scholarly journals CarboLogR: a Shiny/R application for statistical analysis of bacterial utilisation of carbon sources

2019 ◽  
Author(s):  
Kevin Vervier ◽  
Hilary P. Browne ◽  
Trevor D. Lawley
Keyword(s):  
Statistical Analysis ◽  
Bacterial Growth ◽  
Statistical Power ◽  
Carbon Sources ◽  
Growth Curves ◽  
Growth Patterns ◽  
Supplementary Information ◽  
Phenotype Microarray ◽  
Link Type ◽  
High Level

AbstractSummaryThe Biolog Phenotype Microarray (PM) and Anaerobic MicroPlates (AN) 96-well plates utilise colorimetric redox reactions to rapidly screen bacteria for the ability to utilise different carbon sources and other metabolites. Measurement of substrate utilisation as bacterial growth curves typically involves extended data normalization, outlier detection, and statistical analysis. The CarboLogR package streamlines this process with a Shiny application, guiding users from raw data generated from Biolog assays to growth profile comparison. We applied chemoinformatics approaches to define clusters of carbon sources, based on molecular similarities, increasing statistical power. Altogether, CarboLogR is a novel integrated tool providing automatic and high-level resolution for bacterial growth patterns and carbon source usage.Availability and ImplementationCarboLogR application can be downloaded and installed from Github repository https://github.com/kevinVervier/CarboLogR. Tutorial, data, and examples can be downloaded at https://github.com/kevinVervier/CarboLogR/[email protected] InformationSupplementary data are available at Bioinformatics online.

scholarly journals Insight into phenotypic and genotypic differences between vaginal Lactobacillus crispatus BC5 and Lactobacillus gasseri BC12 to unravel nutritional and stress factors influencing their metabolic activity

2021 ◽  
Vol 7 (6) ◽  
Author(s):  
Paolo Emidio Costantini ◽  
Andrea Firrincieli ◽  
Stefano Fedi ◽  
Carola Parolin ◽  
Carlo Viti ◽  
...  
Keyword(s):  
Type Species ◽  
Carbon Sources ◽  
Nitrogen Sources ◽  
Stress Factors ◽  
Genotypic Differences ◽  
Phenotype Microarray ◽  
Genetic Traits ◽  
Content Type ◽  
Phenotypic Profile ◽  
Link Type

The vaginal microbiota, normally characterized by lactobacilli presence, is crucial for vaginal health. Members belonging to L. crispatus and L. gasseri species exert crucial protective functions against pathogens, although a total comprehension of factors that influence their dominance in healthy women is still lacking. Here we investigated the complete genome sequence and comprehensive phenotypic profile of L. crispatus strain BC5 and L. gasseri strain BC12, two vaginal strains featured by anti-bacterial and anti-viral activities. Phenotype microarray (PM) results revealed an improved capacity of BC5 to utilize different carbon sources as compared to BC12, although some specific carbon sources that can be associated to the human diet were only metabolized by BC12, i.e. uridine, amygdalin, tagatose. Additionally, the two strains were mostly distinct in the capacity to utilize the nitrogen sources under analysis. On the other hand, BC12 showed tolerance/resistance towards twice the number of stressors (i.e. antibiotics, toxic metals etc.) with respect to BC5. The divergent phenotypes observed in PM were supported by the identification in either BC5 or BC12 of specific genetic determinants that were found to be part of the core genome of each species. The PM results in combination with comparative genome data provide insights into the possible environmental factors and genetic traits supporting the predominance of either L. crispatus BC5 or L. gasseri BC12 in the vaginal niche, giving also indications for metabolic predictions at the species level.

scholarly journals wft4galaxy: A Workflow Tester for Galaxy

2017 ◽  
Author(s):  
Marco Enrico Piras ◽  
Luca Pireddu ◽  
Gianluigi Zanetti
Keyword(s):  
Complex Analysis ◽  
Computer Programs ◽  
Supplementary Information ◽  
Automated Testing ◽  
Continuous Integration ◽  
Link Type ◽  
Scientific Analysis ◽  
The Galaxy ◽  
Supplementary Material ◽  
High Level

ABSTRACTMotivationWorkflow managers for scientific analysis provide a high-level programming platform facilitating standardization, automation, collaboration and access to sophisticated computing resources. The Galaxy workflow manager provides a prime example of this type of platform. As compositions of simpler tools, workflows effectively comprise specialized computer programs implementing often very complex analysis procedures. To date, no simple way exists to automatically test Galaxy workflows and ensure their correctness has appeared in the literature.ResultsWith wft4galaxy we offer a tool to bring automated testing to Galaxy workflows, making it feasible to bring continuous integration to their development and ensuring that defects are detected promptly. wft4galaxy can be easily installed as a regular Python program or launched directly as a Docker container – the latter reducing installation effort to a minimum.Availabilitywft4galaxy is available online at https://github.com/phnmnl/wft4galaxy under the Academic Free License v3.0.Supplementary informationSupplementary information is available at http://wft4galaxy.readthedocs.io.

scholarly journals Outlier detection for improved differential splicing quantification from RNA-Seq experiments with replicates

2017 ◽  
Author(s):  
Scott Norton ◽  
Jorge Vaquero-Garcia ◽  
Yoseph Barash
Keyword(s):  
Outlier Detection ◽  
Statistical Power ◽  
Probability Model ◽  
Real Life ◽  
Supplementary Information ◽  
Rna Seq ◽  
Differential Splicing ◽  
Experimental Conditions ◽  
Link Type ◽  
Extensive Evaluation

AbstractMotivationA key component in many RNA-Seq based studies is contrasting multiple replicates from different experimental conditions. In this setup replicates play a key role as they allow to capture underlying biological variability inherent to the compared conditions, as well as experimental variability. However, what constitutes a “bad” replicate is not necessarily well defined. Consequently, researchers might discard valuable data or downstream analysis may be hampered by failed experiments.ResultsHere we develop a probability model to weigh a given RNA-Seq sample as a representative of an experimental condition when performing alternative splicing analysis. We demonstrate that this model detects outlier samples which are consistently and significantly different compared to other samples from the same condition. Moreover, we show that instead of discarding such samples the proposed weighting scheme can be used to downweight samples and specific splicing variations suspected as outliers, gaining statistical power. These weights can then be used for differential splicing (DS) analysis, where the resulting algorithm offers a generalization of the MAJIQ algorithm. Using both synthetic and real-life data we perform an extensive evaluation of the improved MAJIQ algorithm in different scenarios involving perturbed samples, mislabeled samples, no-signal groups, and different levels of coverage, showing it compares favorably to other tools. Overall, this work offers an outlier detection algorithm that can be combined with any splicing pipeline, a generalized and improved version of MAJIQ for differential splicing detection, and an evaluation pipeline researchers can use to evaluate which algorithm may work best for their needs.AvailabilityProgram is accessible via http://majiq.biociphers.org/norton_et_al_2017/Contacthttp://[email protected] informationSupplementary data are available at Bioinformatics online.

Power of Modified Brown-Forsythe and Mixed-Model Approaches in Split-Plot Designs

Methodology ◽  
2017 ◽  
Vol 13 (1) ◽  
pp. 9-22 ◽  
Author(s):  
Pablo Livacic-Rojas ◽  
Guillermo Vallejo ◽  
Paula Fernández ◽  
Ellián Tuero-Herrero
Keyword(s):  
Repeated Measures ◽  
Statistical Power ◽  
Mixed Model ◽  
Covariance Structure ◽  
Simulation Method ◽  
Future Research ◽  
Repeated Measures Design ◽  
Fixed And Random Effects ◽  
Split Plot ◽  
High Level

Abstract. Low precision of the inferences of data analyzed with univariate or multivariate models of the Analysis of Variance (ANOVA) in repeated-measures design is associated to the absence of normality distribution of data, nonspherical covariance structures and free variation of the variance and covariance, the lack of knowledge of the error structure underlying the data, and the wrong choice of covariance structure from different selectors. In this study, levels of statistical power presented the Modified Brown Forsythe (MBF) and two procedures with the Mixed-Model Approaches (the Akaike’s Criterion, the Correctly Identified Model [CIM]) are compared. The data were analyzed using Monte Carlo simulation method with the statistical package SAS 9.2, a split-plot design, and considering six manipulated variables. The results show that the procedures exhibit high statistical power levels for within and interactional effects, and moderate and low levels for the between-groups effects under the different conditions analyzed. For the latter, only the Modified Brown Forsythe shows high level of power mainly for groups with 30 cases and Unstructured (UN) and Autoregressive Heterogeneity (ARH) matrices. For this reason, we recommend using this procedure since it exhibits higher levels of power for all effects and does not require a matrix type that underlies the structure of the data. Future research needs to be done in order to compare the power with corrected selectors using single-level and multilevel designs for fixed and random effects.

التغير المناخي واثره في المقنن المائي لمحصول العنب في محافظة ديالى

2019 ◽  
Vol 1 (34) ◽  
pp. 391-422
Author(s):  
اشواق حسن حميد صالح
Keyword(s):  
Climate Change ◽  
Statistical Analysis ◽  
Wind Speed ◽  
Extreme Temperature ◽  
Solar Brightness ◽  
The Subject ◽  
Climate Station ◽  
The Times ◽  
High Level ◽  
Very High

Climate change and its impact on water resources is the problem of the times. Therefore, this study is concerned with the subject of climate change and its impact on the water ration of the grape harvest in Diyala Governorate. The study was based on the data of the Khanaqin climate station for the period 1973-2017, (1986-2017) due to lack of data at governorate level. The general trend of the elements of the climate and its effect on the water formula was extracted. The equation of change was extracted for the duration of the study. The statistical analysis was also used between the elements of the climate (actual brightness, normal temperature, micro and maximum degrees Celsius, wind speed m / s, relative humidity% The results of the statistical analysis confirm that the water ration for the study area is based mainly on the X7 evaporation / netting variable, which is affected by a set of independent variables X1 Solar Brightness X4 X5 Extreme Temperature Wind Speed ​​3X Minimal Temperature and Very High Level .

Application of Phenotype Microarray for Profiling Carbon Sources Utilization between Biofilm and Non-Biofilm of Pseudomonas aeruginosa from Clinical Isolates

2020 ◽  
Vol 21 (14) ◽  
pp. 1539-1550
Author(s):  
Nur S. Ismail ◽  
Suresh K. Subbiah ◽  
Niazlin M. Taib
Keyword(s):  
Pseudomonas Aeruginosa ◽  
Carbon Sources ◽  
Anaerobic Respiration ◽  
Regulatory System ◽  
Negative Control ◽  
High Morbidity ◽  
Metabolic Profiles ◽  
Phenotype Microarray ◽  
Diverse Environment ◽  
Phenotype Microarrays

Background: This is the fastest work in obtaining the metabolic profiles of Pseudomonas aeruginosa in order to combat the infection diseases which leads to high morbidity and mortality rates. Pseudomonas aeruginosa is a high versatility of gram-negative bacteria that can undergo aerobic and anaerobic respiration. Capabilities in deploying different carbon sources, energy metabolism and regulatory system, ensure the survival of this microorganism in the diverse environment condition. Determination of differences in carbon sources utilization among biofilm and non-biofilm of Pseudomonas aeruginosa provides a platform in understanding the metabolic activity of the microorganism. Methods: The study was carried out from September 2017 to February 2019. Four archive isolates forming strong and intermediate biofilm and non-biofilms producer were subcultured from archive isolates. ATCC 27853 P. aeruginosa was used as a negative control or non-biofilm producing microorganism. Biofilm formation was confirmed by Crystal Violet Assay (CVA) and Congo Red Agar (CRA). Metabolic profiles of the biofilm and non-biofilms isolates were determined by phenotype microarrays (Biolog Omnilog). Results and Discussion: In this study, Pseudomonas aeruginosa biofilm isolates utilized uridine, L-threonine and L-serine while non-biofilm utilized adenosine, inosine, monomethyl, sorbic acid and succinamic acid. Conclusion: The outcome of this result will be used for future studies to improve detection or inhibit the growth of P. aeruginosa biofilm and non-biofilm respectively.

DO REALLY EMOTIONAL QUOTIENT AND SPIRITUAL QUOTIENT AFFECT ON EMPLOYEE PERFORMANCE?

2017 ◽  
Vol 1 (1) ◽  
pp. 33-37
Author(s):  
Shofia Amin ◽  
Nany Mawaddah
Keyword(s):  
Emotional Intelligence ◽  
Statistical Analysis ◽  
Least Squares ◽  
Work Performance ◽  
Employee Performance ◽  
Spiritual Intelligence ◽  
Path Modeling ◽  
Emotional Quotient ◽  
High Level ◽  
Positive Effect

The main purpose of this study is to examine the effect of emotional quotient on work performance, and the effect of spiritual quotient on work performance at BPMPPT of Jambi City. Using 68 employees as respondent, the data were collected by distributing questionnaire and analyzed by using partial least squares path modeling (PLS-SEM). The results of the analysis show that overall emotional intelligence and spiritual intelligence employee BPMPPT Jambi city is at a high level of quotient. While employee performance BPMPPT Jambi city is at a level of performance was enough. The statistical analysis shows that partially and simultantly emotional quotient and spiritual quotient has significant and positive effect on employee performance. Keywords: Emotional Quotient, Spiritual Quotient, Performance

scholarly journals Phyllobacterium loti sp. nov. isolated from nodules of Lotus corniculatus

2014 ◽  
Vol 64 (Pt_3) ◽  
pp. 781-786 ◽  
Author(s):  
Maximo Sánchez ◽  
Martha-Helena Ramírez-Bahena ◽  
Alvaro Peix ◽  
María J. Lorite ◽  
Juan Sanjuán ◽  
...  
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Sequence Similarity ◽  
Carbon Sources ◽  
Lotus Corniculatus ◽  
Culture Conditions ◽  
Rrna Gene ◽  
Content Type ◽  
Link Type ◽  
The 16S Rrna Gene

Strain S658T was isolated from a Lotus corniculatus nodule in a soil sample obtained in Uruguay. Phylogenetic analysis of the 16S rRNA gene and atpD gene showed that this strain clustered within the genus Phyllobacterium . The closest related species was, in both cases, Phyllobacterium trifolii PETP02T with 99.8 % sequence similarity in the 16S rRNA gene and 96.1 % in the atpD gene. The 16S rRNA gene contains an insert at the beginning of the sequence that has no similarities with other inserts present in the same gene in described rhizobial species. Ubiquinone Q-10 was the only quinone detected. Strain S658T differed from its closest relatives through its growth in diverse culture conditions and in the assimilation of several carbon sources. It was not able to reproduce nodules in Lotus corniculatus. The results of DNA–DNA hybridization, phenotypic tests and fatty acid analyses confirmed that this strain should be classified as a representative of a novel species of the genus Phyllobacterium , for which the name Phyllobacterium loti sp. nov. is proposed. The type strain is S658T( = LMG 27289T = CECT 8230T).

scholarly journals Effect of erythritol and xylitol on Streptococcus pyogenes causing peritonsillar abscesses

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Siiri Kõljalg ◽  
Risto Vaikjärv ◽  
Imbi Smidt ◽  
Tiiu Rööp ◽  
Anirikh Chakrabarti ◽  
...  
Keyword(s):  
Streptococcus Pyogenes ◽  
Bacterial Growth ◽  
Growth Curves ◽  
Culture Collection ◽  
Exponential Phase ◽  
Clinical Isolates ◽  
Growth Inhibitors ◽  
Throat Culture ◽  
Potent Growth

AbstractPolyols are effective against caries-causing streptococci but the effect on oropharynx-derived pyogenic streptococci is not well characterised. We aimed to study the effect of erythritol (ERY) and xylitol (XYL) against Streptococcus pyogenes isolated from peritonsillar abscesses (PTA). We used 31 clinical isolates and 5 throat culture collection strains. Inhibition of bacterial growth by polyols at 2.5%, 5% and 10% concentrations was studied and the results were scored. Amylase levels in PTA pus were compared to polyol effectivity scores (PES). Growth curves of four S. pyogenes isolates were analysed. Our study showed that XYL was more effective than ERY inhibiting 71–97% and 48–84% of isolates, respectively, depending of concentrations. 48% of clinical and all throat strains were inhibited by polyols in all concentrations (PES 3). PES was negative or zero in 26% of the isolates in the presence of ERY and in 19% of XYL. ERY enhanced the growth of S. pyogenes isolated from pus with high amylase levels. Polyols in all concentrations inhibited the growth in exponential phase. In conclusion, ERY and XYL are potent growth inhibitors of S. pyogenes isolated from PTA. Therefore, ERY and XYL may have potential in preventing PTA in the patients with frequent tonsillitis episodes.

Decomposition of Growth Curves into Growth Rate and Acceleration: a Novel Procedure to Monitor Bacterial Growth and the Time-Dependent Effect of Antimicrobials

2021 ◽  
Author(s):  
M. Luisa Navarro-Pérez ◽  
M. Coronada Fernández-Calderón ◽  
Virginia Vadillo-Rodríguez
Keyword(s):  
Growth Rate ◽  
Mathematical Models ◽  
Bacterial Growth ◽  
Time Course ◽  
Antimicrobial Agents ◽  
Numerical Procedure ◽  
Growth Curves ◽  
Predictive Microbiology ◽  
Insight Into ◽  
Over Time

In this paper, a simple numerical procedure is presented to monitor the growth of Streptococcus sanguinis over time in the absence and presence of propolis, a natural antimicrobial. In particular, it is shown that the real-time decomposition of growth curves obtained through optical density measurements into growth rate and acceleration can be a powerful tool to precisely assess a large range of key parameters [ i.e. lag time ( t 0 ), starting growth rate ( γ 0 ), initial acceleration of the growth ( a 0 ), maximum growth rate ( γ max ), maximum acceleration ( a max ) and deceleration ( a min ) of the growth and the total number of cells at the beginning of the saturation phase ( N s )] that can be readily used to fully describe growth over time. Consequently, the procedure presented provides precise data of the time course of the different growth phases and features, which is expected to be relevant, for instance, to thoroughly evaluate the effect of new antimicrobial agents. It further provides insight into predictive microbiology, likely having important implications to assumptions adopted in mathematical models to predict the progress of bacterial growth. Importance: The new and simple numerical procedure presented in this paper to analyze bacterial growth will possibly allow identifying true differences in efficacy among antimicrobial drugs for their applications in human health, food security, and environment, among others. It further provides insight into predictive microbiology, likely helping in the development of proper mathematical models to predict the course of bacterial growth under diverse circumstances.

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