Unboxing the black box-one step forward to understand the soil microbiome: A systematic review.

Soil is one of the most important assets of the planet Earth, responsible for maintaining the biodiversity and managing the ecosystem services for both managed and natural ecosystems. It encompasses large proportion of microscopic biodiversity, including prokaryotes and the microscopic eukaryotes. Soil microbiome is critical in managing the soil functions, but their activities have diminutive recognition in few systems like desert land and forest ecosystems. Soil microbiome is highly dependent on abiotic and biotic factors like pH, carbon content, soil structure, texture, and vegetation, but it can notably vary with ecosystems and the respective inhabitants. Thus, unboxing this black box is essential to comprehend the basic components adding to the soil systems and supported ecosystem services. Recent advancements in the field of molecular microbial ecology have delivered commanding tools to examine this genetic trove of soil biodiversity. Objective of this review is to provide a critical evaluation of the work on the soil microbiome, especially since the advent of the NGS techniques. The review also focuses on advances in our understanding of soil communities, their interactions, and functional capabilities along with understanding their role in maneuvering the biogeochemical cycle while underlining and tapping the unprecedented metagenomics data to infer the ecological attributes of yet undiscovered soil microbiome. This review focuses key research directions that could shape the future of basic and applied research into the soil microbiome. This review has led us to understand that it is difficult to generalize that soil microbiome plays a substantiated role in shaping the soil networks and it is indeed a vital resource for sustaining the ecosystem functioning. Exploring soil microbiome will help in unlocking their roles in various soil network. It could be resourceful in exploring and forecasting its impacts on soil systems and for dealing with alleviating problems like rapid climate change.

Quantification of prostate tumour diameter and volume from MR images using 3D ellipsoid model and its impact on PI-RADS v2.1 assessment.

Maximum diameter and volume of the tumour provide important clinical information and are decision-making parameters for patients suspected with prostate cancer (PCa). The objectives of this study were to develop an automated method for 3D tumour measurement and compare it with the radiologist's manual assessment, as well as to investigate the impact of 3D tumour measurement on Prostate Imaging-Reporting and Data System version-2.1 (PI-RADS v2.1) scoring of prostate cancer. Tumour maximum diameter and volume were calculated using automated ellipsoid-fit method. For all PI-RADS scores, mean ± standard deviation range of tumour maximum diameter and volume measured using ellipsoid-fit method were 1.36 ± 0.28 to 1.97 ± 0.67 cm and 0.49 ± 0.31 to 1.05 ± 0.78 cc and manual assessment were in range of 0.73 ± 0.12 to 1.14 ± 0.25 cm and 0.36 ± 0.21 to 0.93 ± 0.39 cc, respectively. Ellipsoid-fit method showed significantly (p < 0.05) higher values for maximum diameter and volume than manual assessment. 3D measurement of tumour using ellipsoid-fit method was found to have higher maximum diameter and volume values (in 40-61% patients) compared to conventional assessment by radiologist, which may have an impact on PI-RADS v2.1 scoring system.

Machine learning-based analysis of a semi-automated PI-RADS v2.1 scoring for prostate cancer.

Background: Prostate Imaging-Reporting and Data System version 2.1 (PI-RADS v2.1) was developed to standardize the interpretation of multiparametric MRI (mpMRI) for prostate cancer (PCa) detection. However, a significant inter-reader variability among radiologists has been found in the PI-RADS assessment. The purpose of this study was to evaluate the diagnostic performance of an in-house developed semi-automated model for PI-RADS v2.1 scoring using machine learning methods. Methods: The study cohort included an MRI dataset of 59 patients (PI-RADS v2.1 score 2 = 18, score 3 = 10, score 4 = 16, and score 5 = 15). The proposed semi-automated model involved prostate gland and zonal segmentation, 3D co-registration, lesion region of interest marking, and lesion measurement. PI-RADS v2.1 scores were assessed based on lesion measurements and compared with the radiologist PI-RADS assessment. Machine learning methods were used to evaluate the diagnostic accuracy of the proposed model by classification of PI-RADS v2.1 scores. Results: The semi-automated PI-RADS assessment based on the proposed model correctly classified 50 out of 59 patients and showed a significant correlation (r = 0.94, p < 0.05) with the radiologist assessment. The proposed model achieved an accuracy of 88.00% ± 0.98% and an area under the receiver-operating characteristic curve (AUC) of 0.94 for score 2 vs. score 3 vs. score 4 vs. score 5 classification and accuracy of 93.20 ± 2.10% and AUC of 0.99 for low score vs. high score classification using fivefold cross-validation. Conclusion: The proposed semi-automated PI-RADS v2.1 assessment system could minimize the inter-reader variability among radiologists and improve the objectivity of scoring.

Assessment of regional water demand for coal-based power plants in India: exploring its regional impact on other cross-sectoral water stress.

Water use in coal power generation is one of the key points to highlight for the countries like India because country electricity demand increases rapidly which led to increase in water demand. The coal power sector in India will remain to be the dominant source of electricity generation until 2040 and will require a regular water supply, which is already in a stressful condition. This work focuses on the regional assessment of water withdrawal and consumption of the coal power sector at three broad stages includes fuel extraction, fuel preparation, and power generation. Our analysis reveals that 99% of the total water supply to the sector was withdrawn by power plants. Further, the study assessed its trade-off with other sectoral water demand adopting WSI (Water Stress Index) criteria for both surface and groundwater sources. The results highlighted the per capita groundwater to be under severe stress and similar status was also identified in the case of fresh surface water except for the Central region. The overall WSI status was found to be severe in all regions of India. This situation creates a water-scarce situation for water-guzzling power plants that are dependent on surface water and faces the competitive situation with the agriculture and domestic sector. Results of the study concluded that the technological up-gradation at the power plants could be helpful to reduce the total water demand by 78% of coal power sector which can be reduced the severity of regional water stress. Our study aids policymakers to identify the region which is more vulnerable in terms of cross-sectoral water demand and also fulfills the need for quality data availability at a regional scale that may use in the future towards sustainable water-resources management practices.

Characterisation of prostate cancer using texture analysis for diagnostic and prognostic monitoring.

Automated classification of significant prostate cancer (PCa) using MRI plays a potential role in assisting in clinical decision-making. Multiparametric MRI using a machine-aided approach is a better step to improve the overall accuracy of diagnosis of PCa. The objective of this study was to develop and validate a framework for differentiating Prostate Imaging-Reporting and Data System version 2 (PI-RADS v2) grades (grade 2 to grade 5) of PCa using texture features and machine learning (ML) methods with diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC). The study cohort included an MRI dataset of 59 patients with clinically proven PCa. Regions of interest (ROIs) for a total of 435 lesions were delineated from the segmented peripheral zones of DWI and ADC. Six texture methods comprising 98 texture features in total (49 each of DWI and ADC) were extracted from lesion ROIs. Random forest (RF) and correlation-based feature selection methods were applied on feature vectors to select the best features for classification. Two ML classifiers, support vector machine (SVM) and K-nearest neighbour, were used and validated by 10-fold cross-validation. The proposed framework achieved high diagnostic performance with a sensitivity of 85.25% ± 3.84%, specificity of 95.71% ± 1.96%, accuracy of 84.90% ± 3.37% and area under the receiver-operating characteristic curve of 0.98 for PI-RADS v2 grades (2 to 5) classification using the RF feature selection method and Gaussian SVM classifier with combined features of DWI + ADC. The proposed computer-assisted framework can distinguish between PCa lesions with different aggressiveness based on PI-RADS v2 standards using texture analysis to improve the efficiency of PCa diagnostic performance.

Aberrations in the microbiome of cyanobacteria from a tropical estuary polluted by heavy metals.

The effect of heavy metal pollution on the microbiome of cyanobacteria in Cochin estuary (CE) on the southwest coast of India is reported in the study. Statistically significant difference in heavy metal concentration was observed between water, suspended particulate matter (SPM) and sediment. The Zn, Cd, Cu, Ni and Cr were 2-6 times higher in the SPM compared with the sediment, while Pb was 10 to 25 times higher. Although nearly 60% of the species diversity of microbiome was common between cyanobacteria enriched from the upstream (S1S) and downstream (S11B), there was a difference in the major groups of heterotrophic bacterial associates. Proteobacteria was the dominant phylum (>80%) in S1S, while it was second only (27.5%) after Planctomycetes (37.4%) in S11B. The results of the current study indicate that the pollution can influence an ecosystem at the micro-niche level.

Segmentation of prostate zones using probabilistic atlas-based method with diffusion-weighted MR images.

BACKGROUND AND OBJECTIVE: Accurate segmentation of prostate and its zones constitute an essential preprocessing step for computer-aided diagnosis and detection system for prostate cancer (PCa) using diffusion-weighted imaging (DWI). However, low signal-to-noise ratio and high variability of prostate anatomic structures are challenging for its segmentation using DWI. We propose a semi-automated framework that segments the prostate gland and its zones simultaneously using DWI. METHODS: In this paper, the Chan-Vese active contour model along with morphological opening operation was used for segmentation of prostate gland. Then segmentation of prostate zones into peripheral zone (PZ) and transition zone (TZ) was carried out using in-house developed probabilistic atlas with partial volume (PV) correction algorithm. The study cohort included MRI dataset of 18 patients (n = 18) as our dataset and methodology were also independently evaluated using 15 MRI scans (n = 15) of QIN-PROSTATE-Repeatability dataset. The atlas for zones of prostate gland was constructed using dataset of twelve patients of our patient cohort. Three-fold cross-validation was performed with 10 repetitions, thus total 30 instances of training and testing were performed on our dataset followed by independent testing on the QIN-PROSTATE-Repeatability dataset. Dice similarity coefficient (DSC), Jaccard coefficient (JC), and accuracy were used for quantitative assessment of the segmentation results with respect to boundaries delineated manually by an expert radiologist. A paired t-test was performed to evaluate the improvement in zonal segmentation performance with the proposed PV correction algorithm. RESULTS: For our dataset, the proposed segmentation methodology produced improved segmentation with DSC of 90.76 ± 3.68%, JC of 83.00 ± 5.78%, and accuracy of 99.42 ± 0.36% for the prostate gland, DSC of 77.73 ± 2.76%, JC of 64.46 ± 3.43%, and accuracy of 82.47 ± 2.22% for the PZ, and DSC of 86.05 ± 1.50%, JC of 75.80 ± 2.10%, and accuracy of 91.67 ± 1.56% for the TZ. The segmentation performance for QIN-PROSTATE-Repeatability dataset was, DSC of 85.50 ± 4.43%, JC of 75.00 ± 6.34%, and accuracy of 81.52 ± 5.55% for prostate gland, DSC of 74.40 ± 1.79%, JC of 59.53 ± 8.70%, and accuracy of 80.91 ± 5.16% for PZ, and DSC of 85.80 ± 5.55%, JC of 74.87 ± 7.90%, and accuracy of 90.59 ± 3.74% for TZ. With the implementation of the PV correction algorithm, statistically significant (p<0.05) improvements were observed in all the metrics (DSC, JC, and accuracy) for both prostate zones, PZ and TZ segmentation. CONCLUSIONS: The proposed segmentation methodology is stable, accurate, and easy to implement for segmentation of prostate gland and its zones (PZ and TZ). The atlas-based segmentation framework with PV correction algorithm can be incorporated into a computer-aided diagnostic system for PCa localization and treatment planning.

Tropical forest conversion to rubber plantation in southwest China results in lower fungal beta diversity and reduced network complexity.

Despite the extensive, ongoing conversion of tropical forests to rubber plantation, the effects of this land-use change on soil fungal community diversity and composition are still poorly known. We compared a network of sites of tropical forest in southern Yunnan, China, with a network of rubber plantation sites originally derived from this forest. Soil DNA was amplified for ITS2 and sequenced using Illumina MiSeq. We found that there was a major shift in community composition across all phyla, including a large reduction in ectomycorrhizal fungi likely related to the absence of hosts. Conversion from forest to rubber plantation had no effect on total fungal α-diversity, but rubber plantation had lower ß-diversity, resulting in lower overall gamma diversity. Networks based on co-occurrence of operational taxonomic unit in each land-use type showed that network complexity decreased with land-use change from forest to rubber plantation. Further investigation of soil functionality is needed to investigate whether this lower network complexity is related to reduced soil ecosystem resilience.

Tropical forest conversion to rubber plantation affects soil micro- & mesofaunal community & diversity.

Tropical rainforests play important roles in carbon sequestration and are hot spots for biodiversity. Tropical forests are being replaced by rubber (Hevea brasiliensis) plantations, causing widespread concern of a crash in biodiversity. Such changes in aboveground vegetation might have stronger impacts on belowground biodiversity. We studied tropical rainforest fragments and derived rubber plantations at a network of sites in Xishuangbanna, China, hypothesizing a major decrease in diversity with conversion to plantations. We used metabarcoding of the 18S rRNA gene and recovered 2313 OTUs, with a total of 449 OTUs shared between the two land-use types. The most abundant phyla detected were Annelida (66.4% reads) followed by arthropods (15.5% reads) and nematodes (8.9% reads). Of these, only annelids were significantly more abundant in rubber plantation. Taken together, α- and ß-diversity were significantly higher in forest than rubber plantation. Soil pH and spatial distance explained a significant portion of the variability in phylogenetic community structure for both land-use types. Community assembly was primarily influenced by stochastic processes. Overall it appears that forest replacement by rubber plantation results in an overall loss and extensive replacement of soil micro- and mesofaunal biodiversity, which should be regarded as an additional aspect of the impact of forest conversion.

Diversity and Distribution of Thermophilic Bacteria in Hot Springs of Pakistan.

Chilas and Hunza areas, located in the Main Mantle Thrust and Main Karakoram Thrust of the Himalayas, host a range of geochemically diverse hot springs. This Himalayan geothermal region encompassed hot springs ranging in temperature from 60 to 95 °C, in pH from 6.2 to 9.4, and in mineralogy from bicarbonates (Tato Field), sulfates (Tatta Pani) to mixed type (Murtazaabad). Microbial community structures in these geothermal springs remained largely unexplored to date. In this study, we report a comprehensive, culture-independent survey of microbial communities in nine samples from these geothermal fields by employing a bar-coded pyrosequencing technique. The bacterial phyla Proteobacteria and Chloroflexi were dominant in all samples from Tato Field, Tatta Pani, and Murtazaabad. The community structures however depended on temperature, pH, and physicochemical parameters of the geothermal sites. The Murtazaabad hot springs with relatively higher temperature (90-95 °C) favored the growth of phylum Thermotogae, whereas the Tatta Pani thermal spring site TP-H3-b (60 °C) favored the phylum Proteobacteria. At sites with low silica and high temperature, OTUs belonging to phylum Chloroflexi were dominant. Deep water areas of the Murtazaabad hot springs favored the sulfur-reducing bacteria. About 40% of the total OTUs obtained from these samples were unclassified or uncharacterized, suggesting the presence of many undiscovered and unexplored microbiota. This study has provided novel insights into the nature of ecological interactions among important taxa in these communities, which in turn will help in determining future study courses in these sites.

Similarities and Contrasts in the Archaeal Community of Two Japanese Mountains: Mt. Norikura Compared to Mt. Fuji.

The community ecology, abundance, and diversity patterns of soil archaea are poorly understood-despite the fact that they are a major branch of life that is ubiquitous and important in nitrogen cycling in terrestrial ecosystems. We set out to investigate the elevational patterns of archaeal ecology, and how these compare with other groups of organisms. Many studies of different groups of organisms (plants, birds, etc.) have shown a series of distinct communities with elevation, and often a diversity maximum in mid-elevations. We investigated the soil archaeal communities on Mt. Norikura, Japan, using 454 pyrosequencing of the 16S ribosomal RNA (rRNA) gene. There was a strong mid-elevation maximum in diversity, and a mid-elevation maximum in abundance of soil archaea 16S rRNA and amoA genes. These diversity and abundance maximums could not be correlated with any identifiable soil parameter, nor plant diversity. Discrete, predictable communities of archaea occurred at each elevational level, also not explicable in terms of pH or major nutrients. When we compared the archaeal community and diversity patterns with those found in an earlier study of Mt Fuji, both mountains showed mid-elevation maximums in diversity and abundance of archaea, possibly a result of some common environmental factor such as soil disturbance frequency. However, they showed distinct sets of archaeal communities at similar elevational sampling points. Presumably, the difference reflects their distinct geology (Norikura being andesitic, while Fuji is basaltic) and the resulting combinations of soil chemistry and environmental conditions, although no explanatory variable was found. Clearly, many soil archaea have strongly defined niches and will only occur in a narrow subset of the range of possible climate and soil conditions. The findings of a mid-elevation diversity maximum on Norikura provides a further instance of how widespread this unexplained pattern is in nature, in a wide variety of groups of organisms.

Duplicate analysis method: a cheaper alternative to commercial IQC materials in limited resource settings for monitoring CD4 testing.

BACKGROUND: India has a large number of HIV infected patients being followed up at anti-retroviral therapy (ART) centers. The patients are regularly offered CD4 count estimation for deciding their eligibility for ART initiation as well as for monitoring response to ART, making CD4 count estimation a very critical test. Hence, quality control of CD4 testing is utmost important for ultimate success of ART program. As the commercial controls are very expensive, internal quality control (IQC), at present, is being done by duplicate analysis method using previous day samples in most of the laboratories. Hence the study was undertaken to review performance of duplicate analysis method for monitoring daily IQC. METHODS: Quality control (QC) data from 11 Indian laboratories using duplicate analysis and/or commercial controls for IQC of CD4 testing was collected for reviewing information on QC parameters such as precision, accuracy and trend monitoring. Precision was determined by r(2) values and mean % variation for duplicate analysis and coefficient of variation (% CV) for commercial controls. Accuracy was monitored by rate of QC failures for both the types of control and trend monitoring was done by plotting LJ charts for commercial controls and by plotting daily % variation for duplicate analysis. RESULTS: The laboratories using duplicate analysis for IQC showed good precision with mean % variation ranging from 0.5 to 7.2. There was good match between r(2) values and % CV of the laboratories performing both the types of QC methods. Rates of QC failures were 2.3 for duplicate analysis and 3 per laboratory-year for IMMUNO-TROL controls. Daily trend monitoring showed fluctuation of daily counts around mean in LJ charts and of percent variation around 0% in duplicate analysis method. Commercially available controls showed limitations such as altered specimen quality leading to difficulties in manual gating and issues with the establishment of laboratory range. CONCLUSION: Duplicate analysis can serve as a cheaper alternative to commercially available controls for IQC of CD4 testing especially when supplemented with other QC measures for controlling variations caused by reagent, equipment, staff and environment in addition to the successful participation in External Quality Assurance programme.

Effects of functionalized and raw multi-walled carbon nanotubes on soil bacterial community composition.

Carbon nanotubes (CNTs) are widely used in industry, but their environmental impacts on soil microbial communities are poorly known. In this paper, we compare the effect of both raw and acid treated or functionalized (fCNTs) multi-walled carbon nanotubes (MWCNTs) on soil bacterial communities, applying different concentrations of MWCNTs (0 µg/g, 50 µg/g, 500 µg/g and 5000 µg/g) to a soil microcosm system. Soil DNA was extracted at 0, 2 and 8 weeks and the V3 region of the 16S rRNA gene was PCR-amplified and sequenced using paired-end Illumina bar-coded sequencing. The results show that bacterial diversity was not affected by either type of MWCNT. However, overall soil bacterial community composition, as illustrated by NMDS, was affected only by fMWCNT at high concentrations. This effect, detectable at 2 weeks, remained equally strong by 8 weeks. In the case of fMWCNTs, overall changes in relative abundance of the dominant phyla were also found. The stronger effect of fMWCNTs could be explained by their intrinsically acidic nature, as the soil pH was lower at higher concentrations of fMWCNTs. Overall, this study suggests that fMWCNTs may at least temporarily alter microbial community composition on the timescale of at least weeks to months. It appears, by contrast, that raw MWCNTs do not affect soil microbial community composition.

Spatial scaling effects on soil bacterial communities in Malaysian tropical forests.

Spatial scaling to some extent determines biodiversity patterns in larger organisms, but its role in microbial diversity patterns is much less understood. Some studies have shown that bacterial community similarity decreases with distance, whereas others do not support this. Here, we studied soil bacterial communities of tropical rainforest in Malaysia at two spatial scales: a local scale with samples spaced every 5 mover a 150-m transect, and a regional scale with samples 1 to 1,800 km apart. PCR-amplified soil DNA for the bacterial 16S rRNA gene targeting the V1­V3 region was pyrosequenced using Roche/454 GS FLX Titanium platform. A ranked partial Mantel test showed a weak correlation between spatial distance and whole bacterial community dissimilarity, but only at the local scale. In contrast, environmental distance was highly correlated with community dissimilarity at both spatial scales,stressing the greater role of environmental variables rather than spatial distance in determining bacterial community variation at different spatial scales. Soil pH was the only environmental parameter that significantly explained the variance in bacterial community at the local scale, whereas total nitrogen and elevation were additional important factors at the regional scale.We obtained similar results at both scales when only the most abundant OTUs were analyzed. A variance partitioning analysis showed that environmental variables contributed more to bacterial community variation than spatial distance at both scales. In total, our results support a strong influence of the environment in determining bacterial community composition in the rainforests of Malaysia. However, it is possible that the remaining spatial distance effect is due to some of the myriad of other environmental factors which were not considered here, rather than dispersal limitation.

Bacterial diversity in the mountains of South-West China: climate dominates over soil parameters.

Certain patterns in soil bacterial diversity and community composition have become evident from metagenomics studies on a range of scales, from various parts of the world. For example, soil pH has generally been seen as dominating variation in bacterial diversity, above all other soil and climate parameters. It is important however to test the generality of these relationships by studying previously un-sampled areas. We compared soil bacterial diversity and community composition under a wide range of climatic and edaphic conditions in mountainous Yunnan Province, SW China. Soil samples were taken from a range of primary forest types and altitudes, reflecting the great variation of forest environments in this region. From each soil sample, DNA was extracted and pyrosequenced for bacterial 16S rRNA gene identification. In contrast to other recent studies from other parts of the world, pH was a weaker predictor of bacterial community composition and diversity than exchangeable Ca(2+) concentration, and also the more poorly defined environmental parameter of elevation. Samples from within each forest type clustered strongly, showing the distinctive pattern of their microbial communities on a regional scale. It is clear that on a regional scale in a very heterogeneous environment, additional factors beyond pH can emerge as more important in determining bacterial diversity.

Differential modulation of phenotypic composition of HIV-infected and -uninfected PBMCs during cryopreservation.

This article was designed to determine variations in phenotypic composition of fresh and frozen PBMCs for assessing utility of cryopreserved PBMCs for phenotypic assays. Relative percentages of effector memory cells increased significantly as against percentages of naïve cells which showed significant decrease after cryopreservation in HIV-uninfected samples. These differences were not significant in HIV-infected individuals. There was no significant difference in the expression of activation markers in fresh and frozen PBMCs except the HLA DR expression on CD8 cells in HIV-infected individuals, which was significantly decreased in frozen PBMCs. Thus, cryopreservation resulted in differential effect on phenotypic composition of PBMCs in HIV-infected and -uninfected individuals.

Elevational patterns in archaeal diversity on Mt. Fuji.

Little is known of how archaeal diversity and community ecology behaves along elevational gradients. We chose to study Mount Fuji of Japan as a geologically and topographically uniform mountain system, with a wide range of elevational zones. PCR-amplified soil DNA for the archaeal 16 S rRNA gene was pyrosequenced and taxonomically classified against EzTaxon-e archaeal database. At a bootstrap cut-off of 80%, most of the archaeal sequences were classified into phylum Thaumarchaeota (96%) and Euryarchaeota (3.9%), with no sequences classified into other phyla. Archaeal OTU richness and diversity on Fuji showed a pronounced 'peak' in the mid-elevations, around 1500 masl, within the boreal forest zone, compared to the temperate forest zone below and the alpine fell-field and desert zones above. Diversity decreased towards higher elevations followed by a subtle increase at the summit, mainly due to an increase in the relative abundance of the group I.1b of Thaumarchaeota. Archaeal diversity showed a strong positive correlation with soil NH(4)(+), K and NO(3)(-). Archaeal diversity does not parallel plant diversity, although it does roughly parallel bacterial diversity. Ecological hypotheses to explain the mid diversity bulge on Fuji include intermediate disturbance effects, and the result of mid elevations combining a mosaic of upper and lower slope environments. Our findings show clearly that archaeal soil communities are highly responsive to soil environmental gradients, in terms of both their diversity and community composition. Distinct communities of archaea specific to each elevational zone suggest that many archaea may be quite finely niche-adapted within the range of soil environments. A further interesting finding is the presence of a mesophilic component of archaea at high altitudes on a mountain that is not volcanically active. This emphasizes the importance of microclimate - in this case solar heating of the black volcanic ash surface--for the ecology of soil archaea.

Tropical soil bacterial communities in Malaysia: pH dominates in the equatorial tropics too.

The dominant factors controlling soil bacterial community variation within the tropics are poorly known. We sampled soils across a range of land use types--primary (unlogged) and logged forests and crop and pasture lands in Malaysia. PCR-amplified soil DNA for the bacterial 16S rRNA gene targeting the V1-V3 region was pyrosequenced using the 454 Roche machine. We found that land use in itself has a weak but significant effect on the bacterial community composition. However, bacterial community composition and diversity was strongly correlated with soil properties, especially soil pH, total carbon, and C/N ratio. Soil pH was the best predictor of bacterial community composition and diversity across the various land use types, with the highest diversity close to neutral pH values. In addition, variation in phylogenetic structure of dominant lineages (Alphaproteobacteria, Beta/Gammaproteobacteria, Acidobacteria, and Actinobacteria) is also significantly correlated with soil pH. Together, these results confirm the importance of soil pH in structuring soil bacterial communities in Southeast Asia. Our results also suggest that unlike the general diversity pattern found for larger organisms, primary tropical forest is no richer in operational taxonomic units of soil bacteria than logged forest, and agricultural land (crop and pasture) is actually richer than primary forest, partly due to selection of more fertile soils that have higher pH for agriculture and the effects of soil liming raising pH.

Distinctive phyllosphere bacterial communities in tropical trees.

Recent work has suggested that in temperate and subtropical trees, leaf surface bacterial communities are distinctive to each individual tree species and dominated by Alpha- and Gammaproteobacteria. In order to understand how general this pattern is, we studied the phyllosphere bacterial community on leaves of six species of tropical trees at a rainforest arboretum in Malaysia. This represents the first detailed study of 'true' tropical lowland tree phyllosphere communities. Leaf surface DNA was extracted and pyrosequenced targeting the V1-V3 region of 16S rRNA gene. As was previously found in temperate and subtropical trees, each tree species had a distinctive bacterial community on its leaves, clustering separately from other tree species in an ordination analysis. Bacterial communities in the phyllosphere were unique to plant leaves in that very few operational taxonomic units (0.5%) co-occurred in the surrounding soil environment. A novel and distinctive aspect of tropical phyllosphere communities is that Acidobacteria were one of the most abundant phyla across all samples (on average, 17%), a pattern not previously recognized. Sequences belonging to Acidobacteria were classified into subgroups 1-6 among known 24 subdivisions, and subgroup 1 (84%) was the most abundant group, followed by subgroup 3 (15%). The high abundance of Acidobacteria on leaves of tropical trees indicates that there is a strong relationship between host plants and Acidobacteria in tropical rain forest, which needs to be investigated further. The similarity of phyllosphere bacterial communities amongst the tree species sampled shows a significant tendency to follow host plant phylogeny, with more similar communities on more closely related hosts.

A hump-backed trend in bacterial diversity with elevation on Mount Fuji, Japan.

Little is known of how bacterial diversity in soils varies with elevation. One previous study found a decline with elevation, whereas another found no trend. We chose Mount Fuji of Japan as a geologically and topographically simple mountain system. Samples were taken at elevational intervals, between the base of the mountain at 1,000 m and its summit at 3,700 m. Polymerase chain reaction-amplified soil DNA for the bacterial 16S gene targeting V1-V3 region was pyrosequenced using the 454 Roche machine, and taxonomically classified with reference to a bioinformatic database. There was a significant "peak" in total bacterial diversity at around 2,500 m above the tree line with a decline towards the highest elevations around 3,700 m near the summit. Individual bacterial phyla show distinct trends-increase, decrease, or a mid-elevational "bulge" in diversity. Bacterial diversity does not parallel woody plant or herbaceous plant diversity. We suggest that beyond the tree and vegetation line, the more extreme temperature fluctuations, stronger UV, lack of nutrients, and more frequent disturbance of the loose substrate of these slopes allows less competition and greater bacterial species diversity due to "lottery" recruitment. However, at the highest elevations, the physiological challenges are so extreme that fewer bacterial species are capable of surviving.