Biology subjects

Millard, P.

Publications and source records attributed to Millard, P..

17 recordsLinked to original sources

bioRxiv2026

Organizing principles of the cellular electron economy

Life runs on electron flow. Cells extract electrons from nutrients and transfer them through metabolism, coupling carbon use to energy conservation, biosynthesis and redox homeostasis. Yet how and even whether electron flow is organized at the system-level across metabolism remain unknown. Here we formalize the concept of the cellular electron economy: a quantitative, genome-wide, reaction-resolved representation of electron generation, transfer and disposal. This electron-centric perspective reveals a quantitative relationship governed by two distinct organizing factors: the carbon source sets the baseline and maximal rate of electron flow, whereas the capacity to dispose of electrons to terminal sinks determines where within this range the system operates. Carbon uptake can even increase as net electron flux falls. This system-level organization is shown to apply to five microorganisms with different intracellular electron routing pathways and predicts graded physiological responses to oxygen supply across carbon sources and respiratory architectures. The cellular electron economy thus links reaction-level redox chemistry to whole-cell metabolic organization and reveals how the same organizing principles govern electron flow across diverse metabolic architectures.

systems biology↗

bioRxiv2026

Small but Mighty: The Surprising Metabolic Range of a Bacterial Microcompartment

Bacterial microcompartments (BMCs) are protein-based metabolic modules increasingly investigated as potential intracellular nanoreactors. In this study, we engineered Escherichia coli by chromosomally integrating the propanediol utilization (pdu) operon from Citrobacter freundii and evaluated the metabolic versatility of the heterologously produced Pdu BMCs. The formation of well-assembled, operational Pdu BMCs was confirmed in cellula. Oxygen was found to inhibit 1,2-propanediol utilization, an effect alleviated under microaerobic conditions. The engineered E. coli strain assimilated a range of diols and triols, demonstrating that Pdu BMCs process both their native substrate and glycerol and linear diols up to 1,2-butanediol (C4). This substrate promiscuity was exploited to produce high value-added compounds and revealed previously unrecognized potential for plastic upcycling through ethylene glycol metabolism. In keeping with molecular dynamics simulations indicating that the Pdu BMC shell does not impose significant diffusion barriers for longer chain diols and triols, the range of amenable substrates was successfully extended to 1,2-pentanediol (C5) by mutating the diol dehydratase large subunit (PduC). Together, these findings establish heterologous Pdu BMCs as promiscuous and genetically tunable metabolic modules in E. coli, highlighting their potential as scalable platforms for synthetic biology and biotechnological applications. ImportanceBacterial microcompartments (BMCs) are increasingly popular modular platforms for organizing and optimizing metabolic pathways, yet their substrate scope and engineering potential remain underexplored. Here, we demonstrate that heterologous Pdu BMCs expressed in Escherichia coli metabolize a substantially broader range of substrates than previously appreciated, including various diols and triols outside their native range. We further show that BMC performance is modulated by oxygen availability and can be predictably expanded by targeted enzyme engineering. These findings establish Pdu BMCs as flexible, genetically tunable metabolic modules capable of converting diverse feedstocks into value-added products, while also revealing an unanticipated capacity for plastic upcycling via ethylene glycol utilization. By integrating pathway engineering, physiological characterization, and computational modelling, this work advances the design of BMC-based systems for sustainable bioproduction and highlights their potential as customizable intracellular nanoreactors for biotechnology.

biochemistry↗

bioRxiv2026

Acetate promotes nutritional adaptation in Escherichia coli

The long-held view that acetate, one of the main fermentation by-products of Escherichia coli, is toxic to microbial growth is currently challenged. Here, we demonstrate that acetate promotes E. coli adaptation to nutrient changes by accelerating growth resumption, with as little as 250 {micro}M acetate being sufficient to shorten the lag phase by several hours. Acetate was found to be consumed via acetyl-CoA synthetase very early after the nutrient change. Transcriptomics, metabolomics and 13C-isotope labeling experiments show that acetate replenishes metabolic pools in the tricarboxylic acid cycle and upper glycolysis. Single-cell analyses reveal that acetate increases the adaptation speed of individual cells switching to the new nutrient. We conclude that the reuse of excreted acetate by E. coli facilitates metabolic adaptation by transiently replenishing central metabolite pools. This work identifies an unexpected role of acetate in the nutritional adaptation of E. coli, providing new insights into the physiological relevance of overflow metabolism. HighlightsO_LIAcetate facilitates E. coli adaptation from one nutrient to another. C_LIO_LILess than 250 {micro}M acetate is sufficient to halve lag times. C_LIO_LIAcetate helps replenish metabolite pools in central carbon metabolism. C_LIO_LIAcetate excretion is an adaptative strategy to overcome resource fluctuations. C_LI

systems biology↗

bioRxiv2025

Estimating flux dynamics from metabolite concentration time courses with dynafluxr

MotivationQuantifying metabolic fluxes and their dynamics is crucial for addressing fundamental and applied questions in systems and synthetic biology, health, and biotechnology. Since metabolic fluxes are not directly observable, they must be estimated using model-based approaches. While several methods are available to quantify steady-state fluxes, approaches for quantifying flux dynamics remain limited. ResultsWe present a method to quantify flux dynamics from metabolite concentration time courses. Our approach employs constrained B-splines to solve mass balance equations without requiring prior knowledge of catalytic or regulatory mechanisms, or enzymatic parameters. We provide a comprehensive mathematical framework for dynamic flux calculation and demonstrate that our method enables accurate and robust quantification of flux dynamics for both simulated and experimental datasets. Availability and implementationdynafluxr is implemented in R and available on Windows, Unix, and MacOS platforms. The source code and the documentation are freely distributed under GPL-3 license at https://github.com/MetaSys-LISBP/dynafluxr/. A companion notebook producing figures similar to those of this article is available at https://github.com/MetaSys-LISBP/DynafluxR_notebook.

systems biology↗

bioRxiv2025

Acetate as a metabolic booster for glucose-based bioproduction in Escherichia coli

Escherichia coli, a key workhorse in industrial biotechnology, is commonly grown on glucose, which supports rapid growth but leads to acetate overflow, which instead inhibits growth, diverts carbon from the production pathway, and reduces productivity. Recent studies suggest that acetate may also have beneficial effects in glucose-grown E. coli, but its potential in bioprocesses remains unexplored. In this study, we systematically investigated acetates impact on bioproduction using a kinetic model of glucose and acetate metabolism in E. coli. The model predicts that acetate can enhance bioproduction in glucose-grown E. coli through three mechanisms: (i) by minimizing acetate overflow, thereby reducing carbon loss, (ii) by increasing acetyl-CoA levels, thereby boosting the biosynthetic flux of acetyl-CoA-derived compounds, and (iii) by promoting biomass accumulation, thus improving overall productivity. We experimentally validated the predictions of the model for mevalonate and 3-hydroxypropionate production, where acetate supplementation increased productivity by 117% and 34%, respectively. Our findings provide a valuable framework for optimizing E. coli-based bioprocesses and highlight acetates underutilized potential in biotechnology. By leveraging acetate from waste streams as a metabolic booster, this approach could contribute to more sustainable and environmentally friendly bioprocesses. Highlights- A kinetic model was used for rational optimization of E. coli-based bioprocesses - Acetate can enhance growth and production of acetyl-CoA-derived bioproducts - Model predictions were validated for mevalonate and 3-hydroxypropionate production - Acetate can be used as a metabolic booster for glucose-based bioproduction in E. coli

systems biology↗

bioRxiv2024

MultiNMRFit: A software to fit 1D and pseudo-2D NMR spectra

Nuclear Magnetic Resonance (NMR) is widely used for quantitative analysis of metabolic systems. Accurate extraction of NMR signal parameters - such as chemical shift, intensity, coupling constants, and linewidth - is essential for obtaining information on the structure, concentration, and isotopic composition of metabolites. We present MultiNMRFit, an open-source software designed for high-throughput analysis of one-dimensional NMR spectra, whether acquired individually or as pseudo-2D experiments. MultiNMRFit extracts signal parameters (e.g. intensity, area, chemical shift, and coupling constants) by fitting the experimental spectra using built-in or user-defined signal models that account for multiplicity, providing high flexibility along with robust and reproducible results. The software is accessible both as a Python library and via a graphical user interface, enabling intuitive use by end-users with or without computational expertise. We demonstrate the robustness and flexibility of MultiNMRFit on 1H, 13C, and 31P NMR datasets collected in metabolomics and isotope labeling studies. Availability and ImplementationMultiNMRFit is implemented in Python 3 and was tested on Unix, Windows, and MacOS platforms. The source code and the documentation are freely distributed under GPL3 license at https://github.com/NMRTeamTBI/MultiNMRFit/. Supplementary dataSupplementary data are available online. ContactCyril Charlier (charlier@insa-toulouse.fr) and Pierre Millard (millard@insa-toulouse.fr)

bioinformatics↗

bioRxiv2024

Integrative in vivo analysis of the ethanolamine utilization bacterial microcompartment in Escherichia coli.

Bacterial microcompartments (BMCs) are self-assembling protein megacomplexes that encapsulate metabolic pathways. Although approximately 20% of sequenced bacterial genomes contain operons encoding putative BMCs, few have been thoroughly characterized, nor any in the most studied Escherichia coli strains. We used an interdisciplinary approach to gain deep molecular and functional insights into the ethanolamine utilization (Eut) BMC system encoded by the eut operon in E. coli K-12. The eut genotype was linked with the ethanolamine utilization phenotype using deletion and overexpression mutants. The subcellular dynamics and morphology of the E. coli Eut BMC were characterized in cellula by fluorescence microscopy and electron (cryo)microscopy. The minimal proteome reorganization required for ethanolamine utilization and the in vivo stochiometric composition of the Eut BMC were determined by quantitative proteomics. Finally, the first flux map connecting the Eut BMC with central metabolism in cellula was obtained by genome scale modelling and 13C-fluxomics. Our results reveal that, contrary to previous suggestions, ethanolamine serves both as a nitrogen and a carbon source in E. coli K-12, while also contributing significant metabolic overflow. Overall, this study provides a quantitative molecular and functional understanding of the BMCs involved in ethanolamine assimilation by E. coli. ImportanceThe properties of BMCs make them an ideal tool to build orthogonal network structures with minimal interactions with native metabolic and regulatory networks. However, this requires an understanding of how BMCs work natively. In this study, we combined genetic manipulation, multi-omics, modelling and microscopy to address this issue for Eut BMCs. We show that the Eut BMC in E. coli turns ethanolamine into usable carbon and nitrogen substrates to sustain growth. These results improve our understanding of compartmentalization in a widely used bacterial chassis.

microbiology↗

bioRxiv2024

Combining systems and synthetic biology for in vivo enzymology

Enzymatic parameters are classically determined in vitro, under conditions that are far from those encountered in cells, casting doubt on their physiological relevance. We developed a generic approach combining tools from synthetic and systems biology to measure enzymatic parameters in vivo. In the context of a synthetic carotenoid pathway in Saccharomyces cerevisiae, we focused on a phytoene synthase and three phytoene desaturases, which are difficult to study in vitro. We designed, built, and analyzed a collection of yeast strains mimicking substantial variations in substrate concentration by strategically manipulating the expression of geranyl-geranyl pyrophosphate (GGPP) synthase. We successfully determined in vivo Michaelis-Menten parameters (KM, Vmax and kcat) for GGPP-converting phytoene synthase from absolute metabolomics, fluxomics and proteomics data, highlighting differences between in vivo and in vitro parameters. Leveraging the versatility of the same set of strains, we then extracted enzymatic parameters for two of the three phytoene desaturases. Our approach demonstrates the feasibility of assessing enzymatic parameters directly in vivo, providing a novel perspective on the kinetic characteristics of enzymes in real cellular conditions.

systems biology↗

bioRxiv2023

Phosphogluconolactonase as the linchpin of an efficient pentose phosphate pathway

The metabolic networks of microorganisms are remarkably robust to genetic and environmental perturbations. This robustness stems from redundancies such as gene duplications, isoenzymes, alternative metabolic pathways, and also from non-enzymatic reactions. In the oxidative branch of the pentose-phosphate pathway (oxPPP), 6-phosphogluconolactone hydrolysis into 6-phosphogluconate is catalysed by 6-phosphogluconolactonase (Pgl) but in the absence of the latter, the oxPPP flux is thought to be maintained by spontaneous hydrolysis. However, in {Delta}pgl Escherichia coli, an extracellular pathway can also contribute to pentose-phosphate synthesis. This raises question as to whether the intracellular non-enzymatic reaction can compensate for the absence of 6-phosphogluconolactonase and, ultimately, on the role of 6-phosphogluconolactonase in central metabolism. Our results validate that the bypass pathway is active in the absence of Pgl, specifically involving the extracellular spontaneous hydrolysis of gluconolactones to gluconate. Under these conditions, metabolic flux analysis reveals that this bypass pathway accounts for the entire flux into the oxPPP. This alternative metabolic route - partially extracellular - sustains the flux through the oxPPP necessary for cell growth, albeit at a reduced rate in the absence of Pgl. Importantly, these findings imply that intracellular non-enzymatic hydrolysis of 6-phosphogluconolactone does not compensate for the absence of Pgl. This underscores the crucial role of Pgl in ensuring the efficient functioning of the oxPPP.

biochemistry↗

bioRxiv2023

PhysioFit: a software to quantify cell growth parameters and extracellular fluxes

SummaryQuantification of growth parameters and extracellular uptake and production fluxes is central in systems and synthetic biology. Fluxes can be estimated using various mathematical models by fitting time-course measurements of the concentration of cells and extracellular substrates and products. A single tool is available to non-computational biologists to calculate extracellular fluxes, but it is hardly interoperable and is limited to a single hard-coded growth model. We present our open-source flux calculation software, PhysioFit, which can be used with any growth model and is interoperable by design. PhysioFit includes some of the most common growth models, and advanced users can implement additional models to calculate extracellular fluxes and other growth parameters for metabolic systems or experimental setups that follow alternative kinetics. PhysioFit can be used as a Python library and offers a graphical user interface for intuitive use by end-users and a command-line interface to streamline integration into existing pipelines. Availability and ImplementationPhysioFit is implemented in Python 3 and was tested on Windows, Unix and MacOS platforms. PhysioFit is also freely available online at https://workflow4metabolomics.org. The source code, the data and the documentation are freely distributed under GPL3 license at https://github.com/MetaSys-LISBP/PhysioFit/ and https://physiofit.readthedocs.io/.

bioinformatics↗

bioRxiv2023

Metabolic impact of heterologous protein production in Pseudomonas putida: Insights into carbon and energy flux control

For engineered microorganisms, the production of heterologous proteins that are often useless to host cells represents a burden on resources, which have to be shared with normal cellular processes. Within a certain metabolic leeway, this competitive process has no impact on growth. However, once this leeway, or free capacity, is fully utilized, the extra load becomes a metabolic burden that inhibits cellular processes and triggers a broad cellular response, reducing cell growth and often hindering the production of heterologous proteins. In this study, we sought to characterize the metabolic rearrangements occurring in the central metabolism of Pseudomonas putida at different levels of metabolic load. To this end, we constructed a P. putida KT2440 strain that expressed two genes encoding fluorescent proteins, one in the genome under constitutive expression to monitor the free capacity, and the other on an inducible plasmid to probe heterologous protein production. We found that metabolic fluxes are considerably reshuffled, especially at the level of periplasmic pathways, as soon as the metabolic load exceeds the free capacity. Heterologous protein production leads to the decoupling of anabolism and catabolism, resulting in large excess energy production relative to the requirements of protein biosynthesis. Finally, heterologous protein production was found to exert a stronger control on carbon fluxes than on energy fluxes, indicating that the flexible nature of P. putidas central metabolic network is solicited to sustain energy production. HighlightsHeterologous protein production in P. putida reshuffles the periplasmic metabolism. Increased protein production progressively decouples catabolism from anabolism. Protein production exerts a stronger control on energy than on carbon fluxes. Glucose is directed towards ATP production to meet the elevated energy demands.

bioengineering↗

bioRxiv2022

From toxic waste to beneficial nutrient: acetate boosts Escherichia coli growth at low glycolytic flux

Acetate, a major by-product of glycolytic metabolism in Escherichia coli and many other microorganisms, has long been considered a toxic waste compound that inhibits microbial growth. This counterproductive auto-inhibition represents a major problem in biotechnology and has puzzled the scientific community for decades. Recent studies have revealed that acetate is also a co-substrate of glycolytic nutrients and a global regulator of E. coli metabolism and physiology. Here, we used a systems biology strategy to investigate the mutual regulation of glycolytic and acetate metabolism. Computational and experimental results demonstrate that reducing the glycolytic flux enhances co-utilization of acetate with glucose. Acetate metabolism thus compensates for the reduction in glycolytic flux and eventually buffers carbon uptake so that acetate, far from being toxic, actually enhances E. coli growth under these conditions. We validated this mechanism using three orthogonal strategies: chemical inhibition of glucose uptake, glycolytic mutant strains, and alternative substrates with a natively low glycolytic flux. Acetate makes E. coli more robust to glycolytic perturbations and is a valuable nutrient, with a beneficial effect on microbial growth.

systems biology↗

bioRxiv2021

Functional analysis of deoxyhexose sugar utilization in Escherichia coli reveals fermentative metabolism under aerobic conditions

L-rhamnose and L-fucose are the two main 6-deoxyhexoses Escherichia coli can use as carbon and energy sources. Deoxyhexose metabolism leads to the formation of lactaldehyde whose fate depends on oxygen availability. Under anaerobic conditions, lactaldehyde is reduced to 1,2-propanediol whereas under aerobic condition, it should be oxidised into lactate and then channelled into the central metabolism. However, although this all-or-nothing view is accepted in the literature, it seems overly simplistic since propanediol is also reported to be present in the culture medium during aerobic growth on L-fucose. To clarify the functioning of 6-deoxyhexose sugar metabolism, a quantitative metabolic analysis was performed to determine extra- and intracellular fluxes in E. coli K-12 MG1655 (a laboratory strain) and in E. coli Nissle 1917 (a human commensal strain) during anaerobic and aerobic growth on L-rhamnose and L-fucose. As expected, lactaldehyde is fully reduced to 1,2-propanediol in anoxic conditions allowing complete reoxidation of the NADH produced by glyceraldehyde-3-phosphate-dehydrogenase. We also found that net ATP synthesis is ensured by acetate production. More surprisingly, lactaldehyde is also primarily reduced into 1,2-propanediol under aerobic conditions. For growth on L-fucose, 13C-metabolic flux analysis revealed a large excess of available energy, highlighting the need to better characterize ATP utilization processes. The probiotic E. coli Nissle 1917 strain exhibits similar metabolic traits, indicating that they are not the result of the K-12 strains prolonged laboratory use. IMPORTANCEE. colis ability to survive, grow and colonize the gastrointestinal tract stems from its use of partially digested food and hydrolysed glycosylated proteins (mucins) from the intestinal mucus layer as substrates. These include L-fucose and L-rhamnose, two 6-deoxyhexose sugars, whose catabolic pathways have been established by genetic and biochemical studies. However, the functioning of these pathways has only partially been elucidated. Our quantitative metabolic analysis provides a comprehensive picture of 6-deoxyhexose sugar metabolism in E. coli under anaerobic and aerobic conditions. We found that 1,2-propanediol is a major by-product under both conditions, revealing the key role of fermentative pathways in 6-deoxyhexose sugar metabolism. This metabolic trait is shared by both E. coli strains studied here, a laboratory strain and a probiotic strain. Our findings add to our understanding of E. colis metabolism and of its functioning in the bacteriums natural environment.

physiology↗

bioRxiv2021

IsoSolve: an integrative framework to improve isotopic coverage and consolidate isotopic measurements by MS and/or NMR

Stable-isotope labeling experiments are widely used to investigate the topology and functioning of metabolic networks. Label incorporation into metabolites can be quantified using a broad range of mass spectrometry (MS)and nuclear magnetic resonance (NMR)spectroscopy methods, but in general, no single approach can completely cover isotopic space, even for small metabolites. The number of quantifiable isotopic species could be increased, and the coverage of isotopic space improved, by integrating measurements obtained by different methods; however, this approach has remained largely unexplored because no framework able to deal with partial, heterogeneous isotopic measurements has yet been developed. Here, we present a generic computational framework based on symbolic calculus that can integrate any isotopic dataset by connecting measurements to the chemical structure of the molecules. As a test case, we apply this framework to isotopic analyses of amino acids, which are ubiquitous to life, central to many biological questions, and can be analyzed by a broad range of MS and NMR methods. We demonstrate how this integrative framework helps to i) clarify and improve the coverage of isotopic space, ii) evaluate the complementarity and redundancy of different techniques, iii) consolidate isotopic datasets, iv) design experiments, and v) guide future analytical developments. This framework, which can be applied to any labeled element, isotopic tracer, metabolite, and analytical platform, has been implemented in IsoSolve (available at https://github.com/MetaSysLISBP/IsoSolve and https://pypi.org/project/IsoSolve), an open source software that can be readily integrated into data analysis pipelines.

systems biology↗

bioRxiv2020

Control and regulation of acetate overflow in Escherichia coli

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.

systems biology↗

bioRxiv2019

ScalaFlux: a scalable approach to quantify fluxes in metabolic subnetworks

13C-metabolic flux analysis (13C-MFA) allows metabolic fluxes to be quantified in living organisms and is a major tool in biotechnology and systems biology. Current 13C-MFA approaches model label propagation starting from the extracellular 13C-labeled nutrient(s), which limits their applicability to the analysis of pathways close to this metabolic entry point. Here, we propose a new approach to quantify fluxes through any metabolic subnetwork of interest by modeling label propagation directly from the metabolic precursor(s) of this subnetwork. The flux calculations are thus purely based on information from within the subnetwork of interest, and no additional knowledge about the surrounding network (such as atom transitions in upstream reactions or the labeling of the extracellular nutrient) is required. This approach, termed ScalaFlux for SCALAble metabolic FLUX analysis, can be scaled up from individual reactions to pathways to sets of pathways. ScalaFlux has several benefits compared with current 13C-MFA approaches: greater network coverage, lower data requirements, independence from cell physiology, robustness to gaps in data and network information, better computational efficiency, applicability to rich media, and enhanced flux identifiability. We validated ScalaFlux using a theoretical network and simulated data. We also used the approach to quantify fluxes through the prenyl pyrophosphate pathway of Saccharomyces cerevisiae mutants engineered to produce phytoene, using a dataset for which fluxes could not be calculated using existing approaches. A broad range of metabolic systems can be targeted with minimal cost and effort, making ScalaFlux a valuable tool for the analysis of metabolic fluxes.\n\nAuthor SummaryMetabolism is a fundamental biochemical process that enables all organisms to operate and grow by converting nutrients into energy and building blocks. Metabolic flux analysis allows the quantification of metabolic fluxes in vivo, i.e. the actual rates of biochemical conversions in biological systems, and is increasingly used to probe metabolic activity in biology, biotechnology and medicine. Isotope labeling experiments coupled with mathematical models of large metabolic networks are the most commonly used approaches to quantify fluxes within cells. However, many biological questions only require flux information from a subset of reactions, not the full network. Here, we propose a new approach with three main advantages over existing methods: better scalability (fluxes can be measured through a single reaction, a metabolic pathway or a set of pathways of interest), better robustness to missing data and information gaps, and lower requirements in terms of measurements and computational resources. We validate our method both theoretically and experimentally. ScalaFlux can be used for high-throughput flux measurements in virtually any metabolic system and paves the way to the analysis of dynamic fluxome rearrangements.

systems biology↗

bioRxiv2018

Interact: Automated analysis of protein-ligand interactions by 1D and 2D NMR

NMR titration experiments contain rich information on the thermodynamic, kinetic and structural aspects of protein-ligand interactions. Automated tools are required to process the large number of signals typically acquired in these experiments and facilitate quantitative interpretations. We present Interact, a Python script accessible within the Bruker BioSpin TopSpin software, which allows automated analysis of both 1D and 2D NMR titration experiments. Interact performs peak picking and annotation of the successive spectra and supports quantitative interpretation of changes in chemical shifts and linewidths induced by the ligand (e.g. to estimate dissociation constants) through different fitting procedures. Interact can be applied to all types of 1D and 2D NMR experiments and all nuclei, hence facilitating routine analysis of existing and forthcoming NMR titration data. Interact was implemented in Python and can be used on Windows, Unix and MacOS platforms. The source code is distributed under OpenSource license at http://github.com/MetaSys-LISBP/Interact.

bioinformatics↗