Proteomic study uncovers molecular principles of single-cell-level phenotypic heterogeneity in lipid storage of Nannochloropsis oceanica.

BACKGROUND: Nannochloropsis oceanica belongs to a large group of photoautotrophic eukaryotic organisms that play important roles in fixation and cycling of atmospheric CO2. Its capability of storing solar energy and carbon dioxide in the form of triacylglycerol (TAG) of up to 60% of total weight under nitrogen deprivation stress sparked interest in its use for biofuel production. Phenotypes varying in lipid accumulation among an N. oceanica population can be disclosed by single-cell analysis/sorting using fluorescence-activated cell sorting (FACS); yet the phenomenon of single cell heterogeneity in an algae population remains to be fully understood at the molecular level. In this study, combination of FACS and proteomics was used for identification, quantification and differentiation of these heterogeneities on the molecular level. RESULTS: For N. oceanica cultivated under nitrogen deplete (-N) and replete (+N) conditions, two groups differing in lipid content were distinguished. These differentiations could be recognized on the population as well as the single-cell levels; proteomics uncovered alterations in carbon fixation and flux, photosynthetic machinery, lipid storage and turnover in the populations. Although heterogeneity patterns have been affected by nitrogen supply and cultivation conditions of the N. oceanica populations, differentiation itself seems to be very robust against these factors: cultivation under +N, -N, in shaker bottles, and in a photo-bioreactor all split into two subpopulations. Intriguingly, population heterogeneity resumed after subpopulations were separately recultivated for a second round, refuting the possible development of genetic heterogeneity in the course of sorting and cultivation. CONCLUSIONS: This work illustrates for the first time the feasibility of combining FACS and (prote)-omics for mechanistic understanding of phenotypic heterogeneity in lipid-producing microalgae. Such combinatorial method can facilitate molecular breeding and design of bioprocesses.

Proteomics of FACS-sorted heterogeneous Corynebacterium glutamicum populations.

The metabolic status of individual cells in microbial cultures can differ, being relevant for biotechnology, environmental and medical microbiology. However, it is hardly understood in molecular detail due to limitations of current analytical tools. Here, we demonstrate that FACS in combination with proteomics can be used to sort and analyze cell populations based on their metabolic state. A previously established GFP reporter system was used to detect and sort single Corynebacterium glutamicum cells based on the concentration of branched chain amino acids (BCAA) using FACS. A proteomics workflow optimized for small cell numbers was used to quantitatively compare proteomes of a ΔaceE mutant, lacking functional pyruvate dehydrogenase (PD), and the wild type. About 800 proteins could be quantified from 1,000,000 cells. In the ΔaceE mutant BCAA production was coordinated with upregulation of the glyoxylate cycle and TCA cycle to counter the lack of acetyl CoA resulting from the deletion of aceE. BIOLOGICAL SIGNIFICANCE: Metabolic pathways in C. glutamicum WT and ΔaceE, devoid of functional pyruvate dehydrogenase, were compared to understand proteome changes that contribute to the high production of branched chain amino acids (BCAA) in the ΔaceE strain. The data complements previous metabolome studies and corroborates the role of malate provided by the glyoxylate cycle and increased activity of glycolysis and pyruvate carboxylase reaction to replenish the TCA cycle. A slight increase in acetohydroxyacid synthase (ILV subunit B) substantiates the previously reported increased pyruvate pool in C. glutamicumΔaceE, and the benefit of additional ilv gene cluster overexpression for BCAA production.

Characterization of the E. coli proteome and its modifications during growth and ethanol stress.

We set out to provide a resource to the microbiology community especially with respect to systems biology based endeavors. To this end, we generated a comprehensive dataset monitoring the changes in protein expression, copy number, and post translational modifications in a systematic fashion during growth and ethanol stress in E. coli. We utilized high-resolution mass spectrometry (MS) combined with the Super-SILAC approach. In a single experiment, we have identified over 2300 proteins, which represent approximately 88% of the estimated expressed proteome of E. coli and estimated protein copy numbers using the Intensity Based Absolute Quantitation (iBAQ). The dynamic range of protein expression spanned up to six orders of magnitude, with the highest protein copy per cell estimated at approximately 300,000. We focused on the proteome dynamics involved during stationary phase growth. A global up-regulation of proteins related to stress response was detected in later stages of growth. We observed the down-regulation of the methyl directed mismatch repair system containing MutS and MutL of E. coli growing in long term growth cultures, confirming that higher incidence of mutations presents an important mechanism in the increase in genetic diversity and stationary phase survival in E. coli. During ethanol stress, known markers such as alcohol dehydrogenase and aldehyde dehydrogenase were induced, further validating the dataset. Finally, we performed unbiased protein modification detection and revealed changes of many known and unknown protein modifications in both experimental conditions. Data are available via ProteomeXchange with identifier PXD001648.