Biomedical subjects

Anthony V Palumbo

Publications and source records attributed to Anthony V Palumbo.

6 recordsLinked to original sources

PubMed2006

Application of nonlinear analysis methods for identifying relationships between microbial community structure and groundwater geochemistry.

The relationship between groundwater geochemistry and microbial community structure can be complex and difficult to assess. We applied nonlinear and generalized linear data analysis methods to relate microbial biomarkers (phospholipids fatty acids, PLFA) to groundwater geochemical characteristics at the Shiprock uranium mill tailings disposal site that is primarily contaminated by uranium, sulfate, and nitrate. First, predictive models were constructed using feedforward artificial neural networks (NN) to predict PLFA classes from geochemistry. To reduce the danger of overfitting, parsimonious NN architectures were selected based on pruning of hidden nodes and elimination of redundant predictor (geochemical) variables. The resulting NN models greatly outperformed the generalized linear models. Sensitivity analysis indicated that tritium, which was indicative of riverine influences, and uranium were important in predicting the distributions of the PLFA classes. In contrast, nitrate concentration and inorganic carbon were least important, and total ionic strength was of intermediate importance. Second, nonlinear principal components (NPC) were extracted from the PLFA data using a variant of the feedforward NN. The NPC grouped the samples according to similar geochemistry. PLFA indicators of Gram-negative bacteria and eukaryotes were associated with the groups of wells with lower levels of contamination. The more contaminated samples contained microbial communities that were predominated by terminally branched saturates and branched monounsaturates that are indicative of metal reducers, actinomycetes, and Gram-positive bacteria. These results indicate that the microbial community at the site is coupled to the geochemistry and knowledge of the geochemistry allows prediction of the community composition.

Bacteria↗

PubMed2004

Microbial diversity and heterogeneity in sandy subsurface soils.

Microbial community diversity and heterogeneity in saturated and unsaturated subsurface soils from Abbott's Pit in Virginia (1.57, 3.25, and 4.05 m below surface) and Dover Air Force Base in Delaware (6.00 and 7.50 m below surface) were analyzed using a culture-independent small-subunit (SSU) rRNA gene (rDNA)-based cloning approach. Four to six dominant operational taxonomic units (OTUs) were identified in 33 to 100 unique SSU rDNA clones (constituting about 40 to 50% of the total number of SSU rDNA clones in the clone library) from the saturated subsurface samples, whereas no dominant OTUs were observed in the unsaturated subsurface sample. Less than 10% of the clones among samples from different depths at the same location were identical, and the proportion of overlapping OTUs was lower for the samples that were vertically far apart than for adjacent samples. In addition, no OTUs were shared between the Abbott's Pit and Dover samples. The majority of the clones (80%) had sequences that were less than 5% different from those in the current databases. Phylogenetic analysis indicated that most of the bacterial clones were affiliated with members of the Proteobacteria family (90%), gram-positive bacteria (3%), and members of the Acidobacteria family (3%). Principal component analysis revealed that samples from different geographic locations were well separated and that samples from the same location were closely grouped together. In addition, the nonsaturated subsurface samples from Abbott's Pit clustered together and were well separated from the saturated subsurface soil sample. Finally, the overall diversity of the subsurface samples was much lower than that of the corresponding surface soil samples.

Bacteria↗

PubMed2003

Laser-induced breakdown spectroscopy for the environmental determination of total carbon and nitrogen in soils.

Soils from various sites have been analysed with the laser-induced breakdown spectroscopy (LIBS) technique for total elemental determination of carbon and nitrogen. Results from LIBS have been correlated to a standard laboratory-based technique (sample combustion), and strong linear correlations were obtained for determination of carbon concentrations. The LIBES technique was used on soils before and after acid washing, and the technique appears to be useful for the determination of both organic and inorganic soil carbon. The LIBS technique has the potential to be packaged into a field-deployable instrument.

Journal Article↗

PubMed2003

Molecular diversity of denitrifying genes in continental margin sediments within the oxygen-deficient zone off the Pacific coast of Mexico.

To understand the composition and structure of denitrifying communities in the oxygen-deficient zone off the Pacific coast of Mexico, the molecular diversity of nir genes from sediments obtained at four stations was examined by using a PCR-based cloning approach. A total of 50 operational taxonomic units (OTUs) for nirK and 82 OTUs for nirS were obtained from all samples. Forty-four of the nirS clones and 31 of the nirK clones were sequenced; the levels of similarity of the nirS clones were 52 to 92%, and the levels of similarity of the nirS clones were 50 to 99%. The percentages of overlapping OTUs between stations were 18 to 30% for nirS and 5 to 8% for nirK. Sequence analysis revealed that 26% of the nirS clones were related to the nirS genes of Alcaligenes faecalis (80 to 94% similar) and Pseudomonas stutzeri (80 to 99%), whereas 3 to 31% of the nirK clones were closely related to the nirK genes of Pseudomonas sp. strain G-179 (98 to 99%), Bradyrhizobium japonicum (91%), Blastobacter denitrificans (83%), and Alcaligenes xylosoxidans (96%). The rest of the clones, however, were less than 80% similar to nirS and nirK sequences available in sequence databases. The results of a principal-component analysis (PCA) based on the percentage of OTUs and biogeochemical data indicated that the nitrate concentration and oxygen have an effect on the denitrifying communities. The communities at the stations in oxygen-deficient zones were more similar than the communities at the stations in the oxygenated zone. The denitrifying communities were more similar at the stations that were closer together and had similar nitrate levels. Also, the results of PCA based on biogeochemical properties suggest that geographic location and biogeochemical conditions, especially the nitrate and oxygen levels, appear to be the key factors that control the structure of denitrifying communities.

Cloning, Molecular↗

PubMed2002

Metabolomics and microarrays for improved understanding of phenotypic characteristics controlled by both genomics and environmental constraints.

Advances in our understanding of functional genomics are best addressed by integrative studies that include measurements of mRNA, proteins, and low molecular weight metabolites over time and varied conditions. Bioinformatics can then be used to relate this data to the genome. Current technology allows for comprehensive and rapid mRNA expression profiling and mass spectrophotometric measurement of low molecular weight intermediates and metabolic products. In prokaryotic organisms, this combination provides a potentially powerful tool for identifying gene function and regulatory networks even in the absence of a combined proteomic approach.

Carbon Radioisotopes↗

PubMed2002

Spatial and resource factors influencing high microbial diversity in soil.

To begin defining the key determinants that drive microbial community structure in soil, we examined 29 soil samples from four geographically distinct locations taken from the surface, vadose zone, and saturated subsurface using a small-subunit rRNA-based cloning approach. While microbial communities in low-carbon, saturated, subsurface soils showed dominance, microbial communities in low-carbon surface soils showed remarkably uniform distributions, and all species were equally abundant. Two diversity indices, the reciprocal of Simpson's index (1/D) and the log series index, effectively distinguished between the dominant and uniform diversity patterns. For example, the uniform profiles characteristic of the surface communities had diversity index values that were 2 to 3 orders of magnitude greater than those for the high-dominance, saturated, subsurface communities. In a site richer in organic carbon, microbial communities consistently exhibited the uniform distribution pattern regardless of soil water content and depth. The uniform distribution implies that competition does not shape the structure of these microbial communities. Theoretical studies based on mathematical modeling suggested that spatial isolation could limit competition in surface soils, thereby supporting the high diversity and a uniform community structure. Carbon resource heterogeneity may explain the uniform diversity patterns observed in the high-carbon samples even in the saturated zone. Very high levels of chromium contamination (e.g., >20%) in the high-organic-matter soils did not greatly reduce the diversity. Understanding mechanisms that may control community structure, such as spatial isolation, has important implications for preservation of biodiversity, management of microbial communities for bioremediation, biocontrol of root diseases, and improved soil fertility.

Bacteria↗