Bacterial Communities In Soil Samples Research Articles

Bacterial community characterization by deep learning aided image analysis in soil chips

Soil microbes play an important role in governing global processes such as carbon cycling, but it is challenging to study them embedded in their natural environment and at the single cell level due to the opaque nature of the soil. Nonetheless, progress has been achieved in recent years towards visualizing microbial activities and organo-mineral interaction at the pore scale, especially thanks to the development of microfluidic ‘soil chips’ creating transparent soil model habitats. Image-based analyses come with new challenges as manual counting of bacteria in thousands of digital images taken from the soil chips is excessively time-consuming, while simple thresholding cannot be applied due to the background of soil minerals and debris. Here, we adopt the well-developed deep learning algorithm Mask-RCNN to quantitatively analyze the bacterial communities in soil samples from different locations in the world. This work demonstrates analysis of bacterial abundance from three contrasting locations (Greenland, Sweden and Kenya) using deep learning in microfluidic soil chips in order to characterize population and community dynamics. We additionally quantified cell- and colony morphology including cell size, shape and the cell aggregation level via calculation of the distance to the nearest neighbor. This approach allows for the first time an automated visual investigation of soil bacterial communities, and a crude biodiversity measure based on phenotypic cell morphology, which could become a valuable complement to molecular studies.

Effect of different additions of low-density polyethylene and microplastics polyadipate/butylene terephthalate on soil bacterial community structure.

The stress produced from biodegradable plastics on soil ecosystem is a rising global concern. However, effects of such microplastics (MPs) on soil ecology are still debatable. In this study, the biodegradable microplastic PBAT (polyadipate/butylene terephthalate) was used as the target object, compared with the traditional microplastic LDPE (low-density polyethylene). A pot experiment and was high-throughput sequencing analysis used to determine the effect of different additions of MPs on soil bacterial community structure and the correlation between soil bacterial community structure and chemical properties was investigated. Compared with LDPE,the results showed that EC, TN, TP, NH4+-N, and NO3--N changed obviously with the increasing of PBAT addition (p < 0.05), but pH changed little and the community richness was significantly higher in soils with low PBAT addition than that with higher PBAT addition. PBAT is beneficial to soil nitrogen fixation, but it will significantly reduce the soil P content and affect the nitrification and denitrification reaction. It suggested that addition of PBAT MPs and its addition amount result in changes in soil fertility, community abundance, and structure and composition of bacterial communities in soil samples, while the presence of PBAT MPs might affect soil carbon-nitrogen cycle.

Comparison of bacterial communities in soil samples with and without tomato bacterial wilt caused by Ralstonia solanacearum species complex

BackgroundRalstonia solanacearum is one of the most notorious soil-borne phytopathogens. It causes a severe wilt disease with deadly effects on many economically important crops. The microbita of disease-suppressive soils are thought that they can contribute to the disease resistance of crop plants, thus, evaluation of the microbial community and their interaction characteristics between suppressive soil (SS) and conducive soil (CS) will help to understand resistance mechanism. To do this, the bacterial community structure, correlation analysis with soil chemical properties, interaction network of SS (nearly no disease in three years), and CS (suffered heavy bacterial wilt disease) were analyzed.ResultsA higher bacterial community diversity index was found in SS, the relative abundance of Nocardioides, Gaiella and norank_f_Anaerolineaceae were significantly more than that of the CS. Moreover, the relative abundance of main genera Bacillus, norank_o_Gaiellales, Roseiflexus, and norank_o_Gemmatimonadaceae were significantly more than that of the CS. Redundancy analysis at the genus level indicated that the available phosphate played a key role in the bacterial community distribution, and its role was negatively correlated with soil pH, organic matter content, alkali-hydrolyzable nitrogen, and available potassium contents. Interaction network analysis further demonstrated that greater diversity at the genus level existed in the SS network and formed a stable network. Additionally, the species of Mycobacterium, Cyanobacteria, and Rhodobiaceae are the key components that sustain the network stability. Seven clusters of orthologous groups exhibited significant differences between SS and CS. Moreover, 55 bacterial strains with distinct antagonistic activities to R. solancearum were isolated and identified from the healthy tomato plant rhizosphere soil of the CS.ConclusionsOur findings indicate that the bacterial diversity and interaction network differed between the CS and SS samples, providing a good foundation in the study of bacterial wilt.

Difference Analysis Based on 16S rRNA Sequencing of Different Soil Bacterial Communities.

Objective To study the structure and differences of bacterial communities in different soils, and to explore the effectiveness of 16S rRNA sequencing in identification of different soil. Methods Soil samples from 7 places in Shanghai were collected, then bacterial genomic DNA were extracted from them. The fragments of hypervariable region from 16S rRNA sequences were sequenced with high-throughput sequencing techniques. The results were quantified or visualized with bioinformatics software. The differences in diversity and abundance among the three kinds of bacterial communities in soil samples from grassland, forests and beaches were compared and analyzed. Results The statistical differences that existed among the alpha diversity indexes of bacterial communities in soil samples of grassland, forests and beaches had statistical significance. The relative abundance and diversity of bacterial communities in these three kinds of soil were significantly different. Grassland soil had higher Acidobacteria abundance, forest soil had higher Proteobacteria abundance, beach soil had higher Actinobacteria abundance. However, the differences in soil bacterial communities in artificial grasslands, natural grasslands and industrial district grasslands did not have statistical significance. Conclusion 16S rRNA sequencing can effectively distinguish different soils. This method may be able to provide clues for first crime scene inference in criminal cases.

Bacteria as Emerging Indicators of Soil Condition.

The impact of land use change and management on soil microbial community composition remains poorly understood. Therefore, we explored the relationship between a wide range of soil factors and soil bacterial community composition. We included variables related to anthropogenic activity and collected samples across a large spatial scale to interrogate the complex relationships between various bacterial community attributes and soil condition. We provide evidence of strong relationships between individual taxa and specific soil attributes even across large spatial scales and soil and land use types. Collectively, we were able to demonstrate the largely untapped potential of microorganisms to indicate the condition of soil and thereby influence the way that we monitor the effects of anthropogenic activity on soil ecosystems into the future.

Microbial soil community analyses for forensic science: Application to a blind test

Soil complexity, heterogeneity and transferability make it valuable in forensic investigations to help obtain clues as to the origin of an unknown sample, or to compare samples from a suspect or object with samples collected at a crime scene. In a few countries, soil analysis is used in matters from site verification to estimates of time after death. However, up to date the application or use of soil information in criminal investigations has been limited. In particular, comparing bacterial communities in soil samples could be a useful tool for forensic science. To evaluate the relevance of this approach, a blind test was performed to determine the origin of two questioned samples (one from the mock crime scene and the other from a 50:50 mixture of the crime scene and the alibi site) compared to three control samples (soil samples from the crime scene, from a context site 25m away from the crime scene and from the alibi site which was the suspect’s home). Two biological methods were used, Ribosomal Intergenic Spacer Analysis (RISA), and 16S rRNA gene sequencing with Illumina Miseq, to evaluate the discriminating power of soil bacterial communities. Both techniques discriminated well between soils from a single source, but a combination of both techniques was necessary to show that the origin was a mixture of soils. This study illustrates the potential of applying microbial ecology methodologies in soil as an evaluative forensic tool.

Short-term effects of mechanical drainage on fungal and bacterial community structure in a managed grassland soil

This study focused on identifying the short-term effects of mechanical drainage on the structure and diversity of fungal and bacterial communities in soil. Mechanical drainage is a widely used agricultural practice which allows for the management of surface and sub-surface water. It is vital for improving land productivity and reclaiming marginal land. The use of mechanical drainage is known to have several impacts on the physico-chemical components of soil; however, little is known about its effect on the soil microbiome. In the present study, 454 pyrosequencing of the 18S and 16S rRNA gene regions was used to evaluate differences in fungal and bacterial communities in soil samples taken pre and two months post drainage from an extensively managed grassland in Co., Meath, Ireland.Mechanical drainage was found to have no significant impact on soil pH or on soil carbon and nitrogen levels, however a statistically significant reduction in moisture content was recorded (c. 7%). Analysis of metagenetic data showed that Basidiomycota was the largest classifiable fungal phylum accounting for 16% of all sequences. The predominant bacterial phyla identified in all samples were Proteobacteria, Bacteroidetes and Acidobacteria with average relative abundances of 23%, 26% and 27% respectively. Overall fungal and bacterial community structure and diversity remained unchanged in response to mechanical drainage but two fungal phyla, Chytridiomycota and Blastocladiomycota, showed a significant increase in relative abundance in response to drainage. These findings contribute to our overall understanding of how mechanical drainage impacts the soil microbiome.

Digging for biosynthetic dark matter.

An analysis of bacterial communities in soil samples from around the world reveals unexplored diversity in biosynthetic enzymes.

Bacterial diversity assessment in soil of an active Brazilian copper mine using high-throughput sequencing of 16S rDNA amplicons.

Mining activities pose severe environmental risks worldwide, generating extreme pH conditions and high concentrations of heavy metals, which can have major impacts on the survival of organisms. In this work, pyrosequencing of the V3 region of the 16S rDNA was used to analyze the bacterial communities in soil samples from a Brazilian copper mine. For the analysis, soil samples were collected from the slopes (geotechnical structures) and the surrounding drainage of the Sossego mine (comprising the Sossego and Sequeirinho deposits). The results revealed complex bacterial diversity, and there was no influence of deposit geographic location on the composition of the communities. However, the environment type played an important role in bacterial community divergence; the composition and frequency of OTUs in the slope samples were different from those of the surrounding drainage samples, and Acidobacteria, Chloroflexi, Firmicutes, and Gammaproteobacteria were responsible for the observed difference. Chemical analysis indicated that both types of sample presented a high metal content, while the amounts of organic matter and water were higher in the surrounding drainage samples. Non-metric multidimensional scaling (N-MDS) analysis identified organic matter and water as important distinguishing factors between the bacterial communities from the two types of mine environment. Although habitat-specific OTUs were found in both environments, they were more abundant in the surrounding drainage samples (around 50%), and contributed to the higher bacterial diversity found in this habitat. The slope samples were dominated by a smaller number of phyla, especially Firmicutes. The bacterial communities from the slope and surrounding drainage samples were different in structure and composition, and the organic matter and water present in these environments contributed to the observed differences.

A comparative study of microbial communities in soils amended by manures from pigs fed with organic versus synthetic feeds

We applied pyrosequencing to determine bacterial communities in soil samples taken from test fields amended by manures of pigs fed with green feeds (GPMS), synthetic feeds (APMS), and the reference field without swine manure amendment (NPMS), respectively. For each sample, 7050 effective sequences were selected and utilized to do the bacterial diversity and abundance analysis, respectively. In total, 2986, 2873, and 1602 operational taxonomic units were obtained at a 3% distance cut-off in GPMS, APMS, and NPMS, respectively. Bacterial phylotype richness in GPMS was higher than the other samples. NPMS had the least richness. The most dominant class in both GPMS and APMS is Betaproteobacteria, whereas Alphaproteobacteria is dominant in NPMS. Circa 7.5% sequences in GPMS were found to be affiliated with Burkholderiales order. Bacterial diversity and abundance in the soil varied with swine manure amendment, due to nutrient elements as well as toxic metals in swine manures. Compared with the soil amendment by manures from pigs bred with synthetic feeds, more bacterial diversity but less potentially pathogenic bacterial genera in the soil amended by manures of pigs fed with green feeds were found, which indicated that these manures were better land-applied organic fertilizers.