Metabolic cost of rapid adaptation of single yeast cells

Systemic Alterations of Cancer Cells and Their Boost by Polyploidization: Unicellular Attractor (UCA) Model

Using meta-analyses, we introduce a unicellular attractor (UCA) model integrating essential features of the ‘atavistic reversal’, ‘cancer attractor’, ‘somatic mutation’, ‘genome chaos’, and ‘tissue organization field’ theories. The ‘atavistic reversal’ theory is taken as a keystone. We propose a possible mechanism of this reversal, its refinement called ‘gradual atavism’, and evidence for the ‘serial atavism’ model. We showed the gradual core-to-periphery evolutionary growth of the human interactome resulting in the higher protein interaction density and global interactome centrality in the UC center. In addition, we revealed that UC genes are more actively expressed even in normal cells. The modeling of random walk along protein interaction trajectories demonstrated that random alterations in cellular networks, caused by genetic and epigenetic changes, can result in a further gradual activation of the UC center. These changes can be induced and accelerated by cellular stress that additionally activates UC genes (especially during cell proliferation), because the genes involved in cellular stress response and cell cycle are mostly of UC origin. The functional enrichment analysis showed that cancer cells demonstrate the hyperactivation of energetics and the suppression of multicellular genes involved in communication with the extracellular environment (especially immune surveillance). Collectively, these events can unleash selfish cell behavior aimed at survival at all means. All these changes are boosted by polyploidization. The UCA model may facilitate an understanding of oncogenesis and promote the development of therapeutic strategies.

Gradistics: An underappreciated dimension in evolutionary space

The growth of complexity is an unsolved and underappreciated problem. We consider possible causes of this growth, hypotheses testing, molecular mechanisms, complexity measures, cases of simplification, and significance for biomedicine. We focus on a general ability of regulation, which is based on the growing information storage and processing capacities, as the main proxy of complexity. Natural selection is indifferent to complexity. However, complexification can be inferred from the same first principle, on which natural selection is founded. Natural selection depends on potentially unlimited reproduction under limited environmental conditions. Because of the demographic pressure, the simple ecological niches become fulfilled and diversified (due to species splitting and divergence). Diversification increases complexity of biocenoses. After the filling and diversification of simple niches, the more complex niches can arise. This is the 'atomic orbitals' (AO) model. Complexity has many shortcomings but it has an advantage. This advantage is ability to regulatory adaptation, including behavioral, formed in the evolution by means of genetic adaptation. Regulatory adaptation is much faster than genetic one because it is based on the information previously accumulated via genetic adaptation and learning. Regulatory adaptation further increases complexity of biocenoses. This is the 'regulatory advantage' (RA) model. The comparison of both models allows testable predictions. We focus on the animal evolution because of the appearance of higher regulatory level (nervous system), which is absent in other lineages, and relevance to humans (including biomedical aspects).

Growth-Associated Droplet Shrinkage for Bacterial Quantification, Growth Monitoring, and Separation by Ultrahigh-Throughput Microfluidics

Microbiology still relies on en masse cultivation for selection, isolation, and characterization of microorganisms of interest. This constrains the diversity of microbial types and metabolisms that can be investigated in the laboratory also because of intercellular competition during cultivation. Cell individualization by droplet-based microfluidics prior to experimental analysis provides an attractive alternative to access a larger fraction of the microbial biosphere, miniaturizing the required equipment and minimizing reagent use for increased and more efficient analytical throughput. Here, we show that cultivation of a model two-strain bacterial community in droplets significantly reduces representation bias in the grown culture compared to batch cultivation. Further, and based on the droplet shrinkage observed upon cell proliferation, we provide proof-of-concept for a simple strategy that allows absolute quantification of microbial cells in a sample as well as selective recovery of microorganisms of interest for subsequent experimental characterization.

Cancer progression as a learning process

Drug resistance and metastasis—the major complications in cancer—both entail adaptation of cancer cells to stress, whether a drug or a lethal new environment. Intriguingly, these adaptive processes share similar features that cannot be explained by a pure Darwinian scheme, including dormancy, increased heterogeneity, and stress-induced plasticity. Here, we propose that learning theory offers a framework to explain these features and may shed light on these two intricate processes. In this framework, learning is performed at the single-cell level, by stress-driven exploratory trial-and-error. Such a process is not contingent on pre-existing pathways but on a random search for a state that diminishes the stress. We review underlying mechanisms that may support this search, and show by using a learning model that such exploratory learning is feasible in a high-dimensional system as the cell. At the population level, we view the tissue as a network of exploring agents that communicate, restraining cancer formation in health. In this view, disease results from the breakdown of homeostasis between cellular exploratory drive and tissue homeostasis.

Evolution of plasticity: metabolic compensation for fluctuating energy demands at the origin of life

Phenotypic plasticity of physiological functions enables rapid responses to changing environments and may thereby increase the resilience of organisms to environmental change. Here, we argue that the principal hallmarks of life itself, self-replication and maintenance, are contingent on the plasticity of metabolic processes ('metabolic plasticity'). It is likely that the Last Universal Common Ancestor (LUCA), 4 billion years ago, already possessed energy-sensing molecules that could adjust energy (ATP) production to meet demand. The earliest manifestation of metabolic plasticity, switching cells from growth and storage (anabolism) to breakdown and ATP production (catabolism), coincides with the advent of Darwinian evolution. Darwinian evolution depends on reliable translation of information from information-carrying molecules, and on cell genealogy where information is accurately passed between cell generations. Both of these processes create fluctuating energy demands that necessitate metabolic plasticity to facilitate replication of genetic material and (proto)cell division. We propose that LUCA possessed rudimentary forms of these capabilities. Since LUCA, metabolic networks have increased in complexity. Generalist founder enzymes formed the basis of many derived networks, and complexity arose partly by recruiting novel pathways from the untapped pool of reactions that are present in cells but do not have current physiological functions (the so-called 'underground metabolism'). Complexity may thereby be specific to environmental contexts and phylogenetic lineages. We suggest that a Boolean network analysis could be useful to model the transition of metabolic networks over evolutionary time. Network analyses can be effective in modelling phenotypic plasticity in metabolic functions for different phylogenetic groups because they incorporate actual biochemical regulators that can be updated as new empirical insights are gained.

Are droplets really suitable for single-cell analysis? A case study on yeast in droplets

Single-cell analysis has become one of the main cornerstones of biotechnology, inspiring the advent of various microfluidic compartments for cell cultivation such as microwells, microtrappers, microcapillaries, and droplets. A fundamental assumption for using such microfluidic compartments is that unintended stress or harm to cells derived from the microenvironments is insignificant, which is a crucial condition for carrying out unbiased single-cell studies. Despite the significance of this assumption, simple viability or growth tests have overwhelmingly been the assay of choice for evaluating culture conditions while empirical studies on the sub-lethal effect on cellular functions have been insufficient in many cases. In this work, we assessed the effect of culturing cells in droplets on the cellular function using yeast morphology as an indicator. Quantitative morphological analysis using CalMorph, an image-analysis program, demonstrated that cells cultured in flasks, large droplets, and small droplets significantly differed morphologically. From these differences, we identified that the cell cycle was delayed in droplets during the G1 phase and during the process of bud growth likely due to the checkpoint mechanism and impaired mitochondrial function, respectively. Furthermore, comparing small and large droplets, cells cultured in large droplets were morphologically more similar to those cultured in a flask, highlighting the advantage of increasing the droplet size. These results highlight a potential source of bias in cell analysis using droplets and reinforce the significance of assessing culture conditions of microfluidic cultivation methods for specific study cases.

Confining Trypanosoma brucei in emulsion droplets reveals population variabilities in division rates and improves in vitro cultivation

Trypanosome parasites are infecting mammals in Sub-Saharan Africa and are transmitted between hosts through bites of the tsetse fly. The transmission from the insect vector to the mammal host causes a number of metabolic and physiological changes. A fraction of the population continuously adapt to the immune system of the host, indicating heterogeneity at the population level. Yet, the cell to cell variability in populations is mostly unknown. We develop here an analytical method for quantitative measurements at the single cell level based on encapsulation and cultivation of single-cell Trypanosoma brucei in emulsion droplets. We first show that mammalian stage trypanosomes survive for several hours to days in droplets, with an influence of droplet size on both survival and growth. We unravel various growth patterns within a population and find that droplet cultivation of trypanosomes results in 10-fold higher cell densities of the highest dividing cell variants compared to standard cultivation techniques. Some variants reach final cell titers in droplets closer to what is observed in nature than standard culture, of practical interest for cell production. Droplet microfluidics is therefore a promising tool for trypanosome cultivation and analysis with further potential for high-throughput single cell trypanosome analysis.

Cooperative metabolic resource allocation in spatially-structured systems

Natural selection has shaped the evolution of cells and multi-cellular organisms such that social cooperation can often be preferred over an individualistic approach to metabolic regulation. This paper extends a framework for dynamic metabolic resource allocation based on the maximum entropy principle to spatiotemporal models of metabolism with cooperation. Much like the maximum entropy principle encapsulates 'bet-hedging' behaviour displayed by organisms dealing with future uncertainty in a fluctuating environment, its cooperative extension describes how individuals adapt their metabolic resource allocation strategy to further accommodate limited knowledge about the welfare of others within a community. The resulting theory explains why local regulation of metabolic cross-feeding can fulfil a community-wide metabolic objective if individuals take into consideration an ensemble measure of total population performance as the only form of global information. The latter is likely supplied by quorum sensing in microbial systems or signalling molecules such as hormones in multi-cellular eukaryotic organisms.