Richard J. Giannone

This paper investigates how engineered Pseudomonas putida reconfigures metabolic fluxes to enhance muconate production from lignin-related aromatics.

This study uses genome shuffling in Bacillus subtilis to map quantitative trait loci for complex phenotypes, identifying high-confidence QTLs of moderate size.

This study identifies cellular stress tolerance as a key factor in genetic transformability of Candida species and develops a method to improve CRISPR screening efficiency.

This study uses longitudinal proteomics to analyze how Staphylococcus aureus reallocates resources during phage infection, revealing mechanisms of host defense and phage evasion.

This study uses experimental evolution to identify mutations that enhance catabolism of a lignin-derived aromatic dimer in Novosphingobium aromaticivorans, revealing a key enzyme involved in its degradation.

This study characterizes a novel robust Bacillus coagulans strain capable of utilizing pentose and hexose sugars, revealing proteome reallocation and metabolic strategies for biomass hydrolysate utilization.

This study identifies how Yarrowia lipolytica metabolizes hydrocarbons and DP oil, revealing proteome reallocation for growth and chemical production, but also growth inhibition due to reduced protein biosynthesis.

The paper introduces network analysis methods to identify exogenous compounds that trigger specialized metabolite production in fungi and distinguish unknown analytes.

This study demonstrates a modular design approach to selectively produce isoamyl acetate in microbes, achieving high titer, yield, and selectivity through proteome reallocation.

The paper confirms that phages in the human gut microbiome use an alternative genetic code where TAG stop codon is read as glutamine.

The paper analyzes genetic and proteomic differences between undomesticated and conventional Yarrowia lipolytica strains to understand lipid metabolism and sugar utilization in biomass hydrolysates.

The paper repurposes chloramphenicol acetyltransferases to create efficient ester biosynthesis enzymes, demonstrating high titer and conversion in microbial hosts.

This study develops a genome-scale metabolic model for Clostridium thermocellum and applies it to integrate multi-omics data and design strains for biofuel and biochemical production.