On Drugs.

Despite their centrality to medicine, drugs are not easily defined. We introduce two desiderata for a basic definition of medical drugs. It should: (a) capture everything considered to be a drug in medical contexts and (b) rule out anything that is not considered to be a drug. After canvassing a range of options, we find that no single definition of drugs can satisfy both desiderata. We conclude with three responses to our exploration of the drug concept: maintain a monistic concept, or choose one of two pluralistic outcomes. Notably, the distinction between drugs and other substances is placed under pressure by the most plausible of the options available.

Rethinking microbial infallibility in the metagenomics era.

The 'principle of microbial infallibility' was a mainstay of microbial physiology and environmental microbiology in earlier decades. This principle asserts that wherever there is an energetic gain to be made from environmental resources, microorganisms will find a way to take advantage of the situation. Although previously disputed, this claim was revived with the discovery of anammox bacteria and other major contributors to biogeochemistry. Here, we discuss the historical background to microbial infallibility, and focus on its contemporary relevance to metagenomics. Our analysis distinguishes exploration-driven metagenomics from hypothesis-driven metagenomics. In particular, we show how hypothesis-driven metagenomics can use background assumptions of microbial infallibility to enable the formulation of hypotheses to be tested by enrichment cultures. Discoveries of comammox and the anaerobic oxidation of methane are major instances of such strategies, and we supplement them with outlines of additional examples. This overview highlights one way in which metagenomics is making the transition from an exploratory data-analysis programme of research to a hypothesis-testing one. We conclude with a discussion of how microbial infallibility is a heuristic with far-reaching implications for the investigation of life.

Contrasting Strategies: Human Eukaryotic Versus Bacterial Microbiome Research.

Most discussions of human microbiome research have focused on bacterial investigations and findings. Our target is to understand how human eukaryotic microbiome research is developing, its potential distinctiveness, and how problems can be addressed. We start with an overview of the entire eukaryotic microbiome literature (578 papers), show tendencies in the human-based microbiome literature, and then compare the eukaryotic field to more developed human bacterial microbiome research. We are particularly concerned with problems of interpretation that are already apparent in human bacterial microbiome research (e.g. disease causality, probiotic interventions, evolutionary claims). We show where each field converges and diverges, and what this might mean for progress in human eukaryotic microbiome research. Our analysis then makes constructive suggestions for the future of the field.

Metabolic and microbial perspectives on the "evolution of evolution".

Identifying and theorizing major turning points in the history of life generates insights into not only world-changing evolutionary events but also the processes that bring these events about. In his treatment of these issues, Bonner identifies the evolution of sex, multicellularity, and nervous systems as enabling the "evolution of evolution," which involves fundamental transformations in how evolution occurs. By contextualizing his framework within two decades of theorizing about major transitions in evolution, we identify some basic problems that Bonner's theory shares with much of the prevailing literature. These problems include implicit progressivism, theoretical disunity, and a limited ability to explain major evolutionary transformations. We go on to identify events and processes that are neglected by existing views. In contrast with the "vertical" focus on replication, hierarchy, and morphology that preoccupies most of the literature on major transitions, we propose a "horizontal" dimension in which metabolism and microbial innovations play a central explanatory role in understanding the broad-scale organization of life.

Concepts of the last eukaryotic common ancestor.

Insight into the last eukaryotic common ancestor (LECA) is central to any phylogeny-based reconstruction of early eukaryotic evolution. Increasing amounts of data enable such reconstructions, without necessarily providing further insight into what LECA actually was. We consider four possible concepts of LECA: an abstract phylogenetic state, a single cell, a population, and a consortium of organisms. We argue that the view most realistically underlying work in the field is that of LECA as a population. Drawing on recent findings of genomically heterogeneous populations in eukaryotes ('pangenomes'), we examine the evolutionary implications of a pangenomic LECA population. For instance, how does this concept affect standard expectations about the ecology, geography, fitness, and diversification of LECA? Does it affect evolutionary interpretations of LECA's cellular functions? Finally, we examine whether this novel pangenomic concept of LECA has implications for phylogenetic reconstructions of early eukaryote evolution. Our aim is to add to the conceptual toolkit for developing theories of LECA and interpreting genomic datasets.

Microbes, mathematics, and models.

Microbial model systems have a long history of fruitful use in fields that include evolution and ecology. In order to develop further insight into modelling practice, we examine how the competitive exclusion and coexistence of competing species have been modelled mathematically and materially over the course of a long research history. In particular, we investigate how microbial models of these dynamics interact with mathematical or computational models of the same phenomena. Our cases illuminate the ways in which microbial systems and equations work as models, and what happens when they generate inconsistent findings about shared targets. We reveal an iterative strategy of comparative modelling in different media, and suggest reasons why microbial models have a special degree of epistemic tractability in multimodel inquiry.

Microbiota-gut-brain research: A critical analysis.

Microbiota-gut-brain (MGB) research is a fast-growing field of inquiry with important implications for how human brain function and behaviour are understood. Researchers manipulate gut microbes ("microbiota") to reveal connections between intestinal microbiota and normal brain functions (e.g., cognition, emotion, and memory) or pathological states (e.g., anxiety, mood disorders, and neural developmental disorders such as autism). Many claims are made about causal relationships between gut microbiota and human behaviour. By uncovering these relationships, MGB research aims to offer new explanations of mental health and potential avenues of treatment.So far, limited evaluation has been made of MGB's methods and its core experimental findings, many of which are extensively reiterated in copious reviews of the field. These factors, plus the self-help potential of MGB, have combined to encourage uncritical public uptake of MGB discoveries. Both social and professional media focus on the potential for dietary intervention in mental health, and causal relationships are assumed to be established.Our target article has two main aims. One is to examine critically the core practices and findings of experimental MGB research and to raise questions about them for brain and behavioural scientists who may not be familiar with the field. The other is to challenge the way in which MGB findings are presented. Our positive goal is to suggest how current problems and weaknesses may be addressed, in order for both scientific and public audiences to gain a clearer picture of MGB research and its strengths and limitations.

The Experimental Study of Bacterial Evolution and Its Implications for the Modern Synthesis of Evolutionary Biology.

Since the 1940s, microbiologists, biochemists and population geneticists have experimented with the genetic mechanisms of microorganisms in order to investigate evolutionary processes. These evolutionary studies of bacteria and other microorganisms gained some recognition from the standard-bearers of the modern synthesis of evolutionary biology, especially Theodosius Dobzhansky and Ledyard Stebbins. A further period of post-synthesis bacterial evolutionary research occurred between the 1950s and 1980s. These experimental analyses focused on the evolution of population and genetic structure, the adaptive gain of new functions, and the evolutionary consequences of competition dynamics. This large body of research aimed to make evolutionary theory testable and predictive, by giving it mechanistic underpinnings. Although evolutionary microbiologists promoted bacterial experiments as methodologically advantageous and a source of general insight into evolution, they also acknowledged the biological differences of bacteria. My historical overview concludes with reflections on what bacterial evolutionary research achieved in this period, and its implications for the still-developing modern synthesis.

Dysbiosis and Its Discontents.

Dysbiosis is a key term in human microbiome research, especially when microbiome patterns are associated with disease states. Although some questions have been raised about how this term is applied, its use continues undiminished in the literature. We investigate the ways in which microbiome researchers discuss dysbiosis and then assess the impact of different concepts of dysbiosis on microbiome research. After an overview of the term's historical roots, we conduct quantitative and qualitative analyses of a large selection of contemporary dysbiosis statements. We categorize both short definitions and longer conceptual statements about dysbiosis. Further analysis allows us to identify the problematic implications of how dysbiosis is used, particularly with regard to causal hypotheses and normal-abnormal distinctions. We suggest that researchers should reflect carefully on the ways in which they discuss dysbiosis, in order for the field to continue to develop greater predictive scope and explanatory depth.

From endosymbiosis to holobionts: Evaluating a conceptual legacy.

In her influential 1967 paper, Lynn Margulis synthesized a range of data to support the idea of endosymbiosis. Building on the success of this work, she applied the same methodology to promote the role of symbiosis more generally in evolution. As part of this broader project, she coined the term 'holobiont' to refer to a unified entity of symbiont and host. This concept is now applied with great gusto in microbiome research, and often implies not just a physiological unit but also various senses of an evolving system. My analysis will track how Margulis came to propose the term, its current use in microbiome research, and how those applications link back to Margulis. I then evaluate what contemporary use says about Margulis's legacy for microbiome research.

Microbiology, philosophy and education.

There are not only many links between microbiological and philosophical topics, but good educational reasons for microbiologists to explore the philosophical issues in their fields. I examine three broad issues of classification, causality and model systems, showing how these philosophical dimensions have practical implications. I conclude with a discussion of the educational benefits for recognising the philosophy in microbiology.

Losing Complexity: The Role of Simplification in Macroevolution.

Macroevolutionary patterns can be produced by combinations of diverse and even oppositional dynamics. A growing body of data indicates that secondary simplifications of molecular and cellular structures are common. Some major diversifications in eukaryotes have occurred because of loss and minimalisation; numerous episodes in prokaryote evolution have likewise been driven by the reduction of structure. After examining a range of examples of secondary simplification and its consequences across the tree of life, we address how macroevolutionary explanations might incorporate simplification as well as complexification, and adaptive as well as nonadaptive dynamics.

The ecological virus.

Ecology is usually described as the study of organisms interacting with one another and their environments. From this view of ecology, viruses - not usually considered to be organisms - would merely be part of the environment. Since the late 1980s, however, a growing stream of micrographic, experimental, molecular, and model-based (theoretical) research has been investigating how and why viruses should be understood as ecological actors of the most important sort. Viruses, especially phage, have been revealed as participants in the planet's most crucial food webs, even though viruses technically consume nothing (they do not metabolize by themselves). Even more impressively, viruses have been identified as regulators of planetary biogeochemistry, in which they control cycles such as carbon, nitrogen and phosphorus - cycles on which all life depends. Although much biogeochemical research black-boxes the entities filling functional roles, it is useful to focus a little more closely to understand how viruses can be held responsible for the global processes of life. This paper will give a brief overview of the history of virus ecology and tease out the implications of large-scale ecological modelling with viruses. This analysis suggests that viruses should be conceptualized as ecological actors that are at least comparable and possibly equal to organismal actors. Ecological agency can therefore be distinguished from standard interpretations of biological agency.

Histories of molecules: Reconciling the past.

Molecular data and methods have become centrally important to evolutionary analysis, largely because they have enabled global phylogenetic reconstructions of the relationships between organisms in the tree of life. Often, however, molecular stories conflict dramatically with morphology-based histories of lineages. The evolutionary origin of animal groups provides one such case. In other instances, different molecular analyses have so far proved irreconcilable. The ancient and major divergence of eukaryotes from prokaryotic ancestors is an example of this sort of problem. Efforts to overcome these conflicts highlight the role models play in phylogenetic reconstruction. One crucial model is the molecular clock; another is that of 'simple-to-complex' modification. I will examine animal and eukaryote evolution against a backdrop of increasing methodological sophistication in molecular phylogeny, and conclude with some reflections on the nature of historical science in the molecular era of phylogeny.

HOW DO MICROBIAL POPULATIONS AND COMMUNITIES FUNCTION AS MODEL SYSTEMS?

Microbial model systems have made major contributions across the life sciences. Their influence extends beyond strictly microbiological research to inform and enhance general biological understanding. To cast light on how microbial populations and communities function as model systems, we examine their use in historical and contemporary research on evolutionary and ecological dynamics. We assess the pros and cons of microbial model systems, and identify specific ways in which they benefit research. Analyzing microbial model systems is of particular value as biologists become increasingly aware of the microbial world and its interactions with the rest of life.

A Philosophical Perspective on Evolutionary Systems Biology.

Evolutionary systems biology (ESB) is an emerging hybrid approach that integrates methods, models, and data from evolutionary and systems biology. Drawing on themes that arose at a cross-disciplinary meeting on ESB in 2013, we discuss in detail some of the explanatory friction that arises in the interaction between evolutionary and systems biology. These tensions appear because of different modeling approaches, diverse explanatory aims and strategies, and divergent views about the scope of the evolutionary synthesis. We locate these discussions in the context of long-running philosophical deliberations on explanation, modeling, and theoretical synthesis. We show how many of the issues central to ESB's progress can be understood as general philosophical problems. The benefits of addressing these philosophical issues feed back into philosophy too, because ESB provides excellent examples of scientific practice for the development of philosophy of science and philosophy of biology.

Endosymbiosis and its implications for evolutionary theory.

Historically, conceptualizations of symbiosis and endosymbiosis have been pitted against Darwinian or neo-Darwinian evolutionary theory. In more recent times, Lynn Margulis has argued vigorously along these lines. However, there are only shallow grounds for finding Darwinian concepts or population genetic theory incompatible with endosymbiosis. But is population genetics sufficiently explanatory of endosymbiosis and its role in evolution? Population genetics "follows" genes, is replication-centric, and is concerned with vertically consistent genetic lineages. It may also have explanatory limitations with regard to macroevolution. Even so, asking whether population genetics explains endosymbiosis may have the question the wrong way around. We should instead be asking how explanatory of evolution endosymbiosis is, and exactly which features of evolution it might be explaining. This paper will discuss how metabolic innovations associated with endosymbioses can drive evolution and thus provide an explanatory account of important episodes in the history of life. Metabolic explanations are both proximate and ultimate, in the same way genetic explanations are. Endosymbioses, therefore, point evolutionary biology toward an important dimension of evolutionary explanation.

Do simple models lead to generality in ecology?

Modellers of biological, ecological, and environmental systems cannot take for granted the maxim 'simple means general means good'. We argue here that viewing simple models as the main way to achieve generality may be an obstacle to the progress of ecological research. We show how complex models can be both desirable and general, and how simple and complex models can be linked together to produce broad-scale and predictive understanding of biological systems.