909 research outputs found
Invariant Distribution of Promoter Activities in Escherichia coli
Cells need to allocate their limited resources to express a wide range of genes. To understand how Escherichia coli partitions its transcriptional resources between its different promoters, we employ a robotic assay using a comprehensive reporter strain library for E. coli to measure promoter activity on a genomic scale at high-temporal resolution and accuracy. This allows continuous tracking of promoter activity as cells change their growth rate from exponential to stationary phase in different media. We find a heavy-tailed distribution of promoter activities, with promoter activities spanning several orders of magnitude. While the shape of the distribution is almost completely independent of the growth conditions, the identity of the promoters expressed at different levels does depend on them. Translation machinery genes, however, keep the same relative expression levels in the distribution across conditions, and their fractional promoter activity tracks growth rate tightly. We present a simple optimization model for resource allocation which suggests that the observed invariant distributions might maximize growth rate. These invariant features of the distribution of promoter activities may suggest design constraints that shape the allocation of transcriptional resources
A Minimal Model of Metabolism Based Chemotaxis
Since the pioneering work by Julius Adler in the 1960's, bacterial chemotaxis has been predominantly studied as metabolism-independent. All available simulation models of bacterial chemotaxis endorse this assumption. Recent studies have shown, however, that many metabolism-dependent chemotactic patterns occur in bacteria. We hereby present the simplest artificial protocell model capable of performing metabolism-based chemotaxis. The model serves as a proof of concept to show how even the simplest metabolism can sustain chemotactic patterns of varying sophistication. It also reproduces a set of phenomena that have recently attracted attention on bacterial chemotaxis and provides insights about alternative mechanisms that could instantiate them. We conclude that relaxing the metabolism-independent assumption provides important theoretical advances, forces us to rethink some established pre-conceptions and may help us better understand unexplored and poorly understood aspects of bacterial chemotaxis
The Goldbeter-Koshland switch in the first-order region and its response to dynamic disorder
In their classical work (Proc. Natl. Acad. Sci. USA, 1981, 78:6840-6844),
Goldbeter and Koshland mathematically analyzed a reversible covalent
modification system which is highly sensitive to the concentration of
effectors. Its signal-response curve appears sigmoidal, constituting a
biochemical switch. However, the switch behavior only emerges in the
"zero-order region", i.e. when the signal molecule concentration is much lower
than that of the substrate it modifies. In this work we showed that the
switching behavior can also occur under comparable concentrations of signals
and substrates, provided that the signal molecules catalyze the modification
reaction in cooperation. We also studied the effect of dynamic disorders on the
proposed biochemical switch, in which the enzymatic reaction rates, instead of
constant, appear as stochastic functions of time. We showed that the system is
robust to dynamic disorder at bulk concentration. But if the dynamic disorder
is quasi-static, large fluctuations of the switch response behavior may be
observed at low concentrations. Such fluctuation is relevant to many biological
functions. It can be reduced by either increasing the conformation
interconversion rate of the protein, or correlating the enzymatic reaction
rates in the network.Comment: 23 pages, 4 figures, accepted by PLOS ON
A transcriptomic snapshot of early molecular communication between Pasteuria penetrans and Meloidogyne incognita
© The Author(s). 2018Background: Southern root-knot nematode Meloidogyne incognita (Kofoid and White, 1919), Chitwood, 1949 is a key pest of agricultural crops. Pasteuria penetrans is a hyperparasitic bacterium capable of suppressing the nematode reproduction, and represents a typical coevolved pathogen-hyperparasite system. Attachment of Pasteuria endospores to the cuticle of second-stage nematode juveniles is the first and pivotal step in the bacterial infection. RNA-Seq was used to understand the early transcriptional response of the root-knot nematode at 8 h post Pasteuria endospore attachment. Results: A total of 52,485 transcripts were assembled from the high quality (HQ) reads, out of which 582 transcripts were found differentially expressed in the Pasteuria endospore encumbered J2 s, of which 229 were up-regulated and 353 were down-regulated. Pasteuria infection caused a suppression of the protein synthesis machinery of the nematode. Several of the differentially expressed transcripts were putatively involved in nematode innate immunity, signaling, stress responses, endospore attachment process and post-attachment behavioral modification of the juveniles. The expression profiles of fifteen selected transcripts were validated to be true by the qRT PCR. RNAi based silencing of transcripts coding for fructose bisphosphate aldolase and glucosyl transferase caused a reduction in endospore attachment as compared to the controls, whereas, silencing of aspartic protease and ubiquitin coding transcripts resulted in higher incidence of endospore attachment on the nematode cuticle. Conclusions: Here we provide evidence of an early transcriptional response by the nematode upon infection by Pasteuria prior to root invasion. We found that adhesion of Pasteuria endospores to the cuticle induced a down-regulated protein response in the nematode. In addition, we show that fructose bisphosphate aldolase, glucosyl transferase, aspartic protease and ubiquitin coding transcripts are involved in modulating the endospore attachment on the nematode cuticle. Our results add new and significant information to the existing knowledge on early molecular interaction between M. incognita and P. penetrans.Peer reviewedFinal Published versio
The interplay of intrinsic and extrinsic bounded noises in genetic networks
After being considered as a nuisance to be filtered out, it became recently
clear that biochemical noise plays a complex role, often fully functional, for
a genetic network. The influence of intrinsic and extrinsic noises on genetic
networks has intensively been investigated in last ten years, though
contributions on the co-presence of both are sparse. Extrinsic noise is usually
modeled as an unbounded white or colored gaussian stochastic process, even
though realistic stochastic perturbations are clearly bounded. In this paper we
consider Gillespie-like stochastic models of nonlinear networks, i.e. the
intrinsic noise, where the model jump rates are affected by colored bounded
extrinsic noises synthesized by a suitable biochemical state-dependent Langevin
system. These systems are described by a master equation, and a simulation
algorithm to analyze them is derived. This new modeling paradigm should enlarge
the class of systems amenable at modeling.
We investigated the influence of both amplitude and autocorrelation time of a
extrinsic Sine-Wiener noise on: the Michaelis-Menten approximation of
noisy enzymatic reactions, which we show to be applicable also in co-presence
of both intrinsic and extrinsic noise, a model of enzymatic futile cycle
and a genetic toggle switch. In and we show that the
presence of a bounded extrinsic noise induces qualitative modifications in the
probability densities of the involved chemicals, where new modes emerge, thus
suggesting the possibile functional role of bounded noises
Azimuthal Anisotropy of Photon and Charged Particle Emission in Pb+Pb Collisions at 158 A GeV/c
The azimuthal distributions of photons and charged particles with respect to
the event plane are investigated as a function of centrality in Pb + Pb
collisions at 158 A GeV/c in the WA98 experiment at the CERN SPS. The
anisotropy of the azimuthal distributions is characterized using a Fourier
analysis. For both the photon and charged particle distributions the first two
Fourier coefficients are observed to decrease with increasing centrality. The
observed anisotropies of the photon distributions compare well with the
expectations from the charged particle measurements for all centralities.Comment: 8 pages and 6 figures. The manuscript has undergone a major revision.
The unwanted correlations were enhanced in the random subdivision method used
in the earlier version. The present version uses the more established method
of division into subevents separated in rapidity to minimise short range
correlations. The observed results for charged particles are in agreement
with results from the other experiments. The observed anisotropy in photons
is explained using flow results of pions and the correlations arising due to
the decay of the neutral pion
Take an Emotion Walk: Perceiving Emotions from Gaits Using Hierarchical Attention Pooling and Affective Mapping
We present an autoencoder-based semi-supervised approach to classify
perceived human emotions from walking styles obtained from videos or
motion-captured data and represented as sequences of 3D poses. Given the motion
on each joint in the pose at each time step extracted from 3D pose sequences,
we hierarchically pool these joint motions in a bottom-up manner in the
encoder, following the kinematic chains in the human body. We also constrain
the latent embeddings of the encoder to contain the space of
psychologically-motivated affective features underlying the gaits. We train the
decoder to reconstruct the motions per joint per time step in a top-down manner
from the latent embeddings. For the annotated data, we also train a classifier
to map the latent embeddings to emotion labels. Our semi-supervised approach
achieves a mean average precision of 0.84 on the Emotion-Gait benchmark
dataset, which contains both labeled and unlabeled gaits collected from
multiple sources. We outperform current state-of-art algorithms for both
emotion recognition and action recognition from 3D gaits by 7%--23% on the
absolute. More importantly, we improve the average precision by 10%--50% on the
absolute on classes that each makes up less than 25% of the labeled part of the
Emotion-Gait benchmark dataset.Comment: In proceedings of the 16th European Conference on Computer Vision,
2020. Total pages 18. Total figures 5. Total tables
Corporate Social Responsibility and Sustainable Development Goal 9
With the spread of neoliberalism, corporate social responsibility (CSR) and private governance have become integral parts of corporate behavior. This entry discusses the aspects of Goal 9 (industry, innovation, and infrastructure) of the United Nations Sustainable Development Goals (SDGs) in relation to CSR. Goal 9 emphasizes sustainability, resilience, and equity of corporations, industries, and other social and economic actors in the processes of innovation and advancement of infrastructures. Although the concept of CSR, which represents positive social and environmental influences of corporations, is not explicitly mentioned in Goal 9, it is an important mechanism in accomplishing the objectives of the goal
- …