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Proteomics and metabolic burden analysis to understand the impact of recombinant protein production on host cells

ABSTRACT: Recombinant protein production (RPP) using Escherichia coli as an expression host is highly efficient, however, it also in¬ leads to strong host cell metabolic burden. Energy and biomass precursors are withdrawn from the host’s metabolism as they are required for plasmid replication, heterologous gene expression and protein production. In this study, we aim to investigate the effect of early and growth phase induction point on RPP. We have analysed and compared the proteomics data for growth-and protein production-phase to understand the cellular dynamics and recombinant protein-dependent product formation in process with respect to the two different hosts (M15 and DH5⍺) and medium (minimal and complex) cultures. Differential gene analysis shows that significant changes in carbohydrate metabolism, transport metabolism, nucleotide metabolism, amino acid metabolism and energy metabolism. Comprehension of the obtain results suggest that growth inhibition does not showing effect on recombinant protein and product yield but there is an changes in intracellular nucleobases, translation, transcription and cellular metabolism which leads to the degradation and instability during product formation. Overall, deeper knowledge of the cellular behaviour during recombinant protein production can be used to better exploit omics data with the goal of rational strain development.

INSTRUMENT(S): Orbitrap Fusion Lumos

ORGANISM(S): Escherichia Coli

SUBMITTER: Girish Halemirle Rajacharya

LAB HEAD: Syed Shams Yazdani

PROVIDER: PXD050495 | Pride | 2024-03-23

REPOSITORIES: Pride

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Project description:In actinomycetes, antibiotic production is often associated with a morpho-physiological differentiation program that is regulated by complex molecular and metabolic networks. Many aspects of these regulatory circuits have been already elucidated and many others still deserve further investigations. In this regard, the possible role of many small open-reading frames(smORFs) in actinomycete morpho-physiological differentiation is still elusive. In Streptomyces coelicolor, inactivation of the smORF trpM (SCO2038) - whose product modulates L-tryptophan metabolism - impairs production of antibiotics and morphological differentiation. Indeed, it was demonstrated that TrpM is able to interact with PepA (SCO2179), a putative cytosol aminopeptidase playing a key role in antibiotic production and sporulation. In this work, a S. coelicolor trpM knock-in (Sco-trpMKI) mutant strain was generated by cloning trpM into overexpressing vector to further investigate the role of trpM in actinomycete growth and morpho-physiological differentiation. Results highlighted that trpM: i) stimulates growth and actinorhodin production; ii) decreases calcium-dependent antibiotic production; iii) has no effect on undecylprodigiosin production. Metabolic pathways influenced by trpM knock-in were investigated by combining two-difference in gel electrophoresis/nanoliquid chromatography coupled to electrospray linear ion trap tandem mass spectrometry (2D-DIGE/nanoLC-ESI-LIT- MS/MS) and by LC-ESI-MS/MS procedures, respectively. These analyses demonstrated that over-expression of trpM causes an over-representation of factors involved in protein synthesis and nucleotide metabolism as well as a down-representation of proteins involved in central carbon and amino acid metabolism. At the metabolic level, this corresponded to a differential accumulation pattern of different amino acids - including aromatic ones but tryptophan – and central carbon intermediates. PepA was also down-represented in Sco-trpMKI. The latter was produced as recombinant His- tagged protein and was originally proven having the predicted aminopeptidase activity. Altogether, these results highlight the stimulatory effect of trpM in S. coelicolor growth and actinorhodin biosynthesis, which are elicited through the modulation of various metabolic pathways and PepA representation, further confirming the complexity of regulatory networks that control antibiotic production in actinomycetes.

Project description:To cause disease, Salmonella enterica serovar Typhimurium requires two type-III secretion systems, encoded on Salmonella Pathogenicity Islands 1 and 2 (SPI-1 and -2). These secretion systems serve to deliver virulence proteins, termed effectors, into the host cell cytosol. While the importance of these effector proteins to promote colonization and replication within the host has been established, the specific roles of individual secreted effectors in the disease process are not well understood. In this study, we used an in vivo gallbladder epithelial cell infection model to study the function of the SPI-2-encoded effector, SseL. Deletion of the sseL gene resulted in bacterial filamentation and elongation and unusual localization of Salmonella within infected epithelial cells. Infection with the ?sseL strain also caused dramatic changes in lipid metabolism and led to massive accumulation of lipid droplets in infected cells. Some of these changes were investigated through metabolomics of gallbladder tissue. This phenotype was directly attributed to the deubiquitinase activity of SseL, as a Salmonella strain carrying a single point mutation in the catalytic cysteine resulted in the same phenotype as the deletion mutant. Excessive buildup of lipids due to the absence of a functional sseL gene was also observed in S. Typhimurium-infected livers. These results demonstrate that SseL alters host lipid metabolism in infected epithelial cells by modifying ubiquitination patterns of cellular targets. Female C57BL/6 mice were infected with the indicated strain of Salmonella enterica serovar Typhimurium by oral gavage. Four gallbladders were collected and pooled per sample group and metabolites extracted using a mixture of methanol and chloroform. Extracts were infused into a 12-T Apex-Qe hybrid quadrupole-FT-ICR mass spectrometer equipped with an Apollo II electrospray ionization source, a quadrupole mass filter and a hexapole collision cell. Raw mass spectrometry data were processed as described elsewhere (Han et al. 2008. Metabolomics. 4:128-140). To identify differences in metabolite composition between different groups of samples, we filtered the list of masses for metabolites which were present on one set of samples but not the other. Additionally, we calculated the ratios between averaged intensities of metabolites from each group of mice. To assign possible metabolite identities, monoisotopic neutral masses of interest were queried against MassTrix (http://masstrix.org). Masses were searched against the Mus musculus database within a mass error of 3 ppm.

			Action	DRS
	AAR.FASTA	Fasta
	DH5.mzML	Mzml
	DH5.mzid.gz	Mzid
	DH5_LBC5_16_Rep1.raw	Raw
	DH5_LBC5_16_Rep2.raw	Raw

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Proteomics and metabolic burden analysis to understand the impact of recombinant protein production on host cells

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