Quantitative mass spectrometry reveals plasticity of metabolic networks in Mycobacterium smegmatis

Abstract

Mycobacterium tuberculosis has a remarkable ability to persist within the human host as a clinically inapparent or chronically active infection. Fatty acids are thought to be an important carbon source used by the bacteria during long term infection. Catabolism of fatty acids requires reprogramming of metabolic networks, and enzymes central to this reprogramming have been targeted for drug discovery. Mycobacterium smegmatis, a nonpathogenic relative of M. tuberculosis, is often used as a model system because of the similarity of basic cellular processes in these two species. Here, we take a quantitative proteomics-based approach to achieve a global view of how the M. smegmatis metabolic network adjusts to utilization of fatty acids as a carbon source. Two-dimensional liquid chromatography and mass spectrometry of isotopically labeled proteins identified a total of 3,067 proteins with high confidence. This number corresponds to 44% of the predicted M. smegmatis proteome and includes most of the predicted metabolic enzymes. Compared with glucose-grown cells, 162 proteins showed differential abundance in acetate- or propionate-grown cells. Among these, acetate-grown cells showed a higher abundance of proteins that could constitute a functional glycerate pathway. Gene inactivation experiments confirmed that both the glyoxylate shunt and the glycerate pathway are operational in M. smegmatis. In addition to proteins with annotated functions, we demonstrate carbon source-dependent differential abundance of proteins that have not been functionally characterized. These proteins might play as-yet-unidentified roles in mycobacterial carbon metabolism. This study reveals several novel features of carbon assimilation in M. smegmatis, which suggests significant functional plasticity of metabolic networks in this organism.

Fig. 1.

Schematic of strategy to identify differentially abundant proteins using dimethyl labeling and mass spectrometry. Bacteria were cultured on M9 minimal medium containing glucose, acetate, or propionate as the sole carbon source. In forward experiments, the labeling pattern was as depicted in the diagram. In reverse experiments, the labels on the acetate and propionate samples were swapped.

Fig. 2.

Functional classification of quantified proteins. Quantified proteins were categorized into functional categories (gray bars) according to JCVI annotations. The numbers of proteins showing differential protein abundance in acetate/glucose or propionate/glucose comparisons are indicated by black shading within the bar for each functional category. Under the hypergeometric distribution, only two functional categories (“Energy Metabolism” and “Transport and Binding proteins”, labeled with an asterisk) were significantly enriched (false discovery rate of 5%) in the subpopulation of differentially abundant proteins in comparison with the total population of quantified proteins.

Fig. 3.

Scatterplot depicting differential abundance of proteins in propionate/glucose and acetate/glucose comparisons. Each dot represents one protein. Colored protein spots have significant normalized ratios with a SignB value <0.05 in at least three out of four independent experimental repeats. Purple, higher abundance in both acetate and propionate compared with glucose. Brown, lower abundance in both acetate and propionate compared with glucose. Red, higher abundance in acetate compared with glucose. Orange, lower abundance in acetate compared with glucose. Blue, higher abundance in propionate compared with glucose. Green, lower abundance in propionate compared with glucose. Light green, lower abundance in propionate and higher abundance in acetate, both compared with glucose. For clarity, only proteins of special interest are indicated. A more precise representation of the behavior of the proteins with asterisks is provided in supplemental Table S4. The inset shows a magnification of the boxed region of the plot. Data from a single representative experiment are shown. This experiment was repeated four times with similar results.

Fig. 4.

Pathways involved in carbon source assimilation. Highlighting indicates Embden-Meyerhof-Parnas pathway and gluconeogenic pathway (orange), pentose phosphate pathway (blue), Entner-Doudoroff pathway (yellow), glycerate pathway (green), methylcitrate and methylmalonate pathways (pink), tricarboxylic acid cycle and glyoxylate shunt (gray). Enzyme accession numbers without the “MSMEG_” prefix are adjacent to arrows indicating their associated reactions. Differentially abundant proteins are in bold green type with boxes labeled as follows: G (abundance in glucose compared with both acetate and propionate); A (abundance in acetate compared with glucose); and P (abundance in propionate compared with glucose). Color coding in each box indicates higher abundance (red), lower abundance (blue), or no difference (white). Proteins that show different trends in acetate versus glucose and propionate versus glucose are indicated as “no difference” in the G boxes. Only the quantified proteins are indicated. Metabolic pathways have been drawn according to Kyoto encyclopedia of genes and genomes pathway maps.

Fig. 5.

Acetate and propionate activation pathways. Proteins showing higher abundance in either acetate or propionate compared with glucose are indicated in red type; proteins that are present at similar levels in all three carbon substrates (glucose, acetate, and propionate) are indicated in black type.

Fig. 6.

Growth of bacteria lacking malate synthase (glyoxylate shunt) or glyoxylate carboligase (glycerate pathway) on different carbon substrates. A–C, bacterial strains were wild type (WT), malate synthase-deficient (ΔglcB), glyoxylate carboligase-deficient (Δgcl), or deficient in both enzymes (ΔglcB Δgcl). The double mutant strain was complemented with a single copy attB-integrating plasmid encoding glyoxylate carboligase (ΔglcB Δgcl attB::pgcl). Bacteria were grown on M9 minimal medium containing glucose (A) or acetate (B and C) as the sole carbon source. Growth was monitored by measuring the optical densities of the cultures at 600 nm (A_{600 nm}). Symbols and error bars represent mean values and ranges (n = 2 independent experiments).