High prices for rare species can drive large populations extinct: the anthropogenic Allee effect revisited

Consumer demand for plant and animal products threatens many populations with extinction. The anthropogenic Allee effect (AAE) proposes that such extinctions can be caused by prices for wildlife products increasing with species rarity. This price-rarity relationship creates financial incentives to extract the last remaining individuals of a population, despite higher search and harvest costs. The AAE has become a standard approach for conceptualizing the threat of economic markets on endangered species. Despite its potential importance for conservation, AAE theory is based on a simple graphical model with limited analysis of possible population trajectories. By specifying a general class of functions for price-rarity relationships, we show that the classic theory can understate the risk of species extinction. AAE theory proposes that only populations below a critical Allee threshold will go extinct due to increasing price-rarity relationships. Our analysis shows that this threshold can be much higher than the original theory suggests, depending on initial harvest effort. More alarmingly, even species with population sizes above this Allee threshold, for which AAE predicts persistence, can be destined to extinction. Introducing even a minimum price for harvested individuals, close to zero, can cause large populations to cross the classic anthropogenic Allee threshold on a trajectory towards extinction. These results suggest that traditional AAE theory may give a false sense of security when managing large harvested populations

Clinical Perspectives in Integrating Whole Genome Sequencing into the Investigation of Healthcare and Public Health Outbreaks - Hype or Help?

Bioinformatics and Computational Biology analyses were supported by the University of St Andrews Bioinformatics Unit which is funded by a Wellcome Trust ISSF award [grant 097831/Z/11/Z]. The SHAIPI consortium is funded by the Chief Scientist Office through the Scottish Infection Research Network (SIRN10).Outbreaks pose a significant patient safety risk as well as being costly and time consuming to investigate. The implementation of targeted infection prevention and control (IPC) measures relies on infection prevention and control teams (IPCTs) having access to rapid results that accurately detect resistance, and typing results that give clinically useful information on the relatedness of isolates. At present, determining whether transmission has occurred can be a major challenge. Conventional typing results do not always have sufficient granularity or robustness to unequivocally define strains, and sufficient epidemiological data to establish links between patients and the environment is not always available. Whole genome sequencing (WGS) has emerged as the ultimate genotyping tool, but has not yet fully crossed the divide between research method and routine clinical diagnostic microbiology technique. A clinical WGS service was officially established in 2014 as part of the Scottish Healthcare Associated Infection Prevention Institute (SHAIPI) to confirm or refute outbreaks in hospital settings from across Scotland. In this personal view we describe our experiences that we believe provide new insights into the practical application of the use of WGS to investigate healthcare and public health outbreaks. We also propose solutions to overcome barriers to implementation of this technology in a clinical environment.Publisher PDFPeer reviewe

Comprehensive Immune Monitoring of Clinical Trials to Advance Human Immunotherapy.

The success of immunotherapy has led to a myriad of clinical trials accompanied by efforts to gain mechanistic insight and identify predictive signatures for personalization. However, many immune monitoring technologies face investigator bias, missing unanticipated cellular responses in limited clinical material. We present here a mass cytometry (CyTOF) workflow for standardized, systems-level biomarker discovery in immunotherapy trials. To broadly enumerate immune cell identity and activity, we established and extensively assessed a reference panel of 33 antibodies to cover major cell subsets, simultaneously quantifying activation and immune checkpoint molecules in a single assay. This assay enumerates ≥98% of peripheral immune cells with ≥4 positively identifying antigens. Robustness and reproducibility are demonstrated on multiple samples types, across two research centers and by orthogonal measurements. Using automated analysis, we identify stratifying immune signatures in bone marrow transplantation-associated graft-versus-host disease. Together, this validated workflow ensures comprehensive immunophenotypic analysis and data comparability and will accelerate biomarker discovery

The molecular basis of thioalcohol production in human body odour

This work was supported by the BBSRC Grant BB/N006615/1.Body odour is a characteristic trait of Homo sapiens, however its role in human behaviour and evolution is poorly understood. Remarkably, body odour is linked to the presence of a few species of commensal microbes. Herein we discover a bacterial enzyme, limited to odour-forming staphylococci that are able to cleave odourless precursors of thioalcohols, the most pungent components of body odour. We demonstrated using phylogenetics, biochemistry and structural biology that this cysteine-thiol lyase (C-T lyase) is a PLP-dependent enzyme that moved horizontally into a unique monophyletic group of odour-forming staphylococci about 60 million years ago, and has subsequently tailored its enzymatic function to human-derived thioalcohol precursors. Significantly, transfer of this enzyme alone to non-odour producing staphylococci confers odour production, demonstrating that this C-T lyase is both necessary and sufficient for thioalcohol formation. The structure of the C-T lyase compared to that of other related enzymes reveals how the adaptation to thioalcohol precursors has evolved through changes in the binding site to create a constrained hydrophobic pocket that is selective for branched aliphatic thioalcohol ligands. The ancestral acquisition of this enzyme, and the subsequent evolution of the specificity for thioalcohol precursors implies that body odour production in humans is an ancient process.Publisher PDFPeer reviewe

Cryopreservation of a soil microbiome using a Stirling 1 cycle approach - a genomic assessment

Soil microbiomes are dynamic systems that respond to biotic and abiotic environmental factors such as those presented at seasonal scales or due to long-term anthropogenic regime shifts. These can affect the composition and function of microbiomes. Investigation of microbiomes can uncover hidden microbial roles in health and disease and discover microbiome-based interventions. Collections of soil samples are kept by various institutions in either a refrigerated or occasionally frozen state, but conditions are not optimised to ensure the integrity of soil microbiome. In this manuscript, we describe cryopreservation with a controlled rate cooler and estimate the genomic content of an exemplar soil sample before and after cryopreservation. The first hypothesis was to test the genomic integrity of the microbiome. We also enriched the soil sample with a liquid medium to estimate the growth of bacteria and compared their growth before and after cryopreservation. Sequence-based rRNA metabarcoding was used to demonstrate that the controlled rate cooler maintains intact the DNA content of the microbiome. Two methods of cryopreservation were applied and compared with control aliquots of soil. An optimised cryopreservation of soil samples is essential for the development of microbiome research in order to retain stable, functionally intact microbiomes. Our results showed that metabarcoding of 16S and ITS rRNA were useful methods to estimate successful cryopreservation. The soil microbiome after enrichment with liquid medium exhibited a similar response of cryopreserved soil and this was estimated with the comparison of the ten most abundant bacterial taxa. These findings support a successful process of cryopreservation and are promising for future use of this technology. To the best of our knowledge, this study is the first report of cryopreservation of soil using a Stirling cycle cooling approach

Consideration of within-patient diversity highlights transmission pathways and antimicrobial resistance gene variability in vancomycin-resistant Enterococcus faecium

BackgroundWGS is increasingly being applied to healthcare-associated vancomycin-resistant Enterococcus faecium (VREfm) outbreaks. Within-patient diversity could complicate transmission resolution if single colonies are sequenced from identified cases.ObjectivesDetermine the impact of within-patient diversity on transmission resolution of VREfm.Materials and methodsFourteen colonies were collected from VREfm positive rectal screens, single colonies were collected from clinical samples and Illumina WGS was performed. Two isolates were selected for Oxford Nanopore sequencing and hybrid genome assembly to generate lineage-specific reference genomes. Mapping to closely related references was used to identify genetic variations and closely related genomes. A transmission network was inferred for the entire genome set using Phyloscanner.Results and discussionIn total, 229 isolates from 11 patients were sequenced. Carriage of two or three sequence types was detected in 27% of patients. Presence of antimicrobial resistance genes and plasmids was variable within genomes from the same patient and sequence type. We identified two dominant sequence types (ST80 and ST1424), with two putative transmission clusters of two patients within ST80, and a single cluster of six patients within ST1424. We found transmission resolution was impaired using fewer than 14 colonies.ConclusionsPatients can carry multiple sequence types of VREfm, and even within related lineages the presence of mobile genetic elements and antimicrobial resistance genes can vary. VREfm within-patient diversity could be considered in future to aid accurate resolution of transmission networks

Informing network management using fuzzy cognitive maps

Modern conservation requires robust predictions about how management will affect an ecosystem and its species. The large uncertainties about the type and strength of interactions make model predictions particularly unreliable. In this paper, we show how fuzzy cognitive maps can produce robust predictions in complex and uncertain ecosystems. The use of fuzzy cognitive maps has been increasing markedly, but there are two critical issues with the approach: translation of expert knowledge into the FCM is often done incorrectly; and sensitivity analyses are rarely conducted. Translating expert knowledge is a constant challenge for ecological modellers, often because experts know about the behaviour of a system, but modellers need to know model parameters, which subsequently lead to system behaviour. We describe how to correctly incorporate expert knowledge into FCMs, and we describe how to appropriately conduct uncertainty and sensitivity analysis. We illustrate this process with a previously published network for feral cat and black rat control on Christmas Island. Perverse indirect effects of conservation management are a key concern, and methods to help us make informed decisions are required. Fuzzy cognitive maps are a promising approach for this, but it requires the methodological improvements that we present here

From climate change to pandemics: decision science can help scientists have impact

Scientific knowledge and advances are a cornerstone of modern society. They improve our understanding of the world we live in and help us navigate global challenges including emerging infectious diseases, climate change and the biodiversity crisis. For any scientist, whether they work primarily in fundamental knowledge generation or in the applied sciences, it is important to understand how science fits into a decision-making framework. Decision science is a field that aims to pinpoint evidence-based management strategies. It provides a framework for scientists to directly impact decisions or to understand how their work will fit into a decision process. Decision science is more than undertaking targeted and relevant scientific research or providing tools to assist policy makers; it is an approach to problem formulation, bringing together mathematical modelling, stakeholder values and logistical constraints to support decision making. In this paper we describe decision science, its use in different contexts, and highlight current gaps in methodology and application. The COVID-19 pandemic has thrust mathematical models into the public spotlight, but it is one of innumerable examples in which modelling informs decision making. Other examples include models of storm systems (eg. cyclones, hurricanes) and climate change. Although the decision timescale in these examples differs enormously (from hours to decades), the underlying decision science approach is common across all problems. Bridging communication gaps between different groups is one of the greatest challenges for scientists. However, by better understanding and engaging with the decision-making processes, scientists will have greater impact and make stronger contributions to important societal problems

The UK Crop Microbiome Cryobank: a utility and model for supporting Phytobiomes research

Plant microbiomes are the microbial communities essential to the functioning of the phytobiome—the system that consist of plants, their environment, and their associated communities of organisms. A healthy, functional phytobiome is critical to crop health, improved yields and quality food. However, crop microbiomes are relatively under-researched, and this is associated with a fundamental need to underpin phytobiome research through the provision of a supporting infrastructure. The UK Crop Microbiome Cryobank (UKCMC) project is developing a unique, integrated and open-access resource to enable the development of solutions to improve soil and crop health. Six economically important crops (Barley, Fava Bean, Oats, Oil Seed Rape, Sugar Beet and Wheat) are targeted, and the methods as well as data outputs will underpin research activity both in the UK and internationally. This manuscript describes the approaches being taken, from characterisation, cryopreservation and analysis of the crop microbiome through to potential applications. We believe that the model research framework proposed is transferable to different crop and soil systems, acting not only as a mechanism to conserve biodiversity, but as a potential facilitator of sustainable agriculture systems