Distinct temporal diversity profiles for nitrogen cycling genes in a hyporheic microbiome

Linking denitrification and pesticide transformation potentials with community ecology and groundwater discharge in hyporheic sediments in a lowland stream

Contamination of rivers by nitrate and pesticides poses a risk for aquatic ecosystems in lowland catchments that are often intensively used for agriculture. Here, the hyporheic zone, the streambed underneath the stream, plays a vital role due to its efficient self-purification capacity. The present study aims to evaluate the denitrification and transformation potential of 14 pesticides and three transformation products in the hyporheic sediment from a lowland stream with a high N load and by comparing an agricultural straightened section to a natural meandering part of the stream influenced by different groundwater discharges. Batch experiments were set up to evaluate the denitrification and pesticide transformation potentials in hyporheic sediment from two depths (5-15 cm (a) and 15-25 cm (b)). Our results revealed that (i) differences between the agricultural and natural sections of the river did not influence pollutant attenuation, (ii) both the nitrate and pesticide attenuation processes were more rapid in the upper "a" layer compared to the "b" layer due to higher microbial abundance, (iii) high groundwater discharge reduced the denitrification potential while pesticide transformation was unaffected, (iv) denitrification correlated with denitrifier abundance (nirK) in the "b" layer, while this correlation was not seen in the "a" layer, and (v) a microbial community with low diversity can explain limited transformation for the majority of tested pesticides. Overall, our results suggest that high groundwater discharge zones with reduced residence time in the hyporheic zone can be an important source of pesticides and nitrate to surface water.

Snekmer: a scalable pipeline for protein sequence fingerprinting based on amino acid recoding

Motivation

The vast expansion of sequence data generated from single organisms and microbiomes has precipitated the need for faster and more sensitive methods to assess evolutionary and functional relationships between proteins. Representing proteins as sets of short peptide sequences (kmers) has been used for rapid, accurate classification of proteins into functional categories; however, this approach employs an exact-match methodology and thus may be limited in terms of sensitivity and coverage. We have previously used similarity groupings, based on the chemical properties of amino acids, to form reduced character sets and recode proteins. This amino acid recoding (AAR) approach simplifies the construction of protein representations in the form of kmer vectors, which can link sequences with distant sequence similarity and provide accurate classification of problematic protein families.

Results

Here, we describe Snekmer, a software tool for recoding proteins into AAR kmer vectors and performing either (i) construction of supervised classification models trained on input protein families or (ii) clustering for de novo determination of protein families. We provide examples of the operation of the tool against a set of nitrogen cycling families originally collected using both standard hidden Markov models and a larger set of proteins from Uniprot and demonstrate that our method accurately differentiates these sequences in both operation modes.

Availability and implementation

Snekmer is written in Python using Snakemake. Code and data used in this article, along with tutorial notebooks, are available at http://github.com/PNNL-CompBio/Snekmer under an open-source BSD-3 license.

Supplementary information

Supplementary data are available at Bioinformatics Advances online.

Elevated temperatures drive abiotic and biotic degradation of organic matter in a peat bog under oxic conditions

Understanding the effects of elevated temperatures on soil organic matter (SOM) decomposition pathways in northern peatlands is central to predicting their fate under future warming. Peatlands role as carbon (C) sink is dependent on both anoxic conditions and low temperatures that limit SOM decomposition. Previous studies have shown that elevated temperatures due to climate change can disrupt peatland's C balance by enhancing SOM decomposition and increasing CO₂ emissions. However, little is known about how SOM decomposition pathways change at higher temperatures. Here, we used an integrated research approach to investigate the mechanisms behind enhanced CO₂ emissions and SOM decomposition under elevated temperatures of surface peat soil collected from a raised and Sphagnum dominated mid-continental bog (S1 bog) peatland at the Marcel Experimental Forest in Minnesota, USA, incubated under oxic conditions at three different temperatures (4, 21, and 35 °C). Our results indicated that elevated temperatures could destabilize peatland's C pool via a combination of abiotic and biotic processes. In particular, temperature-driven changes in redox conditions can lead to abiotic destabilization of Fe-organic matter (phenol) complexes, previously an underestimated decomposition pathway in peatlands, leading to increased CO₂ production and accumulation of polyphenol-like compounds that could further inhibit extracellular enzyme activities and/or fuel the microbial communities with labile compounds. Further, increased temperatures can alter strategies of microbial communities for nutrient acquisition via changes in the activities of extracellular enzymes by priming SOM decomposition, leading to enhanced CO₂ emission from peatlands. Therefore, coupled biotic and abiotic processes need to be incorporated into process-based climate models to predict the fate of SOM under elevated temperatures and to project the likely impacts of environmental change on northern peatlands and CO₂ emissions.

Contrasting Community Assembly Forces Drive Microbial Structural and Potential Functional Responses to Precipitation in an Incipient Soil System

Microbial communities in incipient soil systems serve as the only biotic force shaping landscape evolution. However, the underlying ecological forces shaping microbial community structure and function are inadequately understood. We used amplicon sequencing to determine microbial taxonomic assembly and metagenome sequencing to evaluate microbial functional assembly in incipient basaltic soil subjected to precipitation. Community composition was stratified with soil depth in the pre-precipitation samples, with surficial communities maintaining their distinct structure and diversity after precipitation, while the deeper soil samples appeared to become more uniform. The structural community assembly remained deterministic in pre- and post-precipitation periods, with homogenous selection being dominant. Metagenome analysis revealed that carbon and nitrogen functional potential was assembled stochastically. Sub-populations putatively involved in the nitrogen cycle and carbon fixation experienced counteracting assembly pressures at the deepest depths, suggesting the communities may functionally assemble to respond to short-term environmental fluctuations and impact the landscape-scale response to perturbations. We propose that contrasting assembly forces impact microbial structure and potential function in an incipient landscape; in situ landscape characteristics (here homogenous parent material) drive community structure assembly, while short-term environmental fluctuations (here precipitation) shape environmental variations that are random in the soil depth profile and drive stochastic sub-population functional dynamics.

A method for achieving complete microbial genomes and improving bins from metagenomics data

Metagenomics facilitates the study of the genetic information from uncultured microbes and complex microbial communities. Assembling complete genomes from metagenomics data is difficult because most samples have high organismal complexity and strain diversity. Some studies have attempted to extract complete bacterial, archaeal, and viral genomes and often focus on species with circular genomes so they can help confirm completeness with circularity. However, less than 100 circularized bacterial and archaeal genomes have been assembled and published from metagenomics data despite the thousands of datasets that are available. Circularized genomes are important for (1) building a reference collection as scaffolds for future assemblies, (2) providing complete gene content of a genome, (3) confirming little or no contamination of a genome, (4) studying the genomic context and synteny of genes, and (5) linking protein coding genes to ribosomal RNA genes to aid metabolic inference in 16S rRNA gene sequencing studies. We developed a semi-automated method called Jorg to help circularize small bacterial, archaeal, and viral genomes using iterative assembly, binning, and read mapping. In addition, this method exposes potential misassemblies from k-mer based assemblies. We chose species of the Candidate Phyla Radiation (CPR) to focus our initial efforts because they have small genomes and are only known to have one ribosomal RNA operon. In addition to 34 circular CPR genomes, we present one circular Margulisbacteria genome, one circular Chloroflexi genome, and two circular megaphage genomes from 19 public and published datasets. We demonstrate findings that would likely be difficult without circularizing genomes, including that ribosomal genes are likely not operonic in the majority of CPR, and that some CPR harbor diverged forms of RNase P RNA. Code and a tutorial for this method is available at https://github.com/lmlui/Jorg and is available on the DOE Systems Biology KnowledgeBase as a beta app.