Overflow metabolism refers to the production of seemingly wasteful by-products by cells during growth on glucose even when oxygen is abundant. Two theories have been proposed to explain acetate overflow in Escherichia coli – global control of the central metabolism and local control of the acetate pathway – but neither accounts for all observations. Here, we develop a kinetic model of E. coli metabolism that quantitatively accounts for observed behaviors and successfully predicts the response of E. coli to new perturbations. We reconcile these theories and clarify the origin, control and regulation of the acetate flux. We also find that, in turns, acetate regulates glucose metabolism by coordinating the expression of glycolytic and TCA genes. Acetate should not be considered a wasteful end-product since it is also a co-substrate and a global regulator of glucose metabolism in E. coli. This has broad implications for our understanding of overflow metabolism.
Transcriptomics data have been deposited in ArrayExpress under accession code E-MTAB-9086.The calibrated kinetic model has been deposited in BioModels database under accession code MODEL2005050001.All the scripts used to perform the simulations, to analyse the models and to generate the figures are provided in the supporting files and at https://github.com/MetaSys-LISBP/acetate_regulationAll data generated or analysed during this study are included in the manuscript and supporting files.
Response of Escherichia coli to acetate concentration during growth on glucoseArrayExpress, E-MTAB-9086.
- Pierre Millard
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
- Michael Doebeli, University of British Columbia, Canada
© 2021, Millard et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Epifluorescence miniature microscopes ('miniscopes') are widely used for in vivo calcium imaging of neural population activity. Imaging data is typically collected during a behavioral task and stored for later offline analysis, but emerging techniques for online imaging can support novel closed-loop experiments in which neural population activity is decoded in real time to trigger neurostimulation or sensory feedback. To achieve short feedback latencies, online imaging systems must be optimally designed to maximize computational speed and efficiency while minimizing errors in population decoding. Here we introduce DeCalciOn, an open-source device for real-time imaging and population decoding of in vivo calcium signals that is hardware compatible with all miniscopes that use the UCLA Data Acquisition (DAQ) interface. DeCalciOn performs online motion stabilization, neural enhancement, calcium trace extraction, and decoding of up to 1024 traces per frame at latencies of <50 ms after fluorescence photons arrive at the miniscope image sensor. We show that DeCalciOn can accurately decode the position of rats (n=12) running on a linear track from calcium fluorescence in the hippocampal CA1 layer, and can categorically classify behaviors performed by rats (n=2) during an instrumental task from calcium fluorescence in orbitofrontal cortex (OFC). DeCalciOn achieves high decoding accuracy at short latencies using innovations such as field-programmable gate array (FPGA) hardware for real time image processing and contour-free methods to efficiently extract calcium traces from sensor images. In summary, our system offers an affordable plug-and-play solution for real-time calcium imaging experiments in behaving animals.
High-throughput sequencing of adaptive immune receptor repertoires is a valuable tool for receiving insights in adaptive immunity studies. Several powerful TCR/BCR repertoire reconstruction and analysis methods have been developed in the past decade. However, detecting and correcting the discrepancy between real and experimentally observed lymphocyte clone frequencies is still challenging. Here we discovered a hallmark anomaly in the ratio between read count and clone count-based frequencies of non-functional clonotypes in multiplex PCR-based immune repertoires. Calculating this anomaly, we formulated a quantitative measure of V- and J-genes frequency bias driven by multiplex PCR during library preparation called Over Amplification Rate (OAR). Based on the OAR concept, we developed an original software for multiplex PCR-specific bias evaluation and correction named iROAR: Immune Repertoire Over Amplification Removal (https://github.com/smiranast/iROAR). The iROAR algorithm was successfully tested on previously published TCR repertoires obtained using both 5' RACE (Rapid Amplification of cDNA Ends)-based and multiplex PCR-based approaches and compared with a biological spike-in-based method for PCR bias evaluation. The developed approach can increase the accuracy and consistency of repertoires reconstructed by different methods making them more applicable for comparative analysis.