bioRxiv Science⌕ Search

Biology subjects

Zemla, M.

Publications and source records attributed to Zemla, M..

2 recordsLinked to original sources

Origin of biogeographically distinct ecotypes during laboratory evolution

Resource partitioning within microbial communities is central to their incredible productivity, including over 1 gigaton of annual methane emissions through syntrophic interactions1. Here, we show how isogenic strains of a sulfate reducing bacterium (Desulfovibrio vulgaris, Dv) and a methanogen (Methanococcus maripaludis, Mm) underwent evolutionary diversification over 300-1,000 generations in a purely planktonic environmental2-4 context giving rise to coexisting ecotypes that could partition resources and improve overall stability, cooperativity, and productivity in a simulated subsurface environment. We discovered that mutations in just 15 Dv and 7 Mm genes gave rise to ecotypes within each species that were spatially enriched between sediment and planktonic phases over the course of only a few generations after transferring the evolved populations to a fluidized bed reactor (FBR). While lactate utilization by Dv in the attached community was significantly greater, the resulting H2 was partially consumed by low affinity hydrogenases in Mm within the same attached phase. The unutilized H2 was scavenged by high affinity hydrogenases in the planktonic phase Mm, generating copious amounts of methane and higher ratio of Mm to Dv. Our findings show how a handful of mutations that arise in one environmental context can drive resource partitioning by ecologically differentiated variants in another environmental context, whose interplay synergistically improves productivity of the entire mutualistic community.

microbiology↗

Biofilm Interaction Mapping and Analysis (BIMA): A tool for deconstructing interspecific interactions in co-culture biofilms

Pseudomonas species are ubiquitous in nature and include numerous medically, agriculturally and technologically beneficial strains of which the interspecific interactions are of great interest for biotechnologies. Specifically, co-cultures containing Pseudomonas stutzeri have been used for bioremediation, biocontrol, aquaculture management and wastewater denitrification. Furthermore, the use of P. stutzeri biofilms, in combination with consortia based approaches, may offer advantages for these processes. Understanding the interspecific interaction within biofilm co-cultures or consortia provides a means for improvement of current technologies. However, the investigation of biofilm based consortia has been limited. We present an adaptable and scalable method for the analysis of macroscopic interactions (colony morphology, inhibition and invasion) between colony forming bacterial strains using an automated printing method followed by analysis of the genes and metabolites involved in the interactions. Using Biofilm Interaction Mapping and Analysis (BIMA), these interactions were investigated between P. stutzeri strain RCH2, a denitrifier isolated from chromium (VI) contaminated soil, and thirteen other species of pseudomonas isolated from non-contaminated soil. The metabolites and genes associated with both active co-culture growth and inhibitory growth were investigated using mass spectrometry based metabolomics and mutant fitness profiling of a DNA-barcoded mutant library. One interaction partner, Pseudomonas fluorescens N1B4 was selected for mutant fitness profiling; with this approach four genes of importance were identified and the effects on interactions were evaluated with deletion mutants and metabolomics. IMPORTANCEThe Biofilm Interaction Mapping and Analysis (BIMA) methodology provides a way to rapidly screen for positive and negative interspecific interactions, followed by an analysis of the genes and metabolites that may be involved. Knowledge of these may offer opportunities for engineered strains with improved function in biotechnology systems. P. stutzeri, an organism with wide-spread utilization in consortia based biotechnologies, was used to demonstrate the utility of this approach. Where little is known about the factors influencing biofilm based interactions, elucidation of the genes and metabolites involved allows for better control of the system for improved function or yield.

microbiology↗