Body plan evolvability: The role of variability in gene regulatory networks.

Recent computational modeling of early fruit fly () development has characterized the degree to which gene regulation networks can be robust to natural variability. In the first few hours of development, broad spatial gradients of maternally derived transcription factors activate embryonic gap genes. These gap patterns determine the subsequent segmented insect body plan through pair-rule gene expression.

Problem of Domain/Building Block Preservation in the Evolution of Biological Macromolecules and Evolutionary Computation.

Structurally and functionally isolated domains in biological macromolecular evolution, both natural and artificial, are largely similar to "schemata", building blocks (BBs), in evolutionary computation (EC). The problem of preserving in subsequent evolutionary searches the already found domains / BBs is well known and quite relevant in biology as well as in EC. Both biology and EC are seeing parallel and independent development of several approaches to identifying and preserving previously identified domains / BBs.

The emergence of hypervirulent bla-positive Klebsiella pneumoniae sequence type 395 in an oncology hospital.

Fifteen hypermucoviscous isolates (13 bla-positive) obtained from 11 oncology patients were analyzed by whole genome sequencing, and selected isolates were assessed in a murine model of sepsis. ST395/K2 isolates harboring rmpA, rmpA2, peg-344, aerobactin, enterobactin, yersiniabactin, type I fimbriae, etc. displayed maximal virulence in the mouse lethality assay (LD = 10 CFU).

Gene regulatory networks in Drosophila early embryonic development as a model for the study of the temporal identity of neuroblasts.

Genes belonging to the "gap" and "gap-like" family constitute the best-studied gene regulatory networks (GRNs) in Drosophila embryogenesis. Gap genes are a core of two subnetworks controlling embryonic segmentation: (hunchback, hb; Krüppel, Kr; giant, gt; and knirps, kni) and (hb; Kr; pou-domain, pdm; and, probably, castor, cas). Of particular interest is that (hb, Kr, pdm, cas) also specifies the temporal identity of stem cells, neuroblasts, in Drosophila neurogenesis.

[Evolutionary Stability of Gene Regulatory Networks That Define the Temporal Identity of Neuroblasts].

The ensemble of gap genes is one of the best studied and most conserved gene regulatory networks (GRNs). Gap genes, such as hunchback (hb), Krüppel (Kr), pou-domain (pdm; pdm1 and pdm2), and castor (cas) genes belong to the well-known families Ikaros (IKZF1/hb), Krüppel-like factor (KLF/Kr), POU domain (BRN1/pdm-1, BRN2/pdm-2), and Castor homologs (CASZ1/cas), which are present in all vertebrate genomes and code for site-specific transcription factors. Gap genes form a core of an embryonic segmentation control subnetwork and define the temporal identity of neuroblasts in Drosophila embryos.

Relative sensitivity analysis of the predictive properties of sloppy models.

Commonly among the model parameters characterizing complex biological systems are those that do not significantly influence the quality of the fit to experimental data, so-called "sloppy" parameters. The sloppiness can be mathematically expressed through saturating response functions (Hill's, sigmoid) thereby embodying biological mechanisms responsible for the system robustness to external perturbations. However, if a sloppy model is used for the prediction of the system behavior at the altered input (e.

Robustness of expression pattern formation due to dynamic equilibrium in gap gene system of an early Drosophila embryo.

The first manifestation of a segmentation pattern in the early Drosophila development is the formation of expression domains of genes belonging to the gap class. In our previous research the phenomenon of the gap system's robustness, exhibited as the ability to reduce highly variable gene expression in the course of development, was explained as a result of gene cross-regulation. In this paper we formulate the rigorous robustness conditions using the inherent properties of gap gene family.

Peculiarities of Anxiety Score Distribution in Adult Cancer Patients.

The goal of the present research is to investigate and analyze possible peculiarities of the psychological state of cancer patients undergoing treatment. Scores characterizing the trait and state anxiety were acquired using the Integrative Anxiety Test from four groups: adults with no appreciable disease, pregnant women, cancer patients examined during the specific antitumor treatment, and cancer patients brought into lasting clinical remission. Statistical analysis of the testing results revealed the bimodal type of the distribution of scores.

Statistical method for estimation of the predictive power of a gene circuit model.

In this paper, a specific aspect of the prediction problem is considered: high predictive power is understood as a possibility to reproduce correct behavior of model solutions at predefined values of a subset of parameters. The problem is discussed in the context of a specific mathematical model, the gene circuit model for segmentation gap gene system in early Drosophila development. A shortcoming of the model is that it cannot be used for predicting the system behavior in mutants when fitted to wild type (WT) data.

Quantitative imaging of gene expression in Drosophila embryos.

Quantitative measurements derived using sophisticated microscopy techniques are essential for understanding the basic principles that control the behavior of biological systems. Here we describe a data pipeline developed to extract quantitative data on segmentation gene expression from confocal images of gene expression patterns in Drosophila. The pipeline consists of image segmentation, background removal, temporal characterization of an embryo, data registration, and data averaging.

Preparation of Drosophila embryos for quantitative imaging of gene expression.

Quantitative measurements derived using sophisticated microscopy techniques are essential for understanding the basic principles that control the behavior of biological systems. We have developed a five-step data pipeline to extract quantitative data on segmentation gene expression from confocal images of gene expression patterns in Drosophila. This protocol describes the preparation of Drosophila embryos for imaging by confocal microscopy.

Modeling of gap gene expression in Drosophila Kruppel mutants.

The segmentation gene network in Drosophila embryo solves the fundamental problem of embryonic patterning: how to establish a periodic pattern of gene expression, which determines both the positions and the identities of body segments. The gap gene network constitutes the first zygotic regulatory tier in this process. Here we have applied the systems-level approach to investigate the regulatory effect of gap gene Kruppel (Kr) on segmentation gene expression.

A regression system for estimation of errors introduced by confocal imaging into gene expression data in situ.

Background: Accuracy of the data extracted from two-dimensional confocal images is limited due to experimental errors that arise in course of confocal scanning. The common way to reduce the noise in images is sequential scanning of the same specimen several times with the subsequent averaging of multiple frames. Attempts to increase the dynamical range of an image by setting too high values of microscope PMT parameters may cause clipping of single frames and introduce errors into the data extracted from the averaged images.

Mechanisms of gap gene expression canalization in the Drosophila blastoderm.

Background: Extensive variation in early gap gene expression in the Drosophila blastoderm is reduced over time because of gap gene cross regulation. This phenomenon is a manifestation of canalization, the ability of an organism to produce a consistent phenotype despite variations in genotype or environment. The canalization of gap gene expression can be understood as arising from the actions of attractors in the gap gene dynamical system.

GCPReg package for registration of the segmentation gene expression data in Drosophila.

In modern functional genomics registration techniques areused to construct reference gene expression patterns and createa spatiotemporal atlas of the expression of all the genes in anetwork. In this paper we present a software package calledGCPReg, which can be used to register the expression patterns ofsegmentation genes in the early Drosophila embryo. The key task,which this package performs, is the extraction of spatially localizedcharacteristic features of expression patterns.

Methods for Acquisition of Quantitative Data from Confocal Images of Gene Expression in situ.

In this review, we summarize original methods for the extraction of quantitative information from confocal images of gene-expression patterns. These methods include image segmentation, the extraction of quantitative numerical data on gene expression, and the removal of background signal and spatial registration. Finally, it is possible to construct a spatiotemporal atlas of gene expression from individual images recorded at each developmental stage.

Estimation of errors introduced by confocal imaging into the data on segmentation gene expression in Drosophila.

Motivation: Currently the confocal scanning microscopy of fluorescently tagged molecules is extensively employed to acquire quantitative data on gene expression at cellular resolution. Following this approach, we generated a large dataset on the expression of segmentation genes in the Drosophila blastoderm, that is widely used in systems biology studies. As data accuracy is of critical importance for the success of studies in this field, we took a shot to evaluate possible errors introduced in the data by acquisition and processing methods.

Pipeline for acquisition of quantitative data on segmentation gene expression from confocal images.

We describe a data pipeline developed to extract the quantitative data on segmentation gene expression from confocal images of gene expression patterns in Drosophila. The pipeline consists of five steps: image segmentation, background removal, temporal characterization of an embryo, data registration and data averaging. This pipeline was successfully applied to obtain quantitative gene expression data at cellular resolution in space and at the 6.

Characterization of the Drosophila segment determination morphome.

Here we characterize the expression of the full system of genes which control the segmentation morphogenetic field of Drosophila at the protein level in one dimension. The data used for this characterization are quantitative with cellular resolution in space and about 6 min in time. We present the full quantitative profiles of all 14 segmentation genes which act before the onset of gastrulation.

Master equation simulation analysis of immunostained Bicoid morphogen gradient.

Background: The concentration gradient of Bicoid protein which determines the developmental pathways in early Drosophila embryo is the best characterized morphogen gradient at the molecular level. Because different developmental fates can be elicited by different concentrations of Bicoid, it is important to probe the limits of this specification by analyzing intrinsic fluctuations of the Bicoid gradient arising from small molecular number. Stochastic simulations can be applied to further the understanding of the dynamics of Bicoid morphogen gradient formation at the molecular number level, and determine the source of the nucleus-to-nucleus expression variation (noise) observed in the Bicoid gradient.

Quantitative and predictive model of transcriptional control of the Drosophila melanogaster even skipped gene.

Here we present a quantitative and predictive model of the transcriptional readout of the proximal 1.7 kb of the control region of the Drosophila melanogaster gene even skipped (eve). The model is based on the positions and sequence of individual binding sites on the DNA and quantitative, time-resolved expression data at cellular resolution.

Removal of background signal from in situ data on the expression of segmentation genes in Drosophila.

Here we present a method for the removal of nonspecific background signal from fluorescently localized expression patterns of Drosophila segmentation genes. Our algorithm for removal of background signal brings the data to a common standard form with zero background and removes systematic error in gene expression levels caused by the presence of background. The method is based on the discovery, reported here, that background is well fit by a very broad two-dimensional paraboloid.