Biology subjects

De Maria, A.

Publications and source records attributed to De Maria, A..

3 recordsLinked to original sources

bioRxiv2024

Expanding the biotechnological scope of metabolic sensors through computation-aided designs

Metabolic sensors are microbial strains modified so that biomass formation correlates with the availability of specific metabolites. These sensors are essential for bioengineering (e.g. in growth-coupled designs) but creating them is often a time-consuming and low-throughput process that can potentially be streamlined by in silico analysis. Here, we present the systematic workflow of designing, implementing, and testing versatile Escherichia coli metabolic sensor strains. Glyoxylate, a key metabolite in (synthetic) CO2 fixation and carbon-conserving pathways, served as the test molecule. Through iterative screening of a compact metabolic model, we identified non-trivial growth-coupled designs that resulted in six metabolic sensors with a wide sensitivity range for glyoxylate, spanning three orders of magnitude in detected concentrations. We further adapted these E. coli strains for sensing glycolate and demonstrated their utility in both pathway engineering (testing a key metabolic module via glyoxylate) and applications in environmental monitoring (quantifying glycolate produced by photosynthetic microalgae). The versatility and ease of implementation of this workflow make it suitable for designing and building multiple metabolic sensors for diverse biotechnological applications. TeaserA streamlined workflow enables the rapid design of versatile E. coli metabolic sensors for detecting key metabolites in bioengineering and monitoring.

synthetic biology↗

bioRxiv2022

Integrated rational and evolutionary engineering of genome-reduced Pseudomonas putida strains empowers synthetic formate assimilation

AO_SCPLOWBSTRACTC_SCPLOWFormate is a promising, water-soluble C1 feedstock for biotechnology since it can be efficiently produced from CO2--but very few industrially-relevant hosts have been engineered towards formatotrophy. Here, the non-pathogenic soil bacterium Pseudomonas putida was adopted as a platform for synthetic formate assimilation. The metabolism of genome-reduced variants of P. putida was rewired to establish synthetic auxotrophies that could be functionally complemented by expressing components of the reductive glycine (rGly) pathway. The rGly pathway mediates the formate [->] glycine [->] serine transformations that yield pyruvate, ultimately assimilated into biomass. We adopted a modular engineering approach, dividing C1 assimilation in segments composed of both heterologous activities (sourced from Methylorubrum extorquens) and native reactions. Promoter engineering of chromosomally-encoded functions coupled to modular expression of rGly pathway elements enabled growth on formate as carbon source and acetate for energy supply. Adaptive laboratory evolution of two lineages of engineered P. putida formatotrophs significantly reduced doubling times to ca. 15 h. During evolution, two catabolic regimes became predominant in independently evolved clones, either via glycine hydroxymethylation (GlyA) or oxidation (ThiO). Taken together, our results expand the landscape of microbial platforms for C1-based biotechnological production towards supporting a formate bioeconomy. GO_SCPLOWRAPHICALC_SCPLOW AO_SCPLOWBSTRACTC_SCPLOW O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=63 SRC="FIGDIR/small/499488v1_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@10b12edorg.highwire.dtl.DTLVardef@7a4eaorg.highwire.dtl.DTLVardef@1dc101aorg.highwire.dtl.DTLVardef@a52d5a_HPS_FORMAT_FIGEXP M_FIG C_FIG

synthetic biology↗

bioRxiv2020

A modular framework for the development of targeted Covid-19 blood transcript profiling panels

Covid-19 morbidity and mortality are associated with a dysregulated immune response. Tools are needed to enhance existing immune profiling capabilities in affected patients. Here we aimed to develop an approach to support the design of focused blood transcriptome panels for profiling the immune response to SARS-CoV-2 infection. We designed a pool of candidates based on a pre-existing and well-characterized repertoire of blood transcriptional modules. Available Covid-19 blood transcriptome data was also used to guide this process. Further selection steps relied on expert curation. Additionally, we developed several custom web applications to support the evaluation of candidates. As a proof of principle, we designed three targeted blood transcript panels, each with a different translational connotation: therapeutic development relevance, SARS biology relevance and immunological relevance. Altogether the work presented here may contribute to the future expansion of immune profiling capabilities via targeted profiling of blood transcript abundance in Covid-19 patients.

immunology↗