Spatial segregation and aging of metabolic processes underlie phenotypic heterogeneity in mycobacteria.

Individual cells within clonal populations of mycobacteria vary in size, growth rate, and antibiotic susceptibility. Heterogeneity is, in part, determined by LamA, a protein found exclusively in mycobacteria. LamA localizes to sites of new cell wall synthesis where it recruits proteins important for polar growth and establishing asymmetry. Here, we report that in addition to this function, LamA interacts with complexes involved in oxidative phosphorylation (OXPHOS) at a subcellular location distinct from cell wall synthesis. Importantly, heterogeneity depends on a unique extension of the mycobacterial ATP synthase, and LamA mediates the coupling between ATP production and cell growth in single cells. Strikingly, as single cells age, concentrations of proteins important for oxidative phosphorylation become less abundant, and older cells rely less on oxidative phosphorylation for growth. Together, our data reveal that central metabolism is spatially organized within a single mycobacterium and varies within a genetically identical population of mycobacteria. Designing therapeutic regimens to account for this heterogeneity may help to treat mycobacterial infections faster and more completely.

An essential periplasmic protein coordinates lipid trafficking and is required for asymmetric polar growth in mycobacteria.

Mycobacteria, including the human pathogen Mycobacterium tuberculosis, grow by inserting new cell wall material at their poles. This process and that of division are asymmetric, producing a phenotypically heterogeneous population of cells that respond non-uniformly to stress (Aldridge et al., 2012; Rego et al., 2017). Surprisingly, deletion of a single gene - lamA - leads to more symmetry, and to a population of cells that is more uniformly killed by antibiotics (Rego et al., 2017). How does LamA create asymmetry? Here, using a combination of quantitative time-lapse imaging, bacterial genetics, and lipid profiling, we find that LamA recruits essential proteins involved in cell wall synthesis to one side of the cell - the old pole. One of these proteins, MSMEG_0317, here renamed PgfA, was of unknown function. We show that PgfA is a periplasmic protein that interacts with MmpL3, an essential transporter that flips mycolic acids in the form of trehalose monomycolate (TMM), across the plasma membrane. PgfA interacts with a TMM analog suggesting a direct role in TMM transport. Yet our data point to a broader function as well, as cells with altered PgfA levels have differences in the abundance of other lipids and are differentially reliant on those lipids for survival. Overexpression of PgfA, but not MmpL3, restores growth at the old poles in cells missing lamA. Together, our results suggest that PgfA is a key determinant of polar growth and cell envelope composition in mycobacteria, and that the LamA-mediated recruitment of this protein to one side of the cell is a required step in the establishment of cellular asymmetry.

Identifying feasible metabolic routes in Mycobacterium smegmatis and possible alterations under diverse nutrient conditions.

BACKGROUND: Many studies on M. tuberculosis have emerged from using M. smegmatis MC(2)155 (Msm), since they share significant similarities and yet Msm is non-pathogenic and faster growing. Although several individual molecules have been studied from Msm, many questions remain open about its metabolism as a whole and its capability to be versatile. Adaptability and versatility are emergent properties of a system, warranting a molecular systems perspective to understand them. RESULTS: We identify feasible metabolic pathways in Msm in reference condition with transcriptome, phenotypic microarray, along with functional annotation of the genome. Together with transcriptome data, specific genes from a set of alternatives have been mapped onto different pathways. About 257 metabolic pathways can be considered to be feasible in Msm. Next, we probe cellular metabolism with an array of alternative carbon and nitrogen sources and identify those that are utilized and favour growth as well as those that do not support growth. In all, about 135 points in the entire metabolic map are probed. Analyzing growth patterns under these conditions, lead us to hypothesize different pathways that can become active in various conditions and possible alternate routes that may be induced, thus explaining the observed physiological adaptations. CONCLUSIONS: The study provides the first detailed analysis of feasible pathways towards adaptability. We obtain mechanistic insights that explain observed phenotypic behaviour by studying gene-expression profiles and pathways inferred from the genome sequence. Comparison of transcriptome and phenome analysis of Msm and Mtb provides a rationale for understanding commonalities in metabolic adaptability.