Extraction of DNA from Plant and Fungus Tissues in situ

Background: When samples are collected in the field and transported to the lab, degradation of the nucleic acids contained in the samples is frequently observed. Immediate extraction and precipitation of the nucleic acids reduces degradation to a minimum, thus preserving accurate sequence information. An extraction method to obtain high quality DNA in field studies is described. Findings. DNA extracted immediately after sampling was compared to DNA extracted after allowing the sampled tissues to air dry at 21°C for 48 or 72 hours. While DNA extracted from fresh tissues exhibited little degradation, DNA extracted from all tissues exposed to 21°C air for 48 or 72 hours exhibited varying degrees of degradation. Yield was higher for extractions from fresh tissues in most cases. Four microcentrifuges were compared for DNA yield: one standard electric laboratory microcentrifuge (max rcf=16,000×g), two battery-operated microcentrifuges (max rcf=5,000 and 3,000 ×g), and one manually-operated microcentrifuge (max rcf=120×g). Yields for all centrifuges were similar. DNA extracted under simulated field conditions was similar in yield and quality to DNA extracted in the laboratory using the same equipment. Conclusions: This CTAB (cetyltrimethylammonium bromide) DNA extraction method employs battery-operated and manually-operated equipment to isolate high quality DNA in the field. The method was tested on plant and fungus tissues, and may be adapted for other types of organisms. The method produced high quality DNA in laboratory tests and under simulated field conditions. The field extraction method should prove useful for working in remote sites, where ice, dry ice, and liquid nitrogen are unavailable; where degradation is likely to occur due to the long distances between the sample site and the laboratory; and in instances where other DNA preservation and transportation methods have been unsuccessful. It may be possible to adapt this method for genomic, metagenomic, transcriptomic and metabolomic projects using samples collected in situ. © 2012 Abu Almakarem et al.; licensee BioMed Central Ltd

Subglacial Lake Vostok (Antarctica) Accretion Ice Contains a Diverse Set of Sequences from Aquatic, Marine and Sediment-Inhabiting Bacteria and Eukarya

Lake Vostok, the 7th largest (by volume) and 4th deepest lake on Earth, is covered by more than 3,700 m of ice, making it the largest subglacial lake known. The combination of cold, heat (from possible hydrothermal activity), pressure (from the overriding glacier), limited nutrients and complete darkness presents extreme challenges to life. Here, we report metagenomic/metatranscriptomic sequence analyses from four accretion ice sections from the Vostok 5G ice core. Two sections accreted in the vicinity of an embayment on the southwestern end of the lake, and the other two represented part of the southern main basin. We obtained 3,507 unique gene sequences from concentrates of 500 ml of 0.22 μm-filtered accretion ice meltwater. Taxonomic classifications (to genus and/or species) were possible for 1,623 of the sequences. Species determinations in combination with mRNA gene sequence results allowed deduction of the metabolic pathways represented in the accretion ice and, by extension, in the lake. Approximately 94% of the sequences were from Bacteria and 6% were from Eukarya. Only two sequences were from Archaea. In general, the taxa were similar to organisms previously described from lakes, brackish water, marine environments, soil, glaciers, ice, lake sediments, deep-sea sediments, deep-sea thermal vents, animals and plants. Sequences from aerobic, anaerobic, psychrophilic, thermophilic, halophilic, alkaliphilic, acidophilic, desiccation-resistant, autotrophic and heterotrophic organisms were present, including a number from multicellular eukaryotes. © 2013 Shtarkman et al

Metagenomic And Metatranscriptomic Analyses Of Lake Vostok Accretion Ice

Lake Vostok (Antarctica) is the 4th deepest lake on Earth, the 6th largest by volume, and 16th largest by area, being similar in area to Ladoga Lake (Russia) and Lake Ontario (North America). However, it is a subglacial lake, constantly covered by more than 3,800 m of glacial ice, and has been covered for at least 15 million years. As the glacier slowly traverses the lake, water from the lake freezes (i.e., accretes) to the bottom of the glacier, such that on the far side of the lake a 230 m thick layer of accretion ice collects. This essentially samples various parts of the lake surface water as the glacier moves across the lake. As the glacier enters the lake, it passes over a shallow embayment. The embayment accretion ice is characterized by its silty inclusions and relatively high concentrations of several ions. It then passes over a peninsula (or island) and into the main basin. The main basin accretion ice is clear with almost no inclusions and low ion content. Metagenomic/metatranscriptomic analysis has been performed on two accretion ice samples; one from the shallow embayment and the other from part of the main lake basin. Ice from the shallow embayment contains a variety of Bacteria as well as a few Archaea and several types of Eukarya. Most are related to species that are psychrophilic, marine, aquatic, or live in lake/ocean sediments, or a combination of these. However, sequences identified as originating from many different thermophiles were found, suggesting the presence of hydrothermal activity in the lake. In contrast to the embayment ice, the ice from the main basin yielded only about 5-6% of the number of sequences. Here again, molecular signatures of psychrophiles, marine, aquatic, a few sediment-dwelling organisms, and a few thermophiles were found. Because of the extreme conditions, it has been hypothesized that Lake Vostok is sterile, or that very few types of organisms inhabit the lake. Our results indicate that it contains a diverse set of organisms, and the number and taxonomic composition varies with position in the lake

Metagenomic And Metatranscriptomic Analyses Of Lake Vostok Accretion Ice

Lake Vostok (Antarctica) is the 4th deepest lake on Earth, the 6th largest by volume, and 16th largest by area, being similar in area to Ladoga Lake (Russia) and Lake Ontario (North America). However, it is a subglacial lake, constantly covered by more than 3,800 m of glacial ice, and has been covered for at least 15 million years. As the glacier slowly traverses the lake, water from the lake freezes (i.e., accretes) to the bottom of the glacier, such that on the far side of the lake a 230 m thick layer of accretion ice collects. This essentially samples various parts of the lake surface water as the glacier moves across the lake. As the glacier enters the lake, it passes over a shallow embayment. The embayment accretion ice is characterized by its silty inclusions and relatively high concentrations of several ions. It then passes over a peninsula (or island) and into the main basin. The main basin accretion ice is clear with almost no inclusions and low ion content. Metagenomic/metatranscriptomic analysis has been performed on two accretion ice samples; one from the shallow embayment and the other from part of the main lake basin. Ice from the shallow embayment contains a variety of Bacteria as well as a few Archaea and several types of Eukarya. Most are related to species that are psychrophilic, marine, aquatic, or live in lake/ocean sediments, or a combination of these. However, sequences identified as originating from many different thermophiles were found, suggesting the presence of hydrothermal activity in the lake. In contrast to the embayment ice, the ice from the main basin yielded only about 5-6% of the number of sequences. Here again, molecular signatures of psychrophiles, marine, aquatic, a few sediment-dwelling organisms, and a few thermophiles were found. Because of the extreme conditions, it has been hypothesized that Lake Vostok is sterile, or that very few types of organisms inhabit the lake. Our results indicate that it contains a diverse set of organisms, and the number and taxonomic composition varies with position in the lake

Ecology of Subglacial Lake Vostok (Antarctica), Based on Metagenomic/Metatranscriptomic Analyses of Accretion Ice

biolog

Extraction of DNA from plant and fungus tissues in situ

Abstract Background When samples are collected in the field and transported to the lab, degradation of the nucleic acids contained in the samples is frequently observed. Immediate extraction and precipitation of the nucleic acids reduces degradation to a minimum, thus preserving accurate sequence information. An extraction method to obtain high quality DNA in field studies is described. Findings DNA extracted immediately after sampling was compared to DNA extracted after allowing the sampled tissues to air dry at 21°C for 48 or 72 hours. While DNA extracted from fresh tissues exhibited little degradation, DNA extracted from all tissues exposed to 21°C air for 48 or 72 hours exhibited varying degrees of degradation. Yield was higher for extractions from fresh tissues in most cases. Four microcentrifuges were compared for DNA yield: one standard electric laboratory microcentrifuge (max rcf = 16,000×g), two battery-operated microcentrifuges (max rcf = 5,000 and 3,000 ×g), and one manually-operated microcentrifuge (max rcf = 120×g). Yields for all centrifuges were similar. DNA extracted under simulated field conditions was similar in yield and quality to DNA extracted in the laboratory using the same equipment. Conclusions This CTAB (cetyltrimethylammonium bromide) DNA extraction method employs battery-operated and manually-operated equipment to isolate high quality DNA in the field. The method was tested on plant and fungus tissues, and may be adapted for other types of organisms. The method produced high quality DNA in laboratory tests and under simulated field conditions. The field extraction method should prove useful for working in remote sites, where ice, dry ice, and liquid nitrogen are unavailable; where degradation is likely to occur due to the long distances between the sample site and the laboratory; and in instances where other DNA preservation and transportation methods have been unsuccessful. It may be possible to adapt this method for genomic, metagenomic, transcriptomic and metabolomic projects using samples collected in situ.</p

Summary of steps in nitrogen metabolism (above) indicated from the metagenomic/metatranscriptomic sequence identities, as well as types of carbon fixation (lower left) and other functions (lower right) indicated by the sequence data.

<p>Each of the pathways was indicated by species determinations that were represented in the metagenomic and metatranscriptomic data sets. Processes also supported by mRNA gene sequences encoding some of the enzymes in the pathways (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0067221#pone.0067221.s016" target="_blank">Tables S11</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0067221#pone.0067221.s017" target="_blank">S12</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0067221#pone.0067221.s018" target="_blank">S13</a>) are underlined. Phyla that include the species identified are provided (in parentheses). Blue arrows represent process that occur under aerobic conditions, while purple arrows indicate anaerobic processes. Carbon fixation pathways are listed below, with taxonomic affinities for each. A large number of sequences closest to those from heterotrophic bacteria and eukaryotes were found in the accretion ice. Other notable metabolic types are listed at the lower right. Abbreviations: Greek alpha = Alphaproteobacteria, Greek beta = Betaproteobacteria, Greek delta = Deltaproteobacteria, Greek epsilon = Epsilonproteobacteria, Greek gamma = Gammaproteobacteria, Ac = Actinobacteria, Ar = Archaea; Cl = Chlorobi; Ch = Chloroflexi, Cy = Cyanobacteria, Fi = Firmicutes, Pl = Planctomycetes. Pathways and taxa in black font denote sequences that exhibited sequence identities between 97 and 100% to sequences in the NCBI nucleotide database. Red font indicates support for sequence identities less than 97%. Examples of species and strains that accomplish each of the pathways are as follows [Species names and accession numbers (in parentheses) for sequences that were of highest identity (≥97% identity, except for <i>Kuenenia stuttgartienssis</i> and an uncultured <i>Nitrosomonas</i> sp., which exhibited 90% identity to the query sequence) the metagenomic/metatranscriptomic query sequences are presented.]: <b>Nitrogen fixation</b> – <i>Anabena azoica</i> (Cy; (GI21388238), <i>Bradyrhizobium</i> sp. ORS 278 (Gαμμαπροτεοβαχτερια, GI146189981), <i>Bradyrhizobium</i> sp. BTAi1 (Alphαπροτεοβαχτερια, GI146403799), <i>Campylobacter concisus</i> (Epsilonπροτεοβαχτερια, GI290759912), <i>Corynebacterium duram</i> (Ac, GI290759824), <i>Frankia alni</i> (Ac, GI111147037), <i>Geobacillus kaustophilus</i> (Fi, GI134290402), <i>Halomonas</i> sp. GS 1-2 (Gαμμαπροτεοβαχτερια, GI285027202), <i>Herbaspirillum</i> sp. B601 (Betαπροτεοβαχτερια, GI62183809), <i>Leptolyngbya boryana</i> (Cy, GI46409901), <i>Mesorhizobium loti</i> (Alphαπροτεοβαχτερια, GI29725918), <i>Nocardioides</i> sp. Cr7-14 (Ac, GI293629578), <i>Nostoc muscorum</i> (Cy, GI29124940), <i>Nostoc punctiforme</i> (Cy, GI186463002), <i>Phicicola gilvus</i> (Ac, GI111146878), <i>Phormidium autumnale</i> (Cy, GI166997748), <i>Rhodobacter changlensis</i> (Alphαπροτεοβαχτερια, GI125656032), <i>Synechococcus</i> sp. C9 (Cy, GI90186509); <b>Nitrification</b> – <i>Bradyrhizobium</i> sp. BTAi1 (Alphαπροτεοβαχτερια, GI146403799), <i>Denitrobacter</i> sp. BBTR53 (Betαπροτεοβαχτερια, GI85002019), <i>Herbaspirillum</i> sp. B601 (Betαπροτεοβαχτερια, GI62183809), uncultured <i>Nitrosomonas</i> sp. (Alphαπροτεοβαχτερια, GI223036385); <b>Denitrification</b> – <i>Bacillus cereus</i> (Fi, GI269994025), <i>Brevudomonas</i> sp. V3M6 (Alphαπροτεοβαχτερια, GI295809779), <i>Caulobacter</i> sp. can1 (Alphαπροτεοβαχτερια, GI288908581), <i>Geobacillus kaustophilus</i> (Fi, GI134290402), <i>Paracoccus</i> sp. YT0095 (Alphαπροτεοβαχτερια, GI158392748), <i>Pseudomonas xanthamarina</i> (Gαμμαπροτεοβαχτερια, GI254621816), <i>Psychrobacter maritimus</i> (Gαμμαπροτεοβαχτερια, GI240129723), uncultured Commomonadaceae sp. (Betαπροτεοβαχτερια, GI184189965); <b>Nitrate reduction</b> – <i>Bacillus cereus</i> (Fi, GI294999187), <i>Delftia acidovorans</i> (Betαπροτεοβαχτερια, GI213536827), <i>Paracoccus yeei</i> (Alphαπροτεοβαχτερια, GI206581410), uncultured <i>Citrobacter</i> sp. (Gαμμαπροτεοβαχτερια, GI257073647), <b>Anammox</b> – <i>Keunenia stuttgartiensis</i> (Pl; GI91199943). Support from mRNA gene sequences for specific processes is presented in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0067221#pone.0067221.s018" target="_blank">Table S13</a>. Pathways with rRNA and mRNA gene sequence support are underlined.</p

Subglacial Lake Vostok (Antarctica) Accretion Ice Contains a Diverse Set of Sequences from Aquatic, Marine and Sediment-Inhabiting Bacteria and Eukarya

<div><p>Lake Vostok, the 7^th largest (by volume) and 4^th deepest lake on Earth, is covered by more than 3,700 m of ice, making it the largest subglacial lake known. The combination of cold, heat (from possible hydrothermal activity), pressure (from the overriding glacier), limited nutrients and complete darkness presents extreme challenges to life. Here, we report metagenomic/metatranscriptomic sequence analyses from four accretion ice sections from the Vostok 5G ice core. Two sections accreted in the vicinity of an embayment on the southwestern end of the lake, and the other two represented part of the southern main basin. We obtained 3,507 unique gene sequences from concentrates of 500 ml of 0.22 µm-filtered accretion ice meltwater. Taxonomic classifications (to genus and/or species) were possible for 1,623 of the sequences. Species determinations in combination with mRNA gene sequence results allowed deduction of the metabolic pathways represented in the accretion ice and, by extension, in the lake. Approximately 94% of the sequences were from Bacteria and 6% were from Eukarya. Only two sequences were from Archaea. In general, the taxa were similar to organisms previously described from lakes, brackish water, marine environments, soil, glaciers, ice, lake sediments, deep-sea sediments, deep-sea thermal vents, animals and plants. Sequences from aerobic, anaerobic, psychrophilic, thermophilic, halophilic, alkaliphilic, acidophilic, desiccation-resistant, autotrophic and heterotrophic organisms were present, including a number from multicellular eukaryotes.</p></div

Summary of proportions of sequences in V5 (left) and V6 (right) categorized by habitat (upper row) and growth conditions (lower row) based on species with highest sequence identities.

<p>Each pie chart is comprised of sequences that were either ≥97% identity or ≥99% identity, and also could be classified by habitat (above) or growth conditions (below). Habitat abbreviations: An = animal associated (most are also found in soils and/or water); Aq = aquatic; I = ice, glaciers and/or polar; M = marine; Pl = plant associated (most are also found in soils and water); S = soils or sediments. Growth conditions abbreviations: Ac = acidophilic or acid tolerant; Al = alkaliphilic or alkali tolerant; D = desiccation resistant; H = halophilic or halotolerant; Ps = psychrophilic or psychrotolerant; T = thermophilic or thermotolerant. Number of sequences (N) used for each is indicated below each pie chart.</p

Summary of broad taxonomic proportions based on the metagenomic and metatranscriptomic data.

<p>The first column presents the proportion of unique sequences from all sequences in the entire data set, regardless of percent identity to sequences deposited in the NCBI nucleotide database. The upper row represents data from V5, and the lower row represents data from V6. The totals are represented in the bar graph on the left in each box, with numerical totals at the top. There were 3,507 unique sequences (3,369+138) in the entire data set, including 3,169 from Bacteria, 2 from Archaea and 198 from Eukarya in V5; and 114 Bacteria and 24 from Eukarya in V6. The middle column includes sequences that have identities between 97 and 100% with sequences in the NCBI database. There were 1,911 unique sequences, including 1,724 from Bacteria, 2 from Archaea and 105 from Eukarya in V5; and 61 from Bacteria and 19 from Eukarya in V6. The final column includes sequences that have identities between 99 and 100% with sequences in the NCBI database. There were 1,102 Bacteria, 2 Archaea and 64 Eukarya in V5; and 36 Bacteria and 11 Eukarya in V6. Scales (in number of sequences) are at the bottom right of each bar graph. Abbreviations: Ac = Actinobacteria; Ad = Acidobacteria; Am = Amoebozoa; An = Animalia; Ap = Archaeplastida; Greek alpha = Alphaproteobacteria; Ar = Archaea; Ba = Bacteroidetes; Greek beta = Betaproteobacteria; Ca = Chromalveolata; CDF = Chlorobi/Deferribacteres/Fibrobacteres; Ch = Chloroflexi; Cy = Cyanobacteria; Greek delta = Deltaproteobacteria; DT = Deinococcus/Thermus; Greek εpsilon = Epsilonproteobacteria; Eu = Eukarya; Ex = Excavata; Fi = Firmicutes; Fs = Fusobacteria; Fu = Fungi; Greek gamma = Gammaproteobacteria; Pl = Planctomyces; Pr = Proteobacteria; Rh = Rhizaria; Sp = Spirochaetes; Te = Tenericutes; u = uncultured/unidentified; Ve = Verrucomicrobia.</p