EnvMine: A text-mining system for the automatic extraction of contextual information

<p>Abstract</p> <p>Background</p> <p>For ecological studies, it is crucial to count on adequate descriptions of the environments and samples being studied. Such a description must be done in terms of their physicochemical characteristics, allowing a direct comparison between different environments that would be difficult to do otherwise. Also the characterization must include the precise geographical location, to make possible the study of geographical distributions and biogeographical patterns. Currently, there is no schema for annotating these environmental features, and these data have to be extracted from textual sources (published articles). So far, this had to be performed by manual inspection of the corresponding documents. To facilitate this task, we have developed EnvMine, a set of text-mining tools devoted to retrieve contextual information (physicochemical variables and geographical locations) from textual sources of any kind.</p> <p>Results</p> <p>EnvMine is capable of retrieving the physicochemical variables cited in the text, by means of the accurate identification of their associated units of measurement. In this task, the system achieves a recall (percentage of items retrieved) of 92% with less than 1% error. Also a Bayesian classifier was tested for distinguishing parts of the text describing environmental characteristics from others dealing with, for instance, experimental settings.</p> <p>Regarding the identification of geographical locations, the system takes advantage of existing databases such as GeoNames to achieve 86% recall with 92% precision. The identification of a location includes also the determination of its exact coordinates (latitude and longitude), thus allowing the calculation of distance between the individual locations.</p> <p>Conclusion</p> <p>EnvMine is a very efficient method for extracting contextual information from different text sources, like published articles or web pages. This tool can help in determining the precise location and physicochemical variables of sampling sites, thus facilitating the performance of ecological analyses. EnvMine can also help in the development of standards for the annotation of environmental features.</p

Bacterial activity in cystic fibrosis lung infections

BACKGROUND: Chronic lung infections are the primary cause of morbidity and mortality in Cystic Fibrosis (CF) patients. Recent molecular biological based studies have identified a surprisingly wide range of hitherto unreported bacterial species in the lungs of CF patients. The aim of this study was to determine whether the species present were active and, as such, worthy of further investigation as potential pathogens. METHODS: Terminal Restriction Fragment Length Polymorphism (T-RFLP) profiles were generated from PCR products amplified from 16S rDNA and Reverse Transcription Terminal Restriction Fragment Length Polymorphism (RT-T-RFLP) profiles, a marker of metabolic activity, were generated from PCR products amplified from 16S rRNA, both extracted from the same CF sputum sample. To test the level of activity of these bacteria, T-RFLP profiles were compared to RT-T-RFLP profiles. RESULTS: Samples from 17 individuals were studied. Parallel analyses identified a total of 706 individual T-RF and RT-T-RF bands in this sample set. 323 bands were detected by T-RFLP and 383 bands were detected by RT-T-RFLP (statistically significant; P ≤ 0.001). For the group as a whole, 145 bands were detected in a T-RFLP profile alone, suggesting metabolically inactive bacteria. 205 bands were detected in an RT-T-RFLP profile alone and 178 bands were detected in both, suggesting a significant degree of metabolic activity. Although Pseudomonas aeruginosa was present and active in many patients, a low occurrence of other species traditionally considered to be key CF pathogens was detected. T-RFLP profiles obtained for induced sputum samples provided by healthy individuals without CF formed a separate cluster indicating a low level of similarity to those from CF patients. CONCLUSION: These results indicate that a high proportion of the bacterial species detected in the sputum from all of the CF patients in the study are active. The widespread activity of bacterial species in these samples emphasizes the potential importance of these previously unrecognized species within the CF lung

Robust estimation of microbial diversity in theory and in practice

Quantifying diversity is of central importance for the study of structure, function and evolution of microbial communities. The estimation of microbial diversity has received renewed attention with the advent of large-scale metagenomic studies. Here, we consider what the diversity observed in a sample tells us about the diversity of the community being sampled. First, we argue that one cannot reliably estimate the absolute and relative number of microbial species present in a community without making unsupported assumptions about species abundance distributions. The reason for this is that sample data do not contain information about the number of rare species in the tail of species abundance distributions. We illustrate the difficulty in comparing species richness estimates by applying Chao's estimator of species richness to a set of in silico communities: they are ranked incorrectly in the presence of large numbers of rare species. Next, we extend our analysis to a general family of diversity metrics ("Hill diversities"), and construct lower and upper estimates of diversity values consistent with the sample data. The theory generalizes Chao's estimator, which we retrieve as the lower estimate of species richness. We show that Shannon and Simpson diversity can be robustly estimated for the in silico communities. We analyze nine metagenomic data sets from a wide range of environments, and show that our findings are relevant for empirically-sampled communities. Hence, we recommend the use of Shannon and Simpson diversity rather than species richness in efforts to quantify and compare microbial diversity.Comment: To be published in The ISME Journal. Main text: 16 pages, 5 figures. Supplement: 16 pages, 4 figure

Effects of social approval bias on self-reported fruit and vegetable consumption: a randomized controlled trial

<p>Abstract</p> <p>Background</p> <p>Self-reports of dietary intake in the context of nutrition intervention research can be biased by the tendency of respondents to answer consistent with expected norms (social approval bias). The objective of this study was to assess the potential influence of social approval bias on self-reports of fruit and vegetable intake obtained using both food frequency questionnaire (FFQ) and 24-hour recall methods.</p> <p>Methods</p> <p>A randomized blinded trial compared reported fruit and vegetable intake among subjects exposed to a potentially biasing prompt to that from control subjects. Subjects included 163 women residing in Colorado between 35 and 65 years of age who were randomly selected and recruited by telephone to complete what they were told would be a future telephone survey about health. Randomly half of the subjects then received a letter prior to the interview describing this as a study of fruit and vegetable intake. The letter included a brief statement of the benefits of fruits and vegetables, a 5-A-Day sticker, and a 5-a-Day refrigerator magnet. The remainder received the same letter, but describing the study purpose only as a more general nutrition survey, with neither the fruit and vegetable message nor the 5-A-Day materials. Subjects were then interviewed on the telephone within 10 days following the letters using an eight-item FFQ and a limited 24-hour recall to estimate fruit and vegetable intake. All interviewers were blinded to the treatment condition.</p> <p>Results</p> <p>By the FFQ method, subjects who viewed the potentially biasing prompts reported consuming more fruits and vegetables than did control subjects (5.2 vs. 3.7 servings per day, p < 0.001). By the 24-hour recall method, 61% of the intervention group but only 32% of the control reported eating fruits and vegetables on 3 or more occasions the prior day (p = 0.002). These associations were independent of age, race/ethnicity, education level, self-perceived health status, and time since last medical check-up.</p> <p>Conclusion</p> <p>Self-reports of fruit and vegetable intake using either a food frequency questionnaire or a limited 24-hour recall are both susceptible to substantial social approval bias. Valid assessments of intervention effects in nutritional intervention trials may require objective measures of dietary change.</p

Global Patterns of Bacterial Beta-Diversity in Seafloor and Seawater Ecosystems

Background Marine microbial communities have been essential contributors to global biomass, nutrient cycling, and biodiversity since the early history of Earth, but so far their community distribution patterns remain unknown in most marine ecosystems. Methodology/Principal Findings The synthesis of 9.6 million bacterial V6-rRNA amplicons for 509 samples that span the global ocean's surface to the deep-sea floor shows that pelagic and benthic communities greatly differ, at all taxonomic levels, and share <10% bacterial types defined at 3% sequence similarity level. Surface and deep water, coastal and open ocean, and anoxic and oxic ecosystems host distinct communities that reflect productivity, land influences and other environmental constraints such as oxygen availability. The high variability of bacterial community composition specific to vent and coastal ecosystems reflects the heterogeneity and dynamic nature of these habitats. Both pelagic and benthic bacterial community distributions correlate with surface water productivity, reflecting the coupling between both realms by particle export. Also, differences in physical mixing may play a fundamental role in the distribution patterns of marine bacteria, as benthic communities showed a higher dissimilarity with increasing distance than pelagic communities. Conclusions/Significance This first synthesis of global bacterial distribution across different ecosystems of the World's oceans shows remarkable horizontal and vertical large-scale patterns in bacterial communities. This opens interesting perspectives for the definition of biogeographical biomes for bacteria of ocean waters and the seabed

Phylogenetic Analysis Suggests That Habitat Filtering Is Structuring Marine Bacterial Communities Across the Globe

The phylogenetic structure and community composition were analysed in an existing data set of marine bacterioplankton communities to elucidate the evolutionary and ecological processes dictating the assembly. The communities were sampled from coastal waters at nine locations distributed worldwide and were examined through the use of comprehensive clone libraries of 16S ribosomal RNA genes. The analyses show that the local communities are phylogenetically different from each other and that a majority of them are phylogenetically clustered, i.e. the species (operational taxonomic units) were more related to each other than expected by chance. Accordingly, the local communities were assembled non-randomly from the global pool of available bacterioplankton. Further, the phylogenetic structures of the communities were related to the water temperature at the locations. In agreement with similar studies, including both macroorganisms and bacteria, these results suggest that marine bacterial communities are structured by “habitat filtering”, i.e. through non-random colonization and invasion determined by environmental characteristics. Different bacterial types seem to have different ecological niches that dictate their survival in different habitats. Other eco-evolutionary processes that may contribute to the observed phylogenetic patterns are discussed. The results also imply a mapping between phenotype and phylogenetic relatedness which facilitates the use of community phylogenetic structure analysis to infer ecological and evolutionary assembly processes

The energy–diversity relationship of complex bacterial communities in Arctic deep-sea sediments

The availability of nutrients and energy is a main driver of biodiversity for plant and animal communities in terrestrial and marine ecosystems, but we are only beginning to understand whether and how energy–diversity relationships may be extended to complex natural bacterial communities. Here, we analyzed the link between phytodetritus input, diversity and activity of bacterial communities of the Siberian continental margin (37–3427 m water depth). Community structure and functions, such as enzymatic activity, oxygen consumption and carbon remineralization rates, were highly related to each other, and with energy availability. Bacterial richness substantially increased with increasing sediment pigment content, suggesting a positive energy–diversity relationship in oligotrophic regions. Richness leveled off, forming a plateau, when mesotrophic sites were included, suggesting that bacterial communities and other benthic fauna may be structured by similar mechanisms. Dominant bacterial taxa showed strong positive or negative relationships with phytodetritus input and allowed us to identify candidate bioindicator taxa. Contrasting responses of individual taxa to changes in phytodetritus input also suggest varying ecological strategies among bacterial groups along the energy gradient. Our results imply that environmental changes affecting primary productivity and particle export from the surface ocean will not only affect bacterial community structure but also bacterial functions in Arctic deep-sea sediment, and that sediment bacterial communities can record shifts in the whole ocean ecosystem functioning

Hypolithic and soil microbial community assembly along an aridity gradient in the Namib Desert

The Namib Dessert is considered the oldest desert in the world and hyperarid for the last 5 million years. However, the environmental buffering provided by quartz and other translucent rocks supports extensive hypolithic microbial communities. In this study, open soil and hypolithic microbial communities have been investigated along an East–West transect characterized by an inverse fog-rainfall gradient. Multivariate analysis showed that structurally different microbial communities occur in soil and in hypolithic zones. Using variation partitioning, we found that hypolithic communities exhibited a fog-related distribution as indicated by the significant East– West clustering. Sodium content was also an important environmental factor affecting the composition of both soil and hypolithic microbial communities. Finally, although null models for patterns in microbial communities were not supported by experimental data, the amount of unexplained variation (68–97 %) suggests that stochastic processes also play a role in the assembly of such communities in the Namib Desert.Web of Scienc