Biogeographic patterns in ocean microbes emerge in a neutral agent-based model.

A key question in ecology and evolution is the relative role of natural selection and neutral evolution in producing biogeographic patterns. We quantify the role of neutral processes by simulating division, mutation, and death of 100,000 individual marine bacteria cells with full 1 million-base-pair genomes in a global surface ocean circulation model. The model is run for up to 100,000 years and output is analyzed using BLAST (Basic Local Alignment Search Tool) alignment and metagenomics fragment recruitment. Simulations show the production and maintenance of biogeographic patterns, characterized by distinct provinces subject to mixing and periodic takeovers by neighbors (coalescence), after which neutral evolution reestablishes the province and the patterns reorganize. The emergent patterns are substantial (e.g., down to 99.5% DNA identity between North and Central Pacific provinces) and suggest that microbes evolve faster than ocean currents can disperse them. This approach can also be used to explore environmental selection

Towards a Processual Microbial Ontology

types: ArticleStandard microbial evolutionary ontology is organized according to a nested hierarchy of entities at various levels of biological organization. It typically detects and defines these entities in relation to the most stable aspects of evolutionary processes, by identifying lineages evolving by a process of vertical inheritance from an ancestral entity. However, recent advances in microbiology indicate that such an ontology has important limitations. The various dynamics detected within microbiological systems reveal that a focus on the most stable entities (or features of entities) over time inevitably underestimates the extent and nature of microbial diversity. These dynamics are not the outcome of the process of vertical descent alone. Other processes, often involving causal interactions between entities from distinct levels of biological organisation, or operating at different time scales, are responsible not only for the destabilisation of pre-existing entities, but also for the emergence and stabilisation of novel entities in the microbial world. In this article we consider microbial entities as more or less stabilised functional wholes, and sketch a network-based ontology that can represent a diverse set of processes including, for example, as well as phylogenetic relations, interactions that stabilise or destabilise the interacting entities, spatial relations, ecological connections, and genetic exchanges. We use this pluralistic framework for evaluating (i) the existing ontological assumptions in evolution (e.g. whether currently recognized entities are adequate for understanding the causes of change and stabilisation in the microbial world), and (ii) for identifying hidden ontological kinds, essentially invisible from within a more limited perspective. We propose to recognize additional classes of entities that provide new insights into the structure of the microbial world, namely ‘‘processually equivalent’’ entities, ‘‘processually versatile’’ entities, and ‘‘stabilized’’ entities.Economic and Social Research Council, U

Send more data: a systematic review of mathematical models of antimicrobial resistance

Abstract Background Antimicrobial resistance is a global health problem that demands all possible means to control it. Mathematical modelling is a valuable tool for understanding the mechanisms of AMR development and spread, and can help us to investigate and propose novel control strategies. However, it is of vital importance that mathematical models have a broad utility, which can be assured if good modelling practice is followed. Objective The objective of this study was to provide a comprehensive systematic review of published models of AMR development and spread. Furthermore, the study aimed to identify gaps in the knowledge required to develop useful models. Methods The review comprised a comprehensive literature search with 38 selected studies. Information was extracted from the selected papers using an adaptation of previously published frameworks, and was evaluated using the TRACE good modelling practice guidelines. Results None of the selected papers fulfilled the TRACE guidelines. We recommend that future mathematical models should: a) model the biological processes mechanistically, b) incorporate uncertainty and variability in the system using stochastic modelling, c) include a sensitivity analysis and model external and internal validation. Conclusion Many mathematical models of AMR development and spread exist. There is still a lack of knowledge about antimicrobial resistance, which restricts the development of useful mathematical models

A review on substances and processes relevant for optical remote sensing of extremely turbid marine areas, with a focus on the Wadden Sea

The interpretation of optical remote sensing data of estuaries and tidal flat areas is hampered by optical complexity and often extreme turbidity. Extremely high concentrations of suspended matter, chlorophyll and dissolved organic matter, local differences, seasonal and tidal variations and resuspension are important factors influencing the optical properties in such areas. This review gives an overview of the processes in estuaries and tidal flat areas and the implications of these for remote sensing in such areas, using the Wadden Sea as a case study area. Results show that remote sensing research in extremely turbid estuaries and tidal areas is possible. However, this requires sensors with a large ground resolution, algorithms tuned for high concentrations of various substances and the local specific optical properties of these substances, a simultaneous detection of water colour and land-water boundaries, a very short time lag between acquisition of remote sensing and in situ data used for validation and sufficient geophysical and ecological knowledge of the area. © 2010 The Author(s)

Advancing microbial sciences by individual-based modelling

Remarkable technological advances have revealed ever more properties and behaviours of individual microorganisms, but the novel data generated by these techniques have not yet been fully exploited. In this Opinion article, we explain how individual-based models (IBMs) can be constructed based on the findings of such techniques and how they help to explore competitive and cooperative microbial interactions. Furthermore, we describe how IBMs have provided insights into self-organized spatial patterns from biofilms to the oceans of the world, phage-CRISPR dynamics and other emergent phenomena. Finally, we discuss how combining individual-based observations with IBMs can advance our understanding at both the individual and population levels, leading to the new approach of microbial individual-based ecology (μIBE)

Energy limitation of cyanophage development : implications for marine carbon cycling

RJP was in receipt of a Natural Environment Research Council (NERC) PhD studentship and a Warwick University IAS Fellowship. This work was also supported in part by NERC grant NE/N003241/1 and Leverhulme Trust grant RPG-2014-354 to A.D.M., D.J.E., and D.J.S.Marine cyanobacteria are responsible for ~25% of the fixed carbon that enters the ocean biosphere. It is thought that abundant co-occurring viruses play an important role in regulating population dynamics of cyanobacteria and thus the cycling of carbon in the oceans. Despite this, little is known about how viral infections ‘play-out’ in the environment, particularly whether infections are resource or energy limited. Photoautotrophic organisms represent an ideal model to test this since available energy is modulated by the incoming light intensity through photophosphorylation. Therefore, we exploited phototrophy of the environmentally relevant marine cyanobacterium Synechococcus and monitored growth of a cyanobacterial virus (cyanophage). We found that light intensity has a marked effect on cyanophage infection dynamics, but that this is not manifest by a change in DNA synthesis. Instead, cyanophage development appears energy limited for the synthesis of proteins required during late infection. We posit that acquisition of auxiliary metabolic genes (AMGs) involved in light-dependent photosynthetic reactions acts to overcome this limitation. We show that cyanophages actively modulate expression of these AMGs in response to light intensity and provide evidence that such regulation may be facilitated by a novel mechanism involving light-dependent splicing of a group I intron in a photosynthetic AMG. Altogether, our data offers a mechanistic link between diurnal changes in irradiance and observed community level responses in metabolism, i.e., through an irradiance-dependent, viral-induced release of dissolved organic matter (DOM).Publisher PDFPeer reviewe

Harmful Elements in Estuarine and Coastal Systems

Estuaries and coastal zones are dynamic transitional systems which provide many economic and ecological benefits to humans, but also are an ideal habitat for other organisms as well. These areas are becoming contaminated by various anthropogenic activities due to a quick economic growth and urbanization. This chapter explores the sources, chemical speciation, sediment accumulation and removal mechanisms of the harmful elements in estuarine and coastal seawaters. It also describes the effects of toxic elements on aquatic flora and fauna. Finally, the toxic element pollution of the Venice Lagoon, a transitional water body located in the northeastern part of Italy, is discussed as a case study, by presenting the procedures adopted to measure the extent of the pollution, the impacts on organisms and the restoration activities

The role of ocean currents in the temperature selection of plankton: insights from an individual-based model.

Biogeography studies that correlate the observed distribution of organisms to environmental variables are typically based on local conditions. However, in cases with substantial translocation, like planktonic organisms carried by ocean currents, selection may happen upstream and local environmental factors may not be representative of those that shaped the local population. Here we use an individual-based model of microbes in the global surface ocean to explore this effect for temperature. We simulate up to 25 million individual cells belonging to up to 50 species with different temperature optima. Microbes are moved around the globe based on a hydrodynamic model, and grow and die based on local temperature. We quantify the role of currents using the "advective temperature differential" metric, which is the optimum temperature of the most abundant species from the model with advection minus that from the model without advection. This differential depends on the location and can be up to 4°C. Poleward-flowing currents, like the Gulf Stream, generally experience cooling and the differential is positive. We apply our results to three global datasets. For observations of optimum growth temperature of phytoplankton, accounting for the effect of currents leads to a slightly better agreement with observations, but there is large variability and the improvement is not statistically significant. For observed Prochlorococcus ecotype ratios and metagenome nucleotide divergence, accounting for advection improves the correlation significantly, especially in areas with relatively strong poleward or equatorward currents

Advancing microbial sciences by individual-based modeling

Remarkable technological advances have revealed ever more properties and behaviours of individual microorganisms, but the novel data generated by these techniques have not yet been fully exploited. In this Opinion article, we explain how individual-based models (IBMs) can be constructed based on the findings of such techniques and how they help to explore competitive and cooperative microbial interactions. Furthermore, we describe how IBMs have provided insights into self-organized spatial patterns from biofilms to the oceans of the world, phage-CRISPR dynamics and other emergent phenomena. Finally, we discuss how combining individual-based observations with IBMs can advance our understanding at both the individual and population levels, leading to the new approach of microbial individual-based ecology (uIBE)

Understanding the evolution of interspecies interactions in microbial communities

ISSN:0962-8436ISSN:1471-2970ISSN:0080-462