PicXAA-Web: a web-based platform for non-progressive maximum expected accuracy alignment of multiple biological sequences

In this article, we introduce PicXAA-Web, a web-based platform for accurate probabilistic alignment of multiple biological sequences. The core of PicXAA-Web consists of PicXAA, a multiple protein/DNA sequence alignment algorithm, and PicXAA-R, an extension of PicXAA for structural alignment of RNA sequences. Both PicXAA and PicXAA-R are probabilistic non-progressive alignment algorithms that aim to find the optimal alignment of multiple biological sequences by maximizing the expected accuracy. PicXAA and PicXAA-R greedily build up the alignment from sequence regions with high local similarity, thereby yielding an accurate global alignment that effectively captures local similarities among sequences. PicXAA-Web integrates these two algorithms in a user-friendly web platform for accurate alignment and analysis of multiple protein, DNA and RNA sequences. PicXAA-Web can be freely accessed at http://gsp.tamu.edu/picxaa/

Molecular Signaling and Dysfunction of the Human Reactive Enteric Glial Cell Phenotype: Implications for GI Infection, IBD, POI, Neurological, Motility, and GI Disorders

BACKGROUND: Clinical observations or animal studies implicate enteric glial cells in motility disorders, irritable bowel syndrome, inflammatory bowel disease, gastrointestinal (GI) infections, postoperative ileus, and slow transit constipation. Mechanisms underlying glial responses to inflammation in human GI tract are not understood. Our goal was to identify the "reactive human enteric glial cell (rhEGC) phenotype" induced by inflammation, and probe its functional relevance. METHODS: Human enteric glial cells in culture from 15 GI-surgical specimens were used to study gene expression, Ca, and purinergic signaling by Ca/fluo-4 imaging and mechanosensitivity. A nanostring panel of 107 genes was designed as a read out of inflammation, transcription, purinergic signaling, vesicular transport protein, channel, antioxidant, and other pathways. A 24-hour treatment with lipopolysaccharide (200 μg/mL) and interferon-γ (10 μg/mL) was used to induce inflammation and study molecular signaling, flow-dependent Ca responses from 3 mL/min to 10 mL/min, adenosine triphosphate (ATP) release, and ATP responses. RESULTS: Treatment induced a "rhEGC phenotype" and caused up-regulation in messenger RNA transcripts of 58% of 107 genes analyzed. Regulated genes included inflammatory genes (54%/IP10; IFN-γ; CxCl2; CCL3; CCL2; C3; s100B; IL-1β; IL-2R; TNF-α; IL-4; IL-6; IL-8; IL-10; IL-12A; IL-17A; IL-22; and IL-33), purine-genes (52%/AdoR2A; AdoR2B; P2RY1; P2RY2; P2RY6; P2RX3; P2RX7; AMPD3; ENTPD2; ENTPD3; and NADSYN1), channels (40%/Panx1; CHRNA7; TRPV1; and TRPA1), vesicular transporters (SYT1, SYT2, SNAP25, and SYP), transcription factors (relA/relB, SOCS3, STAT3, GATA_3, and FOXP3), growth factors (IGFBP5 and GMCSF), antioxidant genes (SOD2 and HMOX1), and enzymes (NOS2; TPH2; and CASP3) (P < 0.0001). Treatment disrupted Ca signaling, ATP, and mechanical/flow-dependent Ca responses in human enteric glial cells. ATP release increased 5-fold and s100B decreased 33%. CONCLUSIONS: The "rhEGC phenotype" is identified by a complex cascade of pro-inflammatory pathways leading to alterations of important molecular and functional signaling pathways (Ca, purinergic, and mechanosensory) that could disrupt GI motility. Inflammation induced a "purinergic switch" from ATP to adenosine diphosphate/adenosine/uridine triphosphate signaling. Findings have implications for GI infection, inflammatory bowel disease, postoperative ileus, motility, and GI disorders

Identifying paediatric nursing-sensitive outcomes in linked administrative health data

There is increasing interest in the contribution of the quality of nursing care to patient outcomes. Due to different casemix and risk profiles, algorithms for administrative health data that identify nursing-sensitive outcomes in adult hospitalised patients may not be applicable to paediatric patients. The study purpose was to test adult algorithms in a paediatric hospital population and make amendments to increase the accuracy of identification of hospital acquitted events. The study also aimed to determine whether the use of linked hospital records improved the likelihood of correctly identifying patient outcomes as nursing sensitive rather than being related to their pre-morbid conditions. Algorithm for nursing-sensitive outcomes used in adult populations have to be amended before application to paediatric populations. Using unlinked individual hospitalisation records to estimate rates of nursing-sensitive outcomes is likely to result in inaccurate rates

Decreased Brain Volume in Adults with Childhood Lead Exposure

Using magnetic resonance imaging to assess brain volumes, Kim Cecil and colleagues find that inner-city children with higher blood lead levels showed regions of decreased gray matter as adults

Reproducing the manual annotation of multiple sequence alignments using a SVM classifier

Motivation: Aligning protein sequences with the best possible accuracy requires sophisticated algorithms. Since the optimal alignment is not guaranteed to be the correct one, it is expected that even the best alignment will contain sites that do not respect the assumption of positional homology. Because formulating rules to identify these sites is difficult, it is common practice to manually remove them. Although considered necessary in some cases, manual editing is time consuming and not reproducible. We present here an automated editing method based on the classification of ‘valid’ and ‘invalid’ sites

How reliably can we predict the reliability of protein structure predictions?

Background: Comparative methods have been the standard techniques for in silico protein structure prediction. The prediction is based on a multiple alignment that contains both reference sequences with known structures and the sequence whose unknown structure is predicted. Intensive research has been made to improve the quality of multiple alignments, since misaligned parts of the multiple alignment yield misleading predictions. However, sometimes all methods fail to predict the correct alignment, because the evolutionary signal is too weak to find the homologous parts due to the large number of mutations that separate the sequences. Results: Stochastic sequence alignment methods define a posterior distribution of possible multiple alignments. They can highlight the most likely alignment, and above that, they can give posterior probabilities for each alignment column. We made a comprehensive study on the HOMSTRAD database of structural alignments, predicting secondary structures in four different ways. We showed that alignment posterior probabilities correlate with the reliability of secondary structure predictions, though the strength of the correlation is different for different protocols. The correspondence between the reliability of secondary structure predictions and alignment posterior probabilities is the closest to the identity function when the secondary structure posterior probabilities are calculated from the posterior distribution of multiple alignments. The largest deviation from the identity function has been obtained in the case of predicting secondary structures from a single optimal pairwise alignment. We also showed that alignment posterior probabilities correlate with the 3D distances between C α amino acids in superimposed tertiary structures. Conclusion: Alignment posterior probabilities can be used to a priori detect errors in comparative models on the sequence alignment level. </p

MACSE: Multiple Alignment of Coding SEquences Accounting for Frameshifts and Stop Codons

Until now the most efficient solution to align nucleotide sequences containing open reading frames was to use indirect procedures that align amino acid translation before reporting the inferred gap positions at the codon level. There are two important pitfalls with this approach. Firstly, any premature stop codon impedes using such a strategy. Secondly, each sequence is translated with the same reading frame from beginning to end, so that the presence of a single additional nucleotide leads to both aberrant translation and alignment

Institutional risk factors for norovirus outbreaks in Hong Kong elderly homes: a retrospective cohort study

<p>Abstract</p> <p>Background</p> <p>Most of the institutional outbreaks of norovirus in Hong Kong occur in elderly homes, the proportion being 69% in 2006. Residents in elderly homes are a special population seriously affected by norovirus infections, it is necessary to investigate the risk factors of the norovirus outbreaks in Hong Kong elderly homes at the facility level.</p> <p>Methods</p> <p>A cohort of 748 elderly homes was followed up from January 2005 to December 2007; each elderly home was treated as one observation unit and the outcome event was the norovirus outbreak. Cox regression models were fitted to estimate the rate ratio (RR) and 95% confidence interval (CI) for the potential risk factors.</p> <p>Results</p> <p>A total of 276 norovirus outbreaks were confirmed during the study period; the outbreak rate was 12.2 (95% CI: 9.9-14.6) per 100 home-years; elderly homes with a larger capacity (RR = 1.4, 95% CI: 1.3-1.5 (per 30-resident increment)), a higher staff-to-resident ratio (RR = 1.2, 95% CI: 1.1-1.3 (per 1/30 increment) and better wheelchair accessibility (RR = 2.0, 95% CI: 1.3-3.2) were found to have an elevated norovirus outbreak rate in Hong Kong elderly homes; Elderly homes with partitions between beds had a lower rate of norovirus outbreaks (RR = 0.6, 95% CI: 0.4-0.8).</p> <p>Conclusions</p> <p>Elderly home capacity, staff-to-resident ratio and wheelchair accessibility were risk factors for norovirus outbreaks in Hong Kong elderly homes. Partitions between beds were a protective factor of norovirus outbreaks. These results should be considered in the infection control in Hong Kong elderly homes.</p

Efficient representation of uncertainty in multiple sequence alignments using directed acyclic graphs

Background A standard procedure in many areas of bioinformatics is to use a single multiple sequence alignment (MSA) as the basis for various types of analysis. However, downstream results may be highly sensitive to the alignment used, and neglecting the uncertainty in the alignment can lead to significant bias in the resulting inference. In recent years, a number of approaches have been developed for probabilistic sampling of alignments, rather than simply generating a single optimum. However, this type of probabilistic information is currently not widely used in the context of downstream inference, since most existing algorithms are set up to make use of a single alignment. Results In this work we present a framework for representing a set of sampled alignments as a directed acyclic graph (DAG) whose nodes are alignment columns; each path through this DAG then represents a valid alignment. Since the probabilities of individual columns can be estimated from empirical frequencies, this approach enables sample-based estimation of posterior alignment probabilities. Moreover, due to conditional independencies between columns, the graph structure encodes a much larger set of alignments than the original set of sampled MSAs, such that the effective sample size is greatly increased. Conclusions The alignment DAG provides a natural way to represent a distribution in the space of MSAs, and allows for existing algorithms to be efficiently scaled up to operate on large sets of alignments. As an example, we show how this can be used to compute marginal probabilities for tree topologies, averaging over a very large number of MSAs. This framework can also be used to generate a statistically meaningful summary alignment; example applications show that this summary alignment is consistently more accurate than the majority of the alignment samples, leading to improvements in downstream tree inference. Implementations of the methods described in this article are available at http://statalign.github.io/WeaveAlign webcite

Assessment of the Food Habits of the Moroccan Dorcas Gazelle in M’Sabih Talaa, West Central Morocco, Using the trnL Approach

Food habits of the Moroccan dorcas gazelle, Gazella dorcas massaesyla, previously investigated in the 1980s using microhistological fecal analysis, in the M’Sabih Talaa Reserve, west central Morocco, were re-evaluated over three seasons (spring, summer and autumn 2009) using the trnL approach to determine the diet composition and its seasonal variation from fecal samples. Taxonomic identification was carried out using the identification originating from the database built from EMBL and the list of plant species within the reserve. The total taxonomic richness in the reserve was 130 instead of 171 species in the 1980s. The diet composition revealed to be much more diversified (71 plant taxa belonging to 57 genus and 29 families) than it was 22 years ago (29 identified taxa). Thirty-four taxa were newly identified in the diet while 13 reported in 1986–87 were not found. Moroccan dorcas gazelle showed a high preference to Acacia gummifera, Anagallis arvensis, Glebionis coronaria, Cladanthus arabicus, Diplotaxis tenuisiliqua, Erodium salzmannii, Limonium thouini, Lotus arenarius and Zizyphus lotus. Seasonal variations occurred in both number (40–41 taxa in spring-summer and 49 taxa in autumn vs. respectively 23–22 and 26 in 1986–1987) and taxonomic type of eaten plant taxa. This dietary diversification could be attributed either to the difference in methods of analysis, trnL approach having a higher taxonomic resolution, or a potential change in nutritional quality of plants over time