Biology subjects

Workman, C. T.

Publications and source records attributed to Workman, C. T..

5 recordsLinked to original sources

bioRxiv2022

Large-scale changes of molecular network states explain complex traits

The complexity of many cellular and organismal traits results from poorly understood mechanisms integrating genetic and environmental factors via molecular networks. Here, we show when and how genetic perturbations lead to molecular changes that are confined to small parts of a network versus when they lead to large-scale adaptations of global network states. Integrating multi-omics profiling of genetically heterogeneous budding and fission yeast strains with an array of cellular traits identified a central state transition of the yeast molecular network that is related to PKA and TOR (PT) signaling. Genetic variants affecting this PT state globally shifted the molecular network along a single-dimensional axis, thereby modulating processes including energy- and amino acid metabolism, transcription, translation, cell cycle control and cellular stress response. We propose that genetic effects can propagate through large parts of molecular networks because of the functional requirement to centrally coordinate the activity of fundamental cellular processes. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=69 SRC="FIGDIR/small/519111v1_ufig1.gif" ALT="Figure 1"> View larger version (16K): org.highwire.dtl.DTLVardef@18d3323org.highwire.dtl.DTLVardef@1185111org.highwire.dtl.DTLVardef@17238c7org.highwire.dtl.DTLVardef@1edc6e6_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical abstract:C_FLOATNO Genetic variants directly or indirectly affecting the activity of PKA and/or TOR signaling cause global changes of transcriptomic and proteomic network states by modulating the activity of diverse cellular functions and network modules. Using marker genes acting downstream of PKA and TOR signaling we are able to quantify the activity status of combined PKA and TOR signaling (PT Score). This PT Score correlates with major transcriptomic and proteomic changes in response to genetic variability. Those large-scale molecular adaptations correlate with and explain phenotypic consequences for multiple cellular traits. Variants affecting the stoichiometry of proteins within a specific module have regional effects that remain confined to smaller parts of the molecular network. Variants affecting only one or very few proteins change molecular networks only locally. The global reorganization of network states caused by variants of the first type result in consequences for many cellular traits (i.e. pleiotropic effects), such as growth on different carbon sources, stress response, energy metabolism and replicative lifespan. (Created with BioRender.com) C_FIG

systems biology↗

bioRxiv2022

Precise and versatile microplate reader-based analyses of biosensor signals from arrayed microbial colonies

Genetically encoded fluorescent biosensors have emerged as a powerful tool to support phenotypic screenings of microbes. Optical analyses of fluorescent sensor signals from colonies grown on solid media can be challenging as imaging devices need to be equipped with appropriate filters matching the properties of fluorescent biosensors. Towards versatile fluorescence analyses of different types of biosensor signals derived from arrayed colonies, we investigate here the use of monochromator equipped microplate readers as an alternative to imaging approaches. Indeed, for analyses of the LacI-controlled expression of the reporter mCherry in Corynebacterium glutamicum, or promoter activity using GFP as reporter in Saccharomyces cerevisiae, an improved sensitivity and dynamic range was observed for a microplate reader-based analyses compared to their analyses via imaging. The microplate reader allowed us to capture signals of ratiometric fluorescent reporter proteins (FRPs) with a high sensitivity and thereby to further improve the analysis of internal pH via the pH-sensitive FRP mCherryEA in Escherichia coli colonies. Applicability of this novel technique was further demonstrated by assessing redox states in C. glutamicum colonies using the FRP Mrx1-roGFP2. By the use of a microplate reader, oxidative redox shifts were measured in a mutant strain lacking the non-enzymatic antioxidant mycothiol (MSH), indicating its major role for maintaining a reduced redox state also in colonies on agar plates. Taken together, analyses of biosensor signals from microbial colonies using a microplate reader allows comprehensive phenotypic screenings and thus facilitates further development of new strains for metabolic engineering and systems biology.

synthetic biology↗

bioRxiv2021

Systematic inference of regulation by protein kinases finds surprising level of transcription factor deactivation

Gene expression is controlled by pathways of regulatory factors often involving the activity of protein kinases on transcription factor proteins. Despite this well established mechanism, the number of well described pathways that include the regulatory role of protein kinases on transcription factors is surprisingly scarce in eukaryotes. To address this, PhosTF was developed to infer functional regulatory interactions and pathways in both simulated and real biological networks, based on linear cyclic causal models with latent variables. GeneNetWeaverPhos, an extension of GeneNetWeaver, was developed to allow the simulation of perturbations in known networks that included the activity of protein kinases and phosphatases on gene regulation. Over 2000 genome-wide gene expression profiles, where the loss or gain of regulatory genes could be observed to perturb gene regulation, were then used to infer the existence of regulatory interactions, and their mode of regulation in the budding yeast Saccharomyces cerevisiae. Despite the additional complexity, our inference performed comparably to the best methods that inferred transcription factor regulation assessed in the DREAM4 challenge on similar simulated networks. Inference on integrated genome-scale data sets for yeast identified [~]8800 protein kinase/phosphatase-transcription factor interactions and [~]6500 interactions among protein kinases and/or phosphatases. Both types of regulatory predictions captured statistically significant numbers of known interactions of their type. Surprisingly, kinases and phosphatases regulated transcription factors by a negative mode or regulation (deactivation) in over 70% of the predictions. Author summaryIn this work we addressed the challenging problem of inferring regulation by protein kinases and phosphatases via their activity on transcription factors. Although many protein kinase activity predictors have been developed for classes of protein kinases on specific amino acids within target sequences, our approach (PhosTF) provides predictions of regulatory activity for specific protein kinases and phosphatases on specific transcription factors. Our inference approach achieves this using the functional output observed in gene expression data of gene knock out stains, along with known transcription factor regulatory interactions. We formulated and tested a model for inference of regulation as well as a model for simulation of genes expression, transcription and translation. The simulation was used for in-silico validation of the inference method, which performed comparably to the best performers on simpler inference problem in the DREAM4 competition. The inference method was then applied to yeast expression data, with significant validation by known kinase/phosphatase interactions. Over 15300 novel regulatory interactions were predicted, suggesting that kinase activity provided a surprising level of repression of gene expression, either through the deactivation of activators or the activation of repressors.

systems biology↗

bioRxiv2021

Emergence of phenotypically distinct subpopulations is a factor in adaptation of recombinant Saccharomyces cerevisiae under glucose-limited conditions

Cells cultured in a nutrient-limited environment can undergo adaptation, which confers improved fitness under long-term energy limitation. We have previously shown how a recombinant S. cerevisiae strain, producing a heterologous insulin product, under glucose-limited conditions adapts over time at the average population level. In this paper, we investigated this adaptation at the single-cell level by application of FACS and showed that three apparent phenotypes underlie the adaptive response observed at the bulk level: (1) cells that drastically reduced insulin production (23 %), (2) cells with reduced enzymatic capacity in central carbon metabolism (46 %), (3) cells that exhibited pseudohyphal growth (31 %). We speculate that the phenotypic heterogeneity is a result of different mechanisms to increase fitness. Cells with reduced insulin productivity have increased fitness by reducing the burden of the heterologous insulin production and the populations with reduced enzymatic capacity of the central carbon metabolism and pseudohyphal growth have increased fitness towards the glucose-limited conditions. The results highlight the importance of considering population heterogeneity when studying adaptation and evolution.

bioengineering↗

bioRxiv2019

Origin of cooperativity in the activation of dimeric transcription factors

Cooperative behavior in the binding of ligands to a protein is often viewed as a complex phenomenon where conformational changes induced by the binding of the first ligand leads to tighter binding of subsequent ligands. We revisit the ligand-dependent activation of dimeric transcription factors and show that this process may appear cooperative even when it results from independent lig- and binding events. This effect is further accentuated through binding of the activated transcription factor to its cognate operator site on the DNA, where we demonstrate that cooperative activation is a stable fixed point. Our analysis nicely accounts for the apparent co-operativity inherent in the biological activity of many dimeric transcription factors.

molecular biology↗