Positive Effect of Lactobacillus acidophilus EG004 on Cognitive Ability of Healthy Mice by Fecal Microbiome Analysis Using Full-Length 16S-23S rRNA Metagenome Sequencing

Recently, the concept of the “gut-brain axis” has risen and suggested that microbes in the GI tract affect the brain by modulating signal molecules. Although many pieces of research were reported in a short period, a signaling mechanism and the effects of a specific bacterial strain are still unclear.

The electronic tree of life (eTOL): a net of long probes to characterize the human microbiome from RNA-seq data

Background Microbiome analysis generally requires PCR-based or metagenomic shotgun sequencing, sophisticated programs, and large volumes of data. Alternative approaches based on widely available RNA-seq data are constrained because of sequence similarities between the transcriptomes of microbes/viruses and those of the host, compounded by the extreme abundance of host sequences in such libraries. Current approaches are also limited to specific microbial groups. There is a need for alternative methods of microbiome analysis that encompass the entire tree of life. Results We report a method to specifically retrieve non-human sequences in human tissue RNA-seq data. For cellular microbes we used a bioinformatic 'net', based on filtered 64-mer small subunit rRNA sequences across the Tree of Life (the 'electronic tree of life', eTOL), to comprehensively (98%) entrap all non-human rRNA sequences present in the target tissue. Using brain as a model, retrieval of matching reads, re-exclusion of human-related sequences, followed by contig building and species identification, is followed by reconfirmation of the abundance and identity of the corresponding species groups. We provide methods to automate this analysis. A variant approach is necessary for viruses. Again, because of significant matches between viral and human sequences, a 'stripping' approach is essential. In addition, contamination during workup is a potential problem, and we discuss strategies to circumvent this issue. To illustrate the versatility of the method, we report the use of the eTOL methodology to unambiguously identify exogenous microbial and viral sequences in human tissue RNA-seq data across the entire tree of life including Archaea, Bacteria, Chloroplastida, basal Eukaryota, Fungi, and Holozoa/Metazoa, and discuss the technical and bioinformatic challenges involved. Conclusions This generic methodology may find wider application in microbiome analysis including diagnostics.

Assessment of Biodegradation and Eco-Toxic Properties of Novel Starch and Gelatine Blend Bioplastics

To combat the release of petroleum-derived plastics into the environment the European Commission has adopted the EU plastics strategy, which aims for a complete ban on single-use plastics by 2030. Environmentally friendly and sustainable packaging like bioplastic is being up taken at significant levels by companies and consumers. In this study, the environmental impact of novel gelatine–starch blend bioplastics is investigated. The assessments included ecotoxicology with different species that can be found in marine and soil environments to simulate natural conditions. Microalgae, plant, and nematode species were chosen as these are representative of their habitats and are known for their sensitivity to pollutants. Degradation rates of these novel bioplastics were assessed as well as microbiome analysis of the soil before and after bioplastic degradation. The main findings of this study are that (i) the bioplastic generated can be fully biodegraded in soil environments at moderate conditions (20 °C) leaving no physical traces; (ii) bioplastic did not exhibit significantly adverse effects on any organisms assessed in this study; (iii) microbiome analysis of the soil after biodegradation showed a decrease in alpha diversity and a significant increase of Actinobacteria and Firmicutes phyla, which were dominative in the soil.

Vaginal health in women and the possibility of predicting preterm birth through microbiome analysis

Background: With the recent development of next-generation sequencing technology, the microbiome in the body is being revealed in detail. It is also possible to describe the normal vaginal microenvironment and, more specifically, any changes in pregnancy. Moreover, we present the hypothesis that the microbiome is a contributing factor to preterm birth (PTB).Current Concepts: High estrogen status stimulates the maturation and proliferation of vaginal epithelial cells and the accumulation of glycogen, which promotes lactic acid production and maintains the vaginal environment at an acidic pH. The vaginas of most premenopausal women are predominantly colonized by Lactobacillus which plays an important role in local defense. Recently, it has also been reported that there are several specific types of Lactobacillus species, while other anaerobes, including Gardnerella and Atopobium also coexist in the vagina. Vaginal dysbiosis is defined as various expressions of microorganisms, secretion of specific metabolites, and changes in pH. During pregnancy, a multitude of microbiome changes occur in the oral cavity, gut, vagina, and placenta. The risk of PTB increases if the microbiome changes to one of dysbiosis. It is possible to analyze the characteristic microbiome composition related to PTB and to develop biomarkers predicting PTB. It is necessary to educate patients based on these findings.Discussion and Conclusion: Microbiome analysis has contributed significantly to understanding the association between women’s vaginal health and PTB. Continued research will also contribute to public health by assisting in the prediction and prevention of PTB.

Releasing the Kraken

Ten years ago, the dramatic rise in the number of microbial genomes led to an inflection point, when the approach of finding short, exact matches in a comprehensive database became just as accurate as older, slower approaches. The new idea led to a method that was hundreds of times times faster than those that came before. Today, exact k-mer matching is a standard technique at the heart of many microbiome analysis tools.

Exploring the Microbiome Analysis and Visualization Landscape

Research on the microbiome has boomed recently, which resulted in a wide range of tools, packages, and algorithms to analyze microbiome data. Here we investigate and map currently existing tools that can be used to perform visual analysis on the microbiome, and associate the including methods, visual representations and data features to the research objectives currently of interest in microbiome research. The analysis is based on a combination of a literature review and workshops including a group of domain experts. Both the reviewing process and workshops are based on domain characterization methods to facilitate communication and collaboration between researchers from different disciplines. We identify several research questions related to microbiomes, and describe how different analysis methods and visualizations help in tackling them.

Metaproteomic Comparison of Cryoconite Communities from Caucasian and Novaya Zemlya Glaciers

Anthropogenic pollution strongly affects glacial microbiological communities and promotes glacial melting. In the early stages of glacial melting formation of small cylindrical holes (cryoconite) occurs. While the microbiome of cryoconite is well described, the effect of anthropogenic pollution on cryoconite microbiological communities still has not been fully understood. Thus, we performed an unbiased functional comparison of the cryoconite communities from the highly polluted Caucasian glaciers and from less polluted glaciers in Novaya Zemlya. For this purpose, we used the shotgun metaproteomics approach which has not been used for cryoconite microbiome analysis previously. We identified 475 protein groups, a third of which were found in both glaciers. Cryoconites in both glaciers have similar microbiological communities with Cyanobacteria as dominant phyla. Nevertheless, we found a slight shift from the dominance of phototrophic Cyanobacteria in Novaya Zemlya to heterotrophic bacteria in the Caucasus. We assume that it might be caused by anthropogenic pollution, but other factors such as differences in seasonal dynamics of microbiological communities should be tested in the future.