Segregostat: a novel concept to control phenotypic diversification dynamics on the example of Gram-negative bacteria

Controlling and managing the degree of phenotypic diversification of microbial populations is a challenging task. This task not only requires detailed knowledge regarding diversification mechanisms but also advanced technical set-ups for the real-time analyses and control of population behaviour on single-cell level. In this work, set-up, design and operation of the so called segregostat are described which, in contrast to a traditional chemostat, allows the control of phenotypic diversification of microbial populations over time. Two exemplary case studies will be discussed, i.e. phenotypic diversification dynamics of Eschericia coli and Pseudomonas putida based on outer membrane permeabilization, emphasizing the applicability and versatility of the proposed approach. Upon nutrient limitation, cell population tends to diversify into several subpopulations exhibiting distinct phenotypic features (non-permeabilized and permeabilized cells). Online analysis leads to the determination of the ratio between cells in these two states, which in turn triggers the addition of glucose pulses in order to maintain a predefined diversification ratio. These results prove that phenotypic diversification can be controlled by means of defined pulse-frequency modulation within continuously running bioreactor set-ups. This lays the foundation for systematic studies, not only of phenotypic diversification but also for all processes where dynamics single-cell approaches are required, such as synthetic co-culture processes.     

Impact of QTL properties on the accuracy of multi-breed genomic prediction

Background

Although simulation studies show that combining multiple breeds in one reference population increases accuracy of genomic prediction, this is not always confirmed in empirical studies. This discrepancy might be due to the assumptions on quantitative trait loci (QTL) properties applied in simulation studies, including number of QTL, spectrum of QTL allele frequencies across breeds, and distribution of allele substitution effects. We investigated the effects of QTL properties and of including a random across- and within-breed animal effect in a genomic best linear unbiased prediction (GBLUP) model on accuracy of multi-breed genomic prediction using genotypes of Holstein-Friesian and Jersey cows.

Methods

Genotypes of three classes of variants obtained from whole-genome sequence data, with moderately low, very low or extremely low average minor allele frequencies (MAF), were imputed in 3000 Holstein-Friesian and 3000 Jersey cows that had real high-density genotypes. Phenotypes of traits controlled by QTL with different properties were simulated by sampling 100 or 1000 QTL from one class of variants and their allele substitution effects either randomly from a gamma distribution, or computed such that each QTL explained the same variance, i.e. rare alleles had a large effect. Genomic breeding values for 1000 selection candidates per breed were estimated using GBLUP modelsincluding a random across- and a within-breed animal effect.

Results

For all three classes of QTL allele frequency spectra, accuracies of genomic prediction were not affected by the addition of 2000 individuals of the other breed to a reference population of the same breed as the selection candidates. Accuracies of both single- and multi-breed genomic prediction decreased as MAF of QTL decreased, especially when rare alleles had a large effect. Accuracies of genomic prediction were similar for the models with and without a random within-breed animal effect, probably because of insufficient power to separate across- and within-breed animal effects.

Conclusions

Accuracy of both single- and multi-breed genomic prediction depends on the properties of the QTL that underlie the trait. As QTL MAF decreased, accuracy decreased, especially when rare alleles had a large effect. This demonstrates that QTL properties are key parameters that determine the accuracy of genomic prediction.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-015-0124-6) contains supplementary material, which is available to authorized users.     

In silico identification and characterization of putative differentially expressed genes involved in common bean (<Emphasis Type="Italic">Phaseolus vulgaris</Emphasis> L.) seed development

Two genotypes of common bean (Phaseolus vulgaris L.) were studied to determine the structural cause of seed abortion in this species. In the non-abortive control (wild-type, cultivar BAT93), the histological analysis revealed a classical pattern of seed development and showed coordinated differentiation of the embryo proper, suspensor, endosperm tissue and seed coat. In contrast, the ethyl methanesulfonate (EMS) mutant (cultivar BAT93) showed disruption in the normal seed development leading to embryo abortion. Aborted embryos from these degenerate seeds showed abnormalities in suspensor and cotyledons at the globular, heart, torpedo and cotyledon stages. Exploring the feasibility of incorporating the available online bioinformatics databases, we identified 22 genes revealing high homology with genes involved in Arabidopsis thaliana embryo development and expressed in common bean immature seeds. The expression patterns of these genes were confirmed by RT–PCR. All genes were highly expressed in seed tissues. To study the expression profiles of isolated genes during Phaseolus embryogenesis, six selected genes were examined by quantitative RT–PCR analysis on the developing embryos of wild-type and EMS mutant plants. All selected genes were expressed differentially at different stages of embryo development. These results could help to improve understanding of the mechanism of common bean embryogenesis.     

Signal processing methods for information enhancement in atrial fibrillation: Spectral analysis and non-linear parameters

Recently, the research efforts in the context of electrocardiographical recording during atrial fibrillation (AF) has been directed to broaden the understandings on the electrophysiological and structural remodelling occurring during the arrhythmia and on characterizing the different types of AF. Following this line, both surface ECG and endocardial electrograms have been thoroughly studied and a series of linear and non-linear parameters were computed either directly on the electrograms or on the derived activation series.

In this paper, we reviewed some signal processing methods used to characterize surface ECG and endocardial electrograms during AF, focusing on spectral and non-linear analysis. In particular, parametric and non-parametric methods for spectral analysis of the residual ECG, i.e. atrial waves obtained from surface ECG after removing ventricular activity, and endocardial recordings are described. The different purposes of spectral analysis (exploring autonomic functions, analysis of spontaneous AF behaviour and predicting therapeutic effects) are illustrated with some examples. In addition, we described some more recent non-linear methods applied to AF, assessing the organization of atrial signals as well as ventricular response in AF. In particular, methods derived from embedding time series and based on entropy computation are illustrated and exemplified.     

A holistic high-throughput screening framework for biofuel feedstock assessment that characterises variations in soluble sugars and cell wall composition in <Emphasis Type="Italic">Sorghum bicolor</Emphasis>

Background

A major hindrance to the development of high yielding biofuel feedstocks is the ability to rapidly assess large populations for fermentable sugar yields. Whilst recent advances have outlined methods for the rapid assessment of biomass saccharification efficiency, none take into account the total biomass, or the soluble sugar fraction of the plant. Here we present a holistic high-throughput methodology for assessing sweet Sorghum bicolor feedstocks at 10 days post-anthesis for total fermentable sugar yields including stalk biomass, soluble sugar concentrations, and cell wall saccharification efficiency.

Results

A mathematical method for assessing whole S. bicolor stalks using the fourth internode from the base of the plant proved to be an effective high-throughput strategy for assessing stalk biomass, soluble sugar concentrations, and cell wall composition and allowed calculation of total stalk fermentable sugars. A high-throughput method for measuring soluble sucrose, glucose, and fructose using partial least squares (PLS) modelling of juice Fourier transform infrared (FTIR) spectra was developed. The PLS prediction was shown to be highly accurate with each sugar attaining a coefficient of determination (R ² ) of 0.99 with a root mean squared error of prediction (RMSEP) of 11.93, 5.52, and 3.23 mM for sucrose, glucose, and fructose, respectively, which constitutes an error of <4% in each case. The sugar PLS model correlated well with gas chromatography–mass spectrometry (GC-MS) and brix measures. Similarly, a high-throughput method for predicting enzymatic cell wall digestibility using PLS modelling of FTIR spectra obtained from S. bicolor bagasse was developed. The PLS prediction was shown to be accurate with an R ² of 0.94 and RMSEP of 0.64 μg.mgDW^-1.h^-1.

Conclusions

This methodology has been demonstrated as an efficient and effective way to screen large biofuel feedstock populations for biomass, soluble sugar concentrations, and cell wall digestibility simultaneously allowing a total fermentable yield calculation. It unifies and simplifies previous screening methodologies to produce a holistic assessment of biofuel feedstock potential.

     

Non-contiguous genome sequence of Mycobacterium simiae strain DSM 44165T

Mycobacterium simiae is a non-tuberculosis mycobacterium causing pulmonary infections in both immunocompetent and imunocompromized patients. We announce the draft genome sequence of M. simiae DSM 44165^T. The 5,782,968-bp long genome with 65.15% GC content (one chromosome, no plasmid) contains 5,727 open reading frames (33% with unknown function and 11 ORFs sizing more than 5000 -bp), three rRNA operons, 52 tRNA, one 66-bp tmRNA matching with tmRNA tags from Mycobacterium avium, Mycobacterium tuberculosis, Mycobacterium bovis, Mycobacterium microti, Mycobacterium marinum, and Mycobacterium africanum and 389 DNA repetitive sequences. Comparing ORFs and size distribution between M. simiae and five other Mycobacterium species M. simiae clustered with M. abscessus and M. smegmatis. A 40-kb prophage was predicted in addition to two prophage-like elements, 7-kb and 18-kb in size, but no mycobacteriophage was seen after the observation of 10⁶ M. simiae cells. Fifteen putative CRISPRs were found. Three genes were predicted to encode resistance to aminoglycosides, betalactams and macrolide-lincosamide-streptogramin B. A total of 163 CAZYmes were annotated. M. simiae contains ESX-1 to ESX-5 genes encoding for a type-VII secretion system. Availability of the genome sequence may help depict the unique properties of this environmental, opportunistic pathogen.     

Desiccation resistance along an aridity gradient in the cactophilic fly Drosophila buzzatii: sex-specific responses to stress

Stress resistance characters are valuable tools for the study of acclimation potential, adaptive strategies and biogeographic patterns in species exposed to environmental variability. Water stress is a challenge to terrestrial arthropods because of their small size and relatively high area: volume ratio. Fruit flies have been investigated to record adaptive morphological and physiological traits, as well as to test their responses to stressful factors. In this study, we investigate the ability to cope with water stress, by examining variation in desiccation resistance in a species that lives mainly in desert lands. Specifically, we explored the genetic and ecological basis of desiccation resistance in populations of Drosophila buzzatii from Northern Argentina. We used a common garden experiment with desiccation treatments on a number of isofemale lines from four populations along an aridity gradient. Our results revealed significant among-population differentiation and substantial amounts of genetic variation for desiccation resistance. We also detected significant genotype-by-environment and genotype-by-sex interactions indicative that desiccation resistance responses of the lines assayed were environment- and sex-specific. In addition, we observed clinal variation in female desiccation resistance along gradients of altitude, temperature and humidity; that desiccation resistance is a sexually dimorphic trait, and that sexual dimorphism increased along the aridity and altitudinal gradients. Based on current evidence, we propose that the observed sex-specific responses may reflect different life history traits, and survival and reproductive strategies in different ecological scenarios.     

Coupling of M3 Acetylcholine Receptor to Gq16 Activates a Natriuretic Peptide Receptor Guanylyl Cyclase

Muscarinic activation of tracheal smooth muscle (TSM) involves a M₃AChR/heterotrimeric-G protein/NPR-GC coupling mechanism. G protein activators Mastoparan (MAS) and Mastoparan-7 stimulated 4- and 10-fold the NPR-GC respectively, being insensitive to PTX and antibodies against Gα_i/o subfamily. Muscarinic and MAS stimulation of NPR-GC was blocked by antibodies against C-terminal of Gα_q16, whose expression was confirmed by RT-PCR. However, synthetic peptides from C-terminal of Gα_q15/16 stimulated the NPR-GC. Coupling of α_q16 to M₃AChR is supported by MAS decreased [³H]QNB binding, being abolished after M₃AChR-4-DAMP-alkylation. Anti-i₃M₃AChR antibodies blocked the muscarinic activation of NPR-GC, and synthetic peptide from i₃M₃AChR (M₃P) was more potent than MAS increasing GTPγ [³⁵S] and decreasing the [³H]QNB activities. Coupling between NPR-GC and Gα_q16 was evaluated by using trypsin-solubilized-fraction from TSM membranes, which displayed a MAS-sensitive-NPR-GC activity, being immunoprecipitated with anti-Gα_q16, also showing an immunoreactive heterotrimeric-G-β -subunit. These data support the existence of a novel transducing cascade, involving Gα_q16β γ coupling M₃AChR to NPR-GC.     

Production of Diamino propionic acid ammonia lyase by a new strain of Salmonella typhimurium PU011

Background  

Seeds of the legume plant Lathyrus sativus, which is grown in arid and semi arid tropical regions, contain Diamino Propionic acid (DAP). DAP is a neurotoxin, which, when consumed, causes a disease called Lathyrism. Lathryrism may manifest as Neurolathyrism or Osteolathyrism, in which the nervous system, and bone formation respectively, are affected. DAP ammonia lyase is produced by a few microorganisms such as Salmonella typhi, Salmonella typhimurium and Pseudomonas, and is capable of detoxifying DAP.     

Quantification of Shared Air: A Social and Environmental Determinant of Airborne Disease Transmission

Background

Tuberculosis is endemic in Cape Town, South Africa where a majority of the population become tuberculosis infected before adulthood. While social contact patterns impacting tuberculosis and other respiratory disease spread have been studied, the environmental determinants driving airborne transmission have not been quantified.

Methods

Indoor carbon dioxide levels above outdoor levels reflect the balance of exhaled breath by room occupants and ventilation. We developed a portable monitor to continuously sample carbon dioxide levels, which were combined with social contact diary records to estimate daily rebreathed litres. A pilot study established the practicality of monitor use up to 48-hours. We then estimated the daily volumes of air rebreathed by adolescents living in a crowded township.

Results

One hundred eight daily records were obtained from 63 adolescents aged between 12- and 20-years. Forty-five lived in wooden shacks and 18 in brick-built homes with a median household of 4 members (range 2–9). Mean daily volume of rebreathed air was 120.6 (standard error: 8.0) litres/day, with location contributions from household (48%), school (44%), visited households (4%), transport (0.5%) and other locations (3.4%). Independent predictors of daily rebreathed volumes included household type (p = 0.002), number of household occupants (p = 0.021), number of sleeping space occupants (p = 0.022) and winter season (p<0.001).

Conclusions

We demonstrated the practical measurement of carbon dioxide levels to which individuals are exposed in a sequence of non-steady state indoor environments. A novel metric of rebreathed air volume reflects social and environmental factors associated with airborne infection and can identify locations with high transmission potential.