Search bioRxiv⌕ Search

bioRxiv · 10.1101/466680

Comparing DNA, RNA and protein levels for measuring microbial activity in nitrogen-amended soils

Abstract

Multi-omic techniques can offer a comprehensive overview of microbial communities at the gene, transcript and protein levels. However, to what extent these levels reflect in situ process rates is less clear, especially in highly complex habitats such as soils. Here we performed microcosm incubations using soil from a site with a history of agricultural management. Microcosms, amended with isotopically labelled ammonium and urea to simulate a fertilization event, showed nitrification (up to 4.1 {+/-} 0.87 {micro}g N-NO3- g-1 dry soil d-1) and accumulation of N2O after 192 hours of incubation. Nitrification activity (NH4+[->]NH2OH[->]NO2-[->]NO3-) was accompanied by a 6-fold increase in relative expression of the 16S rRNA gene (RNA/DNA) between 10 and 192 hours of incubation for ammonia-oxidizing bacteria (AOB) Nitrosomonas and Nitrosospira. In contrast, ammonia-oxidizing archaea (AOA) and complete ammonia oxidizer (comammox) nitrifiers showed stable gene expression during incubations but were generally more abundant (DNA level) than their Betaproteobacteria AOB counterparts. A strong relationship between nitrification activity and (mostly) betaproteobacterial ammonia monooxygenase (amoA; NH4+[->]NH2OH) and nitrite oxidoreductase (nxrA; NO2-[->]NO3-) transcript abundances revealed that mRNA levels quantitatively reflected measured activity and were generally more sensitive than the DNA level in the microcosm incubations. Although peptides related to housekeeping proteins from nitrite-oxidizing microorganisms were detected, their abundance was not significantly correlated with activity, revealing that meta-proteomics provided only a qualitative assessment of activity. Altogether, these findings underscore the strengths and limitations of multi-omic approaches for assessing complex microbial communities and provide the molecular means to assess nitrification processes in soils.\n\nIMPORTANCEEven though the use of omic approaches has expanded our knowledge of the diversity of microbial communities in natural and engineered systems, it is less clear how well the use of whole community DNA-, RNA- or protein-based approaches reflect microbial activities. To this end, we directly compared the different levels of molecular information (i.e., DNA, RNA or proteins) in order to assess which level best correlated with isotope-based measurements of nitrification activity in agricultural soils after fertilization. This work reveals the strengths as well as the associated limitations of metagenomic, metatranscriptomic, and metaproteomic approaches in serving as reliable proxies for examining microbial activities in highly diverse environments like soils.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Orellana, L. H., Hatt, J., Iyer, R., Chourey, K., Hettich, R. L., Spain, J., Yang, W. H., Chee-Sanford, J., Sanford, R. A., Löffler, F. E., Konstantinidis, K. T.. 2018-11-10. Comparing DNA, RNA and protein levels for measuring microbial activity in nitrogen-amended soils. https://doi.org/10.1101/466680

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Cell-scale confinement reorders bacterial speed rankings

Which bacterium swims fastest depends on where the race is run. Speeds are usually measured in open liquid, yet many bacteria live in pores, mucus and host passages no wider than a cell. Using a microfluidic device with eight channel widths (0.80-3.00 m) in one field of view, we tracked unlabeled cells of eight species spanning five motility systems. Chamber height, a polymer additive and channel width each reordered the ranking. Vibrio alginolyticus, the fastest in open liquid, slowed to ~4 m/s in 1.25-m channels, whereas Campylobacter jejuni and Bacillus subtilis kept 33-46 m/s. Open liquid speed did not predict robustness to confinement. In two unrelated lineages, host symbionts that pass through narrow passages during colonization, Caballeronia insecticola and Vibrio fischeri, outran their non-symbiotic relatives in the channels, and crossed them with flagella wrapped around the cell body at nearly the speed of unwrapped cells. Where space is tight, the ability to keep moving, not top speed, sets the ranking.

microbiology↗

The biochemical composition of coronavirus Nucleocapsid proteins drives the bicistronic properties of their sub-genomic mRNAs

The nucleocapsid (N) gene of coronaviruses (CoVs) encodes a structural RNA-binding protein required for viral assembly. In SARS- and MERS-CoV viruses, reading frame 2 of N contains an overlapping open reading frame (ORF) encoding an innate immune antagonist accessory protein. However, the extent of this dual coding capacity across the CoV family, and the genetic features driving overlapping ORF formation, remain unexamined. Here, we developed an in-silico tool (ORFan) to screen structural gene sub-genomic mRNA sequences from 152 species of coronavirus for the presence of overlapping accessory gene candidates. We found that frame 2 of the N gene in Alpha-, Beta- and Delta-CoVs frequently contains a potential accessory ORF (AcORF), conserved at the subgenus level, unlike the spike, envelope and membrane genes. We also show that CoV nucleotide biases in conjunction with codon biases integral to N protein function drive the relatively high abundances of start codons in frame two and stop codons in frame three, explaining the tendency towards frame 2 AcORFs. We further suggest that viral nucleotide biases and the codon composition required for RNA-binding function facilitate overlapping ORF formation in other virus families

microbiology↗

Evaluating non-oxidative glycolysis using 13C metabolic flux analysis

Non-oxidative glycolysis (NOG) converts glucose to acetyl-CoA without emitting CO2 during Escherichia coli bioproduction. Although 13C-metabolic flux analysis (13C-MFA) has the potential to evaluate NOG flux distribution in vivo, the precision of these estimates depends on the labeling patterns of glucose tracers. Because E. coli has multiple native glycolysis pathways, selecting the optimal glucose tracer is important for precise estimates. This study used simulations to evaluate the performance of 18 commercially available glucose tracers in precisely predicting NOG flux. We artificially generated flux distributions of central metabolic pathways, including three types of NOG pathways, and obtained 13C labeling patterns of amino acids metabolized from each glucose tracer. Using these data, we then calculated 95% confidence intervals (CIs) for NOG pathway fluxes. Comparing the sum of CI widths from three NOG fluxes showed that estimation with [1,3-13C]-glucose yielded the narrowest CIs. Several tracers, including [2,3-13C]glucose, were capable of determining fluxes with high precision, but [1-13C]glucose was not one of them, despite often being used for estimating glycolytic fluxes. We then experimentally evaluated [2,3-13C]- and [1-13C]glucose as tracers in E. coli strains with and without the expression of phosphoketolase, which is required for NOG pathways to function. The results suggested that [1-13C]glucose could not detect NOG fluxes, whereas [2,3-13C]glucose estimated the fluxes of all three NOG pathways with narrow CIs.

microbiology↗