Emergent multicellular life cycles in filamentous bacteria owing to density-dependent population dynamics

Evolution: Understanding the origins of facultative multicellular life cycles

Multicellular organisms exhibit a fascinating diversity of life cycles, but little is known about the factors governing life-cycle evolution. New studies of wild yeast and cyanobacteria provide insight into how and why facultative multicellular life cycles arise.

Minor variations in multicellular life cycles have major effects on adaptation

Multicellularity has evolved several independent times over the past hundreds of millions of years and given rise to a wide diversity of complex life. Recent studies have found that large differences in the fundamental structure of early multicellular life cycles can affect fitness and influence multicellular adaptation. Yet, there is an underlying assumption that at some scale or categorization multicellular life cycles are similar in terms of their adaptive potential. Here, we consider this possibility by exploring adaptation in a class of simple multicellular life cycles of filamentous organisms that only differ in one respect, how many daughter filaments are produced. We use mathematical models and evolutionary simulations to show that despite the similarities, qualitatively different mutations fix. In particular, we find that mutations with a tradeoff between cell growth and group survival, i.e. "selfish" or "altruistic" traits, spread differently. Specifically, altruistic mutations more readily spread in life cycles that produce few daughters while in life cycles producing many daughters either type of mutation can spread depending on the environment. Our results show that subtle changes in multicellular life cycles can fundamentally alter adaptation.

An environmentally induced multicellular life cycle of a unicellular cyanobacterium

Understanding the evolutionary transition to multicellularity is a key problem in biology.^1,2,3,4 Nevertheless, the ecological conditions driving such transitions are not well understood. The first known transition to multicellularity occurred 2.5 billion years ago in cyanobacteria,^5,6,7 and today's cyanobacteria are characterized by enormous morphological diversity. They range from unicellular species; unicellular cyanobacteria with packet-like phenotypes, e.g., tetrads; and simple filamentous species to highly differentiated filamentous species.^8,9,10 The cyanobacterium Cyanothece sp. ATCC 51142, an isolate from the intertidal zone of the U.S. Gulf Coast,¹¹ was classified as a unicellular species.¹² We report a facultative life cycle of Cyanothece sp. in which multicellular filaments alternate with unicellular stages. In a series of experiments, we identified salinity and population density as environmental factors triggering the phenotypic switch between the two morphologies. Then, we used numerical models to test hypotheses regarding the nature of the environmental cues and the mechanisms underlying filament dissolution. While the results predict that the observed response is likely caused by an excreted compound in the medium, we cannot fully exclude changes in nutrient availability (as in Tuomi et al.¹³ and Matz and Jürgens¹⁴). The best-fit modeling results show a nonlinear effect of the compound, which is characteristic of density-dependent sensing systems.^15,16 Furthermore, filament fragmentation is predicted to occur by connection cleavage rather than cell death of each alternating cell, which is supported by fluorescent and scanning electron microscopy results. The switch between unicellular and multicellular morphology constitutes an environmentally dependent life cycle that is likely an important step en route to permanent multicellularity.

Eco-evolutionary dynamics of clonal multicellular life cycles

The evolution of multicellular life cycles is a central process in the course of the emergence of multicellularity. The simplest multicellular life cycle is comprised of the growth of the propagule into a colony and its fragmentation to give rise to new propagules. The majority of theoretical models assume selection among life cycles to be driven by internal properties of multicellular groups, resulting in growth competition. At the same time, the influence of interactions between groups on the evolution of life cycles is rarely even considered. Here, we present a model of colonial life cycle evolution taking into account group interactions. Our work shows that the outcome of evolution could be coexistence between multiple life cycles or that the outcome may depend on the initial state of the population - scenarios impossible without group interactions. At the same time, we found that some results of these simpler models remain relevant: evolutionary stable strategies in our model are restricted to binary fragmentation - the same class of life cycles that contains all evolutionarily optimal life cycles in the model without interactions. Our results demonstrate that while models neglecting interactions can capture short-term dynamics, they fall short in predicting the population-scale picture of evolution.

Drug-induced resistance evolution necessitates less aggressive treatment

Increasing body of experimental evidence suggests that anticancer and antimicrobial therapies may themselves promote the acquisition of drug resistance by increasing mutability. The successful control of evolving populations requires that such biological costs of control are identified, quantified and included to the evolutionarily informed treatment protocol. Here we identify, characterise and exploit a trade-off between decreasing the target population size and generating a surplus of treatment-induced rescue mutations. We show that the probability of cure is maximized at an intermediate dosage, below the drug concentration yielding maximal population decay, suggesting that treatment outcomes may in some cases be substantially improved by less aggressive treatment strategies. We also provide a general analytical relationship that implicitly links growth rate, pharmacodynamics and dose-dependent mutation rate to an optimal control law. Our results highlight the important, but often neglected, role of fundamental eco-evolutionary costs of control. These costs can often lead to situations, where decreasing the cumulative drug dosage may be preferable even when the objective of the treatment is elimination, and not containment. Taken together, our results thus add to the ongoing criticism of the standard practice of administering aggressive, high-dose therapies and motivate further experimental and clinical investigation of the mutagenicity and other hidden collateral costs of therapies.

Contrasting the impact of cytotoxic and cytostatic drug therapies on tumour progression

A tumour grows when the total division (birth) rate of its cells exceeds their total mortality (death) rate. The capability for uncontrolled growth within the host tissue is acquired via the accumulation of driver mutations which enable the tumour to progress through various hallmarks of cancer. We present a mathematical model of the penultimate stage in such a progression. We assume the tumour has reached the limit of its present growth potential due to cell competition that either results in total birth rate reduction or death rate increase. The tumour can then progress to the final stage by either seeding a metastasis or acquiring a driver mutation. We influence the ensuing evolutionary dynamics by cytotoxic (increasing death rate) or cytostatic (decreasing birth rate) therapy while keeping the effect of the therapy on net growth reduction constant. Comparing the treatments head to head we derive conditions for choosing optimal therapy. We quantify how the choice and the related gain of optimal therapy depends on driver mutation, metastasis, intrinsic cell birth and death rates, and the details of cell competition. We show that detailed understanding of the cell population dynamics could be exploited in choosing the right mode of treatment with substantial therapy gains.

Cells and organisms evolve to better survive in their environments and to adapt to new challenges. Such dynamics manifest in a particularly problematic way with the evolution of drug resistance, which is increasingly recognized as a key challenge for global health. Thus, developing therapy paradigms that factor in evolutionary dynamics is an important goal. Using a minimal mathematical model of a cancer cell population we contrast cytotoxic (increasing death rate) and cytostatic (decreasing birth rate) treatments while keeping the effect of the therapy on the net growth reduction constant. We then quantify how the choice and the related gain of optimal therapy depends on driver mutation, metastasis, intrinsic cell birth and death rates and the details of cell competition. Most importantly, we identify specific cell population dynamics under which a certain treatment could be significantly better than the alternative.

Emergence of diverse life cycles and life histories at the origin of multicellularity

The evolution of multicellularity has given rise to a remarkable diversity of multicellular life cycles and life histories. Whereas some multicellular organisms are long-lived, grow through cell division, and repeatedly release single-celled propagules (for example, animals), others are short-lived, form by aggregation, and propagate only once, by generating large numbers of solitary cells (for example, cellular slime moulds). There are no systematic studies that explore how diverse multicellular life cycles can come about. Here, we focus on the origin of multicellularity and develop a mechanistic model to examine the primitive life cycles that emerge from a unicellular ancestor when an ancestral gene is co-opted for cell adhesion. Diverse life cycles readily emerge, depending on ecological conditions, group-forming mechanism, and ancestral constraints. Among these life cycles, we recapitulate both extremes of long-lived groups that propagate continuously and short-lived groups that propagate only once, with the latter type of life cycle being particularly favoured when groups can form by aggregation. Our results show how diverse life cycles and life histories can easily emerge at the origin of multicellularity, shaped by ancestral constraints and ecological conditions. Beyond multicellularity, this finding has similar implications for other major transitions, such as the evolution of sociality.

Interacting cells driving the evolution of multicellular life cycles

Evolution of complex multicellular life began from the emergence of a life cycle involving the formation of cell clusters. The opportunity for cells to interact within clusters provided them with an advantage over unicellular life forms. However, what kind of interactions may lead to the evolution of multicellular life cycles? Here, we combine evolutionary game theory with a model for the emergence of multicellular groups to investigate how cell interactions can influence reproduction modes during the early stages of the evolution of multicellularity. In our model, the presence of both cell types is maintained by stochastic phenotype switching during cell division. We identify evolutionary optimal life cycles as those which maximize the population growth rate. Among all interactions captured by two-player games, the vast majority promotes two classes of life cycles: (i) splitting into unicellular propagules or (ii) fragmentation into two offspring clusters of equal (or almost equal) size. Our findings indicate that the three most important characteristics, determining whether multicellular life cycles will evolve, are the average performance of homogeneous groups, heterogeneous groups, and solitary cells.

Multicellular organisms are ubiquitous. But how did the first multicellular organisms arise? It is typically argued that this occurred due to benefits coming from interactions between cells. One example of such interactions is the division of labour. For instance, colonial cyanobacteria delegate photosynthesis and nitrogen fixation to different cells within the colony. In this way, the colony gains a growth advantage over unicellular cyanobacteria. However, not all cell interactions favour multicellular life. Cheater cells residing in a colony without any contribution will outgrow other cells. Then, the growing burden of cheaters may eventually destroy the colony. Here, we ask what kinds of interactions promote the evolution of multicellularity? We investigated all interactions captured by pairwise games and for each of them, we look for the evolutionarily optimal life cycle: How big should the colony grow and how should it split into offspring cells or colonies? We found that multicellularity can evolve with interactions far beyond cooperation or division of labour scenarios. More surprisingly, most of the life cycles found fall into either of two categories: A parent colony splits into two multicellular parts, or it splits into multiple independent cells.

Ecological feedback on diffusion dynamics

Spatial patterns are ubiquitous across different scales of organization in ecological systems. Animal coat pattern, spatial organization of insect colonies and vegetation in arid areas are prominent examples from such diverse ecologies. Typically, pattern formation has been described by reaction-diffusion equations, which consider individuals dispersing between subpopulations of a global pool. This framework applied to public goods game nicely showed the endurance of populations via diffusion and generation of spatial patterns. However, how the spatial characteristics, such as diffusion, are related to the eco-evolutionary process as well as the nature of the feedback from evolution to ecology and vice versa, has been so far neglected. We present a thorough analysis of the ecologically driven evolutionary dynamics in a spatially extended version of ecological public goods games. Furthermore, we show how these evolutionary dynamics feed back into shaping the ecology, thus together determining the fate of the system.

Fragmentation modes and the evolution of life cycles

Reproduction is a defining feature of living systems. To reproduce, aggregates of biological units (e.g., multicellular organisms or colonial bacteria) must fragment into smaller parts. Fragmentation modes in nature range from binary fission in bacteria to collective-level fragmentation and the production of unicellular propagules in multicellular organisms. Despite this apparent ubiquity, the adaptive significance of fragmentation modes has received little attention. Here, we develop a model in which groups arise from the division of single cells that do not separate but stay together until the moment of group fragmentation. We allow for all possible fragmentation patterns and calculate the population growth rate of each associated life cycle. Fragmentation modes that maximise growth rate comprise a restrictive set of patterns that include production of unicellular propagules and division into two similar size groups. Life cycles marked by single-cell bottlenecks maximise population growth rate under a wide range of conditions. This surprising result offers a new evolutionary explanation for the widespread occurrence of this mode of reproduction. All in all, our model provides a framework for exploring the adaptive significance of fragmentation modes and their associated life cycles.

Mode of reproduction is a defining trait of all organisms, including colonial bacteria and multicellular organisms. To produce offspring, aggregates must fragment by splitting into two or more groups. The particular way that a given group fragments defines the life cycle of the organism. For instance, insect colonies can reproduce by splitting or by producing individuals that found new colonies. Similarly, some colonial bacteria propagate by fission or by releasing single cells, while others split in highly sophisticated ways; in multicellular organisms reproduction typically proceeds via a single-cell bottleneck phase. The space of possibilities for fragmentation is so vast that an exhaustive analysis seems daunting. Focusing on fragmentation modes of a simple kind we parametrise all possible modes of group fragmentation and identify those modes leading to the fastest population growth rate. Two kinds of life cycle dominate: one involving division into two equal size groups, and the other involving production of a unicellular propagule. The prevalence of these life cycles in nature is consistent with our null model and suggests that benefits accruing from population growth rate alone may have shaped the evolution of fragmentation mode.

Individual-based modelling of population growth and diffusion in discrete time

Individual-based models (IBMs) of human populations capture spatio-temporal dynamics using rules that govern the birth, behavior, and death of individuals. We explore a stochastic IBM of logistic growth-diffusion with constant time steps and independent, simultaneous actions of birth, death, and movement that approaches the Fisher-Kolmogorov model in the continuum limit. This model is well-suited to parallelization on high-performance computers. We explore its emergent properties with analytical approximations and numerical simulations in parameter ranges relevant to human population dynamics and ecology, and reproduce continuous-time results in the limit of small transition probabilities. Our model prediction indicates that the population density and dispersal speed are affected by fluctuations in the number of individuals. The discrete-time model displays novel properties owing to the binomial character of the fluctuations: in certain regimes of the growth model, a decrease in time step size drives the system away from the continuum limit. These effects are especially important at local population sizes of <50 individuals, which largely correspond to group sizes of hunter-gatherers. As an application scenario, we model the late Pleistocene dispersal of Homo sapiens into the Americas, and discuss the agreement of model-based estimates of first-arrival dates with archaeological dates in dependence of IBM model parameter settings.

Transition from one- to two-dimensional development facilitates maintenance of multicellularity

Filamentous organisms represent an example where incomplete separation after cell division underlies the development of multicellular formations. With a view to understanding the evolution of more complex multicellular structures, we explore the transition of multicellular growth from one to two dimensions. We develop a computational model to simulate multicellular development in populations where cells exhibit density-dependent division and death rates. In both the one- and two-dimensional contexts, multicellular formations go through a developmental cycle of growth and subsequent decay. However, the model shows that a transition to a higher dimension increases the size of multicellular formations and facilitates the maintenance of large cell clusters for significantly longer periods of time. We further show that the turnover rate for cell division and death scales with the number of iterations required to reach the stationary multicellular size at equilibrium. Although size and life cycles of multicellular organisms are affected by other environmental and genetic factors, the model presented here evaluates the extent to which the transition of multicellular growth from one to two dimensions contributes to the maintenance of multicellular structures during development.

Games of multicellularity

Evolutionary game dynamics are often studied in the context of different population structures. Here we propose a new population structure that is inspired by simple multicellular life forms. In our model, cells reproduce but can stay together after reproduction. They reach complexes of a certain size, n, before producing single cells again. The cells within a complex derive payoff from an evolutionary game by interacting with each other. The reproductive rate of cells is proportional to their payoff. We consider all two-strategy games. We study deterministic evolutionary dynamics with mutations, and derive exact conditions for selection to favor one strategy over another. Our main result has the same symmetry as the well-known sigma condition, which has been proven for stochastic game dynamics and weak selection. For a maximum complex size of n=2 our result holds for any intensity of selection. For n≥3 it holds for weak selection. As specific examples we study the prisoner's dilemma and hawk-dove games. Our model advances theoretical work on multicellularity by allowing for frequency-dependent interactions within groups.

Darwin-Wallace Demons: survival of the fastest in populations of duckweeds and the evolutionary history of an enigmatic group of angiosperms

In evolutionary biology, the term 'Darwinian fitness' refers to the lifetime reproductive success of an individual within a population of conspecifics. The idea of a 'Darwinian Demon' emerged from this concept and is defined here as an organism that commences reproduction almost immediately after birth, has a maximum fitness, and lives forever. It has been argued that duckweeds (sub-family Lemnoideae, order Alismatales), a group containing five genera and 34 species of small aquatic monocotyledonous plants with a reduced body plan, can be interpreted as examples of 'Darwinian Demons'. Here we focus on the species Spirodela polyrhiza (Great duckweed) and show that these miniaturised aquatic angiosperms display features that fit the definition of the hypothetical organism that we will call a 'Darwin-Wallace Demon' in recognition of the duel proponents of evolution by natural selection. A quantitative analysis (log-log bivariate plot of annual growth in dry biomass versus standing dry body mass of various green algae and land plants) revealed that duckweeds are thus far the most rapidly growing angiosperms in proportion to their body mass. In light of this finding, we discuss the disposable soma and metabolic optimising theories, summarise evidence for and against the proposition that the Lemnoideae (family Araceae) reflect an example of reductive evolution, and argue that, under real-world conditions (environmental constraints and other limitations), 'Darwin-Wallace Demons' cannot exist, although the concept remains useful in much the same way that the Hardy-Weinberg law does.

Stochastic evolution of staying together

Staying together means that replicating units do not separate after reproduction, but remain attached to each other or in close proximity. Staying together is a driving force for evolution of complexity, including the evolution of multi-cellularity and eusociality. We analyze the fixation probability of a mutant that has the ability to stay together. We assume that the size of the complex affects the reproductive rate of its units and the probability of staying together. We examine the combined effect of natural selection and random drift on the emergence of staying together in a finite sized population. The number of states in the underlying stochastic process is an exponential function of population size. We develop a framework for any intensity of selection and give closed form solutions for special cases. We derive general results for the limit of weak selection.

Evolution of staying together in the context of diffusible public goods

We study the coevolution of staying together and cooperation. Staying together means that replicating units do not separate after reproduction, but remain in proximity. For example, following cell division the two daughter cells may not fully separate but stay attached to each other. Repeated cell division thereby can lead to a simple multi-cellular complex. We assume that cooperators generate a diffusible public good, which can be absorbed by any cell in the system. The production of the public good entails a cost, while the absorption leads to a benefit. Defectors produce no public good. Defectors have a selective advantage unless a mechanism for evolution of cooperation is at work. Here we explore the idea that the public good produced by a cooperating cell is absorbed by cells of the same complex with a probability that depends on the size of the complex. Larger complexes are better at absorbing the public goods produced by their own individuals. We derive analytical conditions for the evolution of staying together, thereby studying the coevolution of clustering and cooperation. If cooperators and defectors differ in their intrinsic efficiency to absorb the public good, then we find multiple stable equilibria and the possibility for coexistence between cooperators and defectors. Finally we study the implications of disadvantages that might arise if complexes become too large.

Biophysical and size-dependent perspectives on plant evolution

Physical laws and processes have profoundly influenced plant evolution. Their effects are invariably size dependent and thus subject to scaling as well as biophysical analyses even though these effects differ depending upon the fluid (water or air) in which plants evolve. Although organisms cannot obviate the effects of physical laws and processes, the consequences of these effects can be altered by ontogenetic or phylogenetic alterations in geometry, shape, or orientation as well as in body size. These assertions are examined using theoretical insights and empirical data drawn from extant and fossil plants pertinent to four evolutionary transitions: (1) the evolution of multicellularity, (2) the transition from an aquatic to an aerial habitat, (3) the evolution of vascular tissues, and (4) the evolution of secondary growth by the independent acquisition of cambia. This examination shows how physical laws limit phenotypic expression, but how they also simultaneously provide alternative, potentially adaptive possibilities.

Phenotypic diversity of multicellular filamentation in oral Streptococci

Filamentous multicellular bacteria are among the most ancient multicellular organisms. They inhabit a great variety of environments and are present in the human body, including the oral cavity. Beside the selective advantages related to the larger size achieved through filamentation, the development of multicellular bacteria can be also driven by simple ecological factors such as birth and death rates at the cellular level. In order to extend earlier results obtained in aquatic species, we investigate the filamentation process of four different strains of oral streptococci, namely S. mutans, S. salivarius, S. oralis and S. anginosus. The results indicate differences in the capacities of different streptococcus species to form filaments, manifested in terms of length and the time-scale of filament elongation. The filamentation pattern of these oral streptococci resembles that of aquatic bacteria, whereby filaments reach a peak length during exponential growth and become short when the population reaches a steady state. Hence, this study validates that multicellularity can be an emergent property of filamentous bacteria of different ecological niches, and that phenotypic differences in filamentation can occur within species of the same genus, in this case oral streptococci. Moreover, given the role that specific oral streptococci can play in the etiology of oral diseases, these results can possibly open new perspectives in the study of the virulence properties of these species.

The origins of multicellular organisms

Multicellularity has evolved in several eukaryotic lineages leading to plants, fungi, and animals. Theoretically, in each case, this involved (1) cell-to-cell adhesion with an alignment-of-fitness among cells, (2) cell-to-cell communication, cooperation, and specialization with an export-of-fitness to a multicellular organism, and (3) in some cases, a transition from "simple" to "complex" multicellularity. When mapped onto a matrix of morphologies based on developmental and physical rules for plants, these three phases help to identify a "unicellular ⇒ colonial ⇒ filamentous (unbranched ⇒ branched) ⇒ pseudoparenchymatous ⇒ parenchymatous" morphological transformation series that is consistent with trends observed within each of the three major plant clades. In contrast, a more direct "unicellular ⇒ colonial or siphonous ⇒ parenchymatous" series is observed in fungal and animal lineages. In these contexts, we discuss the roles played by the cooptation, expansion, and subsequent diversification of ancestral genomic toolkits and patterning modules during the evolution of multicellularity. We conclude that the extent to which multicellularity is achieved using the same toolkits and modules (and thus the extent to which multicellularity is homologous among different organisms) differs among clades and even among some closely related lineages.

Evolution of multicellularity coincided with increased diversification of cyanobacteria and the Great Oxidation Event

Cyanobacteria are among the most diverse prokaryotic phyla, with morphotypes ranging from unicellular to multicellular filamentous forms, including those able to terminally (i.e., irreversibly) differentiate in form and function. It has been suggested that cyanobacteria raised oxygen levels in the atmosphere around 2.45-2.32 billion y ago during the Great Oxidation Event (GOE), hence dramatically changing life on the planet. However, little is known about the temporal evolution of cyanobacterial lineages, and possible interplay between the origin of multicellularity, diversification of cyanobacteria, and the rise of atmospheric oxygen. We estimated divergence times of extant cyanobacterial lineages under Bayesian relaxed clocks for a dataset of 16S rRNA sequences representing the entire known diversity of this phylum. We tested whether the evolution of multicellularity overlaps with the GOE, and whether multicellularity is associated with significant shifts in diversification rates in cyanobacteria. Our results indicate an origin of cyanobacteria before the rise of atmospheric oxygen. The evolution of multicellular forms coincides with the onset of the GOE and an increase in diversification rates. These results suggest that multicellularity could have played a key role in triggering cyanobacterial evolution around the GOE.

Evolutionary construction by staying together and coming together

The evolutionary trajectory of life on earth is one of increasing size and complexity. Yet the standard equations of evolutionary dynamics describe mutation and selection among similar organisms that compete on the same level of organization. Here we begin to outline a mathematical theory that might help to explore how evolution can be constructive, how natural selection can lead from lower to higher levels of organization. We distinguish two fundamental operations, which we call 'staying together' and 'coming together'. Staying together means that individuals form larger units by not separating after reproduction, while coming together means that independent individuals form aggregates. Staying together can lead to specialization and division of labor, but the developmental program must evolve in the basic unit. Coming together can be creative by combining units with different properties. Both operations have been identified in the context of multicellularity, but they have been treated very similarly. Here we point out that staying together and coming together can be found at every level of biological construction and moreover that they face different evolutionary problems. The distinction is particularly clear in the context of cooperation and defection. For staying together the stability of cooperation takes the form of a developmental error threshold, while coming together leads to evolutionary games and requires a mechanism for the evolution of cooperation. We use our models to discuss simple aspects of the evolution of protocells, eukarya, multi-cellularity and animal societies.

Antagonistic interactions between filamentous heterotrophs and the cyanobacterium Nostoc muscorum

BACKGROUND

Little is known about interactions between filamentous heterotrophs and filamentous cyanobacteria. Here, interactions between the filamentous heterotrophic bacteria Fibrella aestuarina (strain BUZ 2) and Fibrisoma limi (BUZ 3) with an axenic strain of the autotrophic filamentous cyanobacterium Nostoc muscorum (SAG 25.82) were studied in mixed cultures under nutrient rich (carbon source present in medium) and poor (carbon source absent in medium) conditions.

FINDINGS

F. aestuarina BUZ 2 significantly reduced the cyanobacterial population whereas F. limi BUZ 3 did not. Physical contact between heterotrophs and autotroph was observed and the cyanobacterial cells showed some level of damage and lysis. Therefore, either contact lysis or entrapment with production of extracellular compounds in close vicinity of host cells could be considered as potential modes of action.The supernatants from pure heterotrophic cultures did not have an effect on Nostoc cultures. However, supernatant from mixed cultures of BUZ 2 and Nostoc had a negative effect on cyanobacterial growth, indicating that the lytic compounds were only produced in the presence of Nostoc.The growth and survival of tested heterotrophs was enhanced by the presence of Nostoc or its metabolites, suggesting that the heterotrophs could utilize the autotrophs and its products as a nutrient source. However, the autotroph could withstand and out-compete the heterotrophs under nutrient poor conditions.

CONCLUSIONS

Our results suggest that the nutrients in cultivation media, which boost or reduce the number of heterotrophs, were the important factor influencing the outcome of the interplay between filamentous heterotrophs and autotrophs. For better understanding of these interactions, additional research is needed. In particular, it is necessary to elucidate the mode of action for lysis by heterotrophs, and the possible defense mechanisms of the autotrophs.