S-system parameter estimation for noisy metabolic profiles using newton-flow analysis.

Biochemical systems are commonly modelled by systems of ordinary differential equations (ODEs). A particular class of such models called S-systems have recently gained popularity in biochemical system modelling. The parameters of an S-system are usually estimated from time-course profiles. However, finding these estimates is a difficult computational problem. Moreover, although several methods have been recently proposed to solve this problem for ideal profiles, relatively little progress has been reported for noisy profiles. We describe a special feature of a Newton-flow optimisation problem associated with S-system parameter estimation. This enables us to significantly reduce the search space, and also lends itself to parameter estimation for noisy data. We illustrate the applicability of our method by applying it to noisy time-course data synthetically produced from previously published 4- and 30-dimensional S-systems. In addition, we propose an extension of our method that allows the detection of network topologies for small S-systems. We introduce a new method for estimating S-system parameters from time-course profiles. We show that the performance of this method compares favorably with competing methods for ideal profiles, and that it also allows the determination of parameters for noisy profiles.

A trap system for the isolation of amino acid sequences inducing GPI anchor addition.

We designed a trap system to isolate different amino acid sequences which could target proteins to the cell surface via GPI anchor transfer. This selection procedure is based on the insertion of various sequences which regenerate a functional GPI anchor signal sequence and therefore provoke re-expression at the surface of a reporter molecule. Using this trap for cell surface targeting sequences, we could show the importance of the defined elements essential for GPI anchor addition. Such a system could be used for an exhaustive analysis of the carboxyl terminus structural requirements for GPI membrane anchoring.

Towards robust network based complex systems : from evolutionary cellular automata to biological models

Abstract Sitting between your past and your future doesn't mean you are in the present. Dakota Skye Complex systems science is an interdisciplinary field grouping under the same umbrella dynamical phenomena from social, natural or mathematical sciences. The emergence of a higher order organization or behavior, transcending that expected of the linear addition of the parts, is a key factor shared by all these systems. Most complex systems can be modeled as networks that represent the interactions amongst the system's components. In addition to the actual nature of the part's interactions, the intrinsic topological structure of underlying network is believed to play a crucial role in the remarkable emergent behaviors exhibited by the systems. Moreover, the topology is also a key a factor to explain the extraordinary flexibility and resilience to perturbations when applied to transmission and diffusion phenomena. In this work, we study the effect of different network structures on the performance and on the fault tolerance of systems in two different contexts. In the first part, we study cellular automata, which are a simple paradigm for distributed computation. Cellular automata are made of basic Boolean computational units, the cells; relying on simple rules and information from- the surrounding cells to perform a global task. The limited visibility of the cells can be modeled as a network, where interactions amongst cells are governed by an underlying structure, usually a regular one. In order to increase the performance of cellular automata, we chose to change its topology. We applied computational principles inspired by Darwinian evolution, called evolutionary algorithms, to alter the system's topological structure starting from either a regular or a random one. The outcome is remarkable, as the resulting topologies find themselves sharing properties of both regular and random network, and display similitudes Watts-Strogtz's small-world network found in social systems. Moreover, the performance and tolerance to probabilistic faults of our small-world like cellular automata surpasses that of regular ones. In the second part, we use the context of biological genetic regulatory networks and, in particular, Kauffman's random Boolean networks model. In some ways, this model is close to cellular automata, although is not expected to perform any task. Instead, it simulates the time-evolution of genetic regulation within living organisms under strict conditions. The original model, though very attractive by it's simplicity, suffered from important shortcomings unveiled by the recent advances in genetics and biology. We propose to use these new discoveries to improve the original model. Firstly, we have used artificial topologies believed to be closer to that of gene regulatory networks. We have also studied actual biological organisms, and used parts of their genetic regulatory networks in our models. Secondly, we have addressed the improbable full synchronicity of the event taking place on. Boolean networks and proposed a more biologically plausible cascading scheme. Finally, we tackled the actual Boolean functions of the model, i.e. the specifics of how genes activate according to the activity of upstream genes, and presented a new update function that takes into account the actual promoting and repressing effects of one gene on another. Our improved models demonstrate the expected, biologically sound, behavior of previous GRN model, yet with superior resistance to perturbations. We believe they are one step closer to the biological reality.

Trait decoupling promotes evolutionary diversification of the trophic and acoustic system of damselfishes.

Trait decoupling, wherein evolutionary release of constraints permits specialization of formerly integrated structures, represents a major conceptual framework for interpreting patterns of organismal diversity. However, few empirical tests of this hypothesis exist. A central prediction, that the tempo of morphological evolution and ecological diversification should increase following decoupling events, remains inadequately tested. In damselfishes (Pomacentridae), a ceratomandibular ligament links the hyoid bar and lower jaws, coupling two main morphofunctional units directly involved in both feeding and sound production. Here, we test the decoupling hypothesis by examining the evolutionary consequences of the loss of the ceratomandibular ligament in multiple damselfish lineages. As predicted, we find that rates of morphological evolution of trophic structures increased following the loss of the ligament. However, this increase in evolutionary rate is not associated with an increase in trophic breadth, but rather with morphofunctional specialization for the capture of zooplanktonic prey. Lineages lacking the ceratomandibular ligament also shows different acoustic signals (i.e. higher variation of pulse periods) from others, resulting in an increase of the acoustic diversity across the family. Our results support the idea that trait decoupling can increase morphological and behavioural diversity through increased specialization rather than the generation of novel ecotypes.

Purification and ligand binding of a soluble class I major histocompatibility complex molecule consisting of the first three domains of H-2Kd fused to beta 2-microglobulin expressed in the baculovirus-insect cell system.

A recombinant baculovirus encoding a single-chain murine major histocompatibility complex class I molecule in which the first three domains of H-2Kd are fused to beta 2-microglobulin (beta 2-m) via a 15-amino acid linker has been isolated and used to infect lepidopteran cells. A soluble, 391-amino acid single-chain H-2Kd (SC-Kd) molecule of 48 kDa was synthesized and glycosylated in insect cells and could be purified in the absence of detergents by affinity chromatography using the anti-H-2Kd monoclonal antibody SF1.1.1.1. We tested the ability of SC-Kd to bind antigenic peptides using a direct binding assay based on photoaffinity labeling. The photoreactive derivative was prepared from the H-2Kd-restricted Plasmodium berghei circumsporozoite protein (P.b. CS) peptide 253-260 (YIPSAEKI), a probe that we had previously shown to be unable to bind to the H-2Kd heavy chain in infected cells in the absence of co-expressed beta 2-microglobulin. SC-Kd expressed in insect cells did not require additional mouse beta 2-m to bind the photoprobe, indicating that the covalently attached beta 2-m could substitute for the free molecule. Similarly, binding of the P.b. CS photoaffinity probe to the purified SC-Kd molecule was unaffected by the addition of exogenous beta 2-m. This is in contrast to H-2KdQ10, a soluble H-2Kd molecule in which beta 2-m is noncovalently bound to the soluble heavy chain, whose ability to bind the photoaffinity probe is greatly enhanced in the presence of an excess of exogenous beta 2-m. The binding of the probe to SC-Kd was allele-specific, since labeling was selectively inhibited only by antigenic peptides known to be presented by the H-2Kd molecule.

Expanding molecular modeling and design tools to non-natural sidechains.

Protein-protein interactions encode the wiring diagram of cellular signaling pathways and their deregulations underlie a variety of diseases, such as cancer. Inhibiting protein-protein interactions with peptide derivatives is a promising way to develop new biological and therapeutic tools. Here, we develop a general framework to computationally handle hundreds of non-natural amino acid sidechains and predict the effect of inserting them into peptides or proteins. We first generate all structural files (pdb and mol2), as well as parameters and topologies for standard molecular mechanics software (CHARMM and Gromacs). Accurate predictions of rotamer probabilities are provided using a novel combined knowledge and physics based strategy. Non-natural sidechains are useful to increase peptide ligand binding affinity. Our results obtained on non-natural mutants of a BCL9 peptide targeting beta-catenin show very good correlation between predicted and experimental binding free-energies, indicating that such predictions can be used to design new inhibitors. Data generated in this work, as well as PyMOL and UCSF Chimera plug-ins for user-friendly visualization of non-natural sidechains, are all available at http://www.swisssidechain.ch. Our results enable researchers to rapidly and efficiently work with hundreds of non-natural sidechains.

Primate adult brain cell autotransplantation produces behavioral and biological recovery in 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine-induced parkinsonian St. Kitts monkeys.

The potential for "replacement cells" to restore function in Parkinson's disease has been widely reported over the past 3 decades, rejuvenating the central nervous system rather than just relieving symptoms. Most such experiments have used fetal or embryonic sources that may induce immunological rejection and generate ethical concerns. Autologous sources, in which the cells to be implanted are derived from recipients' own cells after reprogramming to stem cells, direct genetic modifications, or epigenetic modifications in culture, could eliminate many of these problems. In a previous study on autologous brain cell transplantation, we demonstrated that adult monkey brain cells, obtained from cortical biopsies and kept in culture for 7 weeks, exhibited potential as a method of brain repair after low doses of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) caused dopaminergic cell death. The present study exposed monkeys to higher MPTP doses to produce significant parkinsonism and behavioral impairments. Cerebral cortical cells were biopsied from the animals, held in culture for 7 weeks to create an autologous neural cell "ecosystem" and reimplanted bilaterally into the striatum of the same six donor monkeys. These cells expressed neuroectodermal and progenitor markers such as nestin, doublecortin, GFAP, neurofilament, and vimentin. Five to six months after reimplantation, histological analysis with the dye PKH67 and unbiased stereology showed that reimplanted cells survived, migrated bilaterally throughout the striatum, and seemed to exert a neurorestorative effect. More tyrosine hydroxylase-immunoreactive neurons and significant behavioral improvement followed reimplantation of cultured autologous neural cells as a result of unknown trophic factors released by the grafts. J. Comp. Neurol. 522:2729-2740, 2014. © 2014 Wiley Periodicals, Inc.

Carbon and oxygen isotope study of hydrothermal carbonates in the zinc-lead deposits of the San Vicente district, central Peru: A quantitative modeling on mixing processes and CO2 degassing

Carbon and oxygen isotope studies of the host and gangue carbonates of Mississippi Valley-type zinc-lead deposits in the San Vicente District hosted in the Upper Triassic to Lower Jurassic dolostones of the Pucara basin (central Peru) were used to constrain models of the ore formation. A mixing model between an incoming hot saline slightly acidic radiogenic (Pb, Sr) fluid and the native formation water explains the overall isotopic variation (delta(13)C = - 11.5 to + 2.5 parts per thousand relative to PDB and delta(18)O = + 18.0 to + 24.3 parts per thousand relative to SMOW) of the carbonate generations. The dolomites formed during the main ore stage show a narrower range (delta(13)C = - 0.1 to + 1.7 parts per thousand and delta(18)O = + 18.7 to + 23.4 parts per thousand) which is explained by exchange between the mineralizing fluids and the host carbonates combined with changes in temperature and pressure. This model of fluid-rock interaction explains the pervasive alteration of the host dolomite I and precipitation of sphalerite I. The open-space filling hydrothermal white sparry dolomite and the coexisting sphalerite II formed by prolonged fluid-host dolomite interaction and limited CO2 degassing. Late void-filling dolomite III (or calcite) and the associated sphalerite III formed as the consequence of CO2 degassing and concomitant pH increase of a slightly acidic ore fluid. Widespread brecciation is associated to CO2 outgassing. Consequently, pressure variability plays a major role in the ore precipitation during the late hydrothermal events in San Vicente. The presence of native sulfur associated with extremely carbon-light calcites replacing evaporitic sulfates (e.g., delta(13)C = - 11.5 parts per thousand), altered native organic matter and heavier hydrothermal bitumen (from - 27.0 to - 23.0 parts per thousand delta(13)C) points to thermochemical reduction of sulfate and/or thiosulfate. The delta(13)C- and delta(18)O-values of the altered host dolostone and hydrothermal carbonates, and the carbon isotope composition of the associated organic matter show a strong regional homogeneity. These results coupled with the strong mineralogical and petrographic similarities of the different MVT occurrences perhaps reflects the fact that the mineralizing processes were similar in the whole San Vicente belt, suggesting the existence of a common regional mineralizing hydrothermal system with interconnected plumbing.

Integration of genome-wide association studies with biological knowledge identifies six novel genes related to kidney function.

In conducting genome-wide association studies (GWAS), analytical approaches leveraging biological information may further understanding of the pathophysiology of clinical traits. To discover novel associations with estimated glomerular filtration rate (eGFR), a measure of kidney function, we developed a strategy for integrating prior biological knowledge into the existing GWAS data for eGFR from the CKDGen Consortium. Our strategy focuses on single nucleotide polymorphism (SNPs) in genes that are connected by functional evidence, determined by literature mining and gene ontology (GO) hierarchies, to genes near previously validated eGFR associations. It then requires association thresholds consistent with multiple testing, and finally evaluates novel candidates by independent replication. Among the samples of European ancestry, we identified a genome-wide significant SNP in FBXL20 (P = 5.6 × 10(-9)) in meta-analysis of all available data, and additional SNPs at the INHBC, LRP2, PLEKHA1, SLC3A2 and SLC7A6 genes meeting multiple-testing corrected significance for replication and overall P-values of 4.5 × 10(-4)-2.2 × 10(-7). Neither the novel PLEKHA1 nor FBXL20 associations, both further supported by association with eGFR among African Americans and with transcript abundance, would have been implicated by eGFR candidate gene approaches. LRP2, encoding the megalin receptor, was identified through connection with the previously known eGFR gene DAB2 and extends understanding of the megalin system in kidney function. These findings highlight integration of existing genome-wide association data with independent biological knowledge to uncover novel candidate eGFR associations, including candidates lacking known connections to kidney-specific pathways. The strategy may also be applicable to other clinical phenotypes, although more testing will be needed to assess its potential for discovery in general.

The wound watch: an objective staging system for wounds in the diabetic (db/db) mouse model.

As in cancer biology, in wound healing there is a need for objective staging systems to decide for the best treatment and predictors of outcome. We developed in the diabetic (db/db) wound healing model, a staging system, the "wound watch," based on the quantification of angiogenesis and cell proliferation in open wounds. In chronic wounds, there is often a lack of cellular proliferation and angiogenesis that leads to impaired healing. The wound watch addresses this by quantifying the proliferative phase of wound healing in two dimensions (cellular division and angiogenesis). The results are plotted in a two-dimensional graph to monitor the course of healing and compare the response to different treatments.

Sex differences in urinary levels of several biological indicators of exposure: a simulation study using a compartmental based toxicokinetic model

Toxicokinetic modeling is a useful tool to describe or predict the behavior of a chemical agent in the human or animal organism. A general model based on four compartments was developed in a previous study in order to quantify the effect of human variability on a wide range of biological exposure indicators. The aim of this study was to adapt this existing general toxicokinetic model to three organic solvents, which were methyl ethyl ketone, 1-methoxy-2-propanol and 1,1,1,-trichloroethane, and to take into account sex differences. We assessed in a previous human volunteer study the impact of sex on different biomarkers of exposure corresponding to the three organic solvents mentioned above. Results from that study suggested that not only physiological differences between men and women but also differences due to sex hormones levels could influence the toxicokinetics of the solvents. In fact the use of hormonal contraceptive had an effect on the urinary levels of several biomarkers, suggesting that exogenous sex hormones could influence CYP2E1 enzyme activity. These experimental data were used to calibrate the toxicokinetic models developed in this study. Our results showed that it was possible to use an existing general toxicokinetic model for other compounds. In fact, most of the simulation results showed good agreement with the experimental data obtained for the studied solvents, with a percentage of model predictions that lies within the 95% confidence interval varying from 44.4 to 90%. Results pointed out that for same exposure conditions, men and women can show important differences in urinary levels of biological indicators of exposure. Moreover, when running the models by simulating industrial working conditions, these differences could even be more pronounced. In conclusion, a general and simple toxicokinetic model, adapted for three well known organic solvents, allowed us to show that metabolic parameters can have an important impact on the urinary levels of the corresponding biomarkers. These observations give evidence of an interindividual variablity, an aspect that should have its place in the approaches for setting limits of occupational exposure.

High-precision satellite positioning system as a new tool to study the biomechanics of human locomotion.

New Global Positioning System (GPS) receivers allow now to measure a location on earth at high frequency (5Hz) with a centimetric precision using phase differential positioning method. We studied whether such technique was accurate enough to retrieve basic parameters of human locomotion. Eight subjects walked on an athletics track at four different imposed step frequencies (70-130steps/min) plus a run at free pace. Differential carrier phase localization between a fixed base station and the mobile antenna mounted on the walking person was calculated. In parallel, a triaxial accelerometer, attached to the low back, recorded body accelerations. The different parameters were averaged for 150 consecutive steps of each run for each subject (total of 6000 steps analyzed). We observed a perfect correlation between average step duration measured by accelerometer and by GPS (r=0.9998, N=40). Two important parameters for the calculation of the external work of walking were also analyzed, namely the vertical lift of the trunk and the velocity variation per step. For an average walking speed of 4.0km/h, average vertical lift and velocity variation were, respectively, 4.8cm and 0.60km/h. The average intra-individual step-to-step variability at a constant speed, which includes GPS errors and the biological gait style variation, were found to be 24. 5% (coefficient of variation) for vertical lift and 44.5% for velocity variation. It is concluded that GPS technique can provide useful biomechanical parameters for the analysis of an unlimited number of strides in an unconstrained free-living environment.

Estimating dormant and active hematopoietic stem cell kinetics through extensive modeling of bromodeoxyuridine label-retaining cell dynamics.

Bone marrow hematopoietic stem cells (HSCs) are responsible for both lifelong daily maintenance of all blood cells and for repair after cell loss. Until recently the cellular mechanisms by which HSCs accomplish these two very different tasks remained an open question. Biological evidence has now been found for the existence of two related mouse HSC populations. First, a dormant HSC (d-HSC) population which harbors the highest self-renewal potential of all blood cells but is only induced into active self-renewal in response to hematopoietic stress. And second, an active HSC (a-HSC) subset that by and large produces the progenitors and mature cells required for maintenance of day-to-day hematopoiesis. Here we present computational analyses further supporting the d-HSC concept through extensive modeling of experimental DNA label-retaining cell (LRC) data. Our conclusion that the presence of a slowly dividing subpopulation of HSCs is the most likely explanation (amongst the various possible causes including stochastic cellular variation) of the observed long term Bromodeoxyuridine (BrdU) retention, is confirmed by the deterministic and stochastic models presented here. Moreover, modeling both HSC BrdU uptake and dilution in three stages and careful treatment of the BrdU detection sensitivity permitted improved estimates of HSC turnover rates. This analysis predicts that d-HSCs cycle about once every 149-193 days and a-HSCs about once every 28-36 days. We further predict that, using LRC assays, a 75%-92.5% purification of d-HSCs can be achieved after 59-130 days of chase. Interestingly, the d-HSC proportion is now estimated to be around 30-45% of total HSCs - more than twice that of our previous estimate.