Increasing cellular fitness and product yields in Pseudomonas putida through an engineered phosphoketolase shunt.

BACKGROUND: Pseudomonas putida has received increasing interest as a cell factory due to its remarkable features such as fast growth, a versatile and robust metabolism, an extensive genetic toolbox and its high tolerance to oxidative stress and toxic compounds. This interest is driven by the need to improve microbial performance to a level that enables biologically possible processes to become economically feasible, thereby fostering the transition from an oil-based economy to a more sustainable bio-based one. To this end, one of the current strategies is to maximize the product-substrate yield of an aerobic biocatalyst such as P. putida during growth on glycolytic carbon sources, such as glycerol and xylose. We demonstrate that this can be achieved by implementing the phosphoketolase shunt, through which pyruvate decarboxylation is prevented, and thus carbon loss is minimized. RESULTS: In this study, we introduced the phosphoketolase shunt in the metabolism of P. putida KT2440. To maximize the effect of this pathway, we first tested and selected a phosphoketolase (Xfpk) enzyme with high activity in P. putida. Results of the enzymatic assays revealed that the most efficient Xfpk was the one isolated from Bifidobacterium breve. Using this enzyme, we improved the P. putida growth rate on glycerol and xylose by 44 and 167%, respectively, as well as the biomass yield quantified by OD600 by 50 and 30%, respectively. Finally, we demonstrated the impact on product formation and achieved a 38.5% increase in mevalonate and a 25.9% increase in flaviolin yield from glycerol. A similar effect was observed on the mevalonate-xylose and flaviolin-xylose yields, which increased by 48.7 and 49.4%, respectively. CONCLUSIONS: Pseudomonas putida with the implemented Xfpk shunt grew faster, reached a higher final OD600nm and provided better product-substrate yields than the wild type. By reducing the pyruvate decarboxylation flux, we significantly improved the performance of this important workhorse for industrial applications. This work encompasses the first steps towards full implementation of the non-oxidative glycolysis (NOG) or the glycolysis alternative high carbon yield cycle (GATCHYC), in which a substrate is converted into products without CO2 loss These enhanced properties of P. putida will be crucial for its subsequent use in a range of industrial processes.

Phosphite synthetic auxotrophy as an effective biocontainment strategy for the industrial chassis Pseudomonas putida.

The inclusion of biosafety strategies into strain engineering pipelines is crucial for safe-by-design biobased processes. This in turn might enable a more rapid regulatory acceptance of bioengineered organisms in both industrial and environmental applications. For this reason, we equipped the industrially relevant microbial chassis Pseudomonas putida KT2440 with an effective biocontainment strategy based on a synthetic dependency on phosphite, which is generally not readily available in the environment. The produced PSAG-9 strain was first engineered to assimilate phosphite through the genome-integration of a phosphite dehydrogenase and a phosphite-specific transport complex. Subsequently, to deter the strain from growing on naturally assimilated phosphate, all native genes related to its transport were identified and deleted generating a strain unable to grow on media containing any phosphorous source other than phosphite. PSAG-9 exhibited fitness levels with phosphite similar to those of the wild type with phosphate, and low levels of escape frequency. Beyond biosafety, this strategy endowed P. putida with the capacity to be cultured under non-sterile conditions using phosphite as the sole phosphorous source with a reduced risk of contamination by other microbes, while displaying enhanced NADH regenerative capacity. These industrially beneficial features complement the metabolic advantages for which this species is known for, thereby strengthening it as a synthetic biology chassis with potential uses in industry, with suitability towards environmental release.

High-level integration of murine intestinal transcriptomics data highlights the importance of the complement system in mucosal homeostasis.

BACKGROUND: The mammalian intestine is a complex biological system that exhibits functional plasticity in its response to diverse stimuli to maintain homeostasis. To improve our understanding of this plasticity, we performed a high-level data integration of 14 whole-genome transcriptomics datasets from samples of intestinal mouse mucosa. We used the tool Centrality based Pathway Analysis (CePa), along with information from the Reactome database. RESULTS: The results show an integrated response of the mouse intestinal mucosa to challenges with agents introduced orally that were expected to perturb homeostasis. We observed that a common set of pathways respond to different stimuli, of which the most reactive was the Regulation of Complement Cascade pathway. Altered expression of the Regulation of Complement Cascade pathway was verified in mouse organoids challenged with different stimuli in vitro. CONCLUSIONS: Results of the integrated transcriptomics analysis and data driven experiment suggest an important role of epithelial production of complement and host complement defence factors in the maintenance of homeostasis.

Genotypic and phenotypic analyses of a Pseudomonas aeruginosa chronic bronchiectasis isolate reveal differences from cystic fibrosis and laboratory strains.

BACKGROUND: Pseudomonas aeruginosa is an environmentally ubiquitous Gram-negative bacterium and important opportunistic human pathogen, causing severe chronic respiratory infections in patients with underlying conditions such as cystic fibrosis (CF) or bronchiectasis. In order to identify mechanisms responsible for adaptation during bronchiectasis infections, a bronchiectasis isolate, PAHM4, was phenotypically and genotypically characterized. RESULTS: This strain displays phenotypes that have been associated with chronic respiratory infections in CF including alginate over-production, rough lipopolysaccharide, quorum-sensing deficiency, loss of motility, decreased protease secretion, and hypermutation. Hypermutation is a key adaptation of this bacterium during the course of chronic respiratory infections and analysis indicates that PAHM4 encodes a mutated mutS gene responsible for a ~1,000-fold increase in mutation rate compared to wild-type laboratory strain P. aeruginosa PAO1. Antibiotic resistance profiles and sequence data indicate that this strain acquired numerous mutations associated with increased resistance levels to ß-lactams, aminoglycosides, and fluoroquinolones when compared to PAO1. Sequencing of PAHM4 revealed a 6.38 Mbp genome, 5.9 % of which were unrecognized in previously reported P. aeruginosa genome sequences. Transcriptome analysis suggests a general down-regulation of virulence factors, while metabolism of amino acids and lipids is up-regulated when compared to PAO1 and metabolic modeling identified further potential differences between PAO1 and PAHM4. CONCLUSIONS: This work provides insights into the potential differential adaptation of this bacterium to the lung of patients with bronchiectasis compared to other clinical settings such as cystic fibrosis, findings that should aid the development of disease-appropriate treatment strategies for P. aeruginosa infections.

Dissecting the energy metabolism in Mycoplasma pneumoniae through genome-scale metabolic modeling.

Mycoplasma pneumoniae, a threatening pathogen with a minimal genome, is a model organism for bacterial systems biology for which substantial experimental information is available. With the goal of understanding the complex interactions underlying its metabolism, we analyzed and characterized the metabolic network of M. pneumoniae in great detail, integrating data from different omics analyses under a range of conditions into a constraint-based model backbone. Iterating model predictions, hypothesis generation, experimental testing, and model refinement, we accurately curated the network and quantitatively explored the energy metabolism. In contrast to other bacteria, M. pneumoniae uses most of its energy for maintenance tasks instead of growth. We show that in highly linear networks the prediction of flux distributions for different growth times allows analysis of time-dependent changes, albeit using a static model. By performing an in silico knock-out study as well as analyzing flux distributions in single and double mutant phenotypes, we demonstrated that the model accurately represents the metabolism of M. pneumoniae. The experimentally validated model provides a solid basis for understanding its metabolic regulatory mechanisms.

Reconciling in vivo and in silico key biological parameters of Pseudomonas putida KT2440 during growth on glucose under carbon-limited condition.

BACKGROUND: Genome scale metabolic reconstructions are developed to efficiently engineer biocatalysts and bioprocesses based on a rational approach. However, in most reconstructions, due to the lack of appropriate measurements, experimentally determined growth parameters are simply taken from literature including other organisms, which reduces the usefulness and suitability of these models. Pseudomonas putida KT2440 is an outstanding biocatalyst given its versatile metabolism, its ability to generate sufficient energy and turnover of NADH and NAD. To apply this strain optimally in industrial production, a previously developed genome-scale metabolic model (iJP815) was experimentally assessed and streamlined to enable accurate predictions of the outcome of metabolic engineering approaches. RESULTS: To substantially improve the accuracy of the genome scale model (iJP815), continuous bioreactor cultures on a mineral medium with glucose as a sole carbon source were carried out at different dilution rates, which covered pulling analysis of the macromolecular composition of the biomass. Besides, the maximum biomass yield (on substrate) of 0.397 gDCW · gglc-1, the maintenance coefficient of 0.037 gglc · gDCW-1 · h-1 and the maximum specific growth rate of 0.59 h-1 were determined. Only the DNA fraction increased with the specific growth rate. This resulted in reliable estimation for the Growth-Associated Maintenance (GAM) of 85 mmolATP · gDCW-1 and the Non Growth-Associated Maintenance (NGAM) of 3.96 mmolATP · gDCW-1 · h-1. Both values were found significantly different from previous assignment as a consequence of a lower yield and higher maintenance coefficient than originally assumed. Contrasting already published 13C flux measurements and the improved model allowed for constraining the solution space, by eliminating futile cycles. Furthermore, the model predictions were compared with transcriptomic data at overall good consistency, which helped to identify missing links. CONCLUSIONS: By careful interpretation of growth stoichiometry and kinetics when grown in the presence of glucose, this work reports on an accurate genome scale metabolic model of Pseudomonas putida, providing a solid basis for its use in designing superior strains for biocatalysis. By consideration of substrate specific variation in stoichiometry and kinetics, it can be extended to other substrates and new mutants.

A genetic toolkit and gene switches to limit Mycoplasma growth for biosafety applications.

Mycoplasmas have exceptionally streamlined genomes and are strongly adapted to their many hosts, which provide them with essential nutrients. Owing to their relative genomic simplicity, Mycoplasmas have been used to develop chassis for biotechnological applications. However, the dearth of robust and precise toolkits for genomic manipulation and tight regulation has hindered any substantial advance. Herein we describe the construction of a robust genetic toolkit for M. pneumoniae, and its successful deployment to engineer synthetic gene switches that control and limit Mycoplasma growth, for biosafety containment applications. We found these synthetic gene circuits to be stable and robust in the long-term, in the context of a minimal cell. With this work, we lay a foundation to develop viable and robust biosafety systems to exploit a synthetic Mycoplasma chassis for live attenuated vectors for therapeutic applications.

Absence of IFN-beta impairs antigen presentation capacity of splenic dendritic cells via down-regulation of heat shock protein 70.

Type I IFNs play a key role in linking the innate and adaptive arms of the immune system. Although produced rapidly in response to pathogens, IFNs are also produced at low levels in the absence of infection. In the present study, we demonstrate that constitutively produced IFNs are necessary in vivo to maintain dendritic cells in an "Ag presentation-competent" state. Conventional dendritic cells (cDCs) isolated from spleens of IFN-beta or IFNAR-deficient mice exhibit a highly impaired ability to present Ag and activate naive T cells. Microarray analysis of mRNA isolated from IFN-beta(-/-) and IFNAR(-/-) cDCs revealed diminished expression of two genes that encoded members of the heat shock protein 70 (Hsp70) family. Consistent with this observation, pharmacological inhibition of Hsp70 in cDCs from wild-type mice impaired their T cell stimulatory capacity. Similarly, the Ag presentation ability of splenic cDCs isolated from Hsp70.1/3(-/-) mice was also severely impaired in comparison to wild-type cDCs. Thus, constitutive IFN-beta expression regulates Hsp70 levels to help maintain dendritic cells in a competent state for efficient priming of effector T cells in vivo.

3DM: systematic analysis of heterogeneous superfamily data to discover protein functionalities.

Ten years of experience with molecular class-specific information systems (MCSIS) such as with the hand-curated G protein-coupled receptor database (GPCRDB) or the semiautomatically generated nuclear receptor database has made clear that a wide variety of questions can be answered when protein-related data from many different origins can be flexibly combined. MCSISes revolve around a multiple sequence alignment (MSA) that includes "all" available sequences from the entire superfamily, and it has been shown at many occasions that the quality of these alignments is the most crucial aspect of the MCSIS approach. We describe here a system called 3DM that can automatically build an entire MCSIS. 3DM bases the MSA on a multiple structure alignment, which implies that the availability of a large number of superfamily members with a known three-dimensional structure is a requirement for 3DM to succeed well. Thirteen MCSISes were constructed and placed on the Internet for examination. These systems have been instrumental in a large series of research projects related to enzyme activity or the understanding and engineering of specificity, protein stability engineering, DNA-diagnostics, drug design, and so forth.

Consortia modulation of the stress response: proteomic analysis of single strain versus mixed culture.

The high complexity of naturally occurring microbial communities is the major drawback limiting the study of these important biological systems. In this study, a comparison between pure cultures of Pseudomonas reinekei sp. strain MT1 and stable community cultures composed of MT1 plus the addition of Achromobacter xylosoxidans strain MT3 (in a steady-state proportion 9:1) was used as a model system to study bacterial interactions that take place under simultaneous chemical and oxidative stress. Both are members of a real community isolated from a polluted sediment by enrichment in 4-chlorosalicylate (4CS). The analysis of dynamic states was carried out at the proteome, metabolic profile and population dynamic level. Differential protein expression was evaluated under exposure to 4CS and high concentrations of toxic intermediates (4-chlorocatechol and protoanemonin), including proteins from several functional groups and particularly enzymes of aromatic degradation pathways and outer membrane proteins. Remarkably, 4CS addition generated a strong oxidative stress response in pure strain MT1 culture led by alkyl hydroperoxide reductase, while the community showed an enhanced central metabolism response, where A. xylosoxidans MT3 helped to prevent toxic intermediate accumulation. A significant change in the outer membrane composition of P. reinekei MT1 was observed during the chemical stress caused by 4CS and in the presence of A. xylosoxidans MT3, highlighting the expression of the major outer membrane protein OprF, tightly correlated to 4CC concentration profile and its potential detoxification role.

The regulatory logic of m-xylene biodegradation by Pseudomonas putida mt-2 exposed by dynamic modelling of the principal node Ps/Pr of the TOL plasmid.

The structure of the extant transcriptional control network of the TOL plasmid pWW0 born by Pseudomonas putida mt-2 for biodegradation of m-xylene is far more complex than one would consider necessary from a mere engineering point of view. In order to penetrate the underlying logic of such a network, which controls a major environmental cleanup bioprocess, we have developed a dynamic model of the key regulatory node formed by the Ps/Pr promoters of pWW0, where the clustering of control elements is maximal. The model layout was validated with batch cultures estimating parameter values and its predictive capability was confirmed with independent sets of experimental data. The model revealed how regulatory outputs originated in the divergent and overlapping Ps/Pr segment, which expresses the transcription factors XylS and XylR respectively, are computed into distinct instructions to the upper and lower catabolic xyl operons for either simultaneous or stepwise consumption of m-xylene and/or succinate. In this respect, the model reveals that the architecture of the Ps/Pr is poised to discriminate the abundance of alternative and competing C sources, in particular m-xylene versus succinate. The proposed framework provides a first systemic understanding of the causality and connectivity of the regulatory elements that shape this exemplary regulatory network, facilitating the use of model analysis towards genetic circuit optimization.

Bacterial consortium proteomics under 4-chlorosalicylate carbon-limiting conditions.

In this study, the stable consortium composed by Pseudomonas reinekei strain MT1 and Achromobacter xylosoxidans strain MT3 (cell numbers in proportion 9:1) was under investigation to reveal bacterial interactions that take place under severe nutrient-limiting conditions. The analysis of steady states in continuous cultures was carried out at the proteome, metabolic profile, and population dynamic levels. Carbon-limiting studies showed a higher metabolic versatility in the community through upregulation of parallel catabolic enzymes (salicylate 5-hydroxylase and 17-fold on 2-keto-4-pentenoate hydratase) indicating a possible alternative carbon routing in the upper degradation pathway highlighting the effect of minor proportions of strain MT3 over the major consortia component strain MT1 with a significant change in the expression levels of the enzymes of the mainly induced biodegradation pathway such as salicylate 1-hydroxylase and catechol 1,2-dioxygenase together with important changes in the outer membrane composition of P. reinekei MT1 under different culture conditions. The study has demonstrated the importance of the outer membrane as a sensing/response protective barrier caused by interspecies interactions highlighting the role of the major outer membrane proteins OprF and porin D in P. reinekei sp. MT1 under the culture conditions tested.

The missing link: Bordetella petrii is endowed with both the metabolic versatility of environmental bacteria and virulence traits of pathogenic Bordetellae.

BACKGROUND: Bordetella petrii is the only environmental species hitherto found among the otherwise host-restricted and pathogenic members of the genus Bordetella. Phylogenetically, it connects the pathogenic Bordetellae and environmental bacteria of the genera Achromobacter and Alcaligenes, which are opportunistic pathogens. B. petrii strains have been isolated from very different environmental niches, including river sediment, polluted soil, marine sponges and a grass root. Recently, clinical isolates associated with bone degenerative disease or cystic fibrosis have also been described. RESULTS: In this manuscript we present the results of the analysis of the completely annotated genome sequence of the B. petrii strain DSMZ12804. B. petrii has a mosaic genome of 5,287,950 bp harboring numerous mobile genetic elements, including seven large genomic islands. Four of them are highly related to the clc element of Pseudomonas knackmussii B13, which encodes genes involved in the degradation of aromatics. Though being an environmental isolate, the sequenced B. petrii strain also encodes proteins related to virulence factors of the pathogenic Bordetellae, including the filamentous hemagglutinin, which is a major colonization factor of B. pertussis, and the master virulence regulator BvgAS. However, it lacks all known toxins of the pathogenic Bordetellae. CONCLUSION: The genomic analysis suggests that B. petrii represents an evolutionary link between free-living environmental bacteria and the host-restricted obligate pathogenic Bordetellae. Its remarkable metabolic versatility may enable B. petrii to thrive in very different ecological niches.

Recommended strategies for spectral processing and post-processing of 1D 1H-NMR data of biofluids with a particular focus on urine.

1H NMR spectra from urine can yield information-rich data sets that offer important insights into many biological and biochemical phenomena. However, the quality and utility of these insights can be profoundly affected by how the NMR spectra are processed and interpreted. For instance, if the NMR spectra are incorrectly referenced or inconsistently aligned, the identification of many compounds will be incorrect. If the NMR spectra are mis-phased or if the baseline correction is flawed, the estimated concentrations of many compounds will be systematically biased. Furthermore, because NMR permits the measurement of concentrations spanning up to five orders of magnitude, several problems can arise with data analysis. For instance, signals originating from the most abundant metabolites may prove to be the least biologically relevant while signals arising from the least abundant metabolites may prove to be the most important but hardest to accurately and precisely measure. As a result, a number of data processing techniques such as scaling, transformation and normalization are often required to address these issues. Therefore, proper processing of NMR data is a critical step to correctly extract useful information in any NMR-based metabolomic study. In this review we highlight the significance, advantages and disadvantages of different NMR spectral processing steps that are common to most NMR-based metabolomic studies of urine. These include: chemical shift referencing, phase and baseline correction, spectral alignment, spectral binning, scaling and normalization. We also provide a set of recommendations for best practices regarding spectral and data processing for NMR-based metabolomic studies of biofluids, with a particular focus on urine.

Genome sequence of two members of the chloroaromatic-degrading MT community: Pseudomonas reinekei MT1 and Achromobacter xylosoxidans MT3.

We describe the genome sequence of Pseudomonas reinekei MT1 and Achromobacter xylosoxidans MT3, the most abundant members of a bacterial community capable of degrading chloroaromatic compounds. The MT1 genome contains open reading frames encoding enzymes responsible for the catabolism of chlorosalicylate, methylsalicylate, chlorophenols, phenol, benzoate, p-coumarate, phenylalanine, and phenylacetate. On the other hand, the MT3 strain genome possesses no ORFs to metabolize chlorosalicylates; instead the bacterium is capable of metabolizing nitro-phenolic and phenolic compounds, which can be used as the only carbon and energy source by MT3. We also confirmed that MT3 displays the genetic machinery for the metabolism of chlorocathecols and chloromuconates, where the latter are toxic compounds secreted by MT1 when degrading chlorosalicylates. Altogether, this work will advance our fundamental understanding of bacterial interactions.

Uracil content of 16S rRNA of thermophilic and psychrophilic prokaryotes correlates inversely with their optimal growth temperatures.

We report here the finding of a highly significant inverse correlation of the uracil content of 16S rRNA and the optimum growth temperature (T(opt)) of cultured thermophilic and psychrophilic prokaryotes. This correlation was significantly different from the weaker correlations between the contents of other nucleotides and T(opt). Analysis of the 16S rRNA secondary structure regions revealed a fall in the A:U base-pair content in step with the increase in T(opt) that was much steeper than that of mismatched base-pairs, which are thermodynamically less stable. These findings indicate that the 16S rRNA sequences of thermophiles and psychrophiles are under a strong thermo-adaptive pressure, and that structure-function constraints play a crucial role in determining their 16S rRNA nucleotide composition. The derived relationship between uracil content and T(opt) was used to develop an algorithm to predict the T(opt) values of uncultured prokaryotes lacking cultured close relatives and belonging to the phyla predominantly containing thermophiles. This algorithm may be useful in guiding the design of cultivation conditions for hitherto uncultured microbes.

Characterizing the optimal flux space of genome-scale metabolic reconstructions through modified latin-hypercube sampling.

Genome-Scale Metabolic Reconstructions (GSMRs), along with optimization-based methods, predominantly Flux Balance Analysis (FBA) and its derivatives, are widely applied for assessing and predicting the behavior of metabolic networks upon perturbation, thereby enabling identification of potential novel drug targets and biotechnologically relevant pathways. The abundance of alternate flux profiles has led to the evolution of methods to explore the complete solution space aiming to increase the accuracy of predictions. Herein we present a novel, generic algorithm to characterize the entire flux space of GSMR upon application of FBA, leading to the optimal value of the objective (the optimal flux space). Our method employs Modified Latin-Hypercube Sampling (LHS) to effectively border the optimal space, followed by Principal Component Analysis (PCA) to identify and explain the major sources of variability within it. The approach was validated with the elementary mode analysis of a smaller network of Saccharomyces cerevisiae and applied to the GSMR of Pseudomonas aeruginosa PAO1 (iMO1086). It is shown to surpass the commonly used Monte Carlo Sampling (MCS) in providing a more uniform coverage for a much larger network in less number of samples. Results show that although many fluxes are identified as variable upon fixing the objective value, majority of the variability can be reduced to several main patterns arising from a few alternative pathways. In iMO1086, initial variability of 211 reactions could almost entirely be explained by 7 alternative pathway groups. These findings imply that the possibilities to reroute greater portions of flux may be limited within metabolic networks of bacteria. Furthermore, the optimal flux space is subject to change with environmental conditions. Our method may be a useful device to validate the predictions made by FBA-based tools, by describing the optimal flux space associated with these predictions, thus to improve them.

Comparison of 432 Pseudomonas strains through integration of genomic, functional, metabolic and expression data.

Pseudomonas is a highly versatile genus containing species that can be harmful to humans and plants while others are widely used for bioengineering and bioremediation. We analysed 432 sequenced Pseudomonas strains by integrating results from a large scale functional comparison using protein domains with data from six metabolic models, nearly a thousand transcriptome measurements and four large scale transposon mutagenesis experiments. Through heterogeneous data integration we linked gene essentiality, persistence and expression variability. The pan-genome of Pseudomonas is closed indicating a limited role of horizontal gene transfer in the evolutionary history of this genus. A large fraction of essential genes are highly persistent, still non essential genes represent a considerable fraction of the core-genome. Our results emphasize the power of integrating large scale comparative functional genomics with heterogeneous data for exploring bacterial diversity and versatility.

Harnessing the power of microbial autotrophy.

Autotrophic microorganisms convert CO2 into biomass by deriving energy from light or inorganic electron donors. These CO2-fixing microorganisms have a large, but so far only partially realized, potential for the sustainable production of chemicals and biofuels. Productivities have been improved in autotrophic hosts through the introduction of production pathways and the modification of autotrophic systems by genetic engineering. In addition, approaches are emerging in which CO2 fixation pathways and energy-harvesting systems are transplanted into heterotrophic model microorganisms. Alternative promising concepts are hybrid production systems of autotrophs and heterotrophs, and bio-inorganic hybrids of autotrophic microorganisms with electrocatalysts or light-harvesting semiconductor materials. In this Review, we discuss recent advances and bottlenecks for engineering microbial autotrophy and explore novel strategies that will pave the way towards improved microbial autotrophic production platforms.

Delineating the effect of host environmental signals on a fully virulent strain of Bacillus anthracis using an integrated transcriptomics and proteomics approach.

Pathogenic bacteria sense the host environment and regulate expression of virulence-related genes. Environmental signals like temperature, bicarbonate/CO2 and glucose induce toxin production in Bacillus anthracis, but the mechanisms by which these signals contribute to virulence and overall physiological adaptation remains elusive. An integrated, systems level investigation using transcriptomics and iTRAQ-based proteomics was done to assess the effect of temperature, bicarbonate/CO2 and glucose on B. anthracis. Significant changes observed in amino acid, carbohydrate, energy and nucleotide metabolism indicates events of metabolic readjustments by environmental factors. Directed induction of genes involved in polyamine biosynthesis and iron metabolism revealed the redirection of cellular metabolite pool towards iron uptake. Protein levels of glycolytic enzymes, ptsH and Ldh along with transcripts involved in immune evasion (mprF, bNOS, Phospholipases and asnA), cell surface remodeling (rfbABCD, antABCD, and cls) and utilization of lactate (lutABC) and inositol showed constant repression under environmental perturbations. Discrepancies observed in mRNA/protein level of genes involved in glycolysis, protein synthesis, stress response and nucleotide metabolism hinted at the existence of additional regulatory layers and illustrated the utility of an integrated approach. The above findings might assist in the identification of novel adaptive strategies of B. anthracis during host associated survival and pathogenesis. BIOLOGICAL SIGNIFICANCE: In this study, the changes observed at both transcript and protein level were quantified and integrated to understand the effect of host environmental factors (host temperature, bicarbonate and glucose) in shaping the physiology and adaptive strategies of a fully virulent strain of B. anthracis for efficient survival and virulence in its host. Perturbations affecting toxin production were found to concordantly affect vital metabolic pathways and several known as well as novel virulence factors. These changes act as a valuable asset for generating testable hypotheses that can be further verified by detailed molecular and mutant studies to identify novel adaptive strategies of B. anthracis during infection. Adaptation of an integrated transcriptomics and proteomics approach also led to the identification of discrepancies between mRNA/protein levels among genes across major functional categories. Few of these discrepancies have been previously reported in literature for model organisms. However their existence in B. anthracis and that too as a result of growth perturbations have not been reported till date. These findings demonstrate a substantial role of regulatory processes post mRNA synthesis via post transcriptional, translational or protein degradation mechanisms. This article is part of a Special Issue entitled: Proteomics of non-model organisms.