Evidence map›Paper›PMID 30227897›Full record

ArticleMicrobiome2018

Dynamics of microbial populations mediating biogeochemical cycling in a freshwater lake.

Keith Arora-Williams, Scott W Olesen, Benjamin P Scandella, Kyle Delwiche, Sarah J Spencer, Elise M Myers, Sonali Abraham, Alyssa Sooklal, Sarah P Preheim

Open access · goldAbstract read
In one paragraph

Article in Microbiome, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
4.5field-weighted citation impact, top 5% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed, 56 citations in OpenAlex.

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  12. Metagenomic Assembly: Reconstructing Genomes from Metagenomes.Methods in molecular biology (Clifton, N.J.) · 2021
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 5 institutions in 1 country.

Keith Arora-WilliamsDepartment of Environmental Health and Engineering, Johns Hopkins University, Baltimore, MD, USA.
Scott W OlesenDepartment of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
Benjamin P ScandellaDepartment of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
Kyle DelwicheDepartment of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
Sarah J SpencerDepartment of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
Elise M MyersDepartment of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
Sonali AbrahamDepartment of Environmental Health and Engineering, Johns Hopkins University, Baltimore, MD, USA.
Alyssa SooklalDepartment of Environmental Health and Engineering, Johns Hopkins University, Baltimore, MD, USA.
Sarah P PreheimDepartment of Environmental Health and Engineering, Johns Hopkins University, Baltimore, MD, USA. sprehei1@jhu.edu.ORCID 0000-0001-7365-2382
Johns Hopkins University · USMassachusetts Institute of Technology · USHarvard University · USLamont-Doherty Earth Observatory · USOregon Department of Human Services · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMicrobial processes are intricately linked to the depletion of oxygen in in-land and coastal water bodies, with devastating economic and ecological consequences. Microorganisms deplete oxygen during biomass decomposition, degrading the habitat of many economically important aquatic animals. Microbes then turn to alternative electron acceptors, which alter nutrient cycling and generate potent greenhouse gases. As oxygen depletion is expected to worsen with altered land use and climate change, understanding how chemical and microbial dynamics impact dead zones will aid modeling efforts to guide remediation strategies. More work is needed to understand the complex interplay between microbial genes, populations, and biogeochemistry during oxygen depletion.

resultsHere, we used 16S rRNA gene surveys, shotgun metagenomic sequencing, and a previously developed biogeochemical model to identify genes and microbial populations implicated in major biogeochemical transformations in a model lake ecosystem. Shotgun metagenomic sequencing was done for one time point in Aug., 2013, and 16S rRNA gene sequencing was done for a 5-month time series (Mar.-Aug., 2013) to capture the spatiotemporal dynamics of genes and microorganisms mediating the modeled processes. Metagenomic binning analysis resulted in many metagenome-assembled genomes (MAGs) that are implicated in the modeled processes through gene content similarity to cultured organism and the presence of key genes involved in these pathways. The MAGs suggested some populations are capable of methane and sulfide oxidation coupled to nitrate reduction. Using the model, we observe that modulating these processes has a substantial impact on overall lake biogeochemistry. Additionally, 16S rRNA gene sequences from the metagenomic and amplicon libraries were linked to processes through the MAGs. We compared the dynamics of microbial populations in the water column to the model predictions. Many microbial populations involved in primary carbon oxidation had dynamics similar to the model, while those associated with secondary oxidation processes deviated substantially.

conclusionsThis work demonstrates that the unique capabilities of resident microbial populations will substantially impact the concentration and speciation of chemicals in the water column, unless other microbial processes adjust to compensate for these differences. It further highlights the importance of the biological aspects of biogeochemical processes, such as fluctuations in microbial population dynamics. Integrating gene and population dynamics into biogeochemical models has the potential to improve predictions of the community response under altered scenarios to guide remediation efforts.

Indexed as

MicrobiotaBacteriaCarbonEcosystemLakesMetagenomeMetagenomicsMethaneOxidation-ReductionOxygenCarbonMethaneOxygen16S rRNA gene sequencingBiogeochemical modelMetagenome-assembled genome

Identifiers

PMID30227897
PMCPMC6145348
OpenAlexW2890070380

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.