Results for “spike-ins”

DOE OSTI2023

Continuous culture of anaerobic fungi enables growth and metabolic flux tuning without use of genetic tools

Anaerobic gut fungi (AGF) have potential to valorize lignocellulosic biomass owing to their diverse repertoire of carbohydrate-active enzymes (CAZymes). However, AGF metabolism is poorly understood, and no stable genetic tools are available to manipulate growth and metabolic flux to enhance production of specific targets, e.g., cells, CAZymes, or metabolites. Herein, a cost-effective, Arduino-based, continuous-flow anaerobic bioreactor with online optical density control is presented to probe metabolism and predictably tune fluxes in Caecomyces churrovis. Varying the C. churrovis turbidostat setpoint titer reliably controlled growth rate (from 0.04 to 0.20 h −1 ), metabolic flux, and production rates of acetate, formate, lactate, and ethanol. Bioreactor setpoints to maximize production of each product were identified, and all continuous production rates significantly exceed batch rates. Formate spike-ins increased lactate flux and decreased acetate, ethanol, and formate fluxes. The bioreactor and turbidostat culture schemes demonstrated here offer tools to tailor AGF fermentations to application-specific hydrolysate product profiles.

Agriculture↗

DOE OSTI2023

A standardized quantitative analysis strategy for stable isotope probing metagenomics

ABSTRACT Stable isotope probing (SIP) facilitates culture-independent identification of active microbial populations within complex ecosystems through isotopic enrichment of nucleic acids. Many DNA-SIP studies rely on 16S rRNA gene sequences to identify active taxa, but connecting these sequences to specific bacterial genomes is often challenging. Here, we describe a standardized laboratory and analysis framework to quantify isotopic enrichment on a per-genome basis using shotgun metagenomics instead of 16S rRNA gene sequencing. To develop this framework, we explored various sample processing and analysis approaches using a designed microbiome where the identity of labeled genomes and their level of isotopic enrichment were experimentally controlled. With this ground truth dataset, we empirically assessed the accuracy of different analytical models for identifying active taxa and examined how sequencing depth impacts the detection of isotopically labeled genomes. We also demonstrate that using synthetic DNA internal standards to measure absolute genome abundances in SIP density fractions improves estimates of isotopic enrichment. In addition, our study illustrates the utility of internal standards to reveal anomalies in sample handling that could negatively impact SIP metagenomic analyses if left undetected. Finally, we present SIPmg , an R package to facilitate the estimation of absolute abundances and perform statistical analyses for identifying labeled genomes within SIP metagenomic data. This experimentally validated analysis framework strengthens the foundation of DNA-SIP metagenomics as a tool for accurately measuring the in situ activity of environmental microbial populations and assessing their genomic potential. IMPORTANCE Answering the questions, “who is eating what?” and “who is active?” within complex microbial communities is paramount for our ability to model, predict, and modulate microbiomes for improved human and planetary health. These questions can be pursued using stable isotope probing to track the incorporation of labeled compounds into cellular DNA during microbial growth. However, with traditional stable isotope methods, it is challenging to establish links between an active microorganism’s taxonomic identity and genome composition while providing quantitative estimates of the microorganism’s isotope incorporation rate. Here, we report an experimental and analytical workflow that lays the foundation for improved detection of metabolically active microorganisms and better quantitative estimates of genome-resolved isotope incorporation, which can be used to further refine ecosystem-scale models for carbon and nutrient fluxes within microbiomes.

54 ENVIRONMENTAL SCIENCES↗