The value of position-specific priors in motif discovery using MEME

<p>Abstract</p> <p>Background</p> <p>Position-specific priors have been shown to be a flexible and elegant way to extend the power of Gibbs sampler-based motif discovery algorithms. Information of many types–including sequence conservation, nucleosome positioning, and negative examples–can be converted into a prior over the location of motif sites, which then guides the sequence motif discovery algorithm. This approach has been shown to confer many of the benefits of conservation-based and discriminative motif discovery approaches on Gibbs sampler-based motif discovery methods, but has not previously been studied with methods based on expectation maximization (EM).</p> <p>Results</p> <p>We extend the popular EM-based MEME algorithm to utilize position-specific priors and demonstrate their effectiveness for discovering transcription factor (TF) motifs in yeast and mouse DNA sequences. Utilizing a discriminative, conservation-based prior dramatically improves MEME's ability to discover motifs in 156 yeast TF ChIP-chip datasets, more than doubling the number of datasets where it finds the correct motif. On these datasets, MEME using the prior has a higher success rate than eight other conservation-based motif discovery approaches. We also show that the same type of prior improves the accuracy of motifs discovered by MEME in mouse TF ChIP-seq data, and that the motifs tend to be of slightly higher quality those found by a Gibbs sampling algorithm using the same prior.</p> <p>Conclusions</p> <p>We conclude that using position-specific priors can substantially increase the power of EM-based motif discovery algorithms such as MEME algorithm.</p

HIV-1 DNA Is Maintained in Antigen-Specific CD4+ T Cell Subsets in Patients on Long-Term Antiretroviral Therapy Regardless of Recurrent Antigen Exposure

Memory CD4+ T cells (mCD4s) containing integrated HIV DNA are considered the main barrier to a cure for HIV infection. Here, we analyzed HIV DNA reservoirs in antigen-specific subsets of mCDs to delineate the mechanisms by which HIV reservoirs persist during antiretroviral therapy (ART). HIV Gag, cytomegalovirus (CMV), and tetanus toxoid (TT)-specific mCD4s were isolated from peripheral blood samples obtained from 11 individual subjects, 2-11 years after commencing ART. Antigen-specific mCD4s were identified by the sensitive OX40 assay and purified by cell sorting. Total HIV DNA levels were quantified by real-time PCR, and clonal viral sequences generated from mCD4 subsets and pre-ART plasma samples. Quantitative results and sequence analysis were restricted to five and three study participants, respectively, which was likely due to the low frequency of the antigen-specific mCD4s and relatively low HIV DNA proviral loads. Median HIV Gag-, CMV-, and TT-specific mCD4s were 0.61%, 2.46%, and 0.78% of total mCD4s, and they contained a median of 2.50, 2.38, and 2.55 log 10 copies of HIV DNA per 10 6 cells, respectively. HIV DNA sequences were derived from antigen-specific mCD4s clustered with sequences derived from pre-ART plasma samples. There was a trend toward increased viral diversity in clonal viral sequences derived from CMV-specific mCD4s relative to TT-specific mCD4s. Despite limitations, this study provides direct evidence that HIV reservoirs persist in memory CD4+ T cell subsets maintained by homeostatic proliferation (TT) and adds to growing evidence against viral evolution during ART. Similar future studies require techniques that sample diverse HIV reservoirs and with improved sensitivity

Barriers and opportunities for evidence-based health service planning: the example of developing a Decision Analytic Model to plan services for sexually transmitted infections in the UK

Decision Analytic Models (DAMs) are established means of evidence-synthesis to differentiate between health interventions. They have mainly been used to inform clinical decisions and health technology assessment at the national level, yet could also inform local health service planning. For this, a DAM must take into account the needs of the local population, but also the needs of those planning its services. Drawing on our experiences from stakeholder consultations, where we presented the potential utility of a DAM for planning local health services for sexually transmitted infections (STIs) in the UK, and the evidence it could use to inform decisions regarding different combinations of service provision, in terms of their costs, cost-effectiveness, and public health outcomes, we discuss the barriers perceived by stakeholders to the use of DAMs to inform service planning for local populations, including (1) a tension between individual and population perspectives; (2) reductionism; and (3) a lack of transparency regarding models, their assumptions, and the motivations of those generating models

Sounds, Behaviour, and Auditory Receptors of the Armoured Ground Cricket, Acanthoplus longipes

The auditory sensory system of the taxon Hetrodinae has not been studied previously. Males of the African armoured ground cricket, Acanthoplus longipes (Orthoptera: Tettigoniidae: Hetrodinae) produce a calling song that lasts for minutes and consists of verses with two pulses. About three impulses are in the first pulse and about five impulses are in the second pulse. In contrast, the disturbance stridulation consists of verses with about 14 impulses that are not separated in pulses. Furthermore, the inter-impulse intervals of both types of sounds are different, whereas verses have similar durations. This indicates that the neuronal networks for sound generation are not identical. The frequency spectrum peaks at about 15 kHz in both types of sounds, whereas the hearing threshold has the greatest sensitivity between 4 and 10 kHz. The auditory afferents project into the prothoracic ganglion. The foreleg contains about 27 sensory neurons in the crista acustica; the midleg has 18 sensory neurons, and the hindleg has 14. The auditory system is similar to those of other Tettigoniidae

Quantification of Residual Germinal Center Activity and HIV-1 DNA and RNA Levels Using Fine Needle Biopsies of Lymph Nodes during Antiretroviral Therapy

HIV-1 reservoirs are most often studied in peripheral blood (PB), but not all lymphocytes recirculate, particularly T follicular helper (Tfh) CD4+ T cells, as well as germinal center (GC) B cells, in lymph nodes (LNs). Ultrasound-guided fine needle biopsies (FNBs) from inguinal LNs and PB samples were obtained from 10 healthy controls (HCs) and 21 HIV-1-infected subjects [11 antiretroviral therapy (ART) naive and 10 on ART]. Tfh cells and GC B cells were enumerated by flow cytometry. HIV-1 DNA and cell-associated (CA) RNA levels in LNs and PB were quantified by real-time polymerase chain reaction. FNBs were obtained without adverse events. Tfh cells and GC B cells were highly elevated in ART-naive subjects, with a median GC B cell count >300-fold higher than HCs, but also remained higher in 4 out of the 10 subjects on ART. GC B cell counts and Tfh cell counts were highly correlated with each other, and also with activated T cells in LNs but not in blood. Levels of HIV-1 DNA and CA RNA viral burden in highly purified CD4+ T cells from FNBs were significantly elevated compared with those in CD4+ T cells from PB in the ART-naive group, but only trended toward an increase in the ART patients. FNBs enabled minimally invasive access to, and parallel measurement of residual activated T and B cells and viral burden within LNs in HIV-1-infected patients. These FNBs revealed significant GC activity that was not apparent from corresponding PB samples

Metformin:historical overview

Metformin (dimethylbiguanide) has become the preferred first-line oral blood glucose-lowering agent to manage type 2 diabetes. Its history is linked to Galega officinalis (also known as goat's rue), a traditional herbal medicine in Europe, found to be rich in guanidine, which, in 1918, was shown to lower blood glucose. Guanidine derivatives, including metformin, were synthesised and some (not metformin) were used to treat diabetes in the 1920s and 1930s but were discontinued due to toxicity and the increased availability of insulin. Metformin was rediscovered in the search for antimalarial agents in the 1940s and, during clinical tests, proved useful to treat influenza when it sometimes lowered blood glucose. This property was pursued by the French physician Jean Sterne, who first reported the use of metformin to treat diabetes in 1957. However, metformin received limited attention as it was less potent than other glucose-lowering biguanides (phenformin and buformin), which were generally discontinued in the late 1970s due to high risk of lactic acidosis. Metformin's future was precarious, its reputation tarnished by association with other biguanides despite evident differences. The ability of metformin to counter insulin resistance and address adult-onset hyperglycaemia without weight gain or increased risk of hypoglycaemia gradually gathered credence in Europe, and after intensive scrutiny metformin was introduced into the USA in 1995. Long-term cardiovascular benefits of metformin were identified by the UK Prospective Diabetes Study (UKPDS) in 1998, providing a new rationale to adopt metformin as initial therapy to manage hyperglycaemia in type 2 diabetes. Sixty years after its introduction in diabetes treatment, metformin has become the most prescribed glucose-lowering medicine worldwide with the potential for further therapeutic applications

Mixing patterns and the spread of close-contact infectious diseases

Surprisingly little is known regarding the human mixing patterns relevant to the spread of close-contact infections, such as measles, influenza and meningococcal disease. This study aims to estimate the number of partnerships that individuals make, their stability and the degree to which mixing is assortative with respect to age. We defined four levels of putative at-risk events from casual (physical contact without conversation) to intimate (contact of a sexual nature), and asked university student volunteers to record details on those they contacted at these levels on three separate days. We found that intimate contacts are stable over short time periods whereas there was no evidence of repeat casual contacts with the same individuals. The contacts were increasingly assortative as intimacy increased. Such information will aid the development and parameterisation of models of close contact diseases, and may have direct use in outbreak investigations

Transition probabilities for general birth-death processes with applications in ecology, genetics, and evolution

A birth-death process is a continuous-time Markov chain that counts the number of particles in a system over time. In the general process with $n$ current particles, a new particle is born with instantaneous rate $\lambda_n$ and a particle dies with instantaneous rate $\mu_n$. Currently no robust and efficient method exists to evaluate the finite-time transition probabilities in a general birth-death process with arbitrary birth and death rates. In this paper, we first revisit the theory of continued fractions to obtain expressions for the Laplace transforms of these transition probabilities and make explicit an important derivation connecting transition probabilities and continued fractions. We then develop an efficient algorithm for computing these probabilities that analyzes the error associated with approximations in the method. We demonstrate that this error-controlled method agrees with known solutions and outperforms previous approaches to computing these probabilities. Finally, we apply our novel method to several important problems in ecology, evolution, and genetics

Predicting language diversity with complex network

Evolution and propagation of the world's languages is a complex phenomenon, driven, to a large extent, by social interactions. Multilingual society can be seen as a system of interacting agents, where the interaction leads to a modification of the language spoken by the individuals. Two people can reach the state of full linguistic compatibility due to the positive interactions, like transfer of loanwords. But, on the other hand, if they speak entirely different languages, they will separate from each other. These simple observations make the network science the most suitable framework to describe and analyze dynamics of language change. Although many mechanisms have been explained, we lack a qualitative description of the scaling behavior for different sizes of a population. Here we address the issue of the language diversity in societies of different sizes, and we show that local interactions are crucial to capture characteristics of the empirical data. We propose a model of social interactions, extending the idea from, that explains the growth of the language diversity with the size of a population of country or society. We argue that high clustering and network disintegration are the most important characteristics of models properly describing empirical data. Furthermore, we cancel the contradiction between previous models and the Solomon Islands case. Our results demonstrate the importance of the topology of the network, and the rewiring mechanism in the process of language change

BayesMotif: de novo protein sorting motif discovery from impure datasets

Background Protein sorting is the process that newly synthesized proteins are transported to their target locations within or outside of the cell. This process is precisely regulated by protein sorting signals in different forms. A major category of sorting signals are amino acid sub-sequences usually located at the N-terminals or C-terminals of protein sequences. Genome-wide experimental identification of protein sorting signals is extremely time-consuming and costly. Effective computational algorithms for de novo discovery of protein sorting signals is needed to improve the understanding of protein sorting mechanisms. Methods We formulated the protein sorting motif discovery problem as a classification problem and proposed a Bayesian classifier based algorithm (BayesMotif) for de novo identification of a common type of protein sorting motifs in which a highly conserved anchor is present along with a less conserved motif regions. A false positive removal procedure is developed to iteratively remove sequences that are unlikely to contain true motifs so that the algorithm can identify motifs from impure input sequences. Results Experiments on both implanted motif datasets and real-world datasets showed that the enhanced BayesMotif algorithm can identify anchored sorting motifs from pure or impure protein sequence dataset. It also shows that the false positive removal procedure can help to identify true motifs even when there is only 20% of the input sequences containing true motif instances. Conclusion We proposed BayesMotif, a novel Bayesian classification based algorithm for de novo discovery of a special category of anchored protein sorting motifs from impure datasets. Compared to conventional motif discovery algorithms such as MEME, our algorithm can find less-conserved motifs with short highly conserved anchors. Our algorithm also has the advantage of easy incorporation of additional meta-sequence features such as hydrophobicity or charge of the motifs which may help to overcome the limitations of PWM (position weight matrix) motif model