessible, human CNS-derived multipotent stem cell, useful for the study of fate choice, replacement therapy, and disease modeling.