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.

Metagenomic analysis of ethylene glycol contamination in anaerobic digestion.

Anaerobic digestion is an established method for the biological conversion of waste feedstocks to biogas and biomethane. While anaerobic digestion is an excellent waste management technique, it can be susceptible to toxins and pollutants from contaminated feedstocks, which may have a detrimental impact on a digester's efficiency and productivity. Ethylene glycol (EG) is readily used in the heat-transfer loops of anaerobic digestion facilities to maintain reactor temperature. Failure of the structural integrity of these heat transfer loops can cause EG to leak into the digester, potentially causing a decrease in the resultant gas yields. Batch fermentations were incubated with 0, 10, 100 and 500 ppm (parts per million) of EG, and analysis showed that the EG was completely metabolised by the digester microbiome. The concentrations of EG tested showed significant increases in gas yields, however there were no significant changes to the digester microbiome.

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.

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.

Draft Genome Sequence of Weissella paramesenteroides STCH-BD1, Isolated from Ensiled Sorghum bicolor.

Weissella paramesenteroides has potential as an industrial biocatalyst due to its ability to produce lactic acid. A novel strain of W. paramesenteroides was isolated from ensiled sorghum. The genome was sequenced using a hybrid assembly of Oxford Nanopore and Illumina data to produce a 2-Mbp genome and 22-kbp plasmid sequence.

Bacterial dormancy: A subpopulation of viable but non-culturable cells demonstrates better fitness for revival.

The viable but non culturable (VBNC) state is a condition in which bacterial cells are viable and metabolically active, but resistant to cultivation using a routine growth medium. We investigated the ability of V. parahaemolyticus to form VBNC cells, and to subsequently become resuscitated. The ability to control VBNC cell formation in the laboratory allowed us to selectively isolate VBNC cells using fluorescence activated cell sorting, and to differentiate subpopulations based on their metabolic activity, cell shape and the ability to cause disease in Galleria mellonella. Our results showed that two subpopulations (P1 and P2) of V. parahaemolyticus VBNC cells exist and can remain dormant in the VBNC state for long periods. VBNC subpopulation P2, had a better fitness for survival under stressful conditions and showed 100% revival under favourable conditions. Proteomic analysis of these subpopulations (at two different time points: 12 days (T12) and 50 days (T50) post VBNC) revealed that the proteome of P2 was more similar to that of the starting microcosm culture (T0) than the proteome of P1. Proteins that were significantly up or down-regulated between the different VBNC populations were identified and differentially regulated proteins were assigned into 23 functional groups, the majority being assigned to metabolism functional categories. A lactate dehydrogenase (lldD) protein, responsible for converting lactate to pyruvate, was significantly upregulated in all subpopulations of VBNC cells. Deletion of the lactate dehydrogenase (RIMD2210633:ΔlldD) gene caused cells to enter the VBNC state significantly more quickly compared to the wild-type, and adding lactate to VBNC cells aided their resuscitation and extended the resuscitation window. Addition of pyruvate to the RIMD2210633:ΔlldD strain restored the wild-type VBNC formation profile. This study suggests that lactate dehydrogenase may play a role in regulating the VBNC state.

Campylobacter jejuni 11168H Exposed to Penicillin Forms Persister Cells and Cells With Altered Redox Protein Activity.

The formation of persister cells is one mechanism by which bacteria can survive exposure to environmental stresses. We show that Campylobacter jejuni 11168H forms persister cells at a frequency of 10-3 after exposure to 100 × MIC of penicillin G for 24 h. Staining the cell population with a redox sensitive fluorescent dye revealed that penicillin G treatment resulted in the appearance of a population of cells with increased fluorescence. We present evidence, to show this could be a consequence of increased redox protein activity in, or associated with, the electron transport chain. These data suggest that a population of penicillin G treated C. jejuni cells could undergo a remodeling of the electron transport chain in order to moderate membrane hyperpolarization and intracellular alkalization; thus reducing the antibiotic efficacy and potentially assisting in persister cell formation.

Rapid, Heuristic Discovery and Design of Promoter Collections in Non-Model Microbes for Industrial Applications.

Well-characterized promoter collections for synthetic biology applications are not always available in industrially relevant hosts. We developed a broadly applicable method for promoter identification in atypical microbial hosts that requires no a priori understanding of cis-regulatory element structure. This novel approach combines bioinformatic filtering with rapid empirical characterization to expand the promoter toolkit and uses machine learning to improve the understanding of the relationship between DNA sequence and function. Here, we apply the method in Geobacillus thermoglucosidasius, a thermophilic organism with high potential as a synthetic biology chassis for industrial applications. Bioinformatic screening of G. kaustophilus, G. stearothermophilus, G. thermodenitrificans, and G. thermoglucosidasius resulted in the identification of 636 100 bp putative promoters, encompassing the genome-wide design space and lacking known transcription factor binding sites. Eighty of these sequences were characterized in vivo, and activities covered a 2-log range of predictable expression levels. Seven sequences were shown to function consistently regardless of the downstream coding sequence. Partition modeling identified sequence positions upstream of the canonical -35 and -10 consensus motifs that were predicted to strongly influence regulatory activity in Geobacillus, and artificial neural network and partial least squares regression models were derived to assess if there were a simple, forward, quantitative method for in silico prediction of promoter function. However, the models were insufficiently general to predict pre hoc promoter activity in vivo, most probably as a result of the relatively small size of the training data set compared to the size of the modeled design space.

Higher levels of B-cell mutation in the early germinal centres of an inefficient secondary antibody response to a variant influenza haemagglutinin.

Designing improved vaccines against mutable viruses such as dengue and influenza would be helped by a better understanding of how the B-cell memory compartment responds to variant antigens. Towards this we have recently shown, after secondary immunization of mice with a widely variant dengue virus envelope protein with only 63% amino acid identity, that IgM+ memory B cells with few mutations supported an efficient secondary germinal centre (GC) and serum response, superior to a primary response to the same protein. Here, further investigation of memory responses to variant proteins, using more closely related influenza virus haemagglutinins (HA) that were 82% identical, produced a variant-induced boost response in the GC dominated by highly mutated B cells that failed, not efficiently improving serum avidity even in the presence of extra adjuvant, and that was worse than a primary response. This supports a hypothesis that over a certain level of antigenic differences, cross-reactive memory B-cell populations have reduced competency for affinity maturation. Combined with our previous observations, these findings also provide new parameters of success and failure in antibody memory responses.

Palaeogenomics of the Hydrocarbon Producing Microalga Botryococcus braunii.

Botryococcus braunii is a colonial microalga that appears early in the fossil record and is a sensitive proxy of environmental and hydroclimatic conditions. Palaeozoic Botryococcus fossils which contribute up to 90% of oil shales and approximately 1% of crude oil, co-localise with diagnostic geolipids from the degradation of source-signature hydrocarbons. However more recent Holocene sediments demonstrate no such association. Consequently, Botryococcus are identified in younger sediments by morphology alone, where potential misclassifications could lead to inaccurate paleoenvironmental reconstructions. Here we show that a combination of flow cytometry and ancient DNA (aDNA) sequencing can unambiguously identify Botryococcus microfossils in Holocene sediments with hitherto unparalleled accuracy and rapidity. The application of aDNA sequencing to microfossils offers a far-reaching opportunity for understanding environmental change in the recent geological record. When allied with other high-resolution palaeoenvironmental information such as aDNA sequencing of humans and megafauna, aDNA from microfossils may allow a deeper and more precise understanding of past environments, ecologies and migrations.

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.

Variant proteins stimulate more IgM+ GC B-cells revealing a mechanism of cross-reactive recognition by antibody memory.

Vaccines induce memory B-cells that provide high affinity secondary antibody responses to identical antigens. Memory B-cells can also re-instigate affinity maturation, but how this happens against antigenic variants is poorly understood despite its potential impact on driving broadly protective immunity against pathogens such as Influenza and Dengue. We immunised mice sequentially with identical or variant Dengue-virus envelope proteins and analysed antibody and germinal-centre (GC) responses. Variant protein boosts induced GCs with a higher proportion of IgM+ B cells. The most variant protein re-stimulated GCs with the highest proportion of IgM+ cells with the most diverse, least mutated V-genes and with a slower but efficient serum antibody response. Recombinant antibodies from GC B-cells showed a higher affinity for the variant antigen than antibodies from a primary response, confirming a memory origin. This reveals a new process of antibody memory, that IgM memory cells with fewer mutations participate in secondary responses to variant antigens, demonstrating how the hierarchical structure of B-cell memory is used and indicating the potential and limits of cross-reactive antibody based immunity.

Metagenomic Analysis of Silage.

Metagenomics is defined as the direct analysis of deoxyribonucleic acid (DNA) purified from environmental samples and enables taxonomic identification of the microbial communities present within them. Two main metagenomic approaches exist; sequencing the 16S rRNA gene coding region, which exhibits sufficient variation between taxa for identification, and shotgun sequencing, in which genomes of the organisms that are present in the sample are analyzed and ascribed to "operational taxonomic units"; species, genera or families depending on the extent of sequencing coverage. In this study, shotgun sequencing was used to analyze the microbial community present in cattle silage and, coupled with a range of bioinformatics tools to quality check and filter the DNA sequence reads, perform taxonomic classification of the microbial populations present within the sampled silage, and achieve functional annotation of the sequences. These methods were employed to identify potentially harmful bacteria that existed within the silage, an indication of silage spoilage. If spoiled silage is not remediated, then upon ingestion it could be potentially fatal to the livestock.