
Concerted regulation of all hyphal tips generates fungal fruit body structures: experiments with computer visualisations produced by a new mathematical model of hyphal growth
Audrius Meškauskas, Liam J. McNulty and David Moore
School of Biological Sciences, Stopford Building, The University of Manchester, Oxford Road, Manchester M13 9PT, United Kingdom
Abstract: Filamentous hyphal growth is inherently suited to kinetic analysis, and in many respects the fungal mycelium can be viewed as a very mechanical biological system, which lends itself to mathematical modelling. The mathematics of hyphal tip extension growth are well established. However, even though a hyphal growth equation can be written with confidence, and we have a good understanding of the effects of tropisms on growth, it is not easy to form a mental picture of the behaviour of large populations of hyphal tips. What is required, and what we believe we have produced, is a mathematical model that is sufficiently sophisticated to produce a realistic visualisation of fungal hyphal growth. This provides us with a cyberfungus that can be used for experimentation on the theoretical rules that might govern hyphal patterning, hyphal interactions, and tissue formation and organ development by actually visualising the virtual hyphal growth patterns that result from different regulatory scenarios. From a series of model experiments the most significant observation is that complex fungal fruit body shapes can be simulated by applying the same regulatory functions to all of the growth points active in a structure at any specific time. No global control of fruit body geometry is necessary. No localised regulation is necessary. The shape of the fruit body emerges from the concerted response of the entire population of hyphal tips, in the same way, to the same signals.
Original reference:
Meškauskas, A., McNulty, L. J. & Moore, D. (2004). Concerted regulation of all hyphal tips generates fungal fruit body structures: experiments with computer visualisations produced by a new mathematical model of hyphal growth. Mycological Research 108, 341-353.
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Simulating colonial growth of fungi with the Neighbour-Sensing model of hyphal growth
Audrius Meškauskas, Mark D. Fricker1 and David Moore
School of Biological Sciences, Stopford Building, The University of Manchester, Oxford Road, Manchester M13 9PT, UK. and 1Department of Plant Sciences, University of Oxford, South Parks Road, Oxford OX1 3RB, UK.
Abstract: The Neighbour-Sensing model brings together the basic essentials of hyphal growth kinetics into a vector-based mathematical model in which the growth vector of each virtual hyphal tip is calculated by reference to the surrounding virtual mycelium. The model predicts the growth pattern of many hyphae into three spatial dimensions and has been used to simulate complex fungal fruit body shapes. In this paper we show how the Neighbour-Sensing model can simulate growth in semi-solid substrata like agar or soil, enabling realistic simulation of mycelial colonies of filamentous fungi grown in ‘Petri-dish style’ experimental conditions. Newly implemented capabilities in the model include: a measurement and logging system within the program that maintains basic statistics about the mycelium it is simulating, this facilitates kinetic experimentation; inclusion of ‘substrates’ in the data space causing positive or negative tropisms for the growing mycelium; a horizontal plane tropism that provides a way of simulating colonies growing in or on a substratum like agar or soil by imposing a horizontal geometrical constraint on the data space the cyberhyphal tips can explore; three categories of hypha - standard hyphae are those that start the simulation, leading hyphae can emerge from the colony peripheral growth zone to take on a leading role, and secondary hyphae are branches that can arise late, far behind the peripheral growth zone, when mature hyphal segments resume branching to in-fill the older parts of the colony. We show how the model can be used to investigate hyphal growth kinetics in silico in experimental scenarios that would be difficult or impossible in vivo. We also show that the Neighbour-Sensing model can generate sufficiently realistic cord-like structures to encourage the belief that this model is now sufficiently advanced for parameters to be defined that simulate specific in silico cyberfungi. The potential utility of these cyberspecies is that they provide a means to model the morphogenetic effects of a variety of factors, from environmental and nutritional features to mutations, in experimentally realistic situations, offering a valuable addition to the experimental toolkit of all those interested in fungal growth and morphology.
Original reference:
Meškauskas, A., Fricker, M. D. & Moore, D. (2004). Simulating colonial growth of fungi with the Neighbour-Sensing model of hyphal growth. Mycological Research 108, 1241-1256.
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Branching in fungal hyphae and fungal tissues: growing mycelia in a desktop computer
David Moore, Liam J. McNulty and Audrius Meškauskas*
School of Biological Sciences, Stopford Building, The University of Manchester, Oxford Road, Manchester M13 9PT, United Kingdom, and *Gediminas Technical University, Saulėtekio al. 11, LT-2040 Vilnius, Lithuania
Abstract: In mycelial fungi the formation of hyphal branches is the only way in which the number of growing points can be increased. Cross walls always form at right angles to the long axis of a hypha, and nuclear division is not necessarily linked to cell division. Consequently, no matter how many nuclear divisions occur and no matter how many cross walls are formed there will be no increase in the number of hyphal tips unless a branch arises. Evidently, for the fungi, hyphal branch formation is the equivalent of cell division in animals, plants and protists. The position of origin of a branch, and its direction and rate of growth are the crucial formative events in the development of fungal tissues and organs. Kinetic analyses have shown that fungal filamentous growth can be interpreted on the basis of a regular cell cycle, and encourage the view that a mathematical description of fungal growth might be generalised into predictive simulations of tissue formation. An important point to emphasise is that all kinetic analyses published to date deal exclusively with physical influences on growth and branching kinetics (like temperature, nutrients, etc.). In this chapter we extrapolate from the kinetics so derived to deduce how the biological control events might affect the growth vector of the hyphal apex to produce the patterns of growth and branching that characterise fungal tissues and organs. This chapter presents: (i) a review of the published mathematical models that attempt to describe fungal growth and branching; (ii) a review of the cell biology of fungal growth and branching, particularly as it relates to the construction of fungal tissues; and (iii) a section in which simulated growth patterns are developed as interactive three-dimensional computer visualisations in what we call the Neighbour-Sensing model of hyphal growth. Experiments with this computer model demonstrate that geometrical form of the mycelium emerges as a consequence of the operation of specific locally-effective hyphal tip interactions. It is not necessary to impose complex spatial controls over development of the mycelium to achieve particular morphologies.
Original reference:
Moore, D., McNulty L.J. & Meškauskas, A. (2006). Branching in fungal hyphae and fungal tissues: growing mycelia in a desktop computer. In Branching Morphogenesis, ed. J. Davies. Austin, TX: Landes Bioscience Publishing/Eurekah.com. Chapter 4, pp. 75-90.
[DOWNLOAD a PDF file of this chapter].

Inspiration from microbes: from patterns to networks
Mark D. Fricker1, Dan Bebber1, Peter R. Darrah1, Monika Tlalka1, Sarah C. Watkinson1, Lynne Boddy2, Lisa Yiasoumis3, Hugh M. Cartwright3, Audrius Meškauskas4, Liam, J. McNulty4, David Moore4, David MD Smith5, Toshiyuki Nakagaki5, Chiu F. Lee6 and Neil Johnson6
1Department of Plant Sciences, University of Oxford, South Parks Road, Oxford, OX1 3RB, UK; 2Cardiff School of Biosciences, Main Building, Museum Avenue, PO Box 915, Cardiff CF10 3TL, UK; 3Physical and Theoretical Chemistry Laboratory, Oxford University, South Parks Road, Oxford, OX1 3QZ, UK; 4School of Biological Sciences, Stopford Building, The University of Manchester, Oxford Road, Manchester, M13 9PT, UK; 5Mathematical Institute, 24-29 St Giles', Oxford, OX1 3LB, UK; 6Condensed Matter Physics, Clarendon Laboratory, Parks Road, Oxford, OX1 3PU, UK
Abstract: Many relatively simple organisms, such as bacteria, cellular
and acellular slime moulds and fungi, can self-organise to form patterns or
complex developmental networks with a rich variety of structure and behaviour.
Many of these systems are intimately associated with nutrient acquisition or
distribution, particularly under conditions where resources are limited and
distributed patchily in time and/or space. It is postulated that emergent
structures are likely to be efficient and resilient as they have been subject to
many cycles of evolutionary selection pressure. In comparison to many biological
networks, such as neural networks, genetic and biochemical pathways or food
webs, microbes are also extremely accessible, and provide tractable experimental
systems. In this Chapter, we briefly review areas where emphasis has been given
to morphological representation of microbial structures and discuss areas of
potential overlap with current developments in network theory.
Original reference:
Fricker, M. D., Bebber, D., Darrah, P. R., Tlalka, M., Watkinson, S. C., Boddy, L., Yiasoumis, L., Cartwright, H. M., Meškauskas, A., McNulty, L. J., Moore, D., Smith, D. M. D., Nakagaki, T., Lee, C. F. and Johnson, N. (2005). Inspiration from microbes: from patterns to networks. In: Coping with Complexity, Proceedings of the International Workshop on Complex Agent-based Dynamic Networks held at the Saďd Business School, University of Oxford, 5 - 7 October 2003.
[DOWNLOAD a PDF file replica of this chapter. For copyright reasons this is a non-printing version, though there's nothing to stop you saving it to disk to read at leisure. Our thanks to Mark Fricker for providing this preprint].

A search for developmental gene sequences in the genomes of filamentous fungi
David Moore, Conor Walsh and Geoffrey D. Robson
School of Biological Sciences, The University of Manchester, 1.800 Stopford Building, Manchester M13 9PT, United Kingdom
Abstract: There is now a sufficient number of filamentous fungal genomes in the public databases to warrant at least initial comparisons with animal and plant genomes. Our interest lies in the control of multicellular morphogenesis, which is a feature of filamentous ascomycetes and basidiomycetes. Search of a representative collection of filamentous fungal genomes with gene sequences generally considered to be essential and highly conserved components of normal development in animals failed to reveal any homologies. We conclude that fungal and animal lineages diverged from their common opisthokont line well before the emergence of any multicellular arrangement, and that the unique cell biology of filamentous fungi has caused control of multicellular development in fungi to evolve in a radically different fashion from that in animals and plants.
Original reference:
Moore, D., Walsh, C. & Robson, G. D. (2005). A search for developmental gene sequences in the genomes of filamentous fungi. In Applied Mycology and Biotechnology, vol. 6, Genes, Genomics and Bioinformatics, D.K. Arora and R. Berka, Editors. Elsevier Science Annual Review Series, Elsevier Science.
[DOWNLOAD a PDF file of the preprint of this paper].

Using web agents for data mining of fungal genomes
Audrius Meškauskas
Alte Gfennstr. 22, CH-8600 Dubendorf, Switzerland
Abstract: We created an
application called Sight, a Java™-based package that provides a user-friendly
interface to generate and connect agents for automatic genomic data mining
without requiring programming skills from the user. Sight was originally
developed to automate analysis of the human genome and attempts to generate web
agents for fungus-related Internet resources revealed that some of those
resources use new methods of representing the information they report, and some
servers returned multiple intermediate pages leading towards their response,
which created difficulties for automated recovery of results. Consequently, it
was not possible to use effectively the old version of Sight so this version of
the application was adapted with a little additional programming, creating a new
version for which these features of the fungal genome servers do not represent a
problem. The new version of Sight (v. 3.0.0) that is tailored to servers
carrying fungal databases is freely available for download from the project
website at these URLs: http://bioinformatics.org/jSight/ and
http://jsight.sourceforge.net/index_SF.htm.
Original reference:
Meškauskas, A. (2005). Using web agents for data mining of fungal genomes. In Applied Mycology and Biotechnology, vol. 6, Genes, Genomics and Bioinformatics, D.K. Arora and R. Berka, Editors. Elsevier Science Annual Review Series, Elsevier Science.
[DOWNLOAD a PDF file of the preprint of this paper].

A comprehensive comparative analysis of the occurrence of developmental sequences in fungal, plant and animal genomes
David Moore and Audrius Meškauskas
Faculty of Life Sciences, The University of Manchester, 1.800 Stopford Building, Oxford Road, Manchester M13 9PT, UK
Abstract: We report a fully comprehensive data-mining exercise, involving an estimated total of
590,000 similarity searches, using agents available on the Internet to search for homologies
to polypeptide sequences assigned to the category ‘development’ in the Gene Ontology
Consortium AmiGO database (www.godatabase.org). The results indicate that of 552
such developmental sequences only 78 are shared between all three kingdoms, 72 are
shared only between fungi and animals, 58 sequences are shared between plants and
fungi, and four sequences were common only to Dictyostelium and fungi. No sequences
were strictly fungus specific, but 68 occurred only in plants (Viridiplantae) and 239 occurred
only in animals (Metazoa). Although some homology was indicated for a total of 219 fungal
sequences, 143 (65 %) of the matches returned were assigned E-values of 0.05 and must be
categorised as weak similarities at best. The majority of the highly similar matches found
in this survey proved to be between sequences involved in basic cell metabolism or essential
eukaryotic cell processes (enzymes in common metabolic pathways, transcription
regulators, binding proteins, receptors and membrane proteins). What is lacking is crosskingdom
similarity in the management processes that regulate multicellular development.
The crown group of eukaryotic kingdoms control and regulate their developmental processes
in very different ways. Unfortunately, we know nothing about molecular control
of multicellular fungal developmental biology.
Original reference:
Moore, D. & Meškauskas, A. (2006). A comprehensive comparative analysis of the occurrence of developmental sequences in fungal, plant and animal genomes. Mycological Research, 110: 251-256. DOI: http://dx.doi.org/10.1016/j.mycres.2006.01.003.
[DOWNLOAD a PDF file of the preprint of this paper].

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