The microbial diversity of watermelon snow

During summer months in alpine systems around the world patches of green, orange and red snow appear. The phenomenon is sometimes called watermelon snow and is caused by a bloom of microalgae. The resulting microbiome is teeming with life, including algae, fungi, metazoans, other protists and bacteria. Here, I present data documenting the biological diversity in the ephemeral snow algae microbiome, which grows on snows threatened by global warming. I began by asking: what microbes are found in snow algae blooms? I focussed my work in the southwestern Coastal Mountain Range in B.C., Canada. The data I present detail the algal, bacterial, fungal, metazoan and other protist diversity in blooms and their distribution across the region. These data included sequences from undescribed algal species, with some potentially belonging to species names with no DNA data available. I therefore did an analysis, including five novel algal isolates, to clarify the taxonomy of Raphidonema and its sister genera, using genetic data. I was able to identify my five isolates as R. sempervirens, and in the process name two novel species: R. catena and R. monicae. As bacteria are commonly important mutualistic symbionts of microalgae, I next described their communities living alongside snow algae. I found that, unlike algae, the bacterial community composition does not change with elevation, and instead there are regionally widespread bacteria. I therefore wanted to learn more about the metabolic capabilities of these bacteria common to snow algae blooms. Using a shotgun metagenomics approach, I analyzed the bacterial metagenome, and metagenomically assembled genomes. These data included representative from the widespread bacterial families found during metabarcoding, and I furthered that analysis by describing their metabolic genes related to: nitrogen and sulfur cycling as well as biosynthesis of osmolytes/cryoprotectants, B-vitamins, phytohormones, and xanthophyll pigments. These data act as observations to form hypotheses on the biogeochemistry and microbial ecology of snow algae microbiomes

Phenotype-preserving metric design for high-content image reconstruction by generative inpainting

In the past decades, automated high-content microscopy demonstrated its ability to deliver large quantities of image-based data powering the versatility of phenotypic drug screening and systems biology applications. However, as the sizes of image-based datasets grew, it became infeasible for humans to control, avoid and overcome the presence of imaging and sample preparation artefacts in the images. While novel techniques like machine learning and deep learning may address these shortcomings through generative image inpainting, when applied to sensitive research data this may come at the cost of undesired image manipulation. Undesired manipulation may be caused by phenomena such as neural hallucinations, to which some artificial neural networks are prone. To address this, here we evaluate the state-of-the-art inpainting methods for image restoration in a high-content fluorescence microscopy dataset of cultured cells with labelled nuclei. We show that architectures like DeepFill V2 and Edge Connect can faithfully restore microscopy images upon fine-tuning with relatively little data. Our results demonstrate that the area of the region to be restored is of higher importance than shape. Furthermore, to control for the quality of restoration, we propose a novel phenotype-preserving metric design strategy. In this strategy, the size and count of the restored biological phenotypes like cell nuclei are quantified to penalise undesirable manipulation. We argue that the design principles of our approach may also generalise to other applications.Comment: 8 pages, 3 figures, conference proceeding

Examining anaerobic microbial communities that direct the fate of terrestrial carbon in lake sediments.

Freshwater lake sediments play key roles in the cycling of carbon. This includes hosting microbial communities responsible for mineralizing large amounts of carbon into greenhouse gases—namely CO2 and CH4. Yet despite the important roles of sediment communities, their ecology and community structure linkages to biogeochemical cycling are not well known, and little data exists exploring how sediment microbial communities respond to different organic matter inputs. Here I start by reviewing previous literature on lake sediment microbial communities and the physicochemical factors affecting their composition and diversity. Next I report on data from two experiments, first an in-vitro lab study and then an in-situ field study, in which lake sediments were amended with different plant litters that could result from land use change and or succession in catchments. Microbial communities were examined with next generation amplicon sequencing. These data were linked to rates of CO2 and CH4 flux and dissolved organic matter (DOM) components present in pore water were examined as potential controls on community structure and function. I observed in-vitro that methanogen community composition and activity were affected by OM type, with macrophyte derived C enhancing microbial activity, whereas high concentrations of polyphenolic compounds from terrestrial tree litters inhibited methanogen activity. The polyphenols had an environmental filtering effect, selecting for different bacteria, fungi and methanogen communities. The in-situ experiments involved installing mesocosms with artificial sediments with variable amounts of deciduous and coniferous tree leaf litter. In these mesocosms we observed a link between methanogen community composition and decomposition rates, as measured with bulk CO2 and CH4 production and DOM humification. Decomposition rates were influenced by lake physicochemical factors, particularly the degree of photoexposure. With increased decomposition, specialist taxa of methanogens could thrive that conferred higher rates of methanogenesis. The work presented here demonstrates the adaptability of methanogen lake sediment communities as terminal decomposers under changing terrestrial OM subsidies.Master of Science (MSc) in Biolog

mSphere of Influence: the Rise of Artificial Intelligence in Infection Biology

Artur Yakimovich works in the field of computational virology and applies machine learning algorithms to study host-pathogen interactions. In this mSphere of Influence article, he reflects on two papers "Holographic Deep Learning for Rapid Optical Screening of Anthrax Spores" by Jo et al. (Y. Jo, S. Park, J. Jung, J. Yoon, et al., Sci Adv 3:e1700606, 2017, https://doi.org/10.1126/sciadv. 1700606) and "Bacterial Colony Counting with Convolutional Neural Networks in Digital Microbiology Imaging" by Ferrari and colleagues (A. Ferrari, S. Lombardi, and A. Signoroni, Pattern Recognition 61:629-640, 2017, https://doi.org/10.1016/j.patcog.2016.07.016). Here he discusses how these papers made an impact on him by showcasing that artificial intelligence algorithms can be equally applicable to both classical infection biology techniques and cutting-edge label-free imaging of pathogens

Imaging, Tracking and Computational Analyses of Virus Entry and Egress with the Cytoskeleton

Viruses have a dual nature: particles are “passive substances” lacking chemical energy transformation, whereas infected cells are “active substances” turning-over energy. How passive viral substances convert to active substances, comprising viral replication and assembly compartments has been of intense interest to virologists, cell and molecular biologists and immunologists. Infection starts with virus entry into a susceptible cell and delivers the viral genome to the replication site. This is a multi-step process, and involves the cytoskeleton and associated motor proteins. Likewise, the egress of progeny virus particles from the replication site to the extracellular space is enhanced by the cytoskeleton and associated motor proteins. This overcomes the limitation of thermal diffusion, and transports virions and virion components, often in association with cellular organelles. This review explores how the analysis of viral trajectories informs about mechanisms of infection. We discuss the methodology enabling researchers to visualize single virions in cells by fluorescence imaging and tracking. Virus visualization and tracking are increasingly enhanced by computational analyses of virus trajectories as well as in silico modeling. Combined approaches reveal previously unrecognized features of virus-infected cells. Using select examples of complementary methodology, we highlight the role of actin filaments and microtubules, and their associated motors in virus infections. In-depth studies of single virion dynamics at high temporal and spatial resolutions thereby provide deep insight into virus infection processes, and are a basis for uncovering underlying mechanisms of how cells function

A Bacterial Pathogen Displaying Temperature-Enhanced Virulence of the Microalga Emiliania huxleyi.

Emiliania huxleyi is a globally abundant microalga that plays a significant role in biogeochemical cycles. Over the next century, sea surface temperatures are predicted to increase drastically, which will likely have significant effects on the survival and ecology of E. huxleyi. In a warming ocean, this microalga may become increasingly vulnerable to pathogens, particularly those with temperature-dependent virulence. Ruegeria is a genus of Rhodobacteraceae whose population size tracks that of E. huxleyi throughout the alga's bloom-bust lifecycle. A representative of this genus, Ruegeria sp. R11, is known to cause bleaching disease in a red macroalga at elevated temperatures. To investigate if the pathogenicity of R11 extends to microalgae, it was co-cultured with several cell types of E. huxleyi near the alga's optimum (18°C), and at an elevated temperature (25°C) known to induce virulence in R11. The algal populations were monitored using flow cytometry and pulse-amplitude modulated fluorometry. Cultures of algae without bacteria remained healthy at 18°C, but lower cell counts in control cultures at 25°C indicated some stress at the elevated temperature. Both the C (coccolith-bearing) and S (scale-bearing swarming) cell types of E. huxleyi experienced a rapid decline resulting in apparent death when co-cultured with R11 at 25°C, but had no effect on N (naked) cell type at either temperature. R11 had no initial negative impact on C and S type E. huxleyi population size or health at 18°C, but caused death in older co-cultures. This differential effect of R11 on its host at 18 and 25°C suggest it is a temperature-enhanced opportunistic pathogen of E. huxleyi. We also detected caspase-like activity in dying C type cells co-cultured with R11, which suggests that programmed cell death plays a role in the death of E. huxleyi triggered by R11 - a mechanism induced by viruses (EhVs) and implicated in E. huxleyi bloom collapse. Given that E. huxleyi has recently been shown to have acquired resistance against EhVs at elevated temperature, bacterial pathogens with temperature-dependent virulence, such as R11, may become much more important in the ecology of E. huxleyi in a warming climate

Variation in Snow Algae Blooms in the Coast Range of British Columbia

Snow algae blooms cover vast areas of summer snowfields worldwide, reducing albedo and increasing snow melt. Despite their global prevalence, little is known about the algae species that comprise these blooms. We used 18S and rbcL metabarcoding and light microscopy to characterize algae species composition in 31 snow algae blooms in the Coast Range of British Columbia, Canada. This study is the first to thoroughly document regional variation between blooms. We found all blooms were dominated by the genera Sanguina, Chloromonas, and Chlainomonas. There was considerable variation between blooms, most notably species assemblages above treeline were distinct from forested sites. In contrast to previous studies, the snow algae genus Chlainomonas was abundant and widespread in snow algae blooms. We found few taxa using traditional 18S metabarcoding, but the high taxonomic resolution of rbcL revealed substantial diversity, including OTUs that likely represent unnamed species of snow algae. These three cross-referenced datasets (rbcL, 18S, and microscopy) reveal that alpine snow algae blooms are more diverse than previously thought, with different species of algae dominating different elevations

Concepts in Light Microscopy of Viruses

Viruses threaten humans, livestock, and plants, and are difficult to combat. Imaging of viruses by light microscopy is key to uncover the nature of known and emerging viruses in the quest for finding new ways to treat viral disease and deepening the understanding of virus–host interactions. Here, we provide an overview of recent technology for imaging cells and viruses by light microscopy, in particular fluorescence microscopy in static and live-cell modes. The review lays out guidelines for how novel fluorescent chemical probes and proteins can be used in light microscopy to illuminate cells, and how they can be used to study virus infections. We discuss advantages and opportunities of confocal and multi-photon microscopy, selective plane illumination microscopy, and super-resolution microscopy. We emphasize the prevalent concepts in image processing and data analyses, and provide an outlook into label-free digital holographic microscopy for virus research

Продовольственная проблема Китая: вопросы преобразования системы и безопасности в условиях кризиса

Against the background of a global decline in food security over the past three to four years, China, remaining the world’s largest food importer, has made notable progress in improving its food security. China’s food security transformation has greatly improved not only the availability but also the affordability of food, as well as the sustainability of the Chinese food system. The increase in agricultural production, including grain production in China, indicates a transition from an extensive development model with high resource dependence to a sustainable intensification model. As a result of rapid economic and social development, the food pattern has changed based on high value foods such as meat, dairy products, fish and fish products. However, there are a number of serious problems in China’s food system. China has insufficient self-sufficiency and high import dependence on a number of food products. New to China’s nutritional challenges are the overweight part of the population and the resulting increasing burden on the health care system. In addition, China’s food losses exceed those of developed countries. The changes that the world economy is undergoing, the influence of non-market factors such as ideology, geopolitics and challenges to the multilateral trade and investment system, can seriously disrupt the global agricultural market and reduce the food security of China, which is heavily dependent on foreign food trade. The transformation of China’s food system is aimed at preventing and eliminating the risks of disruption of food imports, diversifying import sources, reducing the cost of agricultural products through scientific and technological progress and increasing investment in infrastructure, the transition of Chinese agriculture from a strategy of increasing production to improving the quality of products and its security.На фоне глобального снижения продовольственной безопасности на протяжении последних трех-четырех лет Китай, оставаясь крупнейшим импортером продовольствия в мире, добился заметных успехов в повышении своей продовольственной безопасности. Преобразования Китая в области продовольственной безопасности значительно улучшили не только наличие, но и доступность продовольствия, а также устойчивость китайской продовольственной системы. Увеличение сельскохозяйственного производства, в том числе производства зерна, в Китае свидетельствует о переходе от модели экстенсивного развития, с высокой ресурсозависимостью, к модели устойчивой интенсификации. В результате быстрого экономического и социального развития изменилась структура питания, основанная на продуктах высокой ценности, таких как мясо, молочные продукты, рыба и рыбные продукты. Тем не менее в продовольственной системе Китая наблюдается ряд серьезных проблем. Китай имеет недостаточную самообеспеченность и высокую импортозависимость по ряду продовольственных товаров. Новыми для Китая проблемами в сфере питания стали избыточный вес части населения и связанная с этим возрастающая нагрузка на систему здравоохранения. Кроме того, потери продовольствия Китая превышают аналогичные показатели развитых стран. Изменения, которые претерпевает мировая экономика, влияние таких нерыночных факторов, как идеология, геополитика и вызовы системе многосторонней торговли и инвестиций, могут серьезно нарушить глобальный сельскохозяйственный рынок и снизить продовольственную безопасность Китая, который в значительной степени зависит от внешней торговли продовольственными товарами. Преобразование продовольственной системы Китая направлено на предотвращение и устранение рисков нарушений импортных поставок продовольствия, диверсификацию источников импорта, снижение себестоимости продукции сельского хозяйства за счет научно-технического прогресса и увеличения инвестиций в инфраструктуру, переход китайского сельского хозяйства от стратегии роста производства к повышению качества продукции и ее безопасности