Professor Johnjoe McFadden

Bovine tuberculosis (BtB) caused by Mycobacterium bovis remains a major problem in both the developed and developing countries. control of BtB in the UK is carried out by test and slaughter of infected animals, based primarily on the tuberculin skin test (ppD). Vaccination with the attenuated strain of the M. bovis pathogen, BcG, is not used to control bovine tuberculosis in cattle at present, due to its variable efficacy and because it interferes with the PPD test. Diagnostic tests capable of Differentiating Infected from Vaccinated Animals (DIVA) have been developed that detect immune responses to M. bovis antigens absent in BCG; but these are too expensive and insufficiently sensitive to be used for BtB control worldwide. to address these problems we aimed to generate a synergistic vaccine and diagnostic approach that would permit the vaccination of cattle without interfering with the conventional ppD-based surveillance. the approach was to widen the pool of M. bovis antigens that could be used as DiVA targets, by identifying antigenic proteins that could be deleted from BcG without affecting the persistence and protective efficacy of the vaccine in cattle. Using transposon mutagenesis we identified genes that were essential and those that were non-essential for persistence in bovine lymph nodes. We then inactivated selected immunogenic, but non-essential genes in BcG Danish to create a diagnostic-compatible triple knock-out ΔBCG TK strain. The protective efficacy of the ΔBcG tK was tested in guinea pigs experimentally infected with M. bovis by aerosol and found to be equivalent to wild-type BcG. A complementary diagnostic skin test was developed with the antigenic proteins encoded by the deleted genes which did not cross-react in vaccinated or in uninfected guinea pigs. this study demonstrates the functionality of a new and improved BcG strain which retains its protective efficacy but is diagnostically compatible with a novel DIVA skin test that could be implemented in control programmes.

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 pathogen’s 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 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.

The co-catabolism of multiple host-derived carbon substrates is required by Mycobacterium tuberculosis (Mtb) to successfully sustain a tuberculosis infection. However, the metabolic plasticity of this pathogen and the complexity of the metabolic networks present a major obstacle in identifying those nodes most amenable to therapeutic interventions. It is therefore critical that we define the metabolic phenotypes of Mtb in different conditions. We applied metabolic flux analysis using stable isotopes and lipid fingerprinting to investigate the metabolic network of Mtb growing slowly in our steady-state chemostat system. We demonstrate that Mtb efficiently co-metabolises either cholesterol or glycerol, in combination with two-carbon generating substrates without any compartmentalisation of metabolism. We discovered that partitioning of flux between the TCA cycle and the glyoxylate shunt combined with a reversible methyl citrate cycle is the critical metabolic nodes which underlie the nutritional flexibility of Mtb. These findings provide novel insights into the metabolic architecture that affords adaptability of bacteria to divergent carbon substrates and expand our fundamental knowledge about the methyl citrate cycle and the glyoxylate shunt.

Understanding the rules of life is one of the most important scientific endeavours and has revolutionised both biology and biotechnology. Remarkable advances in observation techniques allow us to investigate a broad range of complex and dynamic biological processes in which living systems could exploit quantum behaviour to enhance and regulate biological functions. Recent evidence suggests that these non-trivial quantum mechanical effects may play a crucial role in maintaining the non-equilibrium state of biomolecular systems. Quantum biology is the study of such quantum aspects of living systems. In this review, we summarise the latest progress in quantum biology, including the areas of enzyme-catalysed reactions, photosynthesis, spin-dependent reactions, DNA, fluorescent proteins, and ion channels. Many of these results are expected to be fundamental building blocks towards understanding the rules of life.

Leptospirosis is a neglected disease of man and animals that affects nearly half a million people annually and causes considerable economic losses. Current human vaccines are inactivated whole-cell preparations (bacterins) of Leptospira spp. that provide strong homologous protection yet fail to induce a cross-protective immune response. Yearly boosters are required, and serious side-effects are frequently reported so the vaccine is licensed for use in humans in only a handful of countries. Novel universal vaccines require identification of conserved surface-exposed epitopes of leptospiral antigens. Outer membrane β-barrel proteins (βb-OMPs) meet these requirements and have been successfully used as vaccines for other diseases. We report the evaluation of 22 constructs containing protein fragments from 33 leptospiral βb-OMPs, previously identified by reverse and structural vaccinology and cell-surface immunoprecipitation. Three-dimensional structures for each leptospiral βb-OMP were predicted by I-TASSER. The surface-exposed epitopes were predicted using NetMHCII 2.2 and BepiPred 2.0. Recombinant constructs containing regions from one or more βb-OMPs were cloned and expressed in Escherichia coli . IMAC-purified recombinant proteins were adsorbed to an aluminium hydroxide adjuvant to produce the vaccine formulations. Hamsters (4-6 weeks old) were vaccinated with 2 doses containing 50 – 125 μg of recombinant protein, with a 14-day interval between doses. Immunoprotection was evaluated in the hamster model of leptospirosis against a homologous challenge (10 – 20× ED 50 ) with L. interrogans serogroup Icterohaemorrhagiae serovar Copenhageni strain Fiocruz L1-130. Of the vaccine formulations, 20/22 were immunogenic and induced significant humoral immune responses (IgG) prior to challenge. Four constructs induced significant protection (100%, P< 0.001) and sterilizing immunity in two independent experiments, however, this was not reproducible in subsequent evaluations (0 – 33.3% protection, P > 0.05). The lack of reproducibility seen in these challenge experiments and in other reports in the literature, together with the lack of immune correlates and commercially available reagents to characterize the immune response, suggest that the hamster may not be the ideal model for evaluation of leptospirosis vaccines and highlight the need for evaluation of alternative models, such as the mouse.

Persistence has been linked to treatment failure since its discovery over 70 years ago and understanding formation, nature and survival of this key antibiotic refractory subpopulation is crucial to enhancing treatment success and combatting the threat of antimicrobial resistance (AMR). The term ‘persistence’ is often used interchangeably with other terms such as tolerance or dormancy. In this review we focus on ‘antibiotic persistence’ which we broadly define as a feature of a subpopulation of bacterial cells that possesses the non-heritable character of surviving exposure to one or more antibiotics; and persisters as cells that possess this character. We discuss novel molecular mechanisms involved in persister cell formation, as well as environmental factors which can contribute to increased antibiotic persistence in vivo, highlighting recent developments advanced by single-cell studies. We also aim to provide a comprehensive model of persistence, the ‘hunker’ theory which is grounded in intrinsic heterogeneity of bacterial populations and a myriad of ‘hunkering down’ mechanisms which can contribute to antibiotic survival of the persister subpopulation. Finally, we discuss antibiotic persistence as a ‘stepping-stone’ to AMR and stress the urgent need to develop effective anti-persister treatment regimes to treat this highly clinically relevant bacterial sub-population.

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 tuberculosis pathogen, this is particularly important in informing the development of effective drugs targeting the pathogen's metabolism. Here we performed 13C15N dual isotopic labeling of Mycobacterium bovis BCG steady state cultures, quantified intracellular carbon and nitrogen fluxes and inferred reaction bidirectionalities. This was achieved by model scope extension and refinement, implemented in a multi-atom transition model, within the statistical framework of Bayesian model averaging (BMA). Using BMA-based 13C15N-metabolic flux analysis, we jointly resolve carbon and nitrogen fluxes quantitatively. We provide the first nitrogen flux distributions for amino acid and nucleotide biosynthesis in mycobacteria and establish glutamate as the central node for nitrogen metabolism. We improved resolution of the notoriously elusive anaplerotic node in central carbon metabolism and revealed possible operation modes. Our study provides a powerful and statistically rigorous platform to simultaneously infer carbon and nitrogen metabolism in any biological system.

Klebsiella pneumoniae is an important pathogenic bacterium commonly associated with human healthcare and community-acquired infections. In recent years, K. pneumoniae has become a significant threat to global public and veterinary health, because of its high rates of antimicrobial resistance (AMR). Early diagnosis of K. pneumoniae infection and detection of any associated AMR would help to accelerate directed therapy and reduce the risk of the emergence of multidrug-resistant isolates. In this study, we identified three target genes (yhaI, epsL, and xcpW) common to K. pneumoniae isolates from both China and Europe and designed loop-mediated isothermal amplification (LAMP) assays for the detection of K. pneumoniae in clinical samples. We also designed LAMP assays for the detection of five AMR genes commonly associated with K. pneumoniae. The LAMP assays were validated on a total of 319 type reference strains and clinical isolates of diverse genetic backgrounds, in addition to 40 clinical human sputum samples, and were shown to be reliable, highly specific, and sensitive. For the K. pneumoniae-specific LAMP assay, the calculated sensitivity, specificity, and positive and negative predictive values (comparison with culture and matrix-assisted laser desorption/ionization-time of flight mass spectrometry) were all 100% on clinical isolates and, respectively, of 100%, 91%, and 90%, and 100% when tested on clinical sputum samples, while being significantly faster than the reference methods. For the bla(KPC) and other carbapenemases' LAMP assays, the concordance between the LAMP results and the references methods (susceptibility tests) was 100%, on both pure cultures (n = 125) and clinical samples (n = 18). In conclusion, we developed highly sensitive and specific LAMP assays for the clinical identification of K. pneumoniae and detection of carbapenem resistance.

Bovine tuberculosis is an important animal health problem and the predominant cause of zoonotic tuberculosis worldwide. It results in serious economic burden due to losses in productivity and the cost of control programmes. Control could be greatly improved by the introduction of an efficacious cattle vaccine but the most likely candidate, BCG, has several limitations including variable efficacy. Augmentation of BCG with a subunit vaccine booster has been shown to increase protection but the selection of antigens has hitherto been left largely to serendipity. In the present study, we take a rational approach to identify the protective antigens of BCG, selecting a BCG transposon mutant library in naïve and BCG-vaccinated cattle. Ten mutants had increased relative survival in vaccinated compared to naïve cattle, consistent with loss of protective antigen targets making the mutants less visible to the BCG immune response. The immunogenicity of three putative protective antigens, BCG_0116, BCG_0205 (YrbE1B) and BCG_1448 (PPE20) was investigated using peptide pools and PBMCs from BCG vaccinated cattle. BCG vaccination induced PBMC to release elevated levels of IP10, IL-17a and IL-10 in response to all three antigens. Taken together, the data supports the further study of these antigens for use in subunit vaccines.

Background BCG is the most widely used vaccine of all time and remains the only licensed vaccine for use against tuberculosis in humans. BCG also protects other species such as cattle against tuberculosis, but due to its incompatibility with current tuberculin testing regimens remains unlicensed. BCG’s efficacy relates to its ability to persist in the host for weeks, months or even years after vaccination. It is unclear to what degree this ability to resist the host’s immune system is maintained by a dynamic interaction between the vaccine strain and its host as is the case for pathogenic mycobacteria. Results To investigate this question, we constructed transposon mutant libraries in both BCG Pasteur and BCG Danish strains and inoculated them into bovine lymph nodes. Cattle are well suited to such an assay, as they are naturally susceptible to tuberculosis and are one of the few animal species for which a BCG vaccination program has been proposed. After three weeks, the BCG were recovered and the input and output libraries compared to identify mutants with in vivo fitness defects. Less than 10% of the mutated genes were identified as affecting in vivo fitness, they included genes encoding known mycobacterial virulence functions such as mycobactin synthesis, sugar transport, reductive sulphate assimilation, PDIM synthesis and cholesterol metabolism. Many other attenuating genes had not previously been recognised as having a virulence phenotype. To test these genes, we generated and characterised three knockout mutants that were predicted by transposon mutagenesis to be attenuating in vivo: pyruvate carboxylase, a hypothetical protein (BCG_1063), and a putative cyclopropane-fatty-acyl-phospholipid synthase. The knockout strains survived as well as wild type during in vitro culture and in bovine macrophages, yet demonstrated marked attenuation during passage in bovine lymph nodes confirming that they were indeed involved in persistence of BCG in the host. Conclusion These data show that BCG is far from passive during its interaction with the host, rather it continues to employ its remaining virulence factors, to interact with the host’s innate immune system to allow it to persist, a property that is important for its protective efficacy.

Neisseria meningitidis is a global cause of meningitis and septicemia. Immunity to N. meningitidis involves both innate and specific mechanisms with killing by serum bactericidal activity and phagocytic cells. C-reactive protein (CRP) is an acute-phase serum protein that has been shown to help protect the host from several bacterial pathogens, which it recognizes by binding to phosphorylcholine (PC) on their surfaces. Pathogenic Neisseria species can exhibit phase-variable PC modification on type 1 and 2 pili. We have shown that CRP can bind to piliated meningococci in a classical calcium-dependent manner. The binding of CRP to the meningococcus was concentration dependent, of low affinity, and specific for PC. CRP appears to act as an opsonin for N. meningitidis, as CRP-opsonized bacteria showed increased uptake by human macrophages and neutrophils. Further investigation into the downstream effects of CRP-bound N. meningitidis may lead us to a better understanding of meningococcal infection and help direct more effective therapeutic interventions.

Constraint-based approaches facilitate the prediction of cellular metabolic capabilities, based, in turn on predictions of the repertoire of enzymes encoded in the genome. Recently, genome annotations have been used to reconstruct genome scale metabolic reaction networks for numerous species, including Homo sapiens, which allow simulations that provide valuable insights into topics, including predictions of gene essentiality of pathogens, interpretation of genetic polymorphism in metabolic disease syndromes and suggestions for novel approaches to microbial metabolic engineering. These constraint-based simulations are being integrated with the functional genomics portals, an activity that requires efficient implementation of the constraint-based simulations in the web-based environment.

An in-depth study of a novel functionalization of carbon nanotubes for their application as protein and DNA carriers is presented. First, the optimum conditions for the dispersion of singlewalled carbon nanotubes (SWCNTs) with amphiphilic polypeptides were obtained, and the SWCNT–polypeptide complexes were characterized by different techniques (UV–Vis-NIR, CD, and AFM). Based on the properties of the SWCNT–polypeptide complexes, a model that characterizes the adsorption of natural proteins onto SWCNT was described for the first time. This model predicts the adsorption of natural proteins on SWCNTs based on the protein structure and composition, and therefore, allows the design of methods for the preparation of SWCNT–protein complexes. Besides, the use of cationic-designed amphiphilic polypeptides to disperse SWCNTs is applied for subsequent and efficient binding of DNA to carbon nanotubes by a bilayer approach. Therefore, in this article, we develop procedures for the use of SWCNTs as protein and DNA carriers. The systems were delivered into cells showing that the efficiency of delivery is affected by the charge of the complexes, which has important implications in the use of SWCNT as platforms for protein and DNA binding and subsequent use as delivery systems.

Carbon nanotubes (CNTs) are at present being considered as potential nanovectors with the ability to deliver therapeutic cargoes into living cells. Previous studies established the ability of CNTs to enter cells and their therapeutic utility, but an appreciation of global intracellular trafficking associated with their cellular distribution has yet to be described. Despite the many aspects of the uptake mechanism of CNTs being studied, only a few studies have investigated internalization and fate of CNTs inside cells in detail. In the present study, intracellular localization and trafficking of RNA-wrapped, oxidized double-walled CNTs (oxDWNT-RNA) is presented. Fixed cells, previously exposed to oxDWNT-RNA, were subjected to immunocytochemical analysis using antibodies specific to proteins implicated in endocytosis; moreover cell compartment markers and pharmacological inhibitory conditions were also employed in this study. Our results revealed that an endocytic pathway is involved in the internalization of oxDWNT-RNA. The nanotubes were found in clathrin-coated vesicles, after which they appear to be sorted in early endosomes, followed by vesicular maturation, become located in lysosomes. Furthermore, we observed co-localization of oxDWNT-RNA with the small GTP-binding protein (Rab 11), involved in their recycling back to the plasma membrane via endosomes from the trans-golgi network.

One of the most challenging problems in microbiology is to understand how a small fraction of microbes that resists killing by antibiotics can emerge in a population of genetically identical cells, the phenomenon known as persistence or drug tolerance. Its characteristic signature is the biphasic kill curve, whereby microbes exposed to a bactericidal agent are initially killed very rapidly but then much more slowly. Here we relate this problem to the more general problem of understanding the emergence of distinct growth phenotypes in clonal populations. We address the problem mathematically by adopting the framework of the phenomenon of so-called weak ergodicity breaking, well known in dynamical physical systems, which we extend to the biological context. We show analytically and by direct stochastic simulations that distinct growth phenotypes can emerge as a consequence of slow-down of stochastic fluctuations in the expression of a gene controlling growth rate. In the regime of fast gene transcription, the system is ergodic, the growth rate distribution is unimodal, and accounts for one phenotype only. In contrast, at slow transcription and fast translation, weakly non-ergodic components emerge, the population distribution of growth rates becomes bimodal, and two distinct growth phenotypes are identified. When coupled to the well-established growth rate dependence of antibiotic killing, this model describes the observed fast and slow killing phases, and reproduces much of the phenomenology of bacterial persistence. The model has major implications for efforts to develop control strategies for persistent infections.

Mycobacterium tuberculosis infects a third of the world's population. Primary tuberculosis involving active fast bacterial replication is often followed by asymptomatic latent tuberculosis, which is characterised by slow or non-replicating bacteria. Reactivation of the latent infection involving a switch back to active bacterial replication can lead to post-primary transmissible tuberculosis. Mycobacterial mechanisms involved in slow growth or switching growth rate provide rational targets for the development of new drugs against persistent mycobacterial infection. Using chemostat culture to control growth rate, we screened a transposon mutant library by Transposon site hybridization (TraSH) selection to define the genetic requirements for slow and fast growth of Mycobacterium bovis (BCG) and for the requirements of switching growth rate. We identified 84 genes that are exclusively required for slow growth (69 hours doubling time) and 256 genes required for switching from slow to fast growth. To validate these findings we performed experiments using individual M. tuberculosis and M. bovis BCG knock out mutants. We have demonstrated that growth rate control is a carefully orchestrated process which requires a distinct set of genes encoding several virulence determinants, gene regulators, and metabolic enzymes. The mce1 locus appears to be a component of the switch to slow growth rate, which is consistent with the proposed role in virulence of M. tuberculosis. These results suggest novel perspectives for unravelling the mechanisms involved in the switch between acute and persistent TB infections and provide a means to study aspects of this important phenomenon in vitro.

Whereas intracellular carbon metabolism has emerged as an attractive drug target, the carbon sources of intracellularly replicating pathogens, such as the tuberculosis bacillus Mycobacterium tuberculosis, which causes long-term infections in one-third of the world's population, remain mostly unknown. We used a systems-based approach-(13)C-flux spectral analysis (FSA) complemented with manual analysis-to measure the metabolic interaction between M. tuberculosis and its macrophage host cell. (13)C-FSA analysis of experimental data showed that M. tuberculosis obtains a mixture of amino acids, C1 and C2 substrates from its host cell. We experimentally confirmed that the C1 substrate was derived from CO2. (13)C labeling experiments performed on a phosphoenolpyruvate carboxykinase mutant revealed that intracellular M. tuberculosis has access to glycolytic C3 substrates. These findings provide constraints for developing novel chemotherapeutics.

Despite decades of research many aspects of the biology of Mycobacterium tuberculosis remain unclear and this is reflected in the antiquated tools available to treat and prevent tuberculosis and consequently this disease remains a serious public health problem. Important discoveries linking M. tuberculosis’s metabolism and pathogenesis have renewed interest in this area of research. Previous experimental studies were limited to the analysis of individual genes or enzymes whereas recent advances in computational systems biology and high throughput experimental technologies now allow metabolism to be studied on a genome scale. Here we discuss the progress being made in applying system level approaches to studying the metabolism of this important pathogen. The information from these studies will fundamentally change our approach to tuberculosis research and lead to new targets for therapeutic drugs and vaccines.

Despite the introduction of conjugated polysaccharide vaccines for many of the Neisseria meningitidis serogroups, neisserial infections continue to cause septicaemia and meningitis across the world. This is in part due to the difficulties in developing a, cross-protective vaccine that is effective against all serogroups, including serogroup B meningococci. Although convalescent N. meningitidis patients develop a natural long-lasting cross-protective immunity, the antigens that mediate this response remain unknown. To help define the target of this protective immunity we identified the proteins recognized by IgG in sera from meningococcal patients by a combination of 2D protein gels, western blots and mass spectrometry. Although a number of outer membrane antigens were identified the majority of the antigens were cytoplasmic, with roles in cellular processes and metabolism. When recombinant proteins were expressed and used to raise sera in mice, none of the antigens elicited a positive SBA result, however flow cytometry did demonstrate that some, including the ribosomal protein, RplY were localised to the neisserial cell surface.

Mycobacterium tuberculosis requires the enzyme isocitrate lyase (ICL) for growth and virulence in vivo. The demonstration that M. tuberculosis also requires ICL for survival during nutrient starvation and has a role during steady state growth in a glycerol limited chemostat indicates a function for this enzyme which extends beyond fat metabolism. As isocitrate lyase is a potential drug target elucidating the role of this enzyme is of importance; however, the role of isocitrate lyase has never been investigated at the level of in vivo fluxes. Here we show that deletion of one of the two icl genes impairs the replication of Mycobacterium bovis BCG at slow growth rate in a carbon limited chemostat. In order to further understand the role of isocitrate lyase in the central metabolism of mycobacteria the effect of growth rate on the in vivo fluxes was studied for the first time using ¹³C-metabolic flux analysis (MFA). Tracer experiments were performed with steady state chemostat cultures of BCG or M. tuberculosis supplied with ¹³C labeled glycerol or sodium bicarbonate. Through measurements of the ¹³C isotopomer labeling patterns in protein-derived amino acids and enzymatic activity assays we have identified the activity of a novel pathway for pyruvate dissimilation. We named this the GAS pathway because it utilizes the Glyoxylate shunt and Anapleurotic reactions for oxidation of pyruvate, and Succinyl CoA synthetase for the generation of succinyl CoA combined with a very low flux through the succinate--oxaloacetate segment of the tricarboxylic acid cycle. We confirm that M. tuberculosis can fix carbon from CO₂ into biomass. As the human host is abundant in CO₂ this finding requires further investigation in vivo as CO₂ fixation may provide a point of vulnerability that could be targeted with novel drugs. This study also provides a platform for further studies into the metabolism of M. tuberculosis using ¹³C-MFA.

The use of carbon nanotubes as a gene delivery system has been extensively studied in recent years owing to its potential advantages over viral vectors. To achieve this goal, carbon nanotubes have to be functionalized to become compatible with aqueous media and to bind the genetic material. To establish the best conditions for plasmid DNA binding, we compare the dispersion properties of single-, double- and multi-walled carbon nanotubes (SWCNTs, DWCNTs and MWCNTs, respectively) functionalized with a variety of surfactants by non-covalent attachment. The DNA binding properties of the functionalized carbon nanotubes were studied and compared by electrophoresis. Furthermore, a bilayer functionalization method for DNA binding on SWCNTs was developed that utilized RNA-wrapping to solubilize the nanotubes and cationic polymers as a bridge between nanotubes and DNA.

We have designed a drug delivery system for the anti-cancer drugs doxorubicin and mitoxantrone based on carbon nanotubes, which is stable under biological conditions, allows for sustained release, and promotes selectivity through an active targeting scheme. Carbon nanotubes are particularly promising for this area of application due to their high surface area, allowing for high drug loading, and their unique interaction with cellular membranes. We have taken a systematic approach to PEG conjugation in order to create a formulation of stable and therapeutically effective CNTs. The presented drug delivery system may be a means of improving cancer treatment modalities by reducing drug-related side effects.

The development of diagnostic tests which can readily differentiate between vaccinated and tuberculosis-infected individuals is crucial for the wider utilization of bacillus Calmette-Guérin (BCG) as vaccine in humans and animals. BCG_0092 is an antigen that elicits specific delayed type hypersensitivity reactions similar in size and morphological aspects to that elicited by purified protein derivative, in both animals and humans infected with the tubercle bacilli. We carried out bioinformatics analyses of the BCG_0092 and designed a diagnostic test by using the predicted MHC class I epitopes. In addition, we performed a knockout of this gene by homologous recombination in the BCG vaccine strain to allow differentiation of vaccinated from infected individuals. For that, the flanking sequences of the target gene (BCG_0092)were cloned into a suicide vector. Spontaneous double crossovers, which result in wild type revertants or knockouts were selected using SacB. BCG_0092 is present only in members of the Mycobacterium tuberculosis complex. Eight predicted MHC class I epitopes with potential for immunological diagnosis were defined, allowing the design of a specific diagnostic test. The strategy used to delete the (BCG_0092) gene from BCG was successful. The knockout genotype was confirmed by PCR and by Southern blot. The mutant BCG strain has the potential of inducing protection against tuberculosis without interfering with the diagnostic test based on the use of selected epitopes from BCG_0092.

In earlier papers I described the conscious electromagnetic information (CEMI) field theory, which claimed that the substrate of consciousness is the brain's electromagnetic (EM) field. I here further explore this theory by examining the properties and dynamics of the information underlying meaning in consciousness. I argue that meaning suffers from a binding problem, analogous to the binding problem described for visual perception, and describe how the gestalt (holistic) properties of meaning give rise to this binding problem. To clarify the role of information in conscious meaning, I differentiate between extrinsic information that is symbolic and arbitrary, and intrinsic information, which preserves structural aspects of the represented object and thereby maintains some gestalt properties of the represented object. I contrast the requirement for a decoding process to extract meaning from extrinsic information, whereas meaning is intrinsic to the structure of the gestalt intrinsic information and does not require decoding. I thereby argue that to avoid the necessity of a decoding homunculus, conscious meaning must be encoded intrinsically -- as gestalt information -- in the brain. Moreover, I identify fields as the only plausible substrate for encoding gestalt intrinsic information and argue that the binding problem of meaning can only be solved by grounding meaning in this field-based gestalt information. I examine possible substrates for gestalt information in the brain and conclude that the only plausible substrate is the CEMI field.

The tuberculin purified protein derivative (PPD) is a widely used diagnostic antigen for tuberculosis, however it is poorly defined. Most mycobacterial proteins are extensively denatured by the procedure employed in its preparation, which explains previous difficulties in identifying constituents from PPD to characterize their behaviour in B- and T-cell reactions. We here described a proteomics-based characterization of PPD from several different sources by LC-MS/MS, which combines the solute separation power of HPLC, with the detection power of a mass spectrometer. The technique is able to identify proteins from complex mixtures of peptide fragments. A total of 171 different proteins were identified among the four PPD samples (two bovine PPD and two avium PPD) from Brazil and UK. The majority of the proteins were cytoplasmic (77.9%) and involved in intermediary metabolism and respiration (24.25%) but there was a preponderance of proteins involved in lipid metabolism. We identified a group of 21 proteins that are present in both bovine PPD but were not detected in avium PPD preparation. In addition, four proteins found in bovine PPD are absent in Mycobacterium bovis BCG vaccine strain. This study provides a better understanding of the tuberculin PPD components leading to the identification of additional antigens useful as reagents for specific diagnosis of tuberculosis.

Polyethyleneimine-coated double-walled carbon nanotubes (DWCNTs) were used for dual gene and drug delivery, after loading the DWCNTs with the drug chloroquine, a lysosomotropic compound that is able to promote escape from the lysosomal compartment. Different forms of functionalization of the DWCNTs were examined in order to optimize this system. They included the testing of different treatments on DWCNTs to optimize the loading and delivery of chloroquine and the selection of a cationic polymer for coating the DWCNTs for optimum DNA binding and delivery. An acid oxidation treatment of DWCNTs was selected for optimum chloroquine loading together with polyethyleneimine as optimum cationic coating agent for plasmid DNA binding. Optimization of the conditions for choroquine-enhanced gene delivery were developed using luciferase expression as a model system. We have demonstrated that chloroquine-loading increases the ability of polyethyleneimine-coated DWCNTs to deliver functional nucleic acid to human cells. Cell viability tests have shown no cytotoxicity of the functionalized DWCNTs at the concentrations needed for optimum gene delivery. These results support the potential applications of this methodology in gene therapy.

The expression of many antigens, stimulatory molecules, or even metabolic pathways in mycobacteria such asMycobacterium bovisBCG orM. smegmatiswas made possible through the development of shuttle vectors, and several recombinant vaccines have been constructed. However, gene expression in any of these systems relied mostly on the selection of natural promoters expected to provide the required level of expression by trial and error. To establish a systematic selection of promoters with a range of strengths, we generated a library of mutagenized promoters through error-prone PCR of the strong PL5promoter, originally from mycobacteriophage L5. These promoters were cloned upstream of the enhanced green fluorescent protein reporter gene, and recombinantM. smegmatisbacteria exhibiting a wide range of fluorescence levels were identified. A set of promoters was selected and identified as having high (pJK-F8), intermediate (pJK-B7, pJK-E6, pJK-D6), or low (pJK-C1) promoter strengths in bothM. smegmatisandM. bovisBCG. The sequencing of the promoter region demonstrated that it was extensively modified (6 to 11%) in all of the plasmids selected. To test the functionality of the system, two different expression vectors were demonstrated to allow corresponding expression levels of theSchistosoma mansoniantigen Sm29 in BCG. The approach used here can be used to adjust expression levels for synthetic and/or systems biology studies or for vaccine development to maximize the immune response.

Single walled carbon nanotubes (SWCNT) have attracted a great interest due their extraordinary properties that envisage their use for a wide range of applications [reference physical properties]. However, these properties are controlled by the chirality of the SWC-NTs. Unfortunately, the growth processes available to-date produce SWCNTs with different chiralities. Also, the SWCNTs are produced together with a relatively high quantities of impurities such as amorphous carbon and metallic catalyst particles. Indeed, the purification and manipulation remains problematic, hindering some of the possible applications of these materials. In this paper, the purification of SWCNTs with biological polymers is presented. The results shown that DNA and UNA effectively purify SWCNT from the "soot" obtained during the growth process. The results show how effectively total genomic UNA (tgRNA) purifies SWCNT. Atomic force microscopy (AFM) studies reveal how nucleic acids wrap around SWCNTs forming RNA-CNT composites. Moreover, when a RNA-CNT solution is dried on a hydrophilic surface, SWCNTs are found lying or embedded on a self assembled two dimensional UNA network. Using tgRNA is not only a cheap and effective method of solubilising and purifying CNTs but offers a first step towards the self-assembly of CNTs from solution. Furthermore, tgRNA networks could be a convenient method of electrically linking individual RNA functionalised CNTs over a surface which could prove useful for RNA or DNA biosensors.

Systems Biology has established numerous approaches for mechanistic modelling of molecular networks in the cell and a legacy of models. The current frontier is the integration of models expressed in different formalisms to address the multi-scale biological system organisation challenge. We present MUFINS software, implementing a unique set of approaches for multiformalism simulation of interaction networks. We extend the constraint-based modelling (CBM) framework by incorporation of linear inhibition constraints, enabling for the first time linear modelling of networks simultaneously describing gene regulation, signalling and whole-cell metabolism at steady state. We present a use case where a logical hypergraph model of a regulatory network is expressed by linear constraints and integrated with a Genome Scale Metabolic Network (GSMN) of mouse macrophage. We experimentally validate predictions, demonstrating application of our software in an iterative cycle of hypothesis generation, validation and model refinement. MUFINS incorporates an extended version of our Quasi Steady State Petri Net approach to integrate dynamic models with CBM, which we demonstrate through a dynamic model of cortisol signalling integrated with the human Recon2 GSMN and a model of nutrient dynamics in physiological compartments. Finally, we implement a number of methods for deriving metabolic states from ~omics data, including our new variant of the iMAT congruency approach. We compare our approach with iMAT through analysis of 262 individual tumour transcriptomes, recovering features of metabolic reprogramming in cancer. The software provides graphics user interface with network visualisation, which facilitates use by researchers who are not experienced in coding and mathematical modelling environments.

The use of non-viral vectors as delivery systems in gene therapy has been extensively studied recently owing to their advantages over viral vectors. Here, we propose a new gene delivery system based on the use of RNA-wrapped single-walled carbon nanotubes (SWCNTs) complexed with the cationic protein, protamine and the drug chloroquine. Protamine was selected as a cationic protein acting as bridge between negatively charged RNA-wrapped SWCNTs and plasmid DNA. Protamine also contains a nuclear localization signal which enhances the expression of the transfected gene. The drug chloroquine, a lysosomotropic compound which has been reported to increase the transfection efficiency, was attached to RNA-wrapped SWNTs by ionic interactions. The simultaneous delivery of the drug chloroquine with plasmid DNA clearly showed an enhanced gene delivery and expression. The levels of gene expression were quantified using the luciferase reporter gene as model. Optimal conditions for transfection and gene expression were obtained and cytoxicity of the carbon nanotube complexes measured. The optimal complexes were shown to efficiently deliver plasmid DNA for efficient gene expression and may thereby be useful as gene delivery systems for gene therapy. Copyright © 2012 American Scientific Publishers.

Brian D. Robertson and Brendan W. Wren

An understanding of the dynamics of the metabolic profile of a bacterial cell is sought from a dynamical systems analysis of kinetic models. This modelling formalism relies on a deterministic mathematical description of enzyme kinetics and their metabolite regulation. However, it is severely impeded by the lack of available kinetic information, limiting the size of the system that can be modelled. Furthermore, the subsystem of the metabolic network whose dynamics can be modelled is faced with three problems: how to parameterize the model with mostly incomplete steady state data, how to close what is now an inherently open system, and how to account for the impact on growth. In this study we address these challenges of kinetic modelling by capitalizing on multi-‘omics’ steady state data and a genome-scale metabolic network model. We use these to generate parameters that integrate knowledge embedded in the genome-scale metabolic network model, into the most comprehensive kinetic model of the central carbon metabolism of E. coli realized to date. As an application, we performed a dynamical systems analysis of the resulting enriched model. This revealed bistability of the central carbon metabolism and thus its potential to express two distinct metabolic states. Furthermore, since our model-informing technique ensures both stable states are constrained by the same thermodynamically feasible steady state growth rate, the ensuing bistability represents a temporal coexistence of the two states, and by extension, reveals the emergence of a phenotypically heterogeneous population.

New approaches are needed to control leprosy, but understanding of the biology of the causative agent Mycobacterium leprae remains rudimentary, principally because the pathogen cannot be grown in axenic culture. Here, we applied 13C isotopomer analysis to measure carbon metabolism of M. leprae in its primary host cell, the Schwann cell. We compared the results of this analysis with those of a related pathogen, Mycobacterium tuberculosis, growing in its primary host cell, the macrophage. Using 13C isotopomer analysis with glucose as the tracer, we show that whereas M. tuberculosis imports most of its amino acids directly from the host macrophage, M. leprae utilizes host glucose pools as the carbon source to biosynthesize the majority of its amino acids. Our analysis highlights the anaplerotic enzyme phosphoenolpyruvate carboxylase required for this intracellular diet of M. leprae, identifying this enzyme as a potential antileprosy drug target.

An experimental system of Mycobacterium tuberculosis growth in a carbon-limited chemostat has been established by the use of Mycobacterium bovis BCG as a model organism. For this model, carbon-limited chemostats with low concentrations of glycerol were used to simulate possible growth rates during different stages of tuberculosis. A doubling time of 23 h (D 0.03 h 1) was adopted to represent cells during the acute phase of infection, whereas a lower dilution rate equivalent to a doubling time of 69 h (D 0.01 h 1) was used to model mycobacterial persistence. This chemostat model allowed the specific response of the mycobacterial cell to carbon limitation at different growth rates to be elucidated. The macromolecular (RNA, DNA, carbohydrate, and lipid) and elemental (C, H, and N) compositions of the biomass were determined for steady-state cultures, revealing that carbohydrates and lipids comprised more than half of the dry mass of the BCG cell, with only a quarter of the dry weight consisting of protein and RNA. Consistent with studies of other bacteria, the specific growth rate impacts on the macromolecular content of BCG and the proportions of lipid, RNA, and protein increased significantly with the growth rate. The correlation of RNA content with the growth rate indicates that ribosome production in carbon-limited M. bovis BCG cells is subject to growth rate-dependent control. The results also clearly show that the proportion of lipids in the mycobacterial cell is very sensitive to changes in the growth rate, probably reflecting changes in the amounts of storage lipids. Finally, this study demonstrates the utility of the chemostat model of mycobacterial growth for functional genomic, physiology, and systems biology studies.

Enzymes at the phosphoenolpyruvate (PEP)–pyruvate–oxaloacetate or anaplerotic (ANA) node control the metabolic flux to glycolysis, gluconeogenesis, and anaplerosis. Here we used genetic, biochemical, and 13C isotopomer analysis to characterize the role of the enzymes at the ANA node in intracellular survival of the world's most successful bacterial pathogen, Mycobacterium tuberculosis (Mtb). We show that each of the four ANA enzymes, pyruvate carboxylase (PCA), PEP carboxykinase (PCK), malic enzyme (MEZ), and pyruvate phosphate dikinase (PPDK), performs a unique and essential metabolic function during the intracellular survival of Mtb. We show that in addition to PCK, intracellular Mtb requires PPDK as an alternative gateway into gluconeogenesis. Propionate and cholesterol detoxification was also identified as an essential function of PPDK revealing an unexpected role for the ANA node in the metabolism of these physiologically important intracellular substrates and highlighting this enzyme as a tuberculosis (TB)-specific drug target. We show that anaplerotic fixation of CO2 through the ANA node is essential for intracellular survival of Mtb and that Mtb possesses three enzymes (PCA, PCK, and MEZ) capable of fulfilling this function. In addition to providing a back-up role in anaplerosis we show that MEZ also has a role in lipid biosynthesis. MEZ knockout strains have an altered cell wall and were deficient in the initial entry into macrophages. This work reveals that the ANA node is a focal point for controlling the intracellular replication of Mtb, which goes beyond canonical gluconeogenesis and represents a promising target for designing novel anti-TB drugs.

Nitrogen metabolism of Mycobacterium tuberculosis(Mtb) is crucial for the survival of this important pathogen in its primary human host cell, the macrophage, but little is known about the source(s) and their assimilation within this intracellular niche. Here, we have developed 15N-flux spectral ratio analysis(15N-FSRA) to explore Mtb’s nitrogen metabolism; we demonstrate that intracellular Mtb has access to multiple amino acids in the macrophage, including glutamate, glutamine, aspartate, alanine, glycine,and valine; and we identify glutamine as the pre-dominant nitrogen donor. Each nitrogen source is uniquely assimilated into specific amino acid pools,indicating compartmentalized metabolism during intracellular growth. We have discovered that serine is not available to intracellular Mtb, and we show that a serine auxotroph is attenuated in macrophages. This work provides a systems-based tool for exploring the nitrogen metabolism of intracellular pathogens and highlights the enzyme phosphoserine transaminase as an attractive target for the development of novel anti-tuberculosis therapies.

The use of carbon nanotubes as a gene delivery system has been extensively studied in recent years owing to its potential advantages over viral vectors. To achieve this goal, carbon nanotubes have to be functionalized to become compatible with aqueous media and to bind the genetic material. To establish the best conditions for plasmid DNA binding, we compare the dispersion properties of single-, double- and multi-walled carbon nanotubes (SWCNTs, DWCNTs and MWCNTs, respectively) functionalized with a variety of surfactants by non-covalent attachment. The DNA binding properties of the functionalized carbon nanotubes were studied and compared by electrophoresis. Furthermore, a bilayer functionalization method for DNA binding on SWCNTs was developed that utilized RNA-wrapping to solubilize the nanotubes and cationic polymers as a bridge between nanotubes and DNA.

The book starts with a general introduction into the relevance of systems biology for understanding tuberculosis.

Quantum biology is usually considered to be a new discipline, arising from recent research that suggests that biological phenomena such as photosynthesis, enzyme catalysis, avian navigation or olfaction may not only operate within the bounds of classical physics but also make use of a number of the non-trivial features of quantum mechanics, such as coherence, tunnelling and, perhaps, entanglement. However, although the most significant findings have emerged in the past two decades, the roots of quantum biology go much deeper—to the quantum pioneers of the early twentieth century. We will argue that some of the insights provided by these pioneering physicists remain relevant to our understanding of quantum biology today.

BACKGROUND: Neisseria meningitidis is an important human commensal and pathogen that causes several thousand deaths each year, mostly in young children. How the pathogen replicates and causes disease in the host is largely unknown, particularly the role of metabolism in colonization and disease. Completed genome sequences are available for several strains but our understanding of how these data relate to phenotype remains limited. RESULTS: To investigate the metabolism of N. meningitidis we generated and selected a representative Tn5 library on rich medium, a minimal defined medium and in human serum to identify genes essential for growth under these conditions. To relate these data to a systems-wide understanding of the pathogen's biology we constructed a genome-scale metabolic network: Nmb_iTM560. This model was able to distinguish essential and non-essential genes as predicted by the global mutagenesis. These essentiality data, the library and the Nmb_iTM560 model are powerful and widely applicable resources for the study of meningococcal metabolism and physiology. We demonstrate the utility of these resources by predicting and demonstrating metabolic requirements on minimal medium such as a requirement for PEP carboxylase, and by describing the nutritional and biochemical status of N. meningitidis when grown in serum, including a requirement for both the synthesis and transport of amino acids. CONCLUSIONS: This study describes the application of a genome scale transposon library combined with an experimentally validated genome-scale metabolic network of N. meningitidis to identify essential genes and provide novel insight to the pathogen's metabolism both in vitro and during infection.

Efforts to develop carbon nanotubes (CNTs) as nano-vehicles for precise and controlled drug and gene delivery, as well as markers for in vivo biomedical imaging, are currently hampered by uncertainties with regard to their cellular uptake, their fate in the body, and their safety. All of these processes are likely to be affected by the purity of CNT preparation, as well as the size and concentration of CNTs used, parameters that are often poorly controlled in biological experiments. It is demonstrated herein that under the experimental conditions of standard transfection methods, DWNTs are taken up by cultured cells but are then released after 24 h with no discernable stress response. The results support the potential therapeutic use of CNTs in many biomedical settings, such as cancer therapy.

Most healthy adults are protected from meningococcal disease by the presence of naturally acquired anti-meningococcal antibodies; however, the identity of the target antigens of this protective immunity remains unclear, particularly for protection against serogroup B disease. To identify the protein targets of natural protective immunity we developed an immunoprecipitation and proteomics approach to define the immunoproteome of the meningococcus. Sera from 10 healthy individuals showing serum bactericidal activity against both a meningococcal C strain (L91543) and the B strain MC58, together with commercially available pooled human sera were used as probe anti-sera. Immunoprecipitation was performed with each serum sample and live cells from both meningococcal strains. Immunoprecipitated proteins were identified by mass spectrometry. Analysis of the immunoproteome from each serum demonstrated both pan-reactive antigens that were recognised by most sera as well as subject-specific antigens. Most antigens were found in both meningococcal strains but a few were strain-specific. Many of the immunoprecipitated proteins have previously been characterised as surface antigens including adhesins and proteases, several of which have been recognised as vaccine candidate antigens e.g. fHBP, NadA and NHBA. The data clearly demonstrates the presence of meningococcal antibodies in healthy individuals with no history of meningococcal infection and a wide diversity of immune responses. The identification of the immuno-reactive proteins of the meningococcus provides a basis for understanding the role of each antigen in the natural immunity associated with carriage and may help to design vaccination strategies.

Cell growth experiments with a microfluidic device produce large scale time-lapse image data, which contain important information on cell growth and patterns in their genealogy. To extract such information, we propose a scheme to segment and track bacterial cells automatically. In contrast to most published approaches, which often split segmentation and tracking into two independent procedures, we focus on designing an algorithm that describes cell properties evolving between consecutive frames by feeding segmentation and tracking results from one frame to the next one. The cell boundaries are extracted by minimising the Distance Regularised Level Set Evolution model. Each individual cell was identified and tracked by identifying cell septum and membrane as well as developing a trajectory energy minimisation function along time-lapse series. Experiments show that by applying this scheme, cell growth and division can be measured automatically. The results show the efficiency of the approach when testing on different datasets while comparing with other existing algorithms. The proposed approach demonstrates great potential for large scale bacterial cell growth analysis.

Several theories of consciousness first described about a decade ago, including the conscious electromagnetic information (CEMI) field theory, claimed that the substrate of consciousness is the brain's electromagnetic (EM) field. These theories were prompted by the observation, in many diverse systems, that synchronous neuronal firing, which generates coherent EM fields, was a strong correlate of attention, awareness, and consciousness. However, when these theories were first described there was no direct evidence that synchronous firing was actually functional, rather than an epiphenomenon of brain function. Additionally, any EM field-based consciousness would be a 'ghost in the machine' unless the brain's endogenous EM field is also able to influence neuron firing. Once again, when these theories were first described, there was only indirect evidence that the brain's EM field influenced neuron firing patterns in the brain. In this paper I describe recent experimental evidence which demonstrate that synchronous neuronal firing does indeed have a functional role in the brain; and also that the brain's endogenous EM field is involved in recruiting neurons to synchronously firing networks. The new data point to a new and unappreciated form of neural communication in the brain that is likely to have significance for all theories of consciousness. I describe an extension of the CEMI field theory that incorporates these recent experimental findings and integrates the theory with the 'communication through coherence' hypothesis.

Persistence, the phenomenon whereby a small subpopulation of bacterial cells survive sterilization, prolongs antibiotic treatment and contributes to the development of genetic antimicrobial drug resistance (AMR). In this study we performed single-cell tracking of wild-type and high-persister mutant strains of Escherichia coli to identify factors that correlate with persistence. We found, as expected, persistence correlated with slow growth, but also with small birth size. We investigated intergenerational (mother–daughter) and intragenerational (sister–sister) phenotypic inheritance of growth parameters and discovered the mutant phenotype was associated with lower levels of phenotypic inheritance and identified the gene responsible, the transcription factor ydcI. Targeting pathways involved in persistence could reveal approaches to impeding persistence and the development of AMR.

Whenever a genetically homogenous population of bacterial cells is exposed to antibiotics, a tiny fraction of cells survives the treatment,the phenomenon known as bacterial persistence [G.L. Hobby et al., Exp. Biol. Med. 50, 281–285 (1942); J. Bigger, The Lancet 244, 497– 500 (1944)]. Despite its biomedical relevance, the origin of the phenomenon is still unknown, and as a rare, phenotypically resistant subpopulation, persisters are notoriously hard to study and define. Using computerized tracking we show that persisters are small at birth and slowly replicating. We also determine that the highpersister mutant strain of Escherichia coli, HipQ, is associated with the phenotype of reduced phenotypic inheritance (RPI). We identify the gene responsible for RPI, ydcI, which encodes a transcription factor, and propose a mechanism whereby loss of phenotypic inheritance causes increased frequency of persisters. These results provide insight into the generation and maintenance of phenotypic variation and provide potential targets for the development of therapeutic strategies that tackle persistence in bacterial infections.

Despite decades of research, many aspects of the biology of Mycobacterium tuberculosis remain unclear, and this is reflected in the antiquated tools available to treat and prevent tuberculosis and consequently this disease remains a serious public health problem. Important discoveries linking the metabolism of M. tuberculosis and pathogenesis has renewed interest in this area of research. Previous experimental studies were limited to the analysis of individual genes or enzymes, whereas recent advances in computational systems biology and high-throughput experimental technologies now allows metabolism to be studied on a genome scale. In the present article, we discuss the progress being made in applying system-level approaches to study the metabolism of this important pathogen.

Despite decades of research, many aspects of the biology of Mycobacterium tuberculosis remain unclear, and this is reflected in the antiquated tools available to treat and prevent tuberculosis and consequently this disease remains a serious public health problem. Important discoveries linking the metabolism of M. tuberculosis and pathogenesis has renewed interest in this area of research. Previous experimental studies were limited to the analysis of individual genes or enzymes, whereas recent advances in computational systems biology and high-throughput experimental technologies now allows metabolism to be studied on a genome scale. In the present article, we discuss the progress being made in applying system-level approaches to study the metabolism of this important pathogen.