Biology subjects

Noor, E.

Publications and source records attributed to Noor, E..

At least 19 recordsLinked to original sources

bioRxiv2026

The ModelSEED Biochemistry Database, 2026 update: grading multi-source thermodynamics

The ModelSEED Biochemistry Database (https://modelseed.org) supplies foundational mass- and charge-balanced reaction networks for metabolic reconstructions. Here we present an update on the biochemistry where the database has been expanded to [~] 46,000 compounds, and [~] 56,000 reactions, featuring [~] 37,000 metabolic structures. We have expanded our approach for handling thermodynamic data, enabling multiple sources of data to be derived, integrated, and presented to the wider research community. We now publish predictions of pKa, reaction energy (and respective uncertainties), and estimates of reaction direction from multiple independent sources. Each reaction is graded gold, silver or bronze according to the strength of the evidence behind it, so that users can weigh its reliability directly. We also release reaction directions predicted by an ensemble of large language models. This multi-source approach exposes agreements and discrepancies between sources for [~] 33,000 reactions. Finally, to ensure data integrity, a new conflict-resolution pipeline reconciles structures across sources, documenting input from curators. Our work is publicly available at https://github.com/ModelSEED/ModelSEEDDatabase.

biochemistry↗

bioRxiv2026

A microbial growth-coupled platform for in vivo interrogation of Rubisco oxygenase activity

Rubisco catalyzes the primary CO2-fixing reaction of the biosphere, yet its competing oxygenation reaction reduces net global carbon fixation and has resisted direct exploration in living cells. Here, we engineer an auxotrophic Escherichia coli strain in which 2-phosphoglycolate, the direct product of Rubisco oxygenation, becomes essential for growth, making bacterial fitness a quantitative proxy for oxygenation flux in vivo. This provides direct access to catalytic selectivity, something previously inaccessible to carboxylation-coupled assays. The platform enables screening of phylogenetically diverse Form II Rubisco and phosphoribulokinase (Prk) variants circumventing protein purification and extensive in vitro characterization. Adaptive laboratory evolution under oxygenation-selective pressure identified two mutations: Rubisco M115I genetically rebalances the in vivo carboxylation/oxygenation trade-off (resulting in 6-fold reduction in kcat,C), while Prk N216T improves overall flux without altering selectivity. This platform makes Rubiscos least-studied catalytic function selectable and evolvable in vivo, opening the carboxylation/oxygenation trade-off to systematic genetic dissection and engineering.

synthetic biology↗

bioRxiv2025

Age-based approach to characterize the dynamics of cellular processes

Cells continuously produce and degrade multiple small and large molecules, essential for maintaining homeostasis. The study of these dynamics has gained momentum since the development of pulse-chase and wash-in/out methods, utilizing fluorescent or isotopic labeling of cellular components to assess properties such as turnover rates or half-lives. However, standard analyses of these experiments often depend on simplifications such as the homogeneity of analyzed molecules or their immediate labeling, which do not always hold. Here, we present a rigorous analytical framework that interprets the readouts of dynamic labeling experiments as the distribution of metabolic ages, defined as the time that molecules have spent within a cell, and show that metabolic ages can be quantified by dynamic labeling with minimal assumptions. Using age-based interpretation, we demonstrate how the experimentally observed labeling dynamics is connected to a variety of dynamic parameters including half-lives, decay rates, and residence times and how these interpretations are affected by the conditions of delayed input or complex degradation patterns. To aid in the experimental quantification of dynamic parameters, we introduce a compartmental model framework including an open-source software package. We illustrate the frameworks practical utility by quantifying dynamic parameters and determining the kinetic pool structure of budding yeast proteins at optimal and suboptimal growth temperatures. Significance StatementTo be functional, cells must balance the production and degradation of biological molecules. This is often studied by labeling newly-made molecules with isotopic or fluorescent labels. However, determining parameters of these processes, such as degradation rates, is not easy and is challenged by non-instantaneous labeling and complex degradation patterns. We describe a generic framework for interpreting the results of dynamic labeling experiments based on the concept of metabolic age, defined as the time since a molecule entered the metabolic system. By analyzing the effects of heat stress on protein stability in yeast, we illustrate how this framework and its implementation in a custom opensource package enable us to standardize the determination of various dynamic parameters of metabolism.

molecular biology↗

bioRxiv2025

Vsb1, Ypq1 and Ypq2 control dynamic cationic amino acid storage in the yeast vacuole

Although the yeast vacuole plays a crucial role in storing and mobilizing cationic amino acids (CAA), CAA transport at the vacuolar membrane remains poorly understood. Here, by combining analysis of CAA pools, uptake and permeabilization assays, we establish Vsb1 as the principal vacuolar lysine transporter, enabling its strong accumulation in the vacuole while mitigating its toxicity. We further show that, although Ypq1 can mediate proton-independent vacuolar lysine import, it mainly functions as a lysine exporter necessary for lysine mobilization under conditions of lysine scarcity and downregulated as lysine stores are exhausted. Using quantitative models based on dynamic metabolic labeling, we further show that, surprisingly, in growing cells, CAA rapidly exchange between vacuolar and cytosolic compartments, a process involving the export activity of Ypq1 and its paralogue Ypq2, specific for lysine and arginine, respectively. Together, our findings reveal the unexpectedly complex function of Vsb1 and Ypq1/2 as the key transporters mediating dynamic vacuolar CAA storage. 40-word summaryZaremba et al. characterize Vsb1 as the main yeast vacuolar lysine importer and Ypq1/2 as bi- directional vacuolar transporters of lysine and arginine. Their study highlights the role of vacuolar transporters in regulating cationic amino acid homeostasis under fluctuating nutrient availability.

cell biology↗

bioRxiv2025

Rubisco is slow across the tree of life

Rubisco is the main gateway through which inorganic carbon enters the biosphere, catalyzing the vast majority of carbon fixation on Earth. This pivotal enzyme has long been observed to be kinetically constrained. Yet, this impression is based on kinetic measurements heavily focused on eukaryotic rubiscos, a rather conserved group of low genetic diversity. Moreover, the fastest rubiscos that we know of so far were found among the sparsely sampled prokaryotes. Could there be yet faster rubiscos among the uncharted regions of rubiscos phylogenetic diversity? Here, we perform a characterization of more than 250 rubiscos from a wide range of bacteria and archaea, thereby doubling the coverage of the diversity of this key enzyme. We assess the distribution of the carboxylation rates at saturating levels of CO2, and establish that rubisco is a relatively slow enzyme across the tree of life, never exceeding {approx}30 reactions per second at 30{degrees}C. We show that relatively faster subclades share similar evolutionary contexts, involving micro-oxygenic environments or a CO2 concentrating mechanism. Leveraging a simple machine learning model trained on this dataset, we predict the carboxylation rate for all {approx}68,000 sequenced rubisco variants found in nature to date. This study provides the largest and most diverse dataset of natural variants for an enzyme and their associated rates, establishing a solid benchmark for future efforts to predict catalytic rates from sequence data. SignificanceDiscovering a fast carboxylating rubisco has been a long-standing challenge in the scientific community, given its potential impact on sustainable food and fuel production. Yet, only a small fraction of rubiscos natural diversity has been kinetically characterized. Here, we present a large-scale kinetic survey covering the entire spectrum of rubiscos diversity found in nature. Focusing on genetic clusters with above-average rates, we show that rubiscos catalytic rate does not exceed {approx}30 reactions per second at 30{degrees}C. Supported by a machine-learning predictive model, we extend this finding to all sequenced natural variants. Our study provides the most comprehensive kinetic dataset for a single enzyme to date.

systems biology↗

bioRxiv2024

Expanding the biotechnological scope of metabolic sensors through computation-aided designs

Metabolic sensors are microbial strains modified so that biomass formation correlates with the availability of specific metabolites. These sensors are essential for bioengineering (e.g. in growth-coupled designs) but creating them is often a time-consuming and low-throughput process that can potentially be streamlined by in silico analysis. Here, we present the systematic workflow of designing, implementing, and testing versatile Escherichia coli metabolic sensor strains. Glyoxylate, a key metabolite in (synthetic) CO2 fixation and carbon-conserving pathways, served as the test molecule. Through iterative screening of a compact metabolic model, we identified non-trivial growth-coupled designs that resulted in six metabolic sensors with a wide sensitivity range for glyoxylate, spanning three orders of magnitude in detected concentrations. We further adapted these E. coli strains for sensing glycolate and demonstrated their utility in both pathway engineering (testing a key metabolic module via glyoxylate) and applications in environmental monitoring (quantifying glycolate produced by photosynthetic microalgae). The versatility and ease of implementation of this workflow make it suitable for designing and building multiple metabolic sensors for diverse biotechnological applications. TeaserA streamlined workflow enables the rapid design of versatile E. coli metabolic sensors for detecting key metabolites in bioengineering and monitoring.

synthetic biology↗

bioRxiv2023

Demonstration of Bioplastic Production from CO2 and Formate using the Reductive Glycine Pathway in E. coli

There is a strong need to develop technologies that reduce anthropogenic pollution and the dependence on nonrenewable Earth resources. One way of doing so is by harnessing biological systems for replacing the production of fossil-fuel based goods with low-environmental-impact alternatives. Recently, progress was made in engineering the model organism E. coli to grow using CO2 and formate as its only carbon and energy sources using the reductive glycine pathway (rGlyP). Here, we use this engineered strain of E. coli as a host system for the production of polyhydroxybutyrate (PHB), a biologically derived and biodegradable plastic. We confirmed the production of PHB in this strain using Nile red fluorescent microscopy, transmission electron microscopy, and GC measurements. Since formate can be efficiently generated from CO2 by electrochemical reduction using renewable energy sources, this study serves as a proof of concept for the emerging field of electro-bioproduction.

synthetic biology↗

bioRxiv2023

Systematic exploration of prokaryotic form I rubisco maximal carboxylation rates

Autotrophy is the basis for complex life on Earth. Central to this process is rubisco - the enzyme that catalyzes almost all carbon fixation on the planet. Yet, with only a small fraction of rubisco diversity kinetically characterized so far, the underlying biological factors driving the evolution of fast rubiscos in nature remain unclear. We conducted a high-throughput kinetic characterization of over 100 bacterial form I rubiscos, the most ubiquitous group of rubisco sequences in nature, to uncover the determinants of rubiscos carboxylation velocity. We show that the presence of a carboxysome CO2 concentrating mechanism correlates with faster rubiscos with a median 5-fold higher rate. In contrast to prior studies, we find that rubiscos originating from -cyanobacteria exhibit the highest carboxylation rates among form I enzymes ({approx}10 s-1 median versus <7 s-1 in other groups). Our study systematically reveals biological and environmental properties associated with kinetic variation across rubiscos from nature.

systems biology↗

bioRxiv2023

Optimal enzyme profiles in unbranched metabolic pathways

How to optimize the allocation of enzymes in metabolic pathways has been a topic of study for many decades. Although the general problem is complex and non-linear, we have previously shown that it can be solved by convex optimization. In this paper, we focus on unbranched metabolic pathways with simplified enzymatic rate laws and derive analytic solutions to the optimization problem. We revisit existing solutions based on the limit of mass-action rate laws and present new solutions for other rate laws. Furthermore, we revisit a known relationship between flux control coefficients and enzyme abundances in optimal metabolic states. We generalize this relationship to models with density constrains on enzymes and metabolites, and present a new local relationship between optimal reaction elasticities and enzyme amounts. Finally, we apply our theory to derive simple kinetics-based formulae for protein allocation during bacterial growth.

systems biology↗

bioRxiv2023

What fraction of cellular DNA turnover becomes cfDNA?

Cell-free DNA (cfDNA) tests use small amounts of DNA in the bloodstream as biomarkers. While it is thought that cfDNA is largely released by dying cells, the proportion of dying cells DNA that reaches the bloodstream is unknown. Here, we integrate estimates of cellular turnover rates to calculate the expected amount of cfDNA. By comparing this to the actual amount of cell type-specific cfDNA, we estimate the proportion of DNA reaching plasma as cfDNA. We demonstrate that <10% of the DNA from dying cells is detectable in plasma, and the ratios of measured to expected cfDNA levels vary a thousand-fold among cell types, often reaching well below 0.1%. The analysis suggests that local clearance, presumably via phagocytosis, takes up most of the dying cells DNA. Insights into the underlying mechanism may help to understand the physiological significance of cfDNA and improve the sensitivity of liquid biopsies.

systems biology↗

bioRxiv2023

Autotrophic growth of E. coli is achieved by a small number of genetic changes

Synthetic autotrophy is a promising avenue to sustainable bioproduction from CO2. Here, we use iterative laboratory evolution to generate several distinct autotrophic strains. Utilising this genetic diversity, we identify that just three mutations are sufficient for E. coli to grow autotrophically, when introduced alongside non-native energy (formate dehydrogenase) and carbon-fixing (RuBisCO, phosphoribulokinase, carbonic anhydrase) modules. The mutated genes are involved in glycolysis (pgi), central-carbon regulation (crp), and RNA transcription (rpoB). The pgi mutation reduces the enzymes activity, thereby stabilising the carbon-fixing cycle by capping a major branching flux. For the other two mutations, we observe down-regulation of several metabolic pathways and increased expression of native genes associated with the carbon-fixing module (rpiB) and the energy module (fdoGH), as well as an increased ratio of NADH/NAD+ - the cycles electron-donor. This study demonstrates the malleability of metabolism and its capacity to switch trophic modes using only a small number of genetic changes and could facilitate transforming other heterotrophic organisms into autotrophs.

synthetic biology↗

bioRxiv2022

Co-substrate pools can constrain and regulate pathway fluxes in cell metabolism

Cycling of co-substrates, whereby a metabolite is converted among alternate forms via different reactions, is ubiquitous in metabolism. Several cycled co-substrates are well known as energy and electron carriers (e.g. ATP and NAD(P)H), but there are also other metabolites that act as cycled co-substrates in different parts of central metabolism. Here, we develop a mathematical framework to analyse the effect of co-substrate cycling on metabolic flux. In the cases of a single reaction and linear pathways, we find that co-substrate cycling imposes an additional flux limit on a reaction, distinct to the limit imposed by the kinetics of the primary enzyme catalysing that reaction. Using analytical methods, we show that this additional limit is a function of the total pool size and turnover rate of the cycled co-substrate. Expanding from this insight and using simulations, we show that regulation of co-substrate pool size can allow regulation of flux dynamics in branched and coupled pathways. To support theses theoretical insights, we analysed existing flux measurements and enzyme levels from the central carbon metabolism and identified several reactions that could be limited by co-substrate cycling. We discuss how the limitations imposed by co-substrate cycling provide experimentally testable hypotheses on specific metabolic phenotypes. We conclude that measuring and controlling co-substrate pools is crucial for understanding and engineering the dynamics of metabolism.

systems biology↗

bioRxiv2022

An amphipathic helix in Brl1 is required for membrane fusion during nuclear pore complex biogenesis in S. cerevisiae

The nuclear pore complex (NPC) is the central portal for macromolecular exchange between the nucleus and cytoplasm. In all eukaryotes, NPCs assemble into an intact nuclear envelope (NE) during interphase, but the process of NPC biogenesis remains poorly characterized. Furthermore, little is known about how NPC assembly leads to the fusion of the outer and inner NE, and no factors have been identified that could trigger this event. Here we characterize the transmembrane protein Brl1 as an NPC assembly factor required for NE fusion in budding yeast. Brl1 preferentially associates with NPC assembly intermediates and its depletion halts NPC biogenesis, leading to NE herniations that contain inner and outer ring nucleoporins but lack the cytoplasmic export platform. Furthermore, we identify an essential amphipathic helix in the luminal domain of Brl1 that mediates interactions with lipid bilayers. Mutations in this amphipathic helix lead to NPC assembly defects, and cryo-ET analyses reveal multi-layered herniations of the inner nuclear membrane with NPC-like structures at the neck, indicating a failure in NE fusion. Taken together, our results identify a role for Brl1 in NPC assembly and suggest a function of its amphipathic helix in mediating the fusion of the inner and outer nuclear membranes.

cell biology↗

bioRxiv2021

Activating silent glycolysis bypasses in Escherichia coli

All living organisms share similar reactions within their central metabolism to provide precursors for all essential building blocks and reducing power. To identify whether alternative metabolic routes of glycolysis can operate in E. coli, we complementarily employed in silico design, rational engineering, and adaptive laboratory evolution. First, we used a genome-scale model and identified two potential pathways within the metabolic network of this organism replacing canonical Embden-Meyerhof-Parnas (EMP) glycolysis to convert phosphosugars into organic acids. One of these glycolytic routes proceeds via methylglyoxal, the other via serine biosynthesis and degradation. Then, we implemented both pathways in E. coli strains harboring defective EMP glycolysis. Surprisingly, the pathway via methylglyoxal immediately operated in a triosephosphate isomerase deletion strain cultivated on glycerol. By contrast, in a phosphoglycerate kinase deletion strain, the overexpression of methylglyoxal synthase was necessary for implementing a functional methylglyoxal pathway. Furthermore, we engineered the serine shunt which converts 3-phosphoglycerate via serine biosynthesis and degradation to pyruvate, bypassing an enolase deletion. Finally, to explore which of these alternatives would emerge by natural selection we performed an adaptive laboratory evolution study using an enolase deletion strain. The evolved mutants were shown to use the serine shunt. Our study reveals the flexible repurposing of metabolic pathways to create new metabolite links and rewire central metabolism.

synthetic biology↗

bioRxiv2020

Functional reconstitution of a bacterial CO2 concentrating mechanism in E. coli

Many photosynthetic organisms employ a CO2 concentrating mechanism (CCM) to increase the rate of CO2 fixation via the Calvin cycle. CCMs catalyze ≈50% of global photosynthesis, yet it remains unclear which genes and proteins are required to produce this complex adaptation. We describe the construction of a functional CCM in a non-native host, achieved by expressing genes from an autotrophic bacterium in an engineered E. coli strain. Expression of 20 CCM genes enabled E. coli to grow by fixing CO2 from ambient air into biomass, with growth depending on CCM components. Bacterial CCMs are therefore genetically compact and readily transplanted, rationalizing their presence in diverse bacteria. Reconstitution enabled genetic experiments refining our understanding of the CCM, thereby laying the groundwork for deeper study and engineering of the cell biology supporting CO2 assimilation in diverse organisms.One Sentence Summary A bacterial CO2 concentrating mechanism enables E. coli to fix CO2 from ambient air.Competing Interest StatementD.F.S. is a co-founder of Scribe Therapeutics and a scientific advisory board member of Scribe Therapeutics and Mammoth Biosciences. A.B.-E. is co-founder of b.fab. These companies were not involved in this research in any way. All other authors declare no competing interests.View Full Text

synthetic biology↗

bioRxiv2020

Awakening a latent carbon fixation cycle in Escherichia coli

Carbon fixation is one of the most important biochemical processes. Most natural carbon fixation pathways are thought to have emerged from enzymes that originally performed other metabolic tasks. Can we recreate the emergence of a carbon fixation pathway in a heterotrophic host by recruiting only endogenous enzymes? In this study, we address this question by systematically analyzing possible carbon fixation pathways composed only of Escherichia coli native enzymes. We identify the GED (Gnd-Entner-Doudoroff) cycle as the simplest pathway that can operate with high thermodynamic driving force. This autocatalytic route is based on reductive carboxylation of ribulose 5-phosphate (Ru5P) by 6-phosphogluconate dehydrogenase (Gnd), followed by reactions of the Entner-Doudoroff pathway, gluconeogenesis, and the pentose phosphate pathway. We demonstrate the in vivo feasibility of this new-to-nature pathway by constructing E. coli gene deletion strains whose growth on pentose sugars depends on the GED shunt, a linear variant of the GED cycle which does not require the regeneration of Ru5P. Several metabolic adaptations, most importantly the increased production of NADPH, assist in establishing sufficiently high flux to sustain this growth. Our study exemplifies a trajectory for the emergence of carbon fixation in a heterotrophic organism and demonstrates a synthetic pathway of biotechnological interest.Competing Interest StatementThe authors have declared no competing interest.View Full Text

synthetic biology↗

bioRxiv2020

The ModelSEED Database for the integration of metabolic annotations and the reconstruction, comparison, and analysis of metabolic models for plants, fungi, and microbes

For over ten years, ModelSEED has been a primary resource for the construction of draft genome-scale metabolic models based on annotated microbial or plant genomes. Now being released, the biochemistry database serves as the foundation of biochemical data underlying ModelSEED and KBase. The biochemistry database embodies several properties that, taken together, distinguish it from other published biochemistry resources by: (i) including compartmentalization, transport reactions, charged molecules and proton balancing on reactions;; (ii) being extensible by the user community, with all data stored in GitHub; and (iii) design as a biochemical "Rosetta Stone" to facilitate comparison and integration of annotations from many different tools and databases. The database was constructed by combining chemical data from many resources, applying standard transformations, identifying redundancies, and computing thermodynamic properties. The ModelSEED biochemistry is continually tested using flux balance analysis to ensure the biochemical network is modeling-ready and capable of simulating diverse phenotypes. Ontologies can be designed to aid in comparing and reconciling metabolic reconstructions that differ in how they represent various metabolic pathways. ModelSEED now includes 33,978 compounds and 36,645 reactions, available as a set of extensible files on GitHub, and available to search at https://modelseed.org and KBase.

systems biology↗

bioRxiv2018

Synthesis and degradation of FtsZ determines the first cell division in starved bacteria

In natural environments, microbes are typically non-dividing. Such quiescent cells manage fleeting nutrients and gauge when intra- and extracellular resources permit division. Quantitative prediction of the division event as a function of nutritional status is currently achieved through phenomenological models for nutrient-rich, exponentially growing cultures. Such models, however, cannot predict the first division of cells under limiting nutrient availability. To address this, we analyzed the metabolic capability of starved Escherichia coli that were fed pulsed glucose at defined frequencies. Real-time metabolomics and microfluidic single-cell microscopy revealed unexpected, rapid protein and nucleic acid synthesis already in non-dividing cells. Additionally, the lag time to first division shortened as pulsing frequency increased. Here, we demonstrate that the first division from a non-dividing state occurs when the facilitating protein FtsZ reaches division-supporting concentration. A dynamic model quantitatively relates lag time to FtsZ synthesis from nutrient pulses and its protease-dependent degradation. Consistent with model predictions, lag time shortened when FtsZ synthesis was supplemented or protease inhibitors were added. Lag time prolonged when ftsZ was repressed or FtsZ degradation rate was increased. Thus, we provide a basis to quantitatively predict bacterial division using information about molecular determinants and the nutrient input.

microbiology↗