Prevalence and patterns of higher-order interactions

Tekin, Elif; White, Cynthia; Kang, Tina Manzhu; Singh, Nina; Cruz-Loya, Mauricio; Damoiseaux, Robert; Savage, Van M.; Yeh, Pamela J.

doi:10.1101/233312

Cited by 4 publications

(7 citation statements)

References 41 publications

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“…The RBI framework has previously been used to examine drug interactions and pairwise stressor interactions by relying on Bliss Independence as the additive model to determine if there is an interaction between stressors on a population (Beppler et al 2016;Tekin et al 2016Tekin et al , 2018aTekin et al , 2020. We applied this framework to ecological studies exploring the impact of three stressors in each environment.…”

Section: Discussionmentioning

confidence: 99%

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Meta-analysis using new methods for three-stressor combinations reveal substantial higher-order interactions and emergent properties

Diamant

Boyd

Lozano‐Huntelman

et al. 2022

Preprint

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Although natural populations are typically subjected to multiple stressors, most past research has focused on single stressors and two-stressor interactions, with little attention paid to higher-order interactions among three or more stressors. However, higher-order interactions increasingly appear to be widespread. Consequently, we used a recently introduced and improved framework to re-analyze higher-order ecological interactions. We conducted a literature review of the last 100 years (1920-2020) and reanalyzed 151 ecological three-stressor interactions from 45 published papers. We found that 89% (n=134) of the three-stressor combinations resulted in new or different interactions than previously reported. We also found substantial levels of emergent properties - interactions that are only revealed when all three stressors are present. Antagonism was the most prevalent net interaction whereas synergy was the most prevalent emergent interaction. Understanding multiple stressor interactions is crucial for fundamental questions in ecology and also has implications for conservation biology and population management.

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Section: Discussionmentioning

confidence: 99%

“…Yet, there are likely more than two stressors acting on all, or almost all, wild populations. In fact, multiple stressor interactions are more frequent than previously thought, despite having received less attention (Beppler et al 2016;Tekin et al 2018a).…”

Section: Introductionmentioning

confidence: 99%

Meta-analysis using new methods for three-stressor combinations reveal substantial higher-order interactions and emergent properties

Diamant

Boyd

Lozano‐Huntelman

et al. 2022

Preprint

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“…Though conceptually different from i one another, mechanistic support is available for both the Bliss and the Loewe models 31 and there is no agreement on which model should generally be used [32][33][34][35] . Models that implement pairwise interaction data as well as higher order interactions can improve multi-drug predictions of either Bliss or Loewe 21,[36][37][38][39] . Yet, regardless of pairwise interactions, it remains unknown which of these two null models best predict the combined effect of multiple drugs.…”

Section: Main Textmentioning

confidence: 99%

The null additivity of multi-drug combinations

Russ

Kishony

2017

Preprint

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From natural ecology 1-4 to clinical therapy 5-8 , cells are often exposed to mixtures of multiple drugs. Two competing null models are used to predict the combined effect of drugs: response additivity (Bliss) and dosage additivity (Loewe) 9-11 . Here, noting that these models diverge with increased number of drugs, we contrast their predictions with measurements of Escherichia coli growth under combinations of up to 10 different antibiotics. As the number of drugs increases, Bliss maintains accuracy while Loewe systematically loses its predictive power. The total dosage required for growth inhibition, which Loewe predicts should be fixed, steadily increases with the number of drugs, following a square root scaling. This scaling is explained by an approximation to Bliss where, inspired by RA Fisher's classical geometric model 12 , dosages of independent drugs adds up as orthogonal vectors rather than linearly. This dose-orthogonality approximation provides results similar to Bliss, yet uses the dosage language as Loewe and is hence easier to implement and intuit. The rejection of dosage additivity in favor of effect additivity and dosage orthogonality provides a framework for understanding how multiple drugs and stressors add up in nature and the clinic.

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“…Interactions between the components of biological systems are critical for biological function at all levels of organization. Quantitatively understanding these interactions and mapping out their systemslevel consequences have been major aspirations in biology (Tekin et al, 2018). Historically, the study of interactions has been reductionist and largely focused on pairwise effects.…”

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confidence: 99%

“…Perhaps the closest such ''universal'' definition is an operational one, as a deviation from the prediction of a null model where only up to pairwise interactions are included. This definition is the one adopted in quantitative genetics (Weinreich et al, 2013), and it has also been recently used to characterize the function of systems of neurons, the activity of drug cocktails, the folding of proteins or the effect of microbiome composition on host life-history traits (see (Tekin et al, 2018) and references therein). Defined in this way, interactions emerge from the failure of a null model that does not include them.…”

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confidence: 99%