Genomic and metagenomic analysis of microbes in a soil environment affected by the 2011 Great East Japan Earthquake tsunami

Genotype to ecotype in niche environments: adaptation of Arthrobacter to carbon availability and environmental conditions

Niche environmental conditions influence both the structure and function of microbial communities and the cellular function of individual strains. The terrestrial subsurface is a dynamic and diverse environment that exhibits specific biogeochemical conditions associated with depth, resulting in distinct environmental niches. Here, we present the characterization of seven distinct strains belonging to the genus Arthrobacter isolated from varying depths of a single sediment core and associated groundwater from an adjacent well. We characterized genotype and phenotype of each isolate to connect specific cellular functions and metabolisms to ecotype. Arthrobacter isolates from each ecotype demonstrated functional and genomic capacities specific to their biogeochemical conditions of origin, including laboratory-demonstrated characterization of salinity tolerance and optimal pH, and genes for utilization of carbohydrates and other carbon substrates. Analysis of the Arthrobacter pangenome revealed that it is notably open with a volatile accessory genome compared to previous pangenome studies on other genera, suggesting a high potential for adaptability to environmental niches.

Complete genome sequence of Arthrobacter sp. PAMC25564 and its comparative genome analysis for elucidating the role of CAZymes in cold adaptation

BACKGROUND

The Arthrobacter group is a known set of bacteria from cold regions, the species of which are highly likely to play diverse roles at low temperatures. However, their survival mechanisms in cold regions such as Antarctica are not yet fully understood. In this study, we compared the genomes of 16 strains within the Arthrobacter group, including strain PAMC25564, to identify genomic features that help it to survive in the cold environment.

RESULTS

Using 16 S rRNA sequence analysis, we found and identified a species of Arthrobacter isolated from cryoconite. We designated it as strain PAMC25564 and elucidated its complete genome sequence. The genome of PAMC25564 is composed of a circular chromosome of 4,170,970 bp with a GC content of 66.74 % and is predicted to include 3,829 genes of which 3,613 are protein coding, 147 are pseudogenes, 15 are rRNA coding, and 51 are tRNA coding. In addition, we provide insight into the redundancy of the genes using comparative genomics and suggest that PAMC25564 has glycogen and trehalose metabolism pathways (biosynthesis and degradation) associated with carbohydrate active enzyme (CAZymes). We also explain how the PAMC26654 produces energy in an extreme environment, wherein it utilizes polysaccharide or carbohydrate degradation as a source of energy. The genetic pattern analysis of CAZymes in cold-adapted bacteria can help to determine how they adapt and survive in such environments.

CONCLUSIONS

We have characterized the complete Arthrobacter sp. PAMC25564 genome and used comparative analysis to provide insight into the redundancy of its CAZymes for potential cold adaptation. This provides a foundation to understanding how the Arthrobacter strain produces energy in an extreme environment, which is by way of CAZymes, consistent with reports on the use of these specialized enzymes in cold environments. Knowledge of glycogen metabolism and cold adaptation mechanisms in Arthrobacter species may promote in-depth research and subsequent application in low-temperature biotechnology.

The microbiota as a candidate biomarker for SPA pools and SPA thermal spring stability after seismic events

Worldwide, the location of thermal springs overlaps seismic areas, and the higher occurrence of earthquakes may impact on water stability and safety. The hydrogeological perturbations pose environmental and public health risks that can be monitored by well-established chemical, physical and biological parameters. Specific health concerns involve the exposure of the population to the medical or wellness uses of SPA thermal waters, e.g. in respiratory or hydropinic treatments as well as during rehabilitative or recreational activities in pools. Since SPA waters are characterized by their own microbiota, we analysed by 16S amplicon sequencing the dynamics of water microbial communities after the August 2017 Ischia island earthquake. For the first time, we report the impact of a seismic event on a thermal spring water, whose microbiota was deeply characterized before and immediately after the natural disaster. The biodiversity stability of the water underwent a dramatic disturbance following the earthquake, as summarized by a Shannon index moving from 1.300 during May 2016-July 2017, up to 1.600 during the first 20-70 h after the event and slightly slowing down to 1.500 after 30 days and to 1.400 after 6 months. Microbiota analysis showed a sudden reduction of the relative abundance of autochthone thermophilic species within the first 20 h and a parallel increase of other thermophilic species as well as of ectopic bacteria from soil, sediments, sea, freshwater and wastewaters. Cultivable mesophilic bacteria were observed only in the first 20 h sample (7 × 10³/L), even if the presence of faecal contamination traces was detected by Real Time PCR also up to 70 h after the disaster. OTUs analysis of putative metabolic functions showed several changes between pre and post event, such as in the distribution of Sulphur metabolizing and Carbon fixation species. The restoration of the original pattern followed a slow trend, requiring over six months. The observed results confirm the impact of the earthquake on the microbiota structure of the underground thermal spring water, suggesting further perspectives for monitoring water stability and safety issues by a metagenomic approach.

Advances in monitoring soil microbial community dynamic and function

Microorganisms are vital to the overall ecosystem functioning, stability, and sustainability. Soil fertility and health depend on chemical composition and also on the qualitative and quantitative nature of microorganisms inhabiting it. Historically, denaturing gradient gel electrophoresis (DGGE) and temperature gradient gel electrophoresis (TGGE), single-strand conformation polymorphism, DNA amplification fingerprinting, amplified ribosomal DNA restriction analysis, terminal restriction fragment length polymorphism, length heterogeneity PCR, and ribosomal intergenic spacer analysis were used to assess soil microbial community structure (SMCS), abundance, and diversity. However, these methods had significant shortcomings and limitations for application in land reclamation monitoring. SMCS has been primarily determined by phospholipid fatty acid (PLFA) analysis. This method provides a direct measure of viable biomass in addition to a biochemical profile of the microbial community. PLFA has limitations such as overlap in the composition of microorganisms and the specificity of PLFAs signature. In recent years, high-throughput next-generation sequencing has dramatically increased the resolution and detectable spectrum of diverse microbial phylotypes from environmental samples and it plays a significant role in microbial ecology studies. Next-generation sequencings using 454, Illumina, SOLiD, and Ion Torrent platforms are rapid and flexible. The two methods, PLFA and next-generation sequencing, are useful in detecting changes in microbial community diversity and structure in different ecosystems. Single-molecule real-time (SMRT) and nanopore sequencing technologies represent third-generation sequencing (TGS) platforms that have been developed to address the shortcomings of second-generation sequencing (SGS). Enzymatic and soil respiration analyses are performed to further determine soil quality and microbial activities. Other valuable methods that are being recently applied to microbial function and structures include NanoSIM, GeoChip, and DNA stable staple isotope probing (DNA-SIP) technologies. They are powerful metagenomics tool for analyzing microbial communities, including their structure, metabolic potential, diversity, and their impact on ecosystem functions. This review is a critical analysis of current methods used in monitoring soil microbial community dynamic and functions.

The Birth Prevalence of Cleft Lip and/or Cleft Palate After the 2011 Tōhoku Earthquake and Tsunami

Objective:

This study examined whether the 2011 Tōhoku earthquake and tsunami affected the birth prevalence of cleft lip and/or cleft palate (CL/P) in Miyagi Prefecture, where the earthquake and tsunami caused severe damage.

Design:

This was a retrospective cohort study.

Setting:

The study was conducted at university and children’s hospitals in Miyagi Prefecture.

Participants:

The annual and monthly numbers of infants born with CL/P were obtained from medical records. The affected period of birth was defined as 1 year from December 1, 2011, to November 30, 2012. The control period was 5 years from January 1, 2006, to December 31, 2010. The annual and monthly numbers of births in Miyagi Prefecture were obtained using e-Stat, which is a portal for Japanese government statistics.

Main Outcome Measures:

Main outcome measures were birth prevalence of CL/P during the control and affected periods.

Results:

There were no significant differences between the control and affected periods in the prevalence (per 10 000 live births) of cleft lip with or without palate (13.8 vs 16.7; P = .342), isolated cleft palate (5.2 vs 3.2; P = .267), or overall CL/P (19.0 vs 19.9; P = .799).

Conclusions:

We did not observe that the 2011 Tōhoku earthquake and tsunami affected the birth prevalence of CL/P in Miyagi Prefecture, even though it severely impacted human health in the area.

Post-depositional changes in elemental leaching from recovered soils separated from disaster waste and tsunami deposits generated by the Great East Japan Earthquake and tsunami

The Great East Japan Earthquake and subsequent tsunami in 2011 generated massive amounts of disaster waste and tsunami deposits, one-third of which comprised soil and sediment, which are expected to be re-used; however, there has been no previous experience or knowledge of recovered soil. In this study, up-flow column leaching tests were conducted to investigate the elemental leaching behavior in this soil and sediment following its separation and treatment (hereafter termed "recovered soil") to assess whether it can be safely re-used without posing any environmental risk. The pH of the leaching water was slightly alkaline throughout the test period, regardless of the source of the recovered soil. Concentrations of calcium and sulfate ions in the leaching water varied in a similar way to the electrical conductivity (EC), with a stable state being observed initially followed by a rapid decrease until typical concentrations were reached, whereas sodium and chloride ions derived from seawater made a relatively small contribution to the EC. In terms of toxic elements, zinc and copper concentrations decreased as the volume of leaching water increased, whereas lead, fluoride, and arsenic concentrations increased as the concentration of calcium and sulfate ions decreased, indicating that the dissolution of large quantities of compounds such as calcium sulfate controlled the toxic element behavior in the recovered soils. Consequently, there is a need for continuous and careful monitoring of areas where recovered soil is re-used or treatment of the recovered soil prior to its re-use.

A Comprehensive Study on Predicting Functional Role of Metagenomes Using Machine Learning Methods

"Metagenomics" is the study of genomic sequences obtained directly from environmental microbial communities with the aim to linking their structures with functional roles. The field has been aided in the unprecedented advancement through high-throughput omics data sequencing. The outcome of sequencing are biologically rich data sets. Metagenomic data consisting of microbial spe-cies which outnumber microbial samples, lead to the "curse of dimensionality". Hence the focus in metagenomics studies has moved towards developing efficient computational models using Machine Learning (ML), reducing the computational cost. In this paper, we comprehensively assessed various ML approaches to classifying high-dimensional human microbiota effectively into their functional phenotypes. We propose the application of embedded feature selection methods, namely, Extreme Gradient Boost-ing and Penalized Logistic Regression to determine important species. The resultant feature set enhanced the performance of one of the most popular state-of-the-art methods, Random Forest (RF) over metagenomic studies. Experimental results indicate that the proposed method achieved best results in terms of accuracy, area under Receiver Operating Characteristic curve (ROC-AUC) and major improvement in processing time. It outperformed other feature selection methods of filters or wrappers over RF and classifiers such as Support Vector Machine (SVM), Extreme Learning Machine (ELM), and -Nearest Neighbors (-NN).

The Effect of the 2015 Earthquake on the Bacterial Community Compositions in Water in Nepal

We conducted a study to examine the effect of seasonal variations and the disruptive effects of the 2015 Nepal earthquake on microbial communities associated with drinking water sources. We first characterized the microbial communities of water samples in two Nepali regions (Kathmandu and Jhapa) to understand the stability of microbial communities in water samples collected in 2014. We analyzed additional water samples from the same sources collected from May to August 2015, allowing the comparison of samples from dry-to-dry season and from dry-to-monsoon seasons. Emphasis was placed on microbes responsible for maintaining the geobiochemical characteristics of water (e.g., ammonia-oxidizing and nitrite-oxidizing bacteria and archaea and sulfate-reducing bacteria) and opportunistic pathogens often found in water (Acinetobacter). When examining samples from Jhapa, we identified that most geobiochemical microbe populations remained similar. When examining samples from Kathmandu, the abundance of microbial genera responsible for maintaining the geobiochemical characteristics of water increased immediately after the earthquake and decreased 8 months later (December 2015). In addition, microbial source tracking was used to monitor human fecal contamination and revealed deteriorated water quality in some specific sampling sites in Kathmandu post-earthquake. This study highlights a disruption of the environmental microbiome after an earthquake and the restoration of these microbial communities as a function of time and sanitation practices.

Metagenomics and Bioinformatics in Microbial Ecology: Current Status and Beyond

Metagenomic approaches are now commonly used in microbial ecology to study microbial communities in more detail, including many strains that cannot be cultivated in the laboratory. Bioinformatic analyses make it possible to mine huge metagenomic datasets and discover general patterns that govern microbial ecosystems. However, the findings of typical metagenomic and bioinformatic analyses still do not completely describe the ecology and evolution of microbes in their environments. Most analyses still depend on straightforward sequence similarity searches against reference databases. We herein review the current state of metagenomics and bioinformatics in microbial ecology and discuss future directions for the field. New techniques will allow us to go beyond routine analyses and broaden our knowledge of microbial ecosystems. We need to enrich reference databases, promote platforms that enable meta- or comprehensive analyses of diverse metagenomic datasets, devise methods that utilize long-read sequence information, and develop more powerful bioinformatic methods to analyze data from diverse perspectives.

Potential Biotechnological Strategies for the Cleanup of Heavy Metals and Metalloids

Global mechanization, urbanization, and various natural processes have led to the increased release of toxic compounds into the biosphere. These hazardous toxic pollutants include a variety of organic and inorganic compounds, which pose a serious threat to the ecosystem. The contamination of soil and water are the major environmental concerns in the present scenario. This leads to a greater need for remediation of contaminated soils and water with suitable approaches and mechanisms. The conventional remediation of contaminated sites commonly involves the physical removal of contaminants, and their disposition. Physical remediation strategies are expensive, non-specific and often make the soil unsuitable for agriculture and other uses by disturbing the microenvironment. Owing to these concerns, there has been increased interest in eco-friendly and sustainable approaches such as bioremediation, phytoremediation and rhizoremediation for the cleanup of contaminated sites. This review lays particular emphasis on biotechnological approaches and strategies for heavy metal and metalloid containment removal from the environment, highlighting the advances and implications of bioremediation and phytoremediation as well as their utilization in cleaning-up toxic pollutants from contaminated environments.