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Journal articles on the topic 'Microbial analysis'

Author: Grafiati

Published: 10 January 2023

Last updated: 28 January 2023

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1

P. Ambiga, P. Ambiga, R. Bhavani R. Bhavani, P. Sivamani P. Sivamani, and R. R. Thanighai arassu. "Comparative Analysis of Microbial and Human Amylase Activity." Indian Journal of Applied Research 3, no. 3 (October 1, 2011): 380–84. http://dx.doi.org/10.15373/2249555x/mar2013/130.

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2

White, David C. "Microbial community analysis." Environmental Microbiology 4, no. 1 (January 2002): 13–14. http://dx.doi.org/10.1046/j.1462-2920.2002.t01-2-00257.x.

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3

Haleem, Azhar M., Abdul Hameed M, Jawad Al Obaidy, and Ula H. Mahmood. "Microbial Analysis and Cytogenetic Effects of Drinking Bottled Water." Indian Journal of Applied Research 4, no. 6 (October 1, 2011): 1–3. http://dx.doi.org/10.15373/2249555x/june2014/191.

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4

Baldrian, P. "Microbial enzyme-catalyzed processes in soils and their analysis." Plant, Soil and Environment 55, No. 9 (October 14, 2009): 370–78. http://dx.doi.org/10.17221/134/2009-pse.

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Currently, measuring enzyme activities in soils or other lignocellulose-based materials is technically feasible; this measurement is particularly suitable for evaluating soil processes of biopolymer (cellulose, hemicelluloses, lignin, chitin and others) degradation by microbes and for assessing cycling and mobilization of principal nutrients including nitrogen, phosphorus and sulfur. With some considerations, assay methods can provide reliable information on the concentration of enzymes in soil or the rates of enzyme-catalyzed processes. Enzyme analyses in recent studies demonstrated a high level of spatial variability of soil enzyme activity both in depth and in space. The vertical gradients of enzyme activities are most developed in forest soils. Furthermore, enzyme activity in soils is regulated by seasonally-dependent variables such as temperature, moisture and the input of fresh litter. While several enzymes are widely produced by different groups of soil microorganisms, some of them can be used as indicators of the presence or activity of specific microbial taxa.

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5

Xu, Xuanrong, and Yutong Liu. "Quantitative Analysis Method of Ophthalmic Microbial Membrane Function Based on Microbiological Analysis." E3S Web of Conferences 271 (2021): 04040. http://dx.doi.org/10.1051/e3sconf/202127104040.

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Ophthalmic microbial eye membrane is a kind of membrane complex with highly complex structure, but it also has the therapeutic effect of bacteria that can produce microbial eye membrane. Nowadays, there is no effective method to analyze the microbial membrane. Therefore, a quantitative analysis method of ophthalmic microbial membrane function based on microbiological analysis is proposed. The biomass per unit area, substrate coverage and average thickness of the biofilm were quantitatively analyzed with Staphylococcus as material and microbiological analysis method. The structure indexes such as biomass, average thickness and average diffusion distance increased significantly, indicating the transformation process of microbial membrane from occurrence to maturity. Microbiological analysis method can effectively evaluate the occurrence, development and maturation of microbial membrane, and has potential value in studying the theoretical mechanism of microbial membrane formation.

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6

Vestal, J. Robie, and David C. White. "Lipid Analysis in Microbial Ecology." BioScience 39, no. 8 (September 1989): 535–41. http://dx.doi.org/10.2307/1310976.

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7

Bruccoleri, R. "Concordance analysis of microbial genomes." Nucleic Acids Research 26, no. 19 (October 1, 1998): 4482–86. http://dx.doi.org/10.1093/nar/26.19.4482.

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8

Washburn, Michael P., and John R. Yates. "Analysis of the microbial proteome." Current Opinion in Microbiology 3, no. 3 (June 2000): 292–97. http://dx.doi.org/10.1016/s1369-5274(00)00092-8.

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9

Nayak, Pritymanjari. "Microbial Analysis in Dry Socket." Indian Journal of Public Health Research & Development 10, no. 11 (2019): 1084. http://dx.doi.org/10.5958/0976-5506.2019.03651.9.

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10

Monzon, Oihane, Yu Yang, Cong Yu, Qilin Li, and Pedro J. J. Alvarez. "Microbial fuel cells under extreme salinity: performance and microbial analysis." Environmental Chemistry 12, no. 3 (2015): 293. http://dx.doi.org/10.1071/en13243.

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Environmental context The treatment of extremely saline, high-strength wastewaters while producing electricity represents a great opportunity to mitigate environmental effects and recover resources associated with wastes from shale oil and gas production. This paper demonstrates that extreme halophilic microbes can produce electricity at salinity up to 3- to 7-fold higher than sea water. Abstract Many industries generate hypersaline wastewaters with high organic strength, which represent a major challenge for pollution control and resource recovery. This study assesses the potential for microbial fuel cells (MFCs) to treat such wastewaters and generate electricity under extreme salinity. A power density of up to 71mWm–2 (318mWm–3) with a Coulombic efficiency of 42% was obtained with 100gL–1 NaCl, and the capability of MFCs to generate electricity in the presence of up to 250gL–1 NaCl was demonstrated for the first time. Pyrosequencing analysis of the microbial community colonising the anode showed the predominance of a single genus, Halanaerobium (85.7%), which has been found in late flowback fluids and is widely distributed in shale formations and oil reservoirs. Overall, this work encourages further research to assess the feasibility of MFCs to treat hypersaline wastewaters generated by the oil and gas industry.

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11

Manika Das, Manika Das, Sumer Singh, and Bhaben Tanti. "Biochemical Analysis of Paper Mill Effluent & Microbial Degradation of Phenol." International Journal of Scientific Research 2, no. 4 (June 1, 2012): 73–76. http://dx.doi.org/10.15373/22778179/apr2013/58.

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12

O. V., Kyrychenko. "MARKET ANALYSIS AND MICROBIAL BIOPREPARATIONS CREATION FOR CROP GROWING IN UKRAINE." Biotechnologia Acta 8, no. 4 (August 2015): 42–52. http://dx.doi.org/10.15407/biotech8.04.040.

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13

von Wintzingerode, Friedrich, Burkhard Selent, Werner Hegemann, and Ulf B. Göbel. "Phylogenetic Analysis of an Anaerobic, Trichlorobenzene-Transforming Microbial Consortium." Applied and Environmental Microbiology 65, no. 1 (January 1, 1999): 283–86. http://dx.doi.org/10.1128/aem.65.1.283-286.1999.

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ABSTRACT A culture-independent phylogenetic survey for an anaerobic trichlorobenzene-transforming microbial community was carried out. Small-subunit rRNA genes were PCR amplified from community DNA by using primers specific for Bacteria or Euryarchaeotaand were subsequently cloned. Application of a new hybridization-based screening approach revealed 51 bacterial clone families, one of which was closely related to dechlorinating Dehalobacter species. Several clone sequences clustered to rDNA sequences obtained from a molecular study of an anaerobic aquifer contaminated with hydrocarbons and chlorinated solvents (Dojka et al., Appl. Env. Microbiol. 64:3869–3877, 1998).

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14

Hashemi, Seyedbehnam, Sayed Ebrahim Hashemi, Kristian M. Lien, and Jacob J. Lamb. "Molecular Microbial Community Analysis as an Analysis Tool for Optimal Biogas Production." Microorganisms 9, no. 6 (May 28, 2021): 1162. http://dx.doi.org/10.3390/microorganisms9061162.

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The microbial diversity in anaerobic digestion (AD) is important because it affects process robustness. High-throughput sequencing offers high-resolution data regarding the microbial diversity and robustness of biological systems including AD; however, to understand the dynamics of microbial processes, knowing the microbial diversity is not adequate alone. Advanced meta-omic techniques have been established to determine the activity and interactions among organisms in biological processes like AD. Results of these methods can be used to identify biomarkers for AD states. This can aid a better understanding of system dynamics and be applied to producing comprehensive models for AD. The paper provides valuable knowledge regarding the possibility of integration of molecular methods in AD. Although meta-genomic methods are not suitable for on-line use due to long operating time and high costs, they provide extensive insight into the microbial phylogeny in AD. Meta-proteomics can also be explored in the demonstration projects for failure prediction. However, for these methods to be fully realised in AD, a biomarker database needs to be developed.

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15

Djokic, Lidija, M. Savic, Tanja Narancic, and Branka Vasiljevic. "Metagenomic analysis of soil microbial communities." Archives of Biological Sciences 62, no. 3 (2010): 559–64. http://dx.doi.org/10.2298/abs1003559d.

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Ramonda serbica and Ramonda nathaliae, rare resurrection plants growing in the Balkan Peninsula, produce a high amount of phenolic compounds as a response to stress. The composition and size of bacterial communities in two rhizosphere soil samples of these plants were analyzed using a metagenomic approach. Fluorescent in situ hybridization (FISH) experiments together with DAPI staining showed that the metabolically active bacteria represent only a small fraction, approximately 5%, of total soil bacteria. Using universal bacteria - specific primers 16S rDNA genes were amplified directly from metagenomic DNAs and two libraries were constructed. The Restriction Fragment Length Polymorphism (RLFP) method was used in library screening. Amongst 192 clones, 35 unique operational taxonomic units (OTUs) were determined from the rhizosphere of R. nathaliae, and 13 OTUs out of 80 clones in total from the library of R. serbica. Representative clones from each OTU were sequenced. The majority of sequences from metagenomes showed very little similarity to any cultured bacteria. In conclusion, the bacterial communities in the studied soil samples showed quite poor diversity. .

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16

Kumar, DhivyaAshok. "Lacrimal sac infections and microbial analysis." TNOA Journal of Ophthalmic Science and Research 55, no. 4 (2017): 293. http://dx.doi.org/10.4103/tjosr.tjosr_23_18.

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17

Chivian, Dylan, Paramvir S. Dehal, Keith Keller, and Adam P. Arkin. "metaMicrobesOnline: phylogenomic analysis of microbial communities." Nucleic Acids Research 41, no. D1 (November 30, 2012): D648—D654. http://dx.doi.org/10.1093/nar/gks1202.

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18

Lund, Jesper Beltoft, Markus List, and Jan Baumbach. "Interactive microbial distribution analysis using BioAtlas." Nucleic Acids Research 45, W1 (April 29, 2017): W509—W513. http://dx.doi.org/10.1093/nar/gkx304.

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19

Slots, Jørgen. "Microbial analysis in supportive periodontal treatment." Periodontology 2000 12, no. 1 (October 1996): 56–59. http://dx.doi.org/10.1111/j.1600-0757.1996.tb00082.x.

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20

Zink, Albert R., Udo Reischl, Hans Wolf, and Andreas G. Nerlich. "Molecular analysis of ancient microbial infections." FEMS Microbiology Letters 213, no. 2 (August 2002): 141–47. http://dx.doi.org/10.1111/j.1574-6968.2002.tb11298.x.

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21

Chizhikov, Vladimir, Avraham Rasooly, Konstantin Chumakov, and Dan D. Levy. "Microarray Analysis of Microbial Virulence Factors." Applied and Environmental Microbiology 67, no. 7 (July 1, 2001): 3258–63. http://dx.doi.org/10.1128/aem.67.7.3258-3263.2001.

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ABSTRACT Hybridization with oligonucleotide microchips (microarrays) was used for discrimination among strains of Escherichia coli and other pathogenic enteric bacteria harboring various virulence factors. Oligonucleotide microchips are miniature arrays of gene-specific oligonucleotide probes immobilized on a glass surface. The combination of this technique with the amplification of genetic material by PCR is a powerful tool for the detection of and simultaneous discrimination among food-borne human pathogens. The presence of six genes (eaeA, slt-I,slt-II, fliC, rfbE, andipaH) encoding bacterial antigenic determinants and virulence factors of bacterial strains was monitored by multiplex PCR followed by hybridization of the denatured PCR product to the gene-specific oligonucleotides on the microchip. The assay was able to detect these virulence factors in 15 Salmonella,Shigella, and E. coli strains. The results of the chip analysis were confirmed by hybridization of radiolabeled gene-specific probes to genomic DNA from bacterial colonies. In contrast, gel electrophoretic analysis of the multiplex PCR products used for the microarray analysis produced ambiguous results due to the presence of unexpected and uncharacterized bands. Our results suggest that microarray analysis of microbial virulence factors might be very useful for automated identification and characterization of bacterial pathogens.

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22

Lan, Mei, Jia Yuan Zhang, Wei Wei Zhao, Meng Dong, and Yong Zhang. "Analysis of Microbial Characteristics for BAF." Applied Mechanics and Materials 295-298 (February 2013): 264–67. http://dx.doi.org/10.4028/www.scientific.net/amm.295-298.264.

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In the biological aerated filter, the number of microorganisms and activity play a key role on the removal of the organic matter. Studying the microbial mass distribution is a useful method for understanding the organic matter degradation mechanism, and it can provide theoretical basis for the operations. Blood count plate was adopted to determine the number of living bacterium, the test results show that attachment biomass of activated carbon reduce with the increase of the height. The biomass and the viable bacterial number counted in the height of 25cm from BAF water level is 15.0 CFU/g·dwC whereas 3.24mg/g·dwc by VAS, which is the largest along the height. Backwashing restored the microbial activity in BAF, after back washing, biomass at different height from25 to105cm are 0.6 mg VAS/g·dwc or so, which is almost similar to filtering beginning.

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23

Galperin, Michael Y., David M. Kristensen, Kira S. Makarova, Yuri I. Wolf, and Eugene V. Koonin. "Microbial genome analysis: the COG approach." Briefings in Bioinformatics 20, no. 4 (September 14, 2017): 1063–70. http://dx.doi.org/10.1093/bib/bbx117.

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Abstract For the past 20 years, the Clusters of Orthologous Genes (COG) database had been a popular tool for microbial genome annotation and comparative genomics. Initially created for the purpose of evolutionary classification of protein families, the COG have been used, apart from straightforward functional annotation of sequenced genomes, for such tasks as (i) unification of genome annotation in groups of related organisms; (ii) identification of missing and/or undetected genes in complete microbial genomes; (iii) analysis of genomic neighborhoods, in many cases allowing prediction of novel functional systems; (iv) analysis of metabolic pathways and prediction of alternative forms of enzymes; (v) comparison of organisms by COG functional categories; and (vi) prioritization of targets for structural and functional characterization. Here we review the principles of the COG approach and discuss its key advantages and drawbacks in microbial genome analysis.

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24

Dahllöf, Ingela. "Molecular community analysis of microbial diversity." Current Opinion in Biotechnology 13, no. 3 (June 2002): 213–17. http://dx.doi.org/10.1016/s0958-1669(02)00314-2.

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25

Knierim, B., B. van Leer, RI Webb, M. Lin, T. Goddard, P. Wilmes, KL McDonald, P. Hugenholtz, JT Liphardt, and M. Auer. "Three-Dimensional Analysis of Microbial Communities." Microscopy and Microanalysis 16, S2 (July 2010): 388–89. http://dx.doi.org/10.1017/s1431927610060605.

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26

Liu, Jing, and Bo Mattiasson. "Microbial BOD sensors for wastewater analysis." Water Research 36, no. 15 (September 2002): 3786–802. http://dx.doi.org/10.1016/s0043-1354(02)00101-x.

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27

Riesenfeld, Christian S., Patrick D. Schloss, and Jo Handelsman. "Metagenomics: Genomic Analysis of Microbial Communities." Annual Review of Genetics 38, no. 1 (December 2004): 525–52. http://dx.doi.org/10.1146/annurev.genet.38.072902.091216.

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28

Puchkov, E. O. "Computer image analysis of microbial colonies." Microbiology 79, no. 2 (April 2010): 141–46. http://dx.doi.org/10.1134/s0026261710020025.

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29

Andrade-Linares, Diana R., Anika Lehmann, and Matthias C. Rillig. "Microbial stress priming: a meta-analysis." Environmental Microbiology 18, no. 4 (February 2, 2016): 1277–88. http://dx.doi.org/10.1111/1462-2920.13223.

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30

BEPPU, Teruhiko. "Analysis and application of microbial functions." Journal of the agricultural chemical society of Japan 60, no. 7 (1986): 529–35. http://dx.doi.org/10.1271/nogeikagaku1924.60.529.

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31

Broomall, Stacey M., Mohamed Ait Ichou, Michael D. Krepps, Lauren A. Johnsky, Mark A. Karavis, Kyle S. Hubbard, Joseph M. Insalaco, et al. "Whole-Genome Sequencing in Microbial Forensic Analysis of Gamma-Irradiated Microbial Materials." Applied and Environmental Microbiology 82, no. 2 (November 13, 2015): 596–607. http://dx.doi.org/10.1128/aem.02231-15.

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ABSTRACTEffective microbial forensic analysis of materials used in a potential biological attack requires robust methods of morphological and genetic characterization of the attack materials in order to enable the attribution of the materials to potential sources and to exclude other potential sources. The genetic homogeneity and potential intersample variability of many of the category A to C bioterrorism agents offer a particular challenge to the generation of attributive signatures, potentially requiring whole-genome or proteomic approaches to be utilized. Currently, irradiation of mail is standard practice at several government facilities judged to be at particularly high risk. Thus, initial forensic signatures would need to be recovered from inactivated (nonviable) material. In the study described in this report, we determined the effects of high-dose gamma irradiation on forensic markers of bacterial biothreat agent surrogate organisms with a particular emphasis on the suitability of genomic DNA (gDNA) recovered from such sources as a template for whole-genome analysis. While irradiation of spores and vegetative cells affected the retention of Gram and spore stains and sheared gDNA into small fragments, we found that irradiated material could be utilized to generate accurate whole-genome sequence data on the Illumina and Roche 454 sequencing platforms.

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32

Sun, Yanmei, Jincheng Wei, Peng Liang, and Xia Huang. "Microbial community analysis in biocathode microbial fuel cells packed with different materials." AMB Express 2, no. 1 (2012): 21. http://dx.doi.org/10.1186/2191-0855-2-21.

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33

Yi, Li-Na, Zhi-Ping Li, Li Liu, Yong-Qiang Bi, Xiao-Tong Wang, and Ju-Ping Yi. "Functional microbial stimulation for oil recovery enhancement based on microbial community analysis." Biotechnology & Biotechnological Equipment 32, no. 6 (October 15, 2018): 1468–76. http://dx.doi.org/10.1080/13102818.2018.1523689.

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34

Wu, Yining, Xin Zhao, Min Jin, Yan Li, Shuai Li, Fanying Kong, Jun Nan, and Aijie Wang. "Copper removal and microbial community analysis in single-chamber microbial fuel cell." Bioresource Technology 253 (April 2018): 372–77. http://dx.doi.org/10.1016/j.biortech.2018.01.046.

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35

KIM, J., S. JUNG, J. REGAN, and B. LOGAN. "Electricity generation and microbial community analysis of alcohol powered microbial fuel cells." Bioresource Technology 98, no. 13 (September 2007): 2568–77. http://dx.doi.org/10.1016/j.biortech.2006.09.036.

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36

Villanueva, Laura, Antoni Navarrete, Jordi Urmeneta, David C. White, and Ricardo Guerrero. "Analysis of diurnal and vertical microbial diversity of a hypersaline microbial mat." Archives of Microbiology 188, no. 2 (March 15, 2007): 137–46. http://dx.doi.org/10.1007/s00203-007-0229-6.

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37

Maddalwar, Shrirang R., and Arti S. Shanware. "Growth Curve Analysis of Rhizobium leguminosarum Using Voltage Produced by Microbial Fuel Cell." International Journal of Life-Sciences Scientific Research 4, no. 6 (November 2018): 2111–15. http://dx.doi.org/10.21276/ijlssr.2018.4.6.7.

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38

Valášková, V., and P. Baldrian. "Denaturing gradient gel electrophoresis as a fingerprinting method for the analysis of soil microbial communities." Plant, Soil and Environment 55, No. 10 (October 21, 2009): 413–23. http://dx.doi.org/10.17221/132/2009-pse.

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In soil microbial ecology, the effects of environmental factors and their gradients, temporal changes or the response to specific experimental treatments of microbial communities can only be effectively analyzed using methods that address the structural differences among whole communities. Fingerprinting methods are the most appropriate technique for this task when multiple samples must be analyzed. Among the methods currently used to compare microbial communities based on nucleic acid sequences, the techniques based on differences in the melting properties of double-stranded molecules, denaturing gradient gel electrophoresis (DGGE) or temperature gradient gel electrophoresis (TGGE), are the most widely used. Their main advantage is that they provide the possibility to further analyze whole sequences contained in fingerprints using molecular methods. In addition to the analysis of microbial communities based on DNA extracted from soils, DGGE/TGGE can also be used for the assessment of the active part of the community based on the analysis of RNA-derived sequences or for the analysis of sequences of functional genes encoding for proteins involved in important soil processes.

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39

De Schamphelaire, Liesje, Angela Cabezas, Massimo Marzorati, Michael W. Friedrich, Nico Boon, and Willy Verstraete. "Microbial Community Analysis of Anodes from Sediment Microbial Fuel Cells Powered by Rhizodeposits of Living Rice Plants." Applied and Environmental Microbiology 76, no. 6 (January 22, 2010): 2002–8. http://dx.doi.org/10.1128/aem.02432-09.

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ABSTRACT By placing the anode of a sediment microbial fuel cell (SMFC) in the rhizosphere of a rice plant, root-excreted rhizodeposits can be microbially oxidized with concomitant current generation. Here, various molecular techniques were used to characterize the composition of bacterial and archaeal communities on such anodes, as influenced by electrical circuitry, sediment matrix, and the presence of plants. Closed-circuit anodes in potting soil were enriched with Desulfobulbus-like species, members of the family Geobacteraceae, and as yet uncultured representatives of the domain Archaea.

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40

Li, Zhen, Rishika Haynes, Eugene Sato, Malcolm S. Shields, Yoshiko Fujita, and Chikashi Sato. "Microbial Community Analysis of a Single Chamber Microbial Fuel Cell Using Potato Wastewater." Water Environment Research 86, no. 4 (April 1, 2014): 324–30. http://dx.doi.org/10.2175/106143013x13751480308641.

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41

Zhdanova, G. O., E. Yu Konovalova, M. Yu Tolstoy, A. V. Kashevsky, L. Barbora, P. Goswami, S. Goel, V. A. Fialkow, A. B. Kupchinsky, and D. I. Stom. "Comparative Analysis of Electrogenic Activity of Complex Microbial Preparations in Microbial Fuel Cells." IOP Conference Series: Earth and Environmental Science 272 (June 21, 2019): 032161. http://dx.doi.org/10.1088/1755-1315/272/3/032161.

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42

Kim, Min, Kalu I. Ekpeghere, Soo-Hyeon Kim, Jae-Soo Chang, and Sung-Cheol Koh. "Analysis of Microbial Communities in Aquatic Sediment Microbial Fuel Cells Injected with Glucose." Korean Journal of Microbiology 48, no. 4 (December 31, 2012): 254–61. http://dx.doi.org/10.7845/kjm.2012.061.

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43

Clarke, Erik L., Abigail P. Lauder, Casey E. Hofstaedter, Young Hwang, Ayannah S. Fitzgerald, Ize Imai, Wojciech Biernat, et al. "Microbial Lineages in Sarcoidosis. A Metagenomic Analysis Tailored for Low–Microbial Content Samples." American Journal of Respiratory and Critical Care Medicine 197, no. 2 (January 15, 2018): 225–34. http://dx.doi.org/10.1164/rccm.201705-0891oc.

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44

von Stockar, U., and J. S. Liu. "Does microbial life always feed on negative entropy? Thermodynamic analysis of microbial growth." Biochimica et Biophysica Acta (BBA) - Bioenergetics 1412, no. 3 (August 1999): 191–211. http://dx.doi.org/10.1016/s0005-2728(99)00065-1.

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45

Phung, Nguyet Thu, Jiyoung Lee, Kui Hyun Kang, In Seop Chang, Geoffrey Michael Gadd, and Byung Hong Kim. "Analysis of microbial diversity in oligotrophic microbial fuel cells using 16S rDNA sequences." FEMS Microbiology Letters 233, no. 1 (April 2004): 77–82. http://dx.doi.org/10.1016/j.femsle.2004.01.041.

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46

Kugarajah, Vaidhegi, Moogambigai Sugumar, and Sangeetha Dharmalingam. "Nanocomposite membrane and microbial community analysis for improved performance in microbial fuel cell." Enzyme and Microbial Technology 140 (October 2020): 109606. http://dx.doi.org/10.1016/j.enzmictec.2020.109606.

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47

Tellez, Joseph, Crystal Jaing, Jun Wang, Ralph Green, and Mingyi Chen. "Comprehensive Analysis Of Microbial Signatures For Lymphomagenesis Using a Novel Microbial Detection Array." Blood 122, no. 21 (November 15, 2013): 4282. http://dx.doi.org/10.1182/blood.v122.21.4282.4282.

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Abstract Introduction Infectious agents are estimated to play a causative role in approximately 20% of cancers worldwide. Viral infections, notably the Epstein-Barr virus (EBV) are associated with 10-15% of B-cell lymphomas and are found at a higher frequency in immunosuppressed patients with B-cell malignancy. The risks posed by these pathogens increases with age. Early detection can impact treatment options and may play a critical role in patient survival. We report the use of the Lawrence Livermore Microbial Detection Array (LLMDA), a highly sensitive and comprehensive detection system that contains probes for all known sequenced viruses and bacteria designed to identify pathogen-associated diseases. Our study focuses on detecting pathogens that may be associated with lymphomas, in order to develop appropriate therapeutic treatment strategies for pathogen-associated B-cell lymphomas. Methods The LLMDA is a pan-Microbial Detection Array (MDA) capable of detecting all known viruses (including phages), bacteria and plasmids and uses a novel statistical analysis method to identify organisms from complex mixtures hybridized to the array. The LLMDA contains a more comprehensive bacterial and viral target spectrum, more probes per target and is based on more updated sequence data than other existing microbial detection/discovery arrays. Family-specific probes representing complete genomes of all sequenced bacteria and viruses, conserved segments of these genomes, and plasmids were selected. Probes possess adequate sequence variation to allow detection of divergent species with homology to sequenced organisms. Using the LLMDA we tested indolent and aggressive stage B cell lymphomas and normal tissues as controls. We demonstrated the system’s accuracy by investigating the pathogen profiles of previously analyzed post-transplant lymphoproliferative disorder (PTLD) tumors. We also applied the technique to fresh frozen and formalin fixed, paraffin-embedded (FFPE) tissues to evaluate the range of sample types amenable to the LLMDA analysis. Results We evaluated tissue from 34 lymphoma cases using LLMDA. These included 30 B cell (9 indolent and 21 aggressive stage), 2 T cell and 2 NKT cell, 4 plasmacytomas as well as 8 specimens of benign lymphoid tissue. Five of 21 aggressive stage B cell lymphomas were EBER+, and all the indolent stage B cell lymphomas were EBER-. Both NKT cell lymphomas were EBER+, and the T cell lymphomas and benign tissues were EBER-. Five of the PTLD cases (4 B cell lymphomas and 1 NKT cell lymphoma) were EBER+ and 5 were EBER-. Finally, two of the FFPE tissues (1 B cell lymphoma and 1 NKT cell lymphoma) were EBER+ and 1 EBER-, in conformity with the previously analysis of EBER status in these samples. We have confirmed the accuracy of the technique by detecting EBV in EBV-positive lymphomas while observing no false-positive results in EBV-negative lymphomas Conclusions We have confirmed the LLMDA’s efficacy for detecting viruses in pathogen-associated disease. This technique may provide a powerful and sensitive method for identifying known viral pathogens associated with tumors and may also prove useful for the discovery of novel tumor-associated viruses. Disclosures: No relevant conflicts of interest to declare.

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Luo, Yong, Renduo Zhang, Guangli Liu, Jie Li, Mingchen Li, and Cuiping Zhang. "Electricity generation from indole and microbial community analysis in the microbial fuel cell." Journal of Hazardous Materials 176, no. 1-3 (April 15, 2010): 759–64. http://dx.doi.org/10.1016/j.jhazmat.2009.11.100.

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Katuri, Krishna P., Ann-Marie Enright, Vincent O'Flaherty, and Dónal Leech. "Microbial analysis of anodic biofilm in a microbial fuel cell using slaughterhouse wastewater." Bioelectrochemistry 87 (October 2012): 164–71. http://dx.doi.org/10.1016/j.bioelechem.2011.12.002.

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Sahl, Jason W., Norman R. Pace, and John R. Spear. "Comparative Molecular Analysis of Endoevaporitic Microbial Communities." Applied and Environmental Microbiology 74, no. 20 (August 29, 2008): 6444–46. http://dx.doi.org/10.1128/aem.00879-08.

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ABSTRACT A phylogenetic comparison of microbial communities in hypersaline evaporites was conducted on crusts from Guerrero Negro, Mexico, and Lindsey Lake, New Mexico, using culture-independent rRNA gene sequence analysis. Many sequences were shared between evaporites, which suggests that similar environments select for specific microbial lineages from a global metacommunity.

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