Evidence map›Paper›PMID 34012428›Full record

ReviewFrontiers in microbiology2021

Towards a Systems Biology Approach to Understanding the Lichen Symbiosis: Opportunities and Challenges of Implementing Network Modelling.

Hadi Nazem-Bokaee, Erik F Y Hom, Andrew C Warden, Sarah Mathews, Cécile Gueidan

Abstract readReview
In one paragraph

Review in Frontiers in microbiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Frontiers in plant science · 2024
    Article
  6. The Tripartite LichenMicroorganisms · 2023
    Article
  7. Article
  8. Review
  9. Article
  10. 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

5 authors.

Hadi Nazem-BokaeeCSIRO Australian National Herbarium, Centre for Australian National Biodiversity Research, National Research Collections Australia, NCMI, Canberra, ACT, Australia.
Erik F Y HomDepartment of Biology and Center for Biodiversity and Conservation Research, The University of Mississippi, University City, MS, United States.
Andrew C WardenCSIRO Land and Water, Canberra, ACT, Australia.
Sarah MathewsDepartment of Biological Sciences, Louisiana State University, Baton Rouge, LA, United States.
Cécile GueidanCSIRO Australian National Herbarium, Centre for Australian National Biodiversity Research, National Research Collections Australia, NCMI, Canberra, ACT, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lichen associations, a classic model for successful and sustainable interactions between micro-organisms, have been studied for many years. However, there are significant gaps in our understanding about how the lichen symbiosis operates at the molecular level. This review addresses opportunities for expanding current knowledge on signalling and metabolic interplays in the lichen symbiosis using the tools and approaches of systems biology, particularly network modelling. The largely unexplored nature of symbiont recognition and metabolic interdependency in lichens could benefit from applying a holistic approach to understand underlying molecular mechanisms and processes. Together with 'omics' approaches, the application of signalling and metabolic network modelling could provide predictive means to gain insights into lichen signalling and metabolic pathways. First, we review the major signalling and recognition modalities in the lichen symbioses studied to date, and then describe how modelling signalling networks could enhance our understanding of symbiont recognition, particularly leveraging omics techniques. Next, we highlight the current state of knowledge on lichen metabolism. We also discuss metabolic network modelling as a tool to simulate flux distribution in lichen metabolic pathways and to analyse the co-dependence between symbionts. This is especially important given the growing number of lichen genomes now available and improved computational tools for reconstructing such models. We highlight the benefits and possible bottlenecks for implementing different types of network models as applied to the study of lichens.

Indexed as

lichen symbiosismetabolic modelnetwork modellingsignallingsystems biology

Identifiers

PMID34012428
PMCPMC8126723

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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.