Biology subjects

Akl, H.

Publications and source records attributed to Akl, H..

3 recordsLinked to original sources

bioRxiv2023

Jump-start and push-start: Mutual activation through crosstalk in coupled quorum sensing pathways

Many bacterial species are able to coordinate population-wide phenotypic responses through the exchange of diffusible chemical signals, a behavior known as quorum sensing. A quorum sensing bacterium may employ multiple types of chemical signals and detect them using inter-connected pathways that crosstalk with each other. While there are many hypotheses for the advantages of sensing multiple signals, the prevalence and functional significance of crosstalk between the sensing pathways are much less understood. Here we explore the effect of intra-cellular signal crosstalk on a simple model of a quorum sensing circuit. The model captures key aspects of typical quorum sensing pathways, including detection of multiple signals that crosstalk at the receptor and promoter levels, positive feedback, and hierarchical positioning of sensing pathways. We find that a variety of behaviors can be tuned by modifying crosstalk and feedback strengths. These include activation or inhibition of one output by the non-cognate signal, broadening of dynamic range of the outputs, and the ability of either the upstream or downstream branch to modulate the feedback circuit of the other branch. Our findings show how crosstalk between quorum sensing pathways can be viewed not solely as a detriment to the flow of information but also as a mechanism that enhances the functional range of the full regulatory system: When positive feedback systems are coupled through crosstalk, several new modes of activation or deactivation become possible.

systems biology↗

bioRxiv2023

The ability to sense the environment is heterogeneously distributed in cell populations

Channel capacity of signaling networks quantifies their fidelity in sensing extracellular inputs. Low estimates of channel capacities for several mammalian signaling networks suggest that cells can barely detect the presence/absence of environmental signals. However, given the extensive heterogeneity and temporal stability of cell state variables, we hypothesize that the sensing ability itself may depend on the state of the cells. In this work, we present an information theoretic framework to quantify the distribution of sensing abilities from single cell data. Using data on two mammalian pathways, we show that sensing abilities are widely distributed in the population and most cells achieve better resolution of inputs compared to an "average cell". We verify these predictions using live cell imaging data on the IGFR/FoxO pathway. Importantly, we identify cell state variables that correlate with cells sensing abilities. This information theoretic framework will significantly improve our understanding of how cells sense in their environment.

systems biology↗

bioRxiv2022

GENERALIST: An efficient generative model for protein sequence families

Generative models of protein sequence families are an important tool in the repertoire of protein scientists and engineers alike. However, state-of-the-art generative approaches face inference, accuracy, and overfitting-related obstacles when modeling moderately sized to large proteins and/or protein families with low sequence coverage. To that end, we present a simple to learn, tunable, and accurate generative model, GENERALIST: GENERAtive nonLInear tenSor-factorizaTion for protein sequences. Compared to state-of-the-art methods, GENERALIST accurately captures several high order summary statistics of amino acid covariation. GENERALIST also predicts conservative local optimal sequences which are likely to fold in stable 3D structure. Importantly, unlike other methods, the density of sequences in GENERALIST-modeled sequence ensembles closely resembles the corresponding natural ensembles. GENERALIST will be an important tool to study protein sequence variability.

biophysics↗