The Impact of Various Time Intervals on the Supragingival Plaque Dynamic Core Microbiome

ObjectiveThe aim of this study was to examine the influence of various time intervals on the composition of the supragingival plaque microbiome, especially the dynamic core microbiome, and to find a suitable observation interval for further studies on oral microbiota.ResultsA total of 359,565 qualified reads for 64 samples were generated for subsequent analyses, which represents 8,452 operational taxonomic units identified at 3% dissimilarity. The dynamic core microbiome detected in the current study included five phyla, 12 genera and 13 species. At the genus level, the relative abundance of bacterial communities under the “1 day,” “1 month,” and “3 months” intervals was clustered into sub-category. At the species level, the number of overlapping species remained stable between the “1 month” and “3 months” intervals, whereas the number of dynamic core species became stable within only 1 week.ConclusionsThis study emphasized the impact of different time intervals (days, weeks and months) on the composition, commonality and diversity of the supragingival microbiome. The analyses found that for various types of studies, the time interval of a month is more suitable for observing the general composition of the supragingival microbiome, and that a week is better for observing the dynamic core microbiome.     

Impact of specific training and competition on myocardial structure and function in different age ranges of male handball players

Handball activity involves cardiac changes and demands a mixture of both eccentric and concentric remodeling within the heart. This study seeks to explore heart performance and cardiac remodeling likely to define cardiac parameters which influence specific performance in male handball players across different age ranges. Forty three players, with a regular training and competitive background in handball separated into three groups aged on average 11.78±0.41 for youth players aka “schools”, “elite juniors” 15.99±0.81 and “elite adults” 24.46±2.63 years, underwent echocardiography and ECG examinations. Incremental ergocycle and specific field (SFT) tests have also been conducted. With age and regular training and competition, myocardial remodeling in different age ranges exhibit significant differences in dilatation’s parameters between “schools” and “juniors” players, such as the end-diastolic diameter (LVEDD) and the end-systolic diameter of the left ventricle (LVESD), the root of aorta (Ao) and left atrial (LA), while significant increase is observed between “juniors” and “adults” players in the interventricular septum (IVS), the posterior wall thicknesses (PWT) and LV mass index. ECG changes are also noted but NS differences were observed in studied parameters. For incremental maximal test, players demonstrate a significant increase in duration and total work between “schools” and “juniors” and, in total work only, between “juniors” and “seniors”. The SFT shows improvement in performance which ranged between 26.17±1.83 sec to 31.23±2.34 sec respectively from “seniors” to “schools”. The cross-sectional approach used to compare groups with prior hypothesis that there would be differences in exercise performance and cardiac parameters depending on duration of prior handball practice, leads to point out the early cardiac remodeling within the heart as adaptive change. Prevalence of cardiac chamber dilation with less hypertrophy remodeling was found from “schools” to “juniors” while a prevalence of cardiac hypertrophy with less pronounced chamber dilation remodeling was noted later.     

Fungal Diversity in Permafrost and Tallgrass Prairie Soils under Experimental Warming Conditions

Soil fungi play a major role in terrestrial ecosystem functioning through interactions with soil structure, plants, micro- and mesofauna, and nutrient cycling through predation, pathogenesis, mutualistic, and saprotrophic roles. The diversity of soil fungi was assessed by sequencing their 28S rRNA gene in Alaskan permafrost and Oklahoma tallgrass prairie soils at experimental sites where the effect of climate warming is under investigation. A total of 226,695 reads were classified into 1,063 genera, covering 62% of the reference data set. Using the Bayesian Classifier offered by the Ribosomal Database Project (RDP) with 50% bootstrapping classification confidence, approximately 70% of sequences were returned as “unclassified” at the genus level, although the majority (∼65%) were classified at the class level, which provided insight into these lesser-known fungal lineages. Those unclassified at the genus level were subjected to BLAST analysis against the ARB-SILVA database, where ∼50% most closely matched nonfungal taxa. Compared to the more abundant sequences, a higher proportion of rare operational taxonomic units (OTU) were successfully classified to genera at 50% bootstrap confidence, indicating that the fungal rare biosphere in these sites is not composed of sequencing artifacts. There was no significant effect after 1 year of warming on the fungal community structure at both sites, except perhaps for a few minor members, but there was a significant effect of sample depth in the permafrost soils. Despite overall significant community structure differences driven by variations in OTU dominance, the prairie and permafrost soils shared 90% and 63% of all fungal sequences, respectively, indicating a fungal “seed bank” common between both sites.     

Characterization of the Fecal Microbiota of Pigs before and after Inoculation with “Brachyspira hampsonii”

“Brachyspira hampsonii” causes disease indistinguishable from swine dysentery, and the structure of the intestinal microbiome likely plays a role in determining susceptibility of individual pigs to infection and development of clinical disease. The objectives of the current study were to determine if the pre-inoculation fecal microbiota differed between inoculated pigs that did (INOC MH) or did not (INOC non-MH) develop mucohaemorrhagic diarrhea following challenge with “B. hampsonii”, and to quantify changes in the structure of the microbiome following development of clinical disease. Fecal microbiota profiles were generated based on amplification and sequencing of the cpn60 universal target sequence from 89 samples from 18 pigs collected at −8, −5, −3 and 0 days post-inoculation, and at termination. No significant differences in richness, diversity or taxonomic composition distinguished the pre-inoculation microbiomes of INOC MH and INOC non-MH pigs. However, the development of bloody diarrhea in inoculated pigs was associated with perturbation of the microbiota relative to INOC non-MH or sham-inoculated control pigs. Specifically, the fecal microbiota of INOC MH pigs was less dense (fewer total 16S rRNA copies per gram of feces), and had a lower Bacteroidetes:Firmicutes ratio. Further investigation of the potential long-term effects of Brachyspira disease on intestinal health and performance is warranted.     

Characterization of the Upper Respiratory Tract Microbiomes of Patients with Pandemic H1N1 Influenza

The upper respiratory tract microbiome has an important role in respiratory health. Influenza A is a common viral infection that challenges that health, and a well-recognized sequela is bacterial pneumonia. Given this connection, we sought to characterize the upper respiratory tract microbiota of individuals suffering from the pandemic H1N1 influenza A outbreak of 2009 and determine if microbiome profiles could be correlated with patient characteristics. We determined the microbial profiles of 65 samples from H1N1 patients by cpn60 universal target amplification and sequencing. Profiles were examined at the phylum and nearest neighbor “species” levels using the characteristics of patient gender, age, originating health authority, sample type and designation (STAT/non-STAT). At the phylum level, Actinobacteria-, Firmicutes- and Proteobacteria-dominated microbiomes were observed, with none of the patient characteristics showing significant profile composition differences. At the nearest neighbor “species” level, the upper respiratory tract microbiomes were composed of 13-20 “species” and showed a trend towards increasing diversity with patient age. Interestingly, at an individual level, most patients had one to three organisms dominant in their microbiota. A limited number of discrete microbiome profiles were observed, shared among influenza patients regardless of patient status variables. To assess the validity of analyses derived from sequence read abundance, several bacterial species were quantified by quantitative PCR and compared to the abundance of cpn60 sequence read counts obtained in the study. A strong positive correlation between read abundance and absolute bacterial quantification was observed. This study represents the first examination of the upper respiratory tract microbiome using a target other than the 16S rRNA gene and to our knowledge, the first thorough examination of this microbiome during a viral infection.     

Transition to quorum sensing in an Agrobacterium population: A stochastic model

Understanding of the intracellular molecular machinery that is responsible for the complex collective behavior of multicellular populations is an exigent problem of modern biology. Quorum sensing, which allows bacteria to activate genetic programs cooperatively, provides an instructive and tractable example illuminating the causal relationships between the molecular organization of gene networks and the complex phenotypes they control. In this work we—to our knowledge for the first time—present a detailed model of the population-wide transition to quorum sensing using the example of Agrobacterium tumefaciens. We construct a model describing the Ti plasmid quorum-sensing gene network and demonstrate that it behaves as an “on–off” gene expression switch that is robust to molecular noise and that activates the plasmid conjugation program in response to the increase in autoinducer concentration. This intracellular model is then incorporated into an agent-based stochastic population model that also describes bacterial motion, cell division, and chemical communication. Simulating the transition to quorum sensing in a liquid medium and biofilm, we explain the experimentally observed gradual manifestation of the quorum-sensing phenotype by showing that the transition of individual model cells into the “on” state is spread stochastically over a broad range of autoinducer concentrations. At the same time, the population-averaged values of critical autoinducer concentration and the threshold population density are shown to be robust to variability between individual cells, predictable and specific to particular growth conditions. Our modeling approach connects intracellular and population scales of the quorum-sensing phenomenon and provides plausible answers to the long-standing questions regarding the ecological and evolutionary significance of the phenomenon. Thus, we demonstrate that the transition to quorum sensing requires a much higher threshold cell density in liquid medium than in biofilm, and on this basis we hypothesize that in Agrobacterium quorum sensing serves as the detector of biofilm formation.     

Open Versus Arthroscopic Surgical Management for Recalcitrant Trochanteric Bursitis: A Systematic Review

BackgroundWhile excision of the trochanteric bursae to treat lateral hip pain has increased in popularity, no comparison exists between the surgical outcomes and complications of the open and arthroscopic techniques involving trochanteric bursectomy. The purpose of this study was to determine the efficacies and complication rates of arthroscopic and open techniques for procedures involving trochanteric bursectomy.MethodsThe terms “trochanteric,” “bursectomy,” “arthroscopic,” “open,” “outcomes,” and “hip” were searched in five electronic databases. Fifteen studies from 120 initial results were included. Patient-reported outcomes (PRO), pain, satisfaction, and complications were included for analysis.ResultsFive hundred-two hips in 474 total patients (77.7% female) were included in this study. The average age was 54. The fourteen distinct PRO scores that were reported by the included studies improved significantly from baseline to final mean follow-up (12-70.8 months for open; 12-42 months for arthroscopic) for both approaches, demonstrating statistically significant patient benefit in a variety of hip arthroscopy settings (P > 0.05). The complication rates of all procedures ranged from 0%-33% and failure to improve pain ranged from 0%-8%. Patient satisfaction with surgery was high at 95% and 82% reported a willingness to undergo the same surgery again. No significant mean differences were found between the open and arthroscopic techniques.ConclusionThe open and arthroscopic approaches for trochanteric bursectomy are both safe and effective procedures in treating refractory lateral hip pain. No significant differences in PROs, pain, total complications, severity of complications, and total failures were seen between technique outcomes.Level of Evidence: IV     

The early life of a leaf‐cutter ant colony constrains symbiont vertical transmission and favors horizontal transmission

Colonial organisms host a large diversity of symbionts (collectively, parasites, mutualists, and commensals) that use vertical transmission (from parent colony to offspring colony) and/or horizontal transmission to disperse between host colonies. The early life of some colonies, characterized by the dispersal and establishment of solitary individuals, may constrain vertical transmission and favor horizontal transmission between large established colonies. We explore this possibility with the miniature cockroach Attaphila fungicola, a symbiont of leaf‐cutter ants and the mutualist fungal gardens they cultivate. The early life of a leaf‐cutter colony is characterized by the dispersal of a female alate (winged “queen”) carrying a fungal pellet, and the subsequent establishment of a foundress (workerless “queen”) raising her incipient fungal garden and colony. Roaches hitchhike on female alates during leaf‐cutter nuptial flights, which strongly suggests that roaches are vertically transmitted to foundresses and their incipient colonies; however, weak compatibility between roaches and incipient gardens may constrain roach vertical transmission. Reciprocally, opportunities for horizontal transmission between large established colonies with abundant fungal gardens may weaken selection against roach‐induced harm (virulence) of incipient gardens. We use a laboratory experiment, behavioral observations, field surveys, and a transmission model to estimate the effect roaches have on the survivorship of incipient gardens and the frequency of roach vertical transmission. Contrary to traditional assumptions, our results indicate that roaches harm incipient gardens and predominantly use horizontal transmission between established leaf‐cutter colonies. Ultimately, “costs of generalism” associated with infecting disparate stages of a host''s lifecycle (e.g., incipient vs. established colonies) may constrain the vertical transmission of roaches and a broad range of symbionts.     

Network Signatures of Survival in Glioblastoma Multiforme

To determine a molecular basis for prognostic differences in glioblastoma multiforme (GBM), we employed a combinatorial network analysis framework to exhaustively search for molecular patterns in protein-protein interaction (PPI) networks. We identified a dysregulated molecular signature distinguishing short-term (survival<225 days) from long-term (survival>635 days) survivors of GBM using whole genome expression data from The Cancer Genome Atlas (TCGA). A 50-gene subnetwork signature achieved 80% prediction accuracy when tested against an independent gene expression dataset. Functional annotations for the subnetwork signature included “protein kinase cascade,” “IκB kinase/NFκB cascade,” and “regulation of programmed cell death” – all of which were not significant in signatures of existing subtypes. Finally, we used label-free proteomics to examine how our subnetwork signature predicted protein level expression differences in an independent GBM cohort of 16 patients. We found that the genes discovered using network biology had a higher probability of dysregulated protein expression than either genes exhibiting individual differential expression or genes derived from known GBM subtypes. In particular, the long-term survivor subtype was characterized by increased protein expression of DNM1 and MAPK1 and decreased expression of HSPA9, PSMD3, and CANX. Overall, we demonstrate that the combinatorial analysis of gene expression data constrained by PPIs outlines an approach for the discovery of robust and translatable molecular signatures in GBM.     

Analysis of 567,758 randomized controlled trials published over 30 years reveals trends in phrases used to discuss results that do not reach statistical significance

The power of language to modify the reader’s perception of interpreting biomedical results cannot be underestimated. Misreporting and misinterpretation are pressing problems in randomized controlled trials (RCT) output. This may be partially related to the statistical significance paradigm used in clinical trials centered around a P value below 0.05 cutoff. Strict use of this P value may lead to strategies of clinical researchers to describe their clinical results with P values approaching but not reaching the threshold to be “almost significant.” The question is how phrases expressing nonsignificant results have been reported in RCTs over the past 30 years. To this end, we conducted a quantitative analysis of English full texts containing 567,758 RCTs recorded in PubMed between 1990 and 2020 (81.5% of all published RCTs in PubMed). We determined the exact presence of 505 predefined phrases denoting results that approach but do not cross the line of formal statistical significance (P < 0.05). We modeled temporal trends in phrase data with Bayesian linear regression. Evidence for temporal change was obtained through Bayes factor (BF) analysis. In a randomly sampled subset, the associated P values were manually extracted. We identified 61,741 phrases in 49,134 RCTs indicating almost significant results (8.65%; 95% confidence interval (CI): 8.58% to 8.73%). The overall prevalence of these phrases remained stable over time, with the most prevalent phrases being “marginally significant” (in 7,735 RCTs), “all but significant” (7,015), “a nonsignificant trend” (3,442), “failed to reach statistical significance” (2,578), and “a strong trend” (1,700). The strongest evidence for an increased temporal prevalence was found for “a numerical trend,” “a positive trend,” “an increasing trend,” and “nominally significant.” In contrast, the phrases “all but significant,” “approaches statistical significance,” “did not quite reach statistical significance,” “difference was apparent,” “failed to reach statistical significance,” and “not quite significant” decreased over time. In a random sampled subset of 29,000 phrases, the manually identified and corresponding 11,926 P values, 68,1% ranged between 0.05 and 0.15 (CI: 67. to 69.0; median 0.06). Our results show that RCT reports regularly contain specific phrases describing marginally nonsignificant results to report P values close to but above the dominant 0.05 cutoff. The fact that the prevalence of the phrases remained stable over time indicates that this practice of broadly interpreting P values close to a predefined threshold remains prevalent. To enhance responsible and transparent interpretation of RCT results, researchers, clinicians, reviewers, and editors may reduce the focus on formal statistical significance thresholds and stimulate reporting of P values with corresponding effect sizes and CIs and focus on the clinical relevance of the statistical difference found in RCTs.

The power of language to modify the reader’s perception of interpreting biomedical results cannot be underestimated. An analysis of more than half a million randomized controlled trials reveals that researchers are using appealing phrases to describe non-significant findings as if they were below the p=0.05 significance threshold.     

A statistical model for describing and simulating microbial community profiles

Many methods have been developed for statistical analysis of microbial community profiles, but due to the complex nature of typical microbiome measurements (e.g. sparsity, zero-inflation, non-independence, and compositionality) and of the associated underlying biology, it is difficult to compare or evaluate such methods within a single systematic framework. To address this challenge, we developed SparseDOSSA (Sparse Data Observations for the Simulation of Synthetic Abundances): a statistical model of microbial ecological population structure, which can be used to parameterize real-world microbial community profiles and to simulate new, realistic profiles of known structure for methods evaluation. Specifically, SparseDOSSA’s model captures marginal microbial feature abundances as a zero-inflated log-normal distribution, with additional model components for absolute cell counts and the sequence read generation process, microbe-microbe, and microbe-environment interactions. Together, these allow fully known covariance structure between synthetic features (i.e. “taxa”) or between features and “phenotypes” to be simulated for method benchmarking. Here, we demonstrate SparseDOSSA’s performance for 1) accurately modeling human-associated microbial population profiles; 2) generating synthetic communities with controlled population and ecological structures; 3) spiking-in true positive synthetic associations to benchmark analysis methods; and 4) recapitulating an end-to-end mouse microbiome feeding experiment. Together, these represent the most common analysis types in assessment of real microbial community environmental and epidemiological statistics, thus demonstrating SparseDOSSA’s utility as a general-purpose aid for modeling communities and evaluating quantitative methods. An open-source implementation is available at http://huttenhower.sph.harvard.edu/sparsedossa2.     

Niche theory‐based modeling of assembly processes of viral communities in bats

Understanding the assembly processes of symbiont communities, including viromes and microbiomes, is important for improving predictions on symbionts’ biogeography and disease ecology. Here, we use phylogenetic, functional, and geographic filters to predict the similarity between symbiont communities, using as a test case the assembly process in viral communities of Mexican bats. We construct generalized linear models to predict viral community similarity, as measured by the Jaccard index, as a function of differences in host phylogeny, host functionality, and spatial co‐occurrence, evaluating the models using the Akaike information criterion. Two model classes are constructed: a “known” model, where virus–host relationships are based only on data reported in Mexico, and a “potential” model, where viral reports of all the Americas are used, but then applied only to bat species that are distributed in Mexico. Although the “known” model shows only weak dependence on any of the filters, the “potential” model highlights the importance of all three filter types—phylogeny, functional traits, and co‐occurrence—in the assemblage of viral communities. The differences between the “known” and “potential” models highlight the utility of modeling at different “scales” so as to compare and contrast known information at one scale to another one, where, for example, virus information associated with bats is much scarcer.     

Socio-Demographic Predictors and Distribution of Pulmonary Tuberculosis (TB) in Xinjiang,China: A Spatial Analysis

Objectives

Xinjiang is one of the high TB burden provinces of China. A spatial analysis was conducted using geographical information system (GIS) technology to improve the understanding of geographic variation of the pulmonary TB occurrence in Xinjiang, its predictors, and to search for targeted interventions.

Methods

Numbers of reported pulmonary TB cases were collected at county/district level from TB surveillance system database. Population data were extracted from Xinjiang Statistical Yearbook (2006~2014). Spatial autocorrelation (or dependency) was assessed using global Moran’s I statistic. Anselin’s local Moran’s I and local Getis-Ord statistics were used to detect local spatial clusters. Ordinary least squares (OLS) regression, spatial lag model (SLM) and geographically-weighted regression (GWR) models were used to explore the socio-demographic predictors of pulmonary TB incidence from global and local perspectives. SPSS17.0, ArcGIS10.2.2, and GeoDA software were used for data analysis.

Results

Incidence of sputum smear positive (SS+) TB and new SS+TB showed a declining trend from 2005 to 2013. Pulmonary TB incidence showed a declining trend from 2005 to 2010 and a rising trend since 2011 mainly caused by the rising trend of sputum smear negative (SS-) TB incidence (p<0.0001). Spatial autocorrelation analysis showed the presence of positive spatial autocorrelation for pulmonary TB incidence, SS+TB incidence and SS-TB incidence from 2005 to 2013 (P <0.0001). The Anselin’s Local Moran’s I identified the “hotspots” which were consistently located in the southwest regions composed of 20 to 28 districts, and the “coldspots” which were consistently located in the north central regions consisting of 21 to 27 districts. Analysis with the Getis-Ord Gi* statistic expanded the scope of “hotspots” and “coldspots” with different intensity; 30 county/districts clustered as “hotspots”, while 47 county/districts clustered as “coldspots”. OLS regression model included the “proportion of minorities” and the “per capita GDP” as explanatory variables that explained 64% the variation in pulmonary TB incidence (adjR² = 0.64). The SLM model improved the fit of the OLS model with a decrease in AIC value from 883 to 864, suggesting “proportion of minorities” to be the only statistically significant predictor. GWR model also improved the fitness of regression (adj R² = 0.68, AIC = 871), which revealed that “proportion of minorities” was a strong predictor in the south central regions while “per capita GDP” was a strong predictor for the southwest regions.

Conclusion

The SS+TB incidence of Xinjiang had a decreasing trend during 2005–2013, but it still remained higher than the national average in China. Spatial analysis showed significant spatial autocorrelation in pulmonary TB incidence. Cluster analysis detected two clusters—the “hotspots”, which were consistently located in the southwest regions, and the “coldspots”, which were consistently located in the north central regions. The exploration of socio-demographic predictors identified the “proportion of minorities” and the “per capita GDP” as predictors and may help to guide TB control programs and targeting intervention.     

Statistical Analysis of Individual Participant Data Meta-Analyses: A Comparison of Methods and Recommendations for Practice

Background

Individual participant data (IPD) meta-analyses that obtain “raw” data from studies rather than summary data typically adopt a “two-stage” approach to analysis whereby IPD within trials generate summary measures, which are combined using standard meta-analytical methods. Recently, a range of “one-stage” approaches which combine all individual participant data in a single meta-analysis have been suggested as providing a more powerful and flexible approach. However, they are more complex to implement and require statistical support. This study uses a dataset to compare “two-stage” and “one-stage” models of varying complexity, to ascertain whether results obtained from the approaches differ in a clinically meaningful way.

Methods and Findings

We included data from 24 randomised controlled trials, evaluating antiplatelet agents, for the prevention of pre-eclampsia in pregnancy. We performed two-stage and one-stage IPD meta-analyses to estimate overall treatment effect and to explore potential treatment interactions whereby particular types of women and their babies might benefit differentially from receiving antiplatelets. Two-stage and one-stage approaches gave similar results, showing a benefit of using anti-platelets (Relative risk 0.90, 95% CI 0.84 to 0.97). Neither approach suggested that any particular type of women benefited more or less from antiplatelets. There were no material differences in results between different types of one-stage model.

Conclusions

For these data, two-stage and one-stage approaches to analysis produce similar results. Although one-stage models offer a flexible environment for exploring model structure and are useful where across study patterns relating to types of participant, intervention and outcome mask similar relationships within trials, the additional insights provided by their usage may not outweigh the costs of statistical support for routine application in syntheses of randomised controlled trials. Researchers considering undertaking an IPD meta-analysis should not necessarily be deterred by a perceived need for sophisticated statistical methods when combining information from large randomised trials.     

Diagnostic Criteria for Depression in Type 2 Diabetes: A Data-Driven Approach

BackgroundWhile depression is a frequent psychiatric comorbid condition in diabetes and has significant clinical impact, the syndromal profile of depression and anxiety symptoms has not been examined in detail.AimsTo determine the syndromal pattern of the depression and anxiety spectrum in a large series of patients with type 2 diabetes, as determined using a data-driven approach based on latent class analysis (LCA).MethodType 2 diabetes participants from the observational community-based Fremantle Diabetes Study Phase II underwent assessment of lifetime depression using the Brief Lifetime Depression Scale, the Patient Health Questionnaire 9-item version (PHQ-9) for current depression symptoms, and the Generalized Anxiety Disorder Scale that was specifically developed and validated for this study. The main outcome measure was classes of patients with a specific syndromal profile of depression and anxiety symptoms based on LCA.ResultsLCA identified four classes that were interpreted as “major anxious depression”, “minor anxious depression”, “subclinical anxiety”, and “no anxious depression”. All nine DSM-IV/5 diagnostic criteria for major depression identified a class with a high frequency of major depression. All symptoms of anxiety had similar high probabilities as symptoms of depression for the “major depression-anxiety” class. There were significant differences between classes in terms of history of depression and anxiety, use of psychoactive medication, and diabetes-related variables.ConclusionsPatients with type 2 diabetes show specific profiles of depression and anxiety. Anxiety symptoms are an integral part of major depression in type 2 diabetes. The different classes identified here provide empirically validated phenotypes for future research.     

Identifying Keystone Species in the Human Gut Microbiome from Metagenomic Timeseries Using Sparse Linear Regression

Human associated microbial communities exert tremendous influence over human health and disease. With modern metagenomic sequencing methods it is now possible to follow the relative abundance of microbes in a community over time. These microbial communities exhibit rich ecological dynamics and an important goal of microbial ecology is to infer the ecological interactions between species directly from sequence data. Any algorithm for inferring ecological interactions must overcome three major obstacles: 1) a correlation between the abundances of two species does not imply that those species are interacting, 2) the sum constraint on the relative abundances obtained from metagenomic studies makes it difficult to infer the parameters in timeseries models, and 3) errors due to experimental uncertainty, or mis-assignment of sequencing reads into operational taxonomic units, bias inferences of species interactions due to a statistical problem called “errors-in-variables”. Here we introduce an approach, Learning Interactions from MIcrobial Time Series (LIMITS), that overcomes these obstacles. LIMITS uses sparse linear regression with boostrap aggregation to infer a discrete-time Lotka-Volterra model for microbial dynamics. We tested LIMITS on synthetic data and showed that it could reliably infer the topology of the inter-species ecological interactions. We then used LIMITS to characterize the species interactions in the gut microbiomes of two individuals and found that the interaction networks varied significantly between individuals. Furthermore, we found that the interaction networks of the two individuals are dominated by distinct “keystone species”, Bacteroides fragilis and Bacteroided stercosis, that have a disproportionate influence on the structure of the gut microbiome even though they are only found in moderate abundance. Based on our results, we hypothesize that the abundances of certain keystone species may be responsible for individuality in the human gut microbiome.     

Excitability of the Primary Motor Cortex Increases More Strongly with Slow- than with Normal-Speed Presentation of Actions

Introduction

The aim of the present study was to investigate how the speed of observed action affects the excitability of the primary motor cortex (M1), as assessed by the size of motor evoked potentials (MEPs) induced by transcranial magnetic stimulation (TMS).

Methods

Eighteen healthy subjects watched a video clip of a person catching a ball, played at three different speeds (normal-, half-, and quarter-speed). MEPs were induced by TMS when the model''s hand had opened to the widest extent just before catching the ball (“open”) and when the model had just caught the ball (“catch”). These two events were locked to specific frames of the video clip (“phases”), rather than occurring at specific absolute times, so that they could easily be compared across different speeds. MEPs were recorded from the thenar (TH) and abductor digiti minimi (ADM) muscles of the right hand.

Results

The MEP amplitudes were higher when the subjects watched the video clip at low speed than when they watched the clip at normal speed. A repeated-measures ANOVA, with the factor VIDEO-SPEED, showed significant main effects. Bonferroni''s post hoc test showed that the following MEP amplitude differences were significant: TH, normal vs. quarter; ADM, normal vs. half; and ADM, normal vs. quarter. Paired t-tests showed that the significant MEP amplitude differences between TMS phases under each speed condition were TH, “catch” higher than “open” at quarter speed; ADM, “catch” higher than “open” at half speed.

Conclusions

These results indicate that the excitability of M1 was higher when the observed action was played at low speed. Our findings suggest that the action observation system became more active when the subjects observed the video clip at low speed, because the subjects could then recognize the elements of action and intention in others.     

Diversity of Basidiomycetes in Michigan Agricultural Soils

We analyzed the communities of soil basidiomycetes in agroecosystems that differ in tillage history at the Kellogg Biological Station Long-Term Ecological Research site near Battle Creek, Michigan. The approach combined soil DNA extraction through a bead-beating method modified to increase recovery of fungal DNA, PCR amplification with basidiomycete-specific primers, cloning and restriction fragment length polymorphism screening of mixed PCR products, and sequencing of unique clones. Much greater diversity was detected than was anticipated in this habitat on the basis of culture-based methods or surveys of fruiting bodies. With “species” defined as organisms yielding PCR products with ≥99% identity in the 5′ 650 bases of the nuclear large-subunit ribosomal DNA, 241 “species” were detected among 409 unique basidiomycete sequences recovered. Almost all major clades of basidiomycetes from basidiomycetous yeasts and other heterobasidiomycetes through polypores and euagarics (gilled mushrooms and relatives) were represented, with a majority from the latter clade. Only 24 of 241 “species” had 99% or greater sequence similarity to named reference sequences in GenBank, and several clades with multiple “species” could not be identified at the genus level by phylogenetic comparisons with named sequences. The total estimated “species” richness for this 11.2-ha site was 367 “species” of basidiomycetes. Since >99% of the study area has not been sampled, the accuracy of our diversity estimate is uncertain. Replication in time and space is required to detect additional diversity and the underlying community structure.     

Sex Differences and Emotion Regulation: An Event-Related Potential Study

Difficulties in emotion regulation have been implicated as a potential mechanism underlying anxiety and mood disorders. It is possible that sex differences in emotion regulation may contribute towards the heightened female prevalence for these disorders. Previous fMRI studies of sex differences in emotion regulation have shown mixed results, possibly due to difficulties in discriminating the component processes of early emotional reactivity and emotion regulation. The present study used event-related potentials (ERPs) to examine sex differences in N1 and N2 components (reflecting early emotional reactivity) and P3 and LPP components (reflecting emotion regulation). N1, N2, P3, and LPP were recorded from 20 men and 23 women who were instructed to “increase,” “decrease,” and “maintain” their emotional response during passive viewing of negative images. Results indicated that women had significantly greater N1 and N2 amplitudes (reflecting early emotional reactivity) to negative stimuli than men, supporting a female negativity bias. LPP amplitudes increased to the “increase” instruction, and women displayed greater LPP amplitudes than men to the “increase” instruction. There were no differences to the “decrease” instruction in women or men. These findings confirm predictions of the female negativity bias hypothesis and suggest that women have greater up-regulation of emotional responses to negative stimuli. This finding is highly significant in light of the female vulnerability for developing anxiety disorders.