Importance of host cell arginine uptake in Francisella phagosomal escape and ribosomal protein amounts

Pathogenicity and virulence of Francisella tularensis

Tularaemia is a zoonotic disease caused by the Gram-negative bacterium, Francisella tularensis. Depending on its entry route into the organism, F. tularensis causes different diseases, ranging from life-threatening pneumonia to less severe ulceroglandular tularaemia. Various strains with different geographical distributions exhibit different levels of virulence. F. tularensis is an intracellular bacterium that replicates primarily in the cytosol of the phagocytes. The main virulence attribute of F. tularensis is the type 6 secretion system (T6SS) and its effectors that promote escape from the phagosome. In addition, F. tularensis has evolved a peculiar envelope that allows it to escape detection by the immune system. In this review, we cover tularaemia, different Francisella strains, and their pathogenicity. We particularly emphasize the intracellular life cycle, associated virulence factors, and metabolic adaptations. Finally, we present how F. tularensis largely escapes immune detection to be one of the most infectious and lethal bacterial pathogens.

promor: a comprehensive R package for label-free proteomics data analysis and predictive modeling

Summary

We present promor, a comprehensive, user-friendly R package that streamlines label-free quantification proteomics data analysis and building machine learning-based predictive models with top protein candidates.

Availability and implementation

promor is freely available as an open source R package on the Comprehensive R Archive Network (CRAN) (https://CRAN.R-project.org/package=promor) and distributed under the Lesser General Public License (version 2.1 or later). Development version of promor is maintained on GitHub (https://github.com/caranathunge/promor) and additional documentation and tutorials are provided on the package website (https://caranathunge.github.io/promor/).

Supplementary information

Supplementary data are available at Bioinformatics Advances online.

The pentose phosphate pathway constitutes a major metabolic hub in pathogenic Francisella

Metabolic pathways are now considered as intrinsic virulence attributes of pathogenic bacteria and thus represent potential targets for antibacterial strategies. Here we focused on the role of the pentose phosphate pathway (PPP) and its connections with other metabolic pathways in the pathophysiology of Francisella novicida. The involvement of the PPP in the intracellular life cycle of Francisella was first demonstrated by studying PPP inactivating mutants. Indeed, we observed that inactivation of the tktA, rpiA or rpe genes severely impaired intramacrophage multiplication during the first 24 hours. However, time-lapse video microscopy demonstrated that rpiA and rpe mutants were able to resume late intracellular multiplication. To better understand the links between PPP and other metabolic networks in the bacterium, we also performed an extensive proteo-metabolomic analysis of these mutants. We show that the PPP constitutes a major bacterial metabolic hub with multiple connections to glycolysis, the tricarboxylic acid cycle and other pathways, such as fatty acid degradation and sulfur metabolism. Altogether our study highlights how PPP plays a key role in the pathogenesis and growth of Francisella in its intracellular niche.

A study of innate immune kinetics reveals a role for a chloride transporter in a virulent Francisella tularensis type B strain

Tularemia is a zoonotic disease of global proportions. Francisella tularensis subspecies tularensis (type A) and holarctica (type B) cause disease in healthy humans, with type A infections resulting in higher mortality. Repeated passage of a type B strain in the mid-20th century generated the Live Vaccine Strain (LVS). LVS remains unlicensed, does not protect against high inhalational doses of type A, and its exact mechanisms of attenuation are poorly understood. Recent data suggest that live attenuated vaccines derived from type B may cross-protect against type A. However, there is a dearth of knowledge regarding virulent type B pathogenesis and its capacity to stimulate the host's innate immune response. We therefore sought to increase our understanding of virulent type B in vitro characteristics using strain OR96-0246 as a model. Adding to our knowledge of innate immune kinetics in macrophages following infection with virulent type B, we observed robust replication of strain OR96-0246 in murine and human macrophages, reduced expression of pro-inflammatory cytokine genes from "wild type" type B-infected macrophages compared to LVS, and delayed macrophage cell death suggesting that virulent type B may suppress macrophage activation. One disruption in LVS is in the gene encoding the chloride transporter ClcA. We investigated the role of ClcA in macrophage infection and observed a replication delay in a clcA mutant. Here, we propose its role in acid tolerance. A greater understanding of LVS attenuation may reveal new mechanisms of pathogenesis and inform strategies toward the development of an improved vaccine against tularemia.

Tail-Robust Quantile Normalization

High-throughput biological data-such as mass spectrometry (MS)-based proteomics data-suffer from systematic non-biological variance due to systematic errors. This hinders the estimation of "real" biological signals and, in turn, decreases the power of statistical tests and biases the identification of differentially expressed proteins. To remove such unintended variation, while retaining the biological signal of interest, analysis workflows for quantitative MS data typically comprise normalization prior to their statistical analysis. Several normalization methods, such as quantile normalization (QN), have originally been developed for microarray data. In contrast to microarray data proteomics data may contain features, in the form of protein intensities that are consistently high across experimental conditions and, hence, are encountered in the tails of the protein intensity distribution. If QN is applied in the presence of such proteins statistical inferences of the features' intensity profiles are impeded due to the biased estimation of their variance. A freely available, novel approach is introduced which serves as an improvement of the classical QN by preserving the biological signals of features in the tails of the intensity distribution and by accounting for sample-dependent missing values (MVs): The "tail-robust quantile normalization" (TRQN).

Robust Summarization and Inference in Proteome-wide Label-free Quantification

Label-Free Quantitative mass spectrometry based workflows for differential expression (DE) analysis of proteins impose important challenges on the data analysis because of peptide-specific effects and context dependent missingness of peptide intensities. Peptide-based workflows, like MSqRob, test for DE directly from peptide intensities and outperform summarization methods which first aggregate MS1 peptide intensities to protein intensities before DE analysis. However, these methods are computationally expensive, often hard to understand for the non-specialized end-user, and do not provide protein summaries, which are important for visualization or downstream processing. In this work, we therefore evaluate state-of-the-art summarization strategies using a benchmark spike-in dataset and discuss why and when these fail compared with the state-of-the-art peptide based model, MSqRob. Based on this evaluation, we propose a novel summarization strategy, MSqRobSum, which estimates MSqRob's model parameters in a two-stage procedure circumventing the drawbacks of peptide-based workflows. MSqRobSum maintains MSqRob's superior performance, while providing useful protein expression summaries for plotting and downstream analysis. Summarizing peptide to protein intensities considerably reduces the computational complexity, the memory footprint and the model complexity, and makes it easier to disseminate DE inferred on protein summaries. Moreover, MSqRobSum provides a highly modular analysis framework, which provides researchers with full flexibility to develop data analysis workflows tailored toward their specific applications.

Tn-Seq reveals hidden complexity in the utilization of host-derived glutathione in Francisella tularensis

Host-derived glutathione (GSH) is an essential source of cysteine for the intracellular pathogen Francisella tularensis. In a comprehensive transposon insertion sequencing screen, we identified several F. tularensis genes that play central and previously unappreciated roles in the utilization of GSH during the growth of the bacterium in macrophages. We show that one of these, a gene we named dptA, encodes a proton-dependent oligopeptide transporter that enables growth of the organism on the dipeptide Cys-Gly, a key breakdown product of GSH generated by the enzyme γ-glutamyltranspeptidase (GGT). Although GGT was thought to be the principal enzyme involved in GSH breakdown in F. tularensis, our screen identified a second enzyme, referred to as ChaC, that is also involved in the utilization of exogenous GSH. However, unlike GGT and DptA, we show that the importance of ChaC in supporting intramacrophage growth extends beyond cysteine acquisition. Taken together, our findings provide a compendium of F. tularensis genes required for intracellular growth and identify new players in the metabolism of GSH that could be attractive targets for therapeutic intervention.

Myo-Inositol as a carbon substrate in Francisella and insights into the metabolism of Francisella sp. strain W12-1067

Recently, a new environmental Francisella strain, Francisella sp. strain W12-1067, has been identified in Germany. This strain is negative for the Francisella pathogenicity island (FPI) but exhibits a putative alternative type VI secretion system. Some known virulence factors of Francisella are present, but the pathogenic capacity of this species is not known yet. In silico genome analysis reveals the presence of a gene cluster tentatively enabling myo-inositol (MI) utilization via a putative inositol oxygenase. Labelling experiments starting from ²H-inositol demonstrate that this gene cluster is indeed involved in the metabolism of MI. We further show that, under in vitro conditions, supply of MI increases growth rates of strain W12-1067 in the absence of glucose and that the metabolism of MI is strongly reduced in a W12-1067 mutant lacking the MI gene cluster. The positive growth effect of MI in the absence of glucose is restored in this mutant strain by introducing the complete MI gene cluster. F. novicida Fx1 is also positive for the MI metabolizing gene cluster and MI again increases growth in a glucose-free medium, in contrast to F. novicida strain U112, which is shown to be a natural mutant of the MI metabolizing gene cluster. Labelling experiments of Francisella sp. strain W12-1067 in medium T containing ¹³C-glucose, ¹³C-serine or ¹³C-glycerol as tracers suggest a bipartite metabolism where glucose is mainly metabolized through glycolysis, but not through the Entner-Doudoroff pathway or the pentose phosphate pathway. Carbon flux from ¹³C-glycerol and ¹³C-serine is less active, and label from these tracers is transferred mostly into amino acids, lactate and fatty acids. Together, the metabolism of Francisella sp. strain W12-1067 seems to be more related to the respective one in F. novicida rather than in F. tularensis subsp. holarctica.

Brucella abortus Depends on l-Serine Biosynthesis for Intracellular Proliferation

l-Serine is a nonessential amino acid and a key intermediate in several relevant metabolic pathways. In bacteria, the major source of l-serine is the phosphorylated pathway, which comprises three enzymes: d-3-phosphoglycerate dehydrogenase (PGDH; SerA), phosphoserine amino transferase (PSAT; SerC), and l-phosphoserine phosphatase (PSP; SerB). The Brucella abortus genome encodes two PGDHs (SerA-1 and SerA-2), involved in the first step in l-serine biosynthesis, and one PSAT and one PSP, responsible for the second and third steps, respectively. In this study, we demonstrate that the serA1 serA2 double mutant and the serC and serB single mutants are auxotrophic for l-serine. These auxotrophic mutants can be internalized but are unable to replicate in HeLa cells and in J774A.1 macrophage-like cells. Replication defects of auxotrophic mutants can be reverted by cell medium supplementation with l-serine at early times postinfection. In addition, the serB mutant is attenuated in the murine intraperitoneal infection model and has an altered lipid composition, since the lack of l-serine abrogates phosphatidylethanolamine synthesis in this strain. Taken together, these results reveal that limited availability of l-serine within the host cell impairs proliferation of the auxotrophic strains, highlighting the relevance of this biosynthetic pathway in Brucella pathogenicity.

Critical Role of a Sheath Phosphorylation Site On the Assembly and Function of an Atypical Type VI Secretion System

The bacterial pathogen Francisella tularensis possesses a noncanonical type VI secretion system (T6SS) that is required for phagosomal escape in infected macrophages. KCl stimulation has been previously used to trigger assembly and secretion of the T6SS in culture. By differential proteomics, we found here that the amounts of the T6SS proteins remained unchanged upon KCl stimulation, suggesting involvement of post-translational modifications in T6SS assembly. A phosphoproteomic analysis indeed identified a unique phosphorylation site on IglB, a key component of the T6SS sheath. Substitutions of Y139 with alanine or phosphomimetics prevented T6SS formation and abolished phagosomal escape whereas substitution with phenylalanine delayed but did not abolish phagosomal escape in J774-1 macrophages. Altogether our data demonstrated that the Y139 site of IglB plays a critical role in T6SS biogenesis, suggesting that sheath phosphorylation could participate to T6SS dynamics.Data are available via ProteomeXchange with identifier PXD013619; and on MS-Viewer, key lkaqkllxwx.

MS-EmpiRe Utilizes Peptide-level Noise Distributions for Ultra-sensitive Detection of Differentially Expressed Proteins

Mass spectrometry based proteomics is the method of choice for quantifying genome-wide differential changes of protein expression in a wide range of biological and biomedical applications. Protein expression changes need to be reliably derived from many measured peptide intensities and their corresponding peptide fold changes. These peptide fold changes vary considerably for a given protein. Numerous instrumental setups aim to reduce this variability, whereas current computational methods only implicitly account for this problem. We introduce a new method, MS-EmpiRe, which explicitly accounts for the noise underlying peptide fold changes. We derive data set-specific, intensity-dependent empirical error fold change distributions, which are used for individual weighing of peptide fold changes to detect differentially expressed proteins (DEPs).In a recently published proteome-wide benchmarking data set, MS-EmpiRe doubles the number of correctly identified DEPs at an estimated FDR cutoff compared with state-of-the-art tools. We additionally confirm the superior performance of MS-EmpiRe on simulated data. MS-EmpiRe requires only peptide intensities mapped to proteins and, thus, can be applied to any common quantitative proteomics setup. We apply our method to diverse MS data sets and observe consistent increases in sensitivity with more than 1000 additional significant proteins in deep data sets, including a clinical study over multiple patients. At the same time, we observe that even the proteins classified as most insignificant by other methods but significant by MS-EmpiRe show very clear regulation on the peptide intensity level. MS-EmpiRe provides rapid processing (< 2 min for 6 LC-MS/MS runs (3 h gradients)) and is publicly available under github.com/zimmerlab/MS-EmpiRe with a manual including examples.

Screen for fitness and virulence factors of Francisella sp. strain W12-1067 using amoebae

Francisella tularensis is the causative agent of the human disease referred to as tularemia. Other Francisella species are known but less is understood about their virulence factors. The role of environmental amoebae in the life-cycle of Francisella is still under discussion. Francisella sp. strain W12-1067 (F-W12) is an environmental Francisella isolate recently identified in Germany which is negative for the Francisella pathogenicity island, but exhibits a putative alternative type VI secretion system. Putative virulence factors have been identified in silico in the genome of F-W12. In this work, we established a "scatter screen", used earlier for pathogenic Legionella, to verify experimentally and identify candidate fitness factors using a transposon mutant bank of F-W12 and Acanthamoeba lenticulata as host organism. In these experiments, we identified 79 scatter clones (amoeba sensitive), which were further analyzed by an infection assay identifying 9 known virulence factors, but also candidate fitness factors of F-W12 not yet described as fitness factors in Francisella. The majority of the identified genes encoded proteins involved in the synthesis or maintenance of the cell envelope (LPS, outer membrane, capsule) or in the metabolism (glycolysis, gluconeogenesis, pentose phosphate pathway). Further ¹³C-flux analysis of the Tn5 glucokinase mutant strain revealed that the identified gene indeed encodes the sole active glucokinase in F-W12. In conclusion, candidate fitness factors of the new Francisella species F-W12 were identified using the scatter screen method which might also be usable for other Francisella species.

Innate Immune Recognition: An Issue More Complex Than Expected

Primary interaction of an intracellular bacterium with its host cell is initiated by activation of multiple signaling pathways in response to bacterium recognition itself or as cellular responses to stress induced by the bacterium. The leading molecules in these processes are cell surface membrane receptors as well as cytosolic pattern recognition receptors recognizing pathogen-associated molecular patterns or damage-associated molecular patterns induced by the invading bacterium. In this review, we demonstrate possible sequences of events leading to recognition of Francisella tularensis, present findings on known mechanisms for manipulating cell responses to protect Francisella from being killed, and discuss newly published data from the perspective of early stages of host-pathogen interaction.

Metabolic adaptation of intracellular bacteria and fungi to macrophages

The mature phagosome of macrophages is a hostile environment for the vast majority of phagocytosed microbes. In addition to active destruction of the engulfed microbes by antimicrobial compounds, restriction of essential nutrients in the phagosomal compartment contributes to microbial growth inhibition and killing. However, some pathogenic microorganisms have not only developed various strategies to efficiently withstand or counteract antimicrobial activities, but also to acquire nutrients within macrophages for intracellular replication. Successful intracellular pathogens are able to utilize host-derived amino acids, carbohydrates and lipids as well as trace metals and vitamins during intracellular growth. This requires sophisticated strategies such as phagosome modification or escape, efficient nutrient transporters and metabolic adaptation. In this review, we discuss the metabolic adaptation of facultative intracellular bacteria and fungi to the intracellular lifestyle inside macrophages.

Differential Substrate Usage and Metabolic Fluxes in Francisella tularensis Subspecies holarctica and Francisella novicida

Francisella tularensis is an intracellular pathogen for many animals causing the infectious disease, tularemia. Whereas F. tularensis subsp. holarctica is highly pathogenic for humans, F. novicida is almost avirulent for humans, but virulent for mice. In order to compare metabolic fluxes between these strains, we performed ¹³C-labeling experiments with F. tularensis subsp. holarctica wild type (beaver isolate), F. tularensis subsp. holarctica strain LVS, or F. novicida strain U112 in complex media containing either [U-¹³C₆]glucose, [1,2-¹³C₂]glucose, [U-¹³C₃]serine, or [U-¹³C₃]glycerol. GC/MS-based isotopolog profiling of amino acids, polysaccharide-derived glucose, free fructose, amino sugars derived from the cell wall, fatty acids, 3-hydroxybutyrate, lactate, succinate and malate revealed uptake and metabolic usage of all tracers under the experimental conditions with glucose being the major carbon source for all strains under study. The labeling patterns of the F. tularensis subsp. holarctica wild type were highly similar to those of the LVS strain, but showed remarkable differences to the labeling profiles of the metabolites from the F. novicida strain. Glucose was directly used for polysaccharide and cell wall biosynthesis with higher rates in F. tularensis subsp. holarctica or metabolized, with higher rates in F. novicida, via glycolysis and the non-oxidative pentose phosphate pathway (PPP). Catabolic turnover of glucose via gluconeogenesis was also observed. In all strains, Ala was mainly synthesized from pyruvate, although no pathway from pyruvate to Ala is annotated in the genomes of F. tularensis and F. novicida. Glycerol efficiently served as a gluconeogenetic substrate in F. novicida, but only less in the F. tularensis subsp. holarctica strains. In any of the studied strains, serine did not serve as a major substrate and was not significantly used for gluconeogenesis under the experimental conditions. Rather, it was only utilized, at low rates, in downstream metabolic processes, e.g., via acetyl-CoA in the citrate cycle and for fatty acid biosynthesis, especially in the F. tularensis subsp. holarctica strains. In summary, the data reflect differential metabolite fluxes in F. tularensis subsp. holarctica and F. novicida suggesting that the different utilization of substrates could be related to host specificity and virulence of Francisella.

Experimental design and data-analysis in label-free quantitative LC/MS proteomics: A tutorial with MSqRob

Label-free shotgun proteomics is routinely used to assess proteomes. However, extracting relevant information from the massive amounts of generated data remains difficult. This tutorial provides a strong foundation on analysis of quantitative proteomics data. We provide key statistical concepts that help researchers to design proteomics experiments and we showcase how to analyze quantitative proteomics data using our recent free and open-source R package MSqRob, which was developed to implement the peptide-level robust ridge regression method for relative protein quantification described by Goeminne et al. MSqRob can handle virtually any experimental proteomics design and outputs proteins ordered by statistical significance. Moreover, its graphical user interface and interactive diagnostic plots provide easy inspection and also detection of anomalies in the data and flaws in the data analysis, allowing deeper assessment of the validity of results and a critical review of the experimental design. Our tutorial discusses interactive preprocessing, data analysis and visualization of label-free MS-based quantitative proteomics experiments with simple and more complex designs. We provide well-documented scripts to run analyses in bash mode on GitHub, enabling the integration of MSqRob in automated pipelines on cluster environments (https://github.com/statOmics/MSqRob).

SIGNIFICANCE

The concepts outlined in this tutorial aid in designing better experiments and analyzing the resulting data more appropriately. The two case studies using the MSqRob graphical user interface will contribute to a wider adaptation of advanced peptide-based models, resulting in higher quality data analysis workflows and more reproducible results in the proteomics community. We also provide well-documented scripts for experienced users that aim at automating MSqRob on cluster environments.

Importance of Metabolic Adaptations in Francisella Pathogenesis

Francisella tularensis is a highly infectious Gram-negative bacterium and the causative agent of the zoonotic disease tularemia. This bacterial pathogen can infect a broad variety of animal species and can be transmitted to humans in numerous ways with various clinical outcomes. Although, Francisella possesses the capacity to infect numerous mammalian cell types, the macrophage constitutes the main intracellular niche, used for in vivo bacterial dissemination. To survive and multiply within infected macrophages, Francisella must imperatively escape from the phagosomal compartment. In the cytosol, the bacterium needs to control the host innate immune response and adapt its metabolism to this nutrient-restricted niche. Our laboratory has shown that intracellular Francisella mainly relied on host amino acid as major gluconeogenic substrates and provided evidence that the host metabolism was also modified upon Francisella infection. We will review here our current understanding of how Francisella copes with the available nutrient sources provided by the host cell during the course of infection.

Transcriptional Profiling of Coxiella burnetii Reveals Extensive Cell Wall Remodeling in the Small Cell Variant Developmental Form

A hallmark of Coxiella burnetii, the bacterial cause of human Q fever, is a biphasic developmental cycle that generates biologically, ultrastructurally, and compositionally distinct large cell variant (LCV) and small cell variant (SCV) forms. LCVs are replicating, exponential phase forms while SCVs are non-replicating, stationary phase forms. The SCV has several properties, such as a condensed nucleoid and an unusual cell envelope, suspected of conferring enhanced environmental stability. To identify genetic determinants of the LCV to SCV transition, we profiled the C. burnetii transcriptome at 3 (early LCV), 5 (late LCV), 7 (intermediate forms), 14 (early SCV), and 21 days (late SCV) post-infection of Vero epithelial cells. Relative to early LCV, genes downregulated in the SCV were primarily involved in intermediary metabolism. Upregulated SCV genes included those involved in oxidative stress responses, arginine acquisition, and cell wall remodeling. A striking transcriptional signature of the SCV was induction (>7-fold) of five genes encoding predicted L,D transpeptidases that catalyze nonclassical 3-3 peptide cross-links in peptidoglycan (PG), a modification that can influence several biological traits in bacteria. Accordingly, of cross-links identified, muropeptide analysis showed PG of SCV with 46% 3-3 cross-links as opposed to 16% 3-3 cross-links for LCV. Moreover, electron microscopy revealed SCV with an unusually dense cell wall/outer membrane complex as compared to LCV with its clearly distinguishable periplasm and inner and outer membranes. Collectively, these results indicate the SCV produces a unique transcriptome with a major component directed towards remodeling a PG layer that likely contributes to Coxiella's environmental resistance.

Peptide-level Robust Ridge Regression Improves Estimation, Sensitivity, and Specificity in Data-dependent Quantitative Label-free Shotgun Proteomics

Peptide intensities from mass spectra are increasingly used for relative quantitation of proteins in complex samples. However, numerous issues inherent to the mass spectrometry workflow turn quantitative proteomic data analysis into a crucial challenge. We and others have shown that modeling at the peptide level outperforms classical summarization-based approaches, which typically also discard a lot of proteins at the data preprocessing step. Peptide-based linear regression models, however, still suffer from unbalanced datasets due to missing peptide intensities, outlying peptide intensities and overfitting. Here, we further improve upon peptide-based models by three modular extensions: ridge regression, improved variance estimation by borrowing information across proteins with empirical Bayes and M-estimation with Huber weights. We illustrate our method on the CPTAC spike-in study and on a study comparing wild-type and ArgP knock-out Francisella tularensis proteomes. We show that the fold change estimates of our robust approach are more precise and more accurate than those from state-of-the-art summarization-based methods and peptide-based regression models, which leads to an improved sensitivity and specificity. We also demonstrate that ionization competition effects come already into play at very low spike-in concentrations and confirm that analyses with peptide-based regression methods on peptide intensity values aggregated by charge state and modification status (e.g. MaxQuant's peptides.txt file) are slightly superior to analyses on raw peptide intensity values (e.g. MaxQuant's evidence.txt file).

Gluconeogenesis, an essential metabolic pathway for pathogenic Francisella

Intracellular multiplication and dissemination of the infectious bacterial pathogen Francisella tularensis implies the utilization of multiple host-derived nutrients. Here, we demonstrate that gluconeogenesis constitutes an essential metabolic pathway in Francisella pathogenesis. Indeed, inactivation of gene glpX, encoding the unique fructose 1,6-bisphosphatase of Francisella, severely impaired bacterial intracellular multiplication when cells were supplemented by gluconeogenic substrates such as glycerol or pyruvate. The ΔglpX mutant also showed a severe virulence defect in the mouse model, confirming the importance of this pathway during the in vivo life cycle of the pathogen. Isotopic profiling revealed the major role of the Embden-Meyerhof (glycolysis) pathway in glucose catabolism in Francisella and confirmed the importance of glpX in gluconeogenesis. Altogether, the data presented suggest that gluconeogenesis allows Francisella to cope with the limiting glucose availability it encounters during its infectious cycle by relying on host amino acids. Hence, targeting the gluconeogenic pathway might constitute an interesting therapeutic approach against this pathogen.