Deductive automated pollen classification in environmental samples via exploratory deep learning and imaging flow cytometry.

Pollen and tracheophyte spores are ubiquitous environmental indicators at local and global scales. Palynology is typically performed manually by microscopic analysis; a specialised and time-consuming task limited in taxonomical precision and sampling frequency, therefore restricting data quality used to inform climate change and pollen forecasting models. We build on the growing work using AI (artificial intelligence) for automated pollen classification to design a flexible network that can deal with the uncertainty of broad-scale environmental applications. We combined imaging flow cytometry with Guided Deep Learning to identify and accurately categorise pollen in environmental samples; here, pollen grains captured within c. 5500 Cal yr BP old lake sediments. Our network discriminates not only pollen included in training libraries to the species level but, depending on the sample, can classify previously unseen pollen to the likely phylogenetic order, family and even genus. Our approach offers valuable insights into the development of a widely transferable, rapid and accurate exploratory tool for pollen classification in 'real-world' environmental samples with improved accuracy over pure deep learning techniques. This work has the potential to revolutionise many aspects of palynology, allowing a more detailed spatial and temporal understanding of pollen in the environment with improved taxonomical resolution.

The evolution of atmospheric particulate matter in an urban landscape since the Industrial Revolution.

Atmospheric particulate matter (PM) causes 3.7 million annual deaths worldwide and potentially damages every organ in the body. The cancer-causing potential of fine particulates (PM2.5) highlights the inextricable link between air quality and human health. With over half of the world's population living in cities, PM2.5 emissions are a major concern, however, our understanding of exposure to urban PM is restricted to relatively recent (post-1990) air quality monitoring programmes. To investigate how the composition and toxicity of PM has varied within an urban region, over timescales encompassing changing patterns of industrialisation and urbanisation, we reconstructed air pollution records spanning 200 years from the sediments of urban ponds in Merseyside (NW England), a heartland of urbanisation since the Industrial Revolution. These archives of urban environmental change across the region demonstrate a key shift in PM emissions from coarse carbonaceous 'soot' that peaked during the mid-twentieth century, to finer combustion-derived PM2.5 post-1980, mirroring changes in urban infrastructure. The evolution of urban pollution to a recent enhanced PM2.5 signal has important implications for understanding lifetime pollution exposures for urban populations over generational timescales.

Uptake of microplastics by marine worms depends on feeding mode and particle shape but not exposure time.

The uptake of microplastics into marine species has been widely documented across trophic levels. Feeding mode is suggested as playing an important role in determining different contamination loads across species, but this theory is poorly supported with empirical evidence. Here we use the two distinct feeding modes of the benthic polychaete, Hediste diversicolor (The Harbour Ragworm) (O.F. Müller, 1776), to test the hypothesis that filter feeding will lead to a greater uptake of microplastic particles than deposit feeding. Worms were exposed to both polyamide microfragments and microfibres in either water (as filter feeders) or sediment (as deposit feeders) for 1 week. No effect of exposure time was found between 1 day and 1 week (p > 0.19) but feeding mode was found to significantly affect the number of microfibres recovered from each worm (p < 0.001). When exposed to microfibers, filter feeding worms took up ≈15,000 % more fibres than deposit feeding worms (p < 0.001), whereas when feeding on microfragments there was no difference between feeding modes. Our data demonstrate that both feeding mode and particle characteristics significantly influence the uptake of microplastics by H. diversicolor. Using imaging flow cytometry, filter feeders were found to take up a broader size range of particles, with significantly more smaller and larger particles than deposit feeders (p < 0.05), commensurate with the range of plastics isolated from the guts of ragworms recovered from the environment. These results demonstrate that biological traits are useful in understanding the uptake of plastics into marine worms and warrant further exploration as a tool for understanding the bioaccessibility of plastics to marine organisms.

In-situ sequencing reveals the effect of storage on lacustrine sediment microbiome demographics and functionality.

The sediment microbiome is a demographically diverse and functionally active biosphere. Ensuring that data acquired from sediment is truly representative of the microbiome is critical to achieving robust analyses. Sample storage and the processing and timing of nucleic acid purification after environmental sample extraction may fundamentally affect the detectable microbial community and thereby significantly alter resultant data. Direct sequencing of environmental samples is increasingly commonplace due to the advent of the portable Oxford Nanopore MinION sequencing device. Here we demonstrate that storing sediment subsamples at - 20 °C or storing the cores at 4 °C for 10 weeks prior to analysis, has a significant effect on the sediment microbiome analysed using sedimentary DNA (sedDNA), especially for Alpha-, Beta- and Deltaproteobacteria species. Furthermore, these significant differences are observed regardless of sediment type. We show that the taxa which are predominantly affected by storage are Proteobacteria, and therefore recommend on-site purifications are performed to ensure an accurate representation of these taxa are observed in the microbiome. Comparisons of sedimentary RNA (sedRNA) analyses, revealed substantial differences between samples purified and sequenced immediately on-site, samples that were frozen before transportation, and cores that were stored at 4 °C prior to analysis. Our data therefore suggest that a more accurate representation of the sediment microbiome demography and functionality may be achieved by environmental sequencing as rapidly as possible to minimise confounding effects of storage.

The Application of Imaging Flow Cytometry for Characterisation and Quantification of Bacterial Phenotypes.

Bacteria modify their morphology in response to various factors including growth stage, nutrient availability, predation, motility and long-term survival strategies. Morphological changes may also be associated with specific physiological phenotypes such as the formation of dormant or persister cells in a "viable but non-culturable" (VBNC) state which frequently display different shapes and size compared to their active counterparts. Such dormancy phenotypes can display various degrees of tolerance to antibiotics and therefore a detailed understanding of these phenotypes is crucial for combatting chronic infections and associated diseases. Cell shape and size are therefore more than simple phenotypic characteristics; they are important physiological properties for understanding bacterial life-strategies and pathologies. However, quantitative studies on the changes to cell morphologies during bacterial growth, persister cell formation and the VBNC state are few and severely constrained by current limitations in the most used investigative techniques of flow cytometry (FC) and light or electron microscopy. In this study, we applied high-throughput Imaging Flow Cytometry (IFC) to characterise and quantify, at single-cell level and over time, the phenotypic heterogeneity and morphological changes in cultured populations of four bacterial species, Bacillus subtilis, Lactiplantibacillus plantarum, Pediococcus acidilactici and Escherichia coli. Morphologies in relation to growth stage and stress responses, cell integrity and metabolic activity were analysed. Additionally, we were able to identify and morphologically classify dormant cell phenotypes such as VBNC cells and monitor the resuscitation of persister cells in Escherichia coli following antibiotic treatment. We therefore demonstrate that IFC, with its high-throughput data collection and image capture capabilities, provides a platform by which a detailed understanding of changes in bacterial phenotypes and their physiological implications may be accurately monitored and quantified, leading to a better understanding of the role of phenotypic heterogeneity in the dynamic microbiome.

A Hybrid Sequencing Approach Completes the Genome Sequence of Thermoanaerobacter ethanolicus JW 200.

Thermoanaerobacter ethanolicus JW 200 has been identified as a potential sustainable biofuel producer due to its ability to readily ferment carbohydrates to ethanol. A hybrid sequencing approach, combining Oxford Nanopore and Illumina DNA sequence reads, was applied to produce a single contiguous genome sequence of 2,911,280 bp.

Using urban man-made ponds to reconstruct a 150-year history of air pollution in northwest England.

A regional pollution history has been reconstructed for the borough of Halton (northwest England) from four urban ponds in north Cheshire and south Merseyside, using environmental analyses of lake sediment stratigraphies. Mineral magnetism, geochemistry and radiometric dating have produced profiles of pollution characteristics dating from the mid-nineteenth century to present day. These pollution profiles reflect the atmospheric deposition of a range of pollutants over 150 years of intensified industry. Distinct phases of pollution deposition and characteristics are identified reflecting: (1) intensification of industry in the nineteenth century; (2) expansion of industry during the twentieth century; (3) post 1956 Clean Air Acts. This work promotes the potential use of these pollution archives for use in epidemiology to better understand links between human health and environmental pollution, especially for diseases with long latency times, where retrospective pollution exposure assessments are important.

Magneto-biomonitoring of intra-urban spatial variations of particulate matter using tree leaves.

Preliminary mineral magnetic results from a pilot project investigating the suitability of roadside tree leaves as depositories of vehicular pollution are presented. Tree leaf surfaces (Lime: Tilia europaea; Sycamore: Acer pseudoplatanus) at four roadside and one woodland location in Wolverhampton, UK, have been monitored (July 2003 to November 2003). Mineral magnetic technologies have revealed spatial variations of particulate pollution concentration throughout the conurbation and data analysis indicates that magnetic concentration parameters are suitable proxies for fine particulate pollution, which are particularly hazardous to health. Site-specific traffic management and associated vehicle behaviour appear to be chiefly responsible for the magnetic concentration differences between sites. Magneto-biomonitoring in this way allows the high-resolution spatial mapping of particulate matter (PM) pollution, which may also benefit epidemiology in better assessing exposure to vehicular-derived particulates. Given the speed, measurement sensitivity and non-destructive nature of the technique, it is proposed that this low-cost approach offers some advantages over centralised monitoring stations to monitor urban roadside particulate pollution.