Construction, comparison and evolution of networks in life sciences and other disciplines

Gysi, Deisy Morselli; Nowick, Katja

doi:10.1098/rsif.2019.0610

Cited by 19 publications

(20 citation statements)

References 393 publications

(527 reference statements)

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“…Within the genus Trichoderma , WGCNA was employed to identify the set of transcripts used by T. reesei during sugarcane bagasse breakdown [23]. Such studies demonstrate that the WGCNA methodology can clarify the molecular mechanisms that underlie biological processes and reveal how changes in gene interactions might lead to an altered phenotype [20]. By employing WGCNA in the present study, we were able to cluster transcripts functionally related to CRE1 and XYR1 and identify the hubs in the groups of interest.…”

Section: Discussionmentioning

confidence: 99%

“…Thus, the regulation of gene expression appears to have a dominant effect on the diversity of plant biomass-degradation strategies of fungi. One interesting in silico approach to exploring the regulation of lignocellulolytic enzymes is through gene coexpression networks, which have proven to be a fundamental tool for identifying simultaneously active transcripts and, consequently, inferring gene interactions in several biological contexts [20, 21].…”

Section: Introductionmentioning

confidence: 99%

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Network Analysis Reveals Different Cellulose Degradation Strategies acrossTrichoderma harzianumStrains Associated with XYR1 and CRE1

Rosolen¹,

Aono²,

Almeida³

et al. 2020

Preprint

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Background: Trichoderma species have attracted attention as alternative plant polysaccharide-degrading enzyme sources, among other reasons. Most Trichoderma spp., such as Trichoderma atroviride and Trichoderma harzianum, are described as mycoparasitic fungi and are widely used in agriculture as biocontrol agents. T. harzianum is also a potential candidate for hydrolytic enzyme production in which gene expression is tightly controlled. Thus, a better understanding of transcriptional regulation related to the main activator (XYR1) and repressor (CRE1) of cellulases and hemicellulases is necessary. Herein, we explore the genetic mechanisms of the key regulators of genes encoding plant cell wall-degrading enzymes by inferring a gene coexpression network for T. harzianum (IOC-3844 and CBMAI-0179) and, for comparative purposes, for T. atroviride CBMAI-0020.Results: Phylogenetic analysis indicated that both regulatory proteins are widely distributed among ascomycete fungi and suggested how T. atroviride is differentiated from T. harzianum. The coexpression network analyses separated the transcripts into several groups according to the expression profile during growth in cellulose or glucose.Groups with xyr1 or cre1 were identified, and within them, transcripts encoding carbohydrate-active enzymes (CAZymes), TFs, sugar and ion transporters, and proteins with unknown function were coexpressed. However, qualitative and quantitative differences among groups and strains were observed. Core transcripts from these groups (hubs) were identified, and they included transcripts not yet characterized or described as related to cellulose degradation. Several metabolic pathways triggered were recognized with high similarity between both regulators during cellulose degradation, but they differed according to the strains. An enrichment related to mycoparasitism in T. atroviride, especially that associated with CRE1, was observed. It was also noticed that the transcripts encoding CAZymes related to polysaccharide degradation in T.harzianum are not necessarily coexpressed with the TFs studied herein. Conclusion: Our results suggest that different strategies related to XYR1 and CRE1 are used by Trichoderma spp. during cellulose degradation and provide new insights into transcripts coexpressed with both TFs in T. harzianum. This knowledge can be exploited to improve the understanding of the genetic mechanisms involved in hydrolytic enzyme regulation, expanding the potential of T. harzianum use in several industrial applications. 3 Due to the expanding population and industrialization, the demand for energy is increasing throughout the world. Currently, the primary energy source is fossil fuels, i.e., nonrenewable sources such as natural gas, oil, and coal [1]. To reduce the dependency on these finite resources, the development of new sustainable alternatives has become critical. In this context, increasing attention has been given to the development of biofuels from biomass [2, 3]. The United States and Brazil are the world's largest bioet...

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Network Analysis Reveals Different Cellulose Degradation Strategies acrossTrichoderma harzianumStrains Associated with XYR1 and CRE1

Rosolen¹,

Aono²,

Almeida³

et al. 2020

Preprint

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“…Network analyses are another useful tool for deconstructing interactions among members of a complex ecosystem such as a microbiome (Berry & Widder, 2014;Gysi & Nowick, 2020). In particular, when no single organism exerts control over a community, networks of co-occurrence may better explain patterns of host-microbe assemblages.…”

Section: Introductionmentioning

confidence: 99%

Testing cophylogeny between coral reef invertebrates and their bacterial and archaeal symbionts

et al. 2021

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Marine invertebrates harbour a complex suite of bacterial and archaeal symbionts, a subset of which are probably linked to host health and homeostasis. Within a complex microbiome it can be difficult to tease apart beneficial or parasitic symbionts from nonessential commensal or transient microorganisms; however, one approach is to detect strong cophylogenetic patterns between microbial lineages and their respective hosts. We employed the Procrustean approach to cophylogeny (PACo) on 16S rRNA gene derived microbial community profiles paired with COI, 18S rRNA and ITS1 host phylogenies. Second, we undertook a network analysis to identify groups of microbes that were co-occurring within our host species. Across 12 coral, 10 octocoral and five sponge species, each host group and their core microbiota (50% prevalence within host species replicates) had a significant fit to the cophylogenetic model. Independent assessment of each microbial genus and family found that bacteria and archaea affiliated to Endozoicomonadaceae, Spirochaetaceae and Nitrosopumilaceae have the strongest cophylogenetic signals. Further, local Moran's I measure of spatial autocorrelation identified 14 ASVs, including Endozoicomonadaceae and Spirochaetaceae, whose distributions were significantly clustered by host phylogeny. Four co-occurring subnetworks were identified, each of which was dominant in a different host group.Endozoicomonadaceae and Spirochaetaceae ASVs were abundant among the subnetworks, particularly one subnetwork that was exclusively comprised of these two bacterial families and dominated the octocoral microbiota. Our results disentangle | 3769 O'BRIEN Et al.

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“…2 This paper uses network theory to address how this capacity arose. Networks allow for a comprehensive understanding of the dynamics of complex entities and their relationships [21]. Network-based approaches to characterizing the kind of cognitive structure that could sustain cultural evolution enable us to address the question of how minds carry out the contextual, combinatorial and hierarchically structured thought processes needed to generate cumulative, adaptive and open-ended cultural novelty [22,23].…”

Section: Introductionmentioning

confidence: 99%

A model of the transition to behavioural and cognitive modernity using reflexively autocatalytic networks

Gabora

Steel

2020

J. R. Soc. Interface.

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This paper proposes a model of the cognitive mechanisms underlying the transition to behavioural and cognitive modernity in the Upper Palaeolithic using autocatalytic networks. These networks have been used to model life’s origins. More recently, they have been applied to the emergence of cognitive structure capable of undergoing cultural evolution. Mental representations of knowledge and experiences play the role of catalytic molecules, the interactions among them (e.g. the forging of new associations or affordances) play the role of reactions, and thought processes are modelled as chains of these interactions. We posit that one or more genetic mutations may have allowed thought to be spontaneously tailored to the situation by modulating the degree of (i) divergence (versus convergence), (ii) abstractness (versus concreteness), and (iii) context specificity. This culminated in persistent, unified autocatalytic semantic networks that bridged previously compartmentalized knowledge and experience. We explain the model using one of the oldest-known uncontested examples of figurative art: the carving of the Hohlenstein–Stadel Löwenmensch, or lion man. The approach keeps track of where in a cultural lineage each innovation appears, and models cumulative change step by step. It paves the way for a broad scientific framework for the origins of both biological and cultural evolutionary processes.

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Construction, comparison and evolution of networks in life sciences and other disciplines

Cited by 19 publications

References 393 publications

Network Analysis Reveals Different Cellulose Degradation Strategies acrossTrichoderma harzianumStrains Associated with XYR1 and CRE1

Network Analysis Reveals Different Cellulose Degradation Strategies acrossTrichoderma harzianumStrains Associated with XYR1 and CRE1

Testing cophylogeny between coral reef invertebrates and their bacterial and archaeal symbionts

A model of the transition to behavioural and cognitive modernity using reflexively autocatalytic networks

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