Evidence map›Paper›PMID 30349057›Full record

ArticleScientific reports2018

Human gut microbe co-cultures have greater potential than monocultures for food waste remediation to commodity chemicals.

Matthew A Perisin, Christian J Sund

Abstract read
In one paragraph

Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Observational
  5. Article
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

2 authors.

Matthew A PerisinUS Army Research Laboratory, RDRL-SEE-B, 2800 Powder Mill Road, Adelphi, MD, 20783, USA. matthew.a.perisin.civ@mail.mil.
Christian J SundUS Army Research Laboratory, RDRL-SEE-B, 2800 Powder Mill Road, Adelphi, MD, 20783, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Food waste represents an underutilized resource for commodity chemical generation. Constituents of the human gut microbiota that are already adapted to a food waste stream could be repurposed for useful chemical production. Industrial fermentations utilizing these microbes maintain organisms in isolation; however, microbial consortia offer an attractive alternative to monocultures in that metabolic interactions may result in more efficient processes with higher yields. Here we computationally assess the ability of co-cultures vs. monocultures to anaerobically convert a Western diet to commodity chemicals. The combination of genome-scale metabolic models with flux-balance analysis predicts that every organism analyzed can benefit from interactions with another microbe, as evidenced by increased biomass fluxes in co-culture vs. monoculture. Furthermore, microbe combinations result in emergent or increased commodity chemical production including butanol, methane, formaldehyde, propionate, hydrogen gas, and urea. These overproducing co-cultures are enriched for mutualistic and commensal interactions. Using Clostridium beijerinckii co-cultures as representative examples, models predict cross-fed metabolites will simultaneously modify multiple internal pathways, evident by different internal metabolic network structures. Differences in degree and betweenness centrality of hub precursor metabolites were correlated to C. beijerinckii metabolic outputs, and thus demonstrate the potential of co-cultures to differentially direct metabolisms to useful products.

Indexed as

GarbageGastrointestinal MicrobiomeAlcoholsBiofuelsCoculture TechniquesEnvironmental Restoration and RemediationHumansUreaAlcoholsBiofuelsUrea

Identifiers

PMID30349057
PMCPMC6197241

What OpenQuestion holds

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Registered trials

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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.