Dataset Information

Investigating proteome constraints of Lactococcus lactis grown in a nutrient-rich environment

ABSTRACT: Proteomics comparison of wild type Lactococcus lactis MG1363 with a mutant strain that has a point mutation in the global carbon catabolite repression regulator (CcpA) grown under glucose-limited chemostat conditions at D = 0.5 /h.

INSTRUMENT(S): LTQ Orbitrap

ORGANISM(S): Lactococcus Lactis Subsp. Cremoris Mg1363

SUBMITTER: Sjef Boeren

LAB HEAD: Sjef Boeren

PROVIDER: PXD021956 | Pride | 2021-03-01

REPOSITORIES: Pride

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Publications

Proteome constraints reveal targets for improving microbial fitness in nutrient-rich environments.

Chen Yu Y van Pelt-KleinJan Eunice E van Olst Berdien B Douwenga Sieze S Boeren Sjef S Bachmann Herwig H Molenaar Douwe D Nielsen Jens J Teusink Bas B

Molecular systems biology 20210401 4

Cells adapt to different conditions via gene expression that tunes metabolism for maximal fitness. Constraints on cellular proteome may limit such expression strategies and introduce trade-offs. Resource allocation under proteome constraints has explained regulatory strategies in bacteria. It is unclear, however, to what extent these constraints can predict evolutionary changes, especially for microorganisms that evolved under nutrient-rich conditions, i.e., multiple available nitrogen sources, ...[more]

PMID: 33821549

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Project description:Amino acid assimilation and metabolism are crucial for bacterial growth and survival and this is particularly obvious for lactic acid bacteria (LAB) that are generally auxotroph for various amino acids. However, amino acid assimilation is poorly characterized and a complete description of the response during amino acid starvation is still lacking in LAB. In this context, the global response of the LAB model Lactococcus lactis was characterized during isoleucine starvation in batch culture. The stress was imposed by isoleucine natural consumption in an initially rich chemically defined medium. Dynamic analyses were performed both using transcriptomic and proteomic approaches. The response was found to occur gradually and could be divided into three major parts that were firstly deduced from transcriptomic analysis and generally corroborated by proteomic results: (i) a global repression of biogenic processes (transcription, translation, and carbon metabolism and transport), (ii) a specific response related to the limiting nutrient (numerous pathways belonging to carbon or nitrogen metabolism and leading to isoleucine supply were activated) and (iii) an additional response connected to oxidative stress (induction of aerobic metabolism, electron transport, thioredoxin metabolism and pyruvate dehydrogenase). The involvement of various regulatory mechanisms such as growth rate regulation, stringent response, CodY, GlnR, and CcpA regulations, was discussed on the basis of transcriptomic data comparisons. Above the full description of L. lactis isoleucine starvation response, this work additionally provided a complex but realistic outlook of the regulation network involved in isoleucine starvation. Such integrated and comparative approach will allow, by its implementation to other regulations and environmental conditions, the whole regulatory network of L. lactis or any other microorganism to be deciphered. Batch cultivation of Lactococcus lactis IL1403 were carried out on a chemically defined medium and under controlled conditions (30 °C, pH 6.6, nitrogen atmosphere). Cell samples were harvested at steady state. Total RNA was extracted from these samples and radiolabelled cDNA were prepared and hybridized on nylon arrays. 1948 amplicons specific of Lactococcus lactis IL1403 genes were spotted twice on the array. Samples corresponding to various growth rates were analyzed simultaneously and 3 independent repetitions were performed.

Project description:Background Array-based comparative genome hybridization (aCGH) is commonly used to determine the genomic content of bacterial strains. In aCGH data, systematic errors are comparable to those occurring in transcriptome data. However, especially for microbes, an additional source of variation exists: differences in hybridization due to gene sequence divergence between the strains hybridized. Current normalization methods do not take this source of variation into consideration. Results We present Supervised Lowess, or S-Lowess, an application of the subset Lowess normalization method that does take difference in genomic content into account. The performance of S-Lowess was assessed on aCGH experiments in which differentially labeled genomic DNA fragments of Lactococcus lactis IL1403 and L. lactis MG1363 strains were hybridized to IL1403 microarrays. Since both genome sequences are known (they have only on average 85 % sequence identity), the success rate in detecting deletions in the MG1363 genome of different aCGH normalization methods can be compared. S-Lowess detects 97% of the deletions, whereas other aCGH normalization methods detect up to only 60% of the deletions. Conclusions S-Lowess removes systematic errors from dual-dye aCGH data in two steps: (i) determination of likely homologous genes (LHG); and (ii) estimation of correction factors for systematic errors from spots of LHG and subset Lowess normalization of the remaining spots using these correction factors. It is implemented in a user-friendly web-tool accessible from http://bioinformatics.biol.rug.nl/websoftware/s-lowess. We demonstrate that it outperforms existing normalization methods and maximizes the number of detectable genomic deletions or duplications from microbial aCGH data. Keywords: comparative genome hybridisation In this study, 4 aCGH comparisons (slides) between L. lactis MG1363 and L. lactis IL1403 were performed (including dye swap with biological replicates; see also supplementary materials). The resulting aCGH slide signals were normalized using the different 'likely homologous gene' (LHG) sets (see above) yielding ratios of signals of labelled DNA of MG1363 over those of IL1403. A maximum of 8 ratios per amplicon (gene) were obtained for the 4 hybridized slides (each with 2 replicate spots per amplicon). Only genes with at least 5 measurements were used in this study. The normalization methods evaluated in this study are: a) no normalization, b) total signal normalization, c) grid-based Lowess (implemented in PreP; f = 0.7) [GarcM-CM--a de la Nava, J et al. 2003. Bioinformatics 19:2328-2329], and d) S-Lowess using different subsets of conserved lactococcal genes (for details see above). Results with the MANOR R package (spatial normalization; standard parameters) [Neuvial P, et al. 2006. BMC Bioinformatics 7:264; Liva S, et al. 2006. Nucleic Acids Res 34:W477-W481] are shown in our supplementary materials.

Dataset Information

Investigating proteome constraints of Lactococcus lactis grown in a nutrient-rich environment

Publications

Proteome constraints reveal targets for improving microbial fitness in nutrient-rich environments.

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