Biology subjects

McFadden, J.

Publications and source records attributed to McFadden, J..

7 recordsLinked to original sources

bioRxiv2026

Phosphoserine aminotransferase SerC is a central metabolic checkpoint and druggable vulnerability in Mycobacterium tuberculosis

Serine metabolism is fundamental to the pathogenicity of Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis (TB), yet its full metabolic scope and therapeutic potential remain unclear. Here we show that the phosphoserine aminotransferase serC is an essential metabolic node that coordinates central carbon and nitrogen flux and enables intracellular survival in the host. Deletion of serC caused severe growth defects across macrophage and murine infection models and rewired central carbon metabolism, reducing glycolytic, tricarboxylic-acid-cycle, and methylcitrate-cycle fluxes while altering one-carbon, branched-chain, and amino-acid biosynthetic pathways. Transposon sequencing identified sdaA-dependent serine deamination and the glycine cleavage system as key determinants of serine-based nitrogen assimilation, while revealing redundancy in serine transport. Our findings validate serine biosynthesis as a vulnerable, druggable metabolic target in Mtb and highlight it as a promising route for the development of urgently needed therapies against TB, which continues to kill millions of people each year.

microbiology↗

bioRxiv2025

Directed evolution and characterisation of light harvesting complexes with altered energy transfer dynamics in purple non-sulfur bacteria

Purple non-sulfur bacteria (PNSB) are metabolically versatile microorganisms that inhabit diverse environments by taking advantage of a remarkably efficient photosynthetic machinery. In this work, we describe the creation of a workflow for experimental studies that aim to compare the energy transfer mechanisms occurring within structural variants of the light-harvesting complex 2 (LH2) of PNSB. Through the creation of a library of LH2 variants using site-directed mutagenesis, we engineered proteins with different spectral properties to be expressed in a LH2-defficient mutant of the model PNSB Rhodobacter sphaeroides. We validated this approach by reproducing a previously described mutant exhibitng a blue-shift, in addition to identifying a novel mutant exhibiting a red-shift of the B850 absorption peak. We characterised the fluorescence lifetime of the purified LH2 spectral variants in vitro, and performed a bacterial growth assay to assess the fitness of the LH2 variants in vivo under oversaturating light conditions. Our results suggest that the LH2s variants expressed by PNSB in nature reflect the intricate tunning of their quantum properties not towards the fastest energy transfer but towards the optimum light-harvesting efficiency which is defined by diverse environmental factors. Statement of significanceIn this work we report a platform for the systematic investigation of the mutational landscape of light harvesting complexes forming part of the photosynthetic machinery of purple non-sulfur bacteria. By conducting directed evolution of selected residues of the light-harvesting antenna (LH2) of Rhodobacter sphaeroides we identified a novel mutant with distinct and red-shifted spectral properties. We characterised the energy transfer dynamics of this and a previous characterised mutant and demonstrated that the new variant confers a phenotypic growth advantage when cultured with high-intensity light. Our findings offer new insights into the mechanisms of light capture and energy transfer also bridging the in vitro observations with quantifiable fitness advantages under the conditions tested.

biophysics↗

bioRxiv2022

Bayesian multi-model-based 13C15N-metabolic flux analysis quantifies carbon-nitrogen metabolism in mycobacteria

Metabolic flux is the final output of cellular regulation and has been extensively studied for carbon but much less is known about nitrogen, which is another important building block for living organisms. For the pathogen Mycobacterium tuberculosis (Mtb), this is particularly important in informing the development of effective drugs targeting Mtbs metabolism. Here we performed 13C15N dual isotopic labelling of mycobacterial steady state cultures and quantified intracellular carbon-nitrogen (CN) and nitrogen (N) fluxes in addition to carbon (C) fluxes and inferred their reaction bidirectionalities. The combination of 13C15N-MFA with a Bayesian multi-model approach allowed us to resolve C and N fluxes simultaneously which was not possible with classical 13C-MFA. We quantified CN fluxes for amino acid and, for the first time, nucleotide biosynthesis. Our analysis identified glutamate as the central CN and N node in mycobacteria, and improved resolution of the anaplerotic node. Our study describes a powerful platform to measure carbon and nitrogen metabolism in any biological system with statistical rigor.

systems biology↗

bioRxiv2021

Metabolic flux partitioning between the TCA cycle and glyoxylate shunt combined with a reversible methyl citrate cycle provide nutritional flexibility for Mycobacterium tuberculosis

The utilisation of multiple host-derived carbon substrates is required by Mycobacterium tuberculosis (Mtb) to successfully sustain a tuberculosis infection thereby identifying the Mtb specific metabolic pathways and enzymes required for carbon co-metabolism as potential drug targets. Metabolic flux represents the final integrative outcome of many different levels of cellular regulation that contribute to the flow of metabolites through the metabolic network. It is therefore critical that we have an in-depth understanding of the rewiring of metabolic fluxes in different conditions. Here, we employed 13C-metabolic flux analysis using stable isotope tracers (13C and 2H) and lipid fingerprinting to investigate the metabolic network of Mtb growing slowly on physiologically relevant carbon sources in a steady state chemostat. We demonstrate that Mtb is able to efficiently co-metabolise combinations of either cholesterol or glycerol along with C2 generating carbon substrates. The uniform assimilation of the carbon sources by Mtb throughout the network indicated no compartmentalization of metabolism in these conditions however there were substrate specific differences in metabolic fluxes. This work identified that partitioning of flux between the TCA cycle and the glyoxylate shunt combined with a reversible methyl citrate cycle as the critical metabolic nodes which underlie the nutritional flexibility of Mtb. These findings provide new insights into the metabolic architecture that affords adaptability of Mtb to divergent carbon substrates. ImportanceEach year more than 1 million people die of tuberculosis (TB). Many more are infected but successfully diagnosed and treated with antibiotics, however antibiotic-resistant TB isolates are becoming ever more prevalent and so novel therapies are urgently needed that can effectively kill the causative agent. Mtb specific metabolic pathways have been identified as an important drug target in TB. However the apparent metabolic plasticity of this pathogen presents a major obstacle to efficient targeting of Mtb specific vulnerabilities and therefore it is critical to define the metabolic fluxes that Mtb utilises in different conditions. Here, we used 13C-metabolic flux analysis to measure the metabolic fluxes that Mtb uses whilst growing on potential in vivo nutrients. Our analysis identified selective use of the metabolic network that included the TCA cycle, glyoxylate shunt and methyl citrate cycle. The metabolic flux phenotypes determined in this study improves our understanding about the co-metabolism of multiple carbon substrates by Mtb identifying a reversible methyl citrate cycle and the glyoxylate shunt as the critical metabolic nodes which underlie the nutritional flexibility of Mtb.

systems biology↗

bioRxiv2019

GSMN-ML- a genome scale metabolic network reconstruction of the obligate human pathogen Mycobacterium leprae

Leprosy, caused by Mycobacterium leprae, has plagued humanity for thousands of years and continues to cause morbidity, disability and stigmatization in two to three million people today. Although effective treatment is available, the disease incidence has remained approximately constant for decades so new approaches, such as vaccine or new drugs, are urgently needed for control. Research is however hampered by the pathogens obligate intracellular lifestyle and the fact that it has never been grown in vitro. Consequently, despite the availability of its complete genome sequence, fundamental questions regarding the biology of the pathogen, such as its metabolism, remain largely unexplored. In order to explore the metabolism of the leprosy bacillus with a long-term aim of developing a medium to grow the pathogen in vitro, we reconstructed an in silico genome scale metabolic model of the bacillus, GSMN-ML. The model was used to explore the growth and biomass production capabilities of the pathogen with a range of nutrient sources, such as amino acids, glucose, glycerol and metabolic intermediates. We also used the model to analyze RNA-seq data from M. leprae grown in mouse foot pads, and performed Differential Producibility Analysis (DPA) to identify metabolic pathways that appear to be active during intracellular growth of the pathogen, which included pathways for central carbon metabolism, co-factor, lipids, amino acids, nucleotides and cell wall synthesis. The GSMN-ML model is thereby a useful in silico tool that can be used to explore the metabolism of the leprosy bacillus, analyze functional genomic experimental data, generate predictions of nutrients required for growth of the bacillus in vitro and identify novel drug targets.\n\nAuthor SummaryMycobacterium leprae, the obligate human pathogen is uncultivable in axenic growth medium, and this hinders research on this pathogen, and the pathogenesis of leprosy. The development of novel therapeutics relies on the understanding of growth, survival and metabolism of this bacterium in the host, the knowledge of which is currently very limited. Here we reconstructed a metabolic network of M. leprae-GSMN-ML, a powerful in silico tool to study growth and metabolism of the leprosy bacillus. We demonstrate the application of GSMN-ML to identify the metabolic pathways, and metabolite classes that M. leprae utilizes during intracellular growth.

microbiology↗

bioRxiv2019

A mixed nitrogen diet and compartmentalized utilization for Mycobacterium tuberculosis replicating in host cells: results of a systems-based analysis

Nitrogen metabolism of Mycobacterium tuberculosis (Mtb) is crucial for the survival and virulence of this pathogen inside host macrophages but little is known about the nitrogen sources acquired from the host or their route of assimilation. Here we performed a systems-based analysis of nitrogen metabolism in intracellullar Mtb and developed 15N-Flux Spectral Ratio Analysis (FSRA) to probe the metabolic cross-talk between the host cell and Mtb. We demonstrate that intracellular Mtb acquires nitrogen from multiple amino acids in the macrophage including glutamate, glutamine, aspartate, alanine, glycine and valine, with glutamine being the predominant nitrogen donor. Each nitrogen source is uniquely assimilated into specific intracellular pools indicating compartmentalised metabolism. This was not observed for in vitro-grown Mtb indicating that there is a switch in nitrogen metabolism when the pathogen enters the intracellular environment. These results provide clues about the potential metabolic targets for development of innovative anti-tuberculosis therapies.

microbiology↗

bioRxiv2018

Spontaneous mutations conferring antibiotic resistance to antitubercular drugs at a range of concentrations in Mycobacterium smegmatis

Mycobacteria population can undergo mutations in their DNA sequence during replication, which if not repaired, would be transferred to future generations. In this study, in vitro spontaneous mutations in Mycobacterium smegmatis mc2155 (Msm) conferring resistance to isoniazid (INHr), rifampicin (RIFr), kanamycin (KANr) and streptomycin (STRr) were determined at several concentrations in a fluctuation assay. Mutation rate was estimated using the P method, and estimates were then compared with the Lea-Coulson method of the median and Ma-Sandri-Sarkar Maximum Likelihood Estimator (MSS-MLE) method available on the Fluctuation analysis calculator (FALCOR). The mutation rates of RIFr ranged from 9.24 x 10-8 - 2.18 x 10-10, INHr 1.2 x 10-7 - 1.20x10-9, STRr 2.77 x 10-8 - 5.31 x 10-8 and KANr 1.7 x 10-8 mutations per cell division. This study provides mutation rate estimates to key antitubercular drugs at a range of concentrations.

microbiology↗