Plants are better engineers: the complexity of plant organ morphogenesis

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Plant are better engineers than us. They reproducibly create new organs while we are still far from being able to engineer plant morphogenesis. It is challenging to understand plant morphogenesis due to its complexity. Complex intersecting regulatory networks often mask general principles. Cells and molecular regulators typically behave variably yet the plant uses these inputs to achieve robust outcomes. Regulatory networks often act in the non-linear range near tipping points such that small stochastic variations are used to make important developmental decisions. With the recent employment of 4D growth tracking combined with quantitative analysis of regulatory networks and computational modeling, we now have better capacity to explore and embrace the complexity of plant organ morphogenesis.

Introduction

Unlike animals, which typically complete organogenesis during embryogenesis, plants continuously and reproducibly create new organs (i.e. leaves, sepals, petals, stamens, and carpels/fruit) throughout their lifecycles. We are starting to be able to engineer the organoid, a mass of cells or tissue grown artificially that resembles an organ, from human and animal cells [1]. Prompted by Richard Feynman’s famous pronouncement, ‘What I cannot create, I do not understand’, we consider the challenges inherent in engineering plant organs.

For classical engineering:

  • (1)

    the design is based on well-understood principles and all components are well defined;

  • (2)

    the system is designed with precise, nearly fault-free components;

  • (3)

    the system operates in the linear range, so that its behavior is predictable [2].

In comparison, development violates all these tenets:

  • (1)

    it is unclear to what extent general principles exist or each organ is a special case. And regulatory components often have multiple overlapping and intersecting functions;

  • (2)

    the cellular and molecular components behave variably, and large faults in these components are tolerated to produce robust organs;

  • (3)

    the regulatory networks often act in the non-linear range and small stochastic changes in key regulators can push the system to different outcomes.

In complexity theory, emergence is the generation of de novo properties in a system that are not found within its component parts. Organs undergo emergence, arriving at a reproducible size, shape, and function that is not present or easily predictable from their cellular and molecular parts. Just think if we could incorporate this ability in our engineering—engineering emergence [2]. In this review, we emphasize quantitative and dynamic research including computational analysis and modeling which allows us to penetrate deeper into complexity and gives us insight into how organ emergence occurs.

Section snippets

The potential for general principles to exist in organ morphogenesis

“If you can’t explain something simply, you don’t understand it well.” - Albert Einstein

It remains unclear to what extent there are general principles in morphogenesis, which if present are hidden by the complexity of the systems. Here we propose that a biophysical feedback loop between mechanical stress and organ growth can be considered a general principle in plant morphogenesis [3, 4, 5]. This biophysical feedback loop was first elucidated in the Arabidopsis thaliana (hereafter Arabidopsis)

Reproducibility at larger scales emerges from variability at smaller scales

“To do a great right do a little wrong.” - William Shakespeare

Fundamentally the size and shape of an organ depend on the number, size, and shape of its constituent cells. Spatially, the anisotropy of cell growth and the orientation of the cell division plane contribute to the organ growth orientation. Temporally, the growth rate of the cells controls the organ growth rate. However, all of these cellular aspects are variable [18, 19, 20, 21] (Figure 2).

The plant promotes variability in cell

Operating in the non-linear regime, close to thresholds and critical points

“It may happen that small differences in the initial conditions produce very great ones in the final phenomena.” - Henri Poincare

Formation of patterns of specialized cell types within organs requires symmetry breaking [32], where two identical cells make different decisions to become distinct cell types. Symmetry breaking can occur because biological systems often operate in the non-linear regime where they are close to thresholds and critical points. Small changes in the concentration of key

Concluding remarks

To reach a more holistic understanding of plant morphogenesis, we need to embrace complexity: 1. Pay attention to the distributions of outcomes and the dynamics of the problem instead of just average differences between samples; 2. Pay attention to variable phenotypes as the genes promoting robustness tend to genetically interact with lots of other genes, making them the hubs of genetic networks [48]; 3. Integrate computational modeling with experiments. Computational modeling can be used for

Conflict of interest statement

Nothing declared.

References and recommended reading

Papers of particular interest, published within the period of review, have been highlighted as:

  • • of special interest

  • •• of outstanding interest

CRediT authorship contribution statement

Mingyuan Zhu: Conceptualization, Writing - original draft, Writing - review & editing. Adrienne HK Roeder: Conceptualization, Writing - review & editing.

Acknowledgements

We apologize to all whose works we could not cite due to length restrictions. We thank Arezki Boudaoud, Joseph Cammarata, Frances Clark, Olivier Hamant, Kate Harline, Josh Strable, Batthula Vijaya Lakshmi Vadde, and the reviewers for critical reading. Work in the Roeder lab is supported by NSFIOS-1553030 and Cornell University, Weill Institute startup funding.

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