DeltaProt: a software toolbox for comparative genomics

DWARF AND ROBUST PLANT regulates plant height via modulating gibberellin biosynthesis in chrysanthemum

YABBY (YAB) genes are specifically expressed in abaxial cells of lateral organs and determine abaxial cell fate. However, most studies have focused on few model plants, and the molecular mechanisms of YAB genes are not well understood. Here, we identified a YAB transcription factor in chrysanthemum (Chrysanthemum morifolium), Dwarf and Robust Plant (CmDRP), that belongs to a distinct FILAMENTOUS FLOWER (FlL)/YAB3 sub-clade lost in Brassicaceae. CmDRP was expressed in various tissues but did not show any polar distribution in chrysanthemum. Overexpression of CmDRP resulted in a semi-dwarf phenotype with a significantly decreased active GA3 content, while reduced expression generated the opposite phenotype. Furthermore, plant height of transgenic plants was partially rescued through the exogenous application of GA3 and Paclobutrazol, and expression of the GA biosynthesis gene CmGA3ox1 was significantly altered in transgenic plants. Yeast one-hybrid, luciferase, and chromatin immunoprecipitation-qPCR analyses showed that CmDRP could directly bind to the CmGA3ox1 promoter and suppress its expression. Our research reveals a nonpolar expression pattern of a YAB family gene in dicots and demonstrates it regulates plant height through the GA pathway, which will deepen the understanding of the genetic and molecular mechanisms of YAB genes.

Classification of Ankle Joint Stiffness during Walking to Determine the Use of Ankle Foot Orthosis after Stroke

Categorization based on quasi-joint stiffness (QJS) may help clinicians select appropriate ankle foot orthoses (AFOs). The objectives of the present study were to classify the gait pattern based on ankle joint stiffness, also called QJS, of the gait in patients after stroke and to clarify differences in the type of AFO among 72 patients after stroke. Hierarchical cluster analysis was used to classify gait patterns based on QJS at least one month before the study, which revealed three distinct subgroups (SGs 1, 2, and 3). The proportion of use of AFOs, articulated AFOs, and non-articulated AFOs were significantly different among SGs 1-3. In SG1, with a higher QJS in the early and middle stance, the proportion of the patients using articulated AFOs was higher, whereas in SG3, with a lower QJS in both stances, the proportion of patients using non-articulated AFOs was higher. In SG2, with a lower QJS in the early stance and higher QJS in the middle stance, the proportion of patients using AFOs was lower. These findings indicate that classification of gait patterns based on QJS in patients after stroke may be helpful in selecting AFO. However, large sample sizes are required to confirm these results.

Mecp2 Deletion from Cholinergic Neurons Selectively Impairs Recognition Memory and Disrupts Cholinergic Modulation of the Perirhinal Cortex

Rett Syndrome is a neurological disorder caused by mutations in the gene encoding methyl CpG binding protein 2 (MeCP2) and characterized by severe intellectual disability. The cholinergic system is a critical modulator of cognitive ability and is affected in patients with Rett Syndrome. To better understand the importance of MeCP2 function in cholinergic neurons, we studied the effect of selective Mecp2 deletion from cholinergic neurons in mice. Mice with Mecp2 deletion from cholinergic neurons were selectively impaired in assays of recognition memory, a cognitive task largely mediated by the perirhinal cortex (PRH). Deletion of Mecp2 from cholinergic neurons resulted in profound alterations in baseline firing of L5/6 neurons and eliminated the responses of these neurons to optogenetic stimulation of cholinergic input to PRH. Both the behavioral and the electrophysiological deficits of cholinergic Mecp2 deletion were rescued by inhibiting ACh breakdown with donepezil treatment.

Use of Raman spectroscopy to screen diabetes mellitus with machine learning tools

Type 2 diabetes mellitus (DM2) is one of the most widely prevalent diseases worldwide and is currently screened by invasive techniques based on enzymatic assays that measure plasma glucose concentration in a laboratory setting. A promising plan of action for screening DM2 is to identify molecular signatures in a non-invasive fashion. This work describes the application of portable Raman spectroscopy coupled with several supervised machine-learning techniques, to discern between diabetic patients and healthy controls (Ctrl), with a high degree of accuracy. Using artificial neural networks (ANN), we accurately discriminated between DM2 and Ctrl groups with 88.9-90.9% accuracy, depending on the sampling site. In order to compare the ANN performance to more traditional methods used in spectroscopy, principal component analysis (PCA) was carried out. A subset of features from PCA was used to generate a support vector machine (SVM) model, albeit with decreased accuracy (76.0-82.5%). The 10-fold cross-validation model was performed to validate both classifiers. This technique is relatively low-cost, harmless, simple and comfortable for the patient, yielding rapid diagnosis. Furthermore, the performance of the ANN-based method was better than the typical performance of the invasive measurement of capillary blood glucose. These characteristics make our method a promising screening tool for identifying DM2 in a non-invasive and automated fashion.

Altered Functional Connectivity Following an Inflammatory White Matter Injury in the Newborn Rat: A High Spatial and Temporal Resolution Intrinsic Optical Imaging Study

Very preterm newborns have an increased risk of developing an inflammatory cerebral white matter injury that may lead to severe neuro-cognitive impairment. In this study we performed functional connectivity (fc) analysis using resting-state optical imaging of intrinsic signals (rs-OIS) to assess the impact of inflammation on resting-state networks (RSN) in a pre-clinical model of perinatal inflammatory brain injury. Lipopolysaccharide (LPS) or saline injections were administered in postnatal day (P3) rat pups and optical imaging of intrinsic signals were obtained 3 weeks later. (rs-OIS) fc seed-based analysis including spatial extent were performed. A support vector machine (SVM) was then used to classify rat pups in two categories using fc measures and an artificial neural network (ANN) was implemented to predict lesion size from those same fc measures. A significant decrease in the spatial extent of fc statistical maps was observed in the injured group, across contrasts and seeds (^*p = 0.0452 for HbO₂ and ^**p = 0.0036 for HbR). Both machine learning techniques were applied successfully, yielding 92% accuracy in group classification and a significant correlation r = 0.9431 in fractional lesion volume prediction (^**p = 0.0020). Our results suggest that fc is altered in the injured newborn brain, showing the long-standing effect of inflammation.

A natural barrier to lateral gene transfer from prokaryotes to eukaryotes revealed from genomes: the 70 % rule

BACKGROUND

The literature harbors many claims for lateral gene transfer (LGT) from prokaryotes to eukaryotes. Such claims are typically founded in analyses of genome sequences. It is undisputed that many genes entered the eukaryotic lineage via the origin of mitochondria and the origin of plastids. Claims for lineage-specific LGT to eukaryotes outside the context of organelle origins and claims of continuous LGT to eukaryotic lineages are more problematic. If eukaryotes acquire genes from prokaryotes continuously during evolution, then sequenced eukaryote genomes should harbor evidence for recent LGT, like prokaryotic genomes do.

RESULTS

Here we devise an approach to investigate 30,358 eukaryotic sequences in the context of 1,035,375 prokaryotic homologs among 2585 phylogenetic trees containing homologs from prokaryotes and eukaryotes. Prokaryote genomes reflect a continuous process of gene acquisition and inheritance, with abundant recent acquisitions showing 80-100 % amino acid sequence identity to their phylogenetic sister-group homologs from other phyla. By contrast, eukaryote genomes show no evidence for either continuous or recent gene acquisitions from prokaryotes. We find that, in general, genes in eukaryotic genomes that share ≥70 % amino acid identity to prokaryotic homologs are genome-specific; that is, they are not found outside individual genome assemblies.

CONCLUSIONS

Our analyses indicate that eukaryotes do not acquire genes through continual LGT like prokaryotes do. We propose a 70 % rule: Coding sequences in eukaryotic genomes that share more than 70 % amino acid sequence identity to prokaryotic homologs are most likely assembly or annotation artifacts. The findings further uncover that the role of differential loss in eukaryote genome evolution has been vastly underestimated.

A Mutation Model from First Principles of the Genetic Code

The paper presents a neutral Codons Probability Mutations (CPM) model of molecular evolution and genetic decay of an organism. The CPM model uses a Markov process with a 20-dimensional state space of probability distributions over amino acids. The transition matrix of the Markov process includes the mutation rate and those single point mutations compatible with the genetic code. This is an alternative to the standard Point Accepted Mutation (PAM) and BLOcks of amino acid SUbstitution Matrix (BLOSUM). Genetic decay is quantified as a similarity between the amino acid distribution of proteins from a (group of) species on one hand, and the equilibrium distribution of the Markov chain on the other. Amino acid data for the eukaryote, bacterium, and archaea families are used to illustrate how both the CPM and PAM models predict their genetic decay towards the equilibrium value of 1. A family of bacteria is studied in more detail. It is found that warm environment organisms on average have a higher degree of genetic decay compared to those species that live in cold environments. The paper addresses a new codon-based approach to quantify genetic decay due to single point mutations compatible with the genetic code. The present work may be seen as a first approach to use codon-based Markov models to study how genetic entropy increases with time in an effectively neutral biological regime. Various extensions of the model are also discussed.

VennPainter: A Tool for the Comparison and Identification of Candidate Genes Based on Venn Diagrams

VennPainter is a program for depicting unique and shared sets of genes lists and generating Venn diagrams, by using the Qt C++ framework. The software produces Classic Venn, Edwards’ Venn and Nested Venn diagrams and allows for eight sets in a graph mode and 31 sets in data processing mode only. In comparison, previous programs produce Classic Venn and Edwards’ Venn diagrams and allow for a maximum of six sets. The software incorporates user-friendly features and works in Windows, Linux and Mac OS. Its graphical interface does not require a user to have programing skills. Users can modify diagram content for up to eight datasets because of the Scalable Vector Graphics output. VennPainter can provide output results in vertical, horizontal and matrix formats, which facilitates sharing datasets as required for further identification of candidate genes. Users can obtain gene lists from shared sets by clicking the numbers on the diagram. Thus, VennPainter is an easy-to-use, highly efficient, cross-platform and powerful program that provides a more comprehensive tool for identifying candidate genes and visualizing the relationships among genes or gene families in comparative analysis.

Imaging of an inflammatory injury in the newborn rat brain with photoacoustic tomography

Background

The precise assessment of cerebral saturation changes during an inflammatory injury in the developing brain, such as seen in periventricular leukomalacia, is not well defined. This study investigated the impact of inflammation on locoregional cerebral oxygen saturation in a newborn rodent model using photoacoustic imaging.

Methods

1 mg/kg of lipopolysaccharide(LPS) diluted in saline or saline alone was injected under ultrasound guidance directly in the corpus callosum of P3 rat pups. Coronal photoacoustic images were carried out 24 h after LPS exposure. Locoregional oxygen saturation (SO₂) and resting state connectivity were assessed in the cortex and the corpus callosum. Microvasculature was then evaluated on cryosection slices by lectin histochemistry.

Results

Significant reduction of SO₂ was found in the corpus callosum; reduced SO₂ was also found in the cortex ipsilateral to the injection site. Seed-based functional connectivity analysis showed that bilateral connectivity was not affected by LPS exposure. Changes in locoregional oxygen saturation were accompanied by a significant reduction in the average length of microvessels in the left cortex but no differences were observed in the corpus callosum.

Conclusion

Inflammation in the developing brain induces marked reduction of locoregional oxygen saturation, predominantly in the white matter not explained by microvascular degeneration. The ability to examine regional saturation offers a new way to monitor injury and understand physiological disturbance non-invasively.

Molecular characterization of cold adaptation of membrane proteins in the Vibrionaceae core-genome

Cold-adaptation strategies have been studied in multiple psychrophilic organisms, especially for psychrophilic enzymes. Decreased enzyme activity caused by low temperatures as well as a higher viscosity of the aqueous environment require certain adaptations to the metabolic machinery of the cell. In addition to this, low temperature has deleterious effects on the lipid bilayer of bacterial membranes and therefore might also affect the embedded membrane proteins. Little is known about the adaptation of membrane proteins to stresses of the cold. In this study we investigate a set of 66 membrane proteins from the core genome of the bacterial family Vibrionaceae to identify general characteristics that discern psychrophilic and mesophilic membrane proteins. Bioinformatical and statistical methods were used to analyze the alignments of the three temperature groups mesophilic, intermediate and psychrophilic. Surprisingly, our results show little or no adaptation to low temperature for those parts of the proteins that are predicted to be inside the membrane. However, changes in amino acid composition and hydrophobicity are found for complete sequences and sequence parts outside the lipid bilayer. Among others, the results presented here indicate a preference for helix-breaking and destabilizing amino acids Ile, Asp and Thr and an avoidance of the helix-forming amino acid Ala in the amino acid composition of psychrophilic membrane proteins. Furthermore, we identified a lower overall hydrophobicity of psychrophilic membrane proteins in comparison to their mesophilic homologs. These results support the stability-flexibility hypothesis and link the cold-adaptation strategies of membrane proteins to those of loop regions of psychrophilic enzymes.