US Long-Term Ecological Research Network

Microbial Observatory at North Temperate Lakes LTER High-resolution temporal and spatial dynamics of microbial community structure in freshwater bog lakes 2005 - 2009 original format

Abstract
The North Temperate Lakes - Microbial Observatory seeks to study freshwater microbes over long time scales (10+ years). Observing microbial communities over multiple years using DNA sequencing allows in-depth assessment of diversity, variability, gene content, and seasonal/annual drivers of community composition. Combining information obtained from DNA sequencing with additional experiments, such as investigating the biochemical properties of specific compounds, gene expression, or nutrient concentrations, provides insight into the functions of microbial taxa. Our 16S rRNA gene amplicon datasets were collected from bog lakes in Vilas County, WI, and from Lake Mendota in Madison, WI. Ribosomal RNA gene amplicon sequencing of freshwater environmental DNA was performed on samples from Crystal Bog, North Sparkling Bog, West Sparkling Bog, Trout Bog, South Sparkling Bog, Hell’s Kitchen, and Mary Lake. These microbial time series are valuable both for microbial ecologists seeking to understand the properties of microbial communities and for ecologists seeking to better understand how microbes contribute to ecosystem functioning in freshwater.
Core Areas
Dataset ID
349
Date Range
-
Methods
Protocol available in methods section of: http://msphere.asm.org/content/2/3/e00169-17
Prior to collection, water temperature and dissolved oxygen concentrations are measured using a YSI 550a. The ranges of the epilimnion and hypolimnion are determined based on the location of the thermocline (where temperature/oxygen is changing the fastest). The two layers are collected separately in 1 meter increments using an integrated water column sampler. Water samples are taken back to the lab, shaken thoroughly, and filtered via peristaltic pump through 0.22 micron filters (Pall Supor). Filters are temporarily stored at -20C after collection and then transferred to -80C after transport on dry ice from Trout Lake Station to UW-Madison. Nutrient samples are collected bi-weekly following standard LTER protocols. DNA is extracted from filters using a FASTDNA SpinKit for Soil with minor modifications. (In cases of low yield or specialized sequencing methods, a phenol-chloroform extraction is used instead). The protocol for sequencing and analysis of data varies by year and by sub-project.
Version Number
4

Microbial Observatory at North Temperate Lakes LTER Spatial and temporal cyanobacterial population dynamics in Lake Mendota 2009 - 2011

Abstract
Toxic cyanobacterial blooms threaten freshwaters worldwide but have proven difficult to predict because the mechanisms of bloom formation and toxin production are unknown, especially on weekly time scales. Water quality management continues to focus on aggregated metrics, such as chlorophyll and total nutrients, which may not be sufficient to explain complex community changes and functions such as toxin production. For example, nitrogen (N) speciation and cycling play an important role, on daily time scales, in shaping cyanobacterial communities because declining N has been shown to select for N fixers. In addition, subsequent N pulses from N<sub>2</sub> fixation may stimulate and sustain toxic cyanobacterial growth. Herein, we describe how rapid early summer declines in N followed by bursts of N fixation have shaped cyanobacterial communities in a eutrophic lake (Lake Mendota, Wisconsin, USA), possibly driving toxic <em>Microcystis</em> blooms throughout the growing season. On weekly time scales in 2010 and *2011, we monitored the cyanobacterial community in a eutrophic lake using the phycocyanin intergenic spacer (PC-IGS) region to determine population dynamics. In parallel, we measured microcystin concentrations, N<sub>2</sub> fixation rates, and potential environmental drivers that contribute to structuring the community.
Core Areas
Dataset ID
299
Date Range
-
Maintenance
completed
Metadata Provider
Methods
Field sample collection and processingAt each location, temperature, dissolved oxygen (DO), and pH were collected at 1 m increments from the surface to the maximum depth (YSI 556MPS). Photic zone depth was defined at 1percent of photosynthetically active radiation (PAR) as measured using a PAR sensor (LiCor 192SA). Integrated photic zone samples were then collected using a weighted 2-inch diameter polypropylene tube. Samples for DNA, nutrients, toxins, and pigment analyses were collected in acid-washed, sterile bottles, (rinsed three times with in situ water before collection) and stored on ice until further processing.Once transported back to the lab, samples were immediately processed. For dissolved reactive phosphorus (DRP), total dissolved phosphorus (TDP), total dissolved nitrogen (TDN), nitrate, and nitrite, 100 mL of water was filtered through a Whatman glass fiber filter (GForF) and frozen at -20 degreeC. For TP and total nitrogen (TN), HCl was added to 100mL of sample to a final concentration of 0.1percent and stored at -20 degreeC. Ammonium samples were immediately measured to avoid oxidation during freezing. Chlorophyll-a and phycocyanin samples were collected onto GForF filters and stored in black tubes at -20 degreeC. For community analysis (DNA), samples were filtered onto 0.2 &micro;m polyethersulfone membrane filters (Supor-200; Pall Corporation) and frozen at -20 degreeC until extraction. 20 mL of unfiltered water was preserved in formalin (3percent final concentration) and stored at room temperature in the dark for microscopy. An additional 50 mL of unfiltered water was stored at -20 degreeC for toxin analysis.Analytical measurementsDRP was measured by the ascorbic acid-molybdenum blue method 4500 P E (Greenberg et al. 1992). Ammonium was measured spectrophotometrically (Solórzano 1969). Nitrate and nitrite were measured individually using high-performance liquid chromatography (HPLC) (Flowers et al. 2009). TPorTDP and TNorTDN were digested as previously described (White et al. 2010), prior to analysis as for DRP and nitrate. For TDN and TN, the resulting solution was oxidized completely to nitrate and was measured via HPLC as above. Nitrate, nitrite, and ammonium were summed and reported as dissolved inorganic nitrogen (DIN).Phycocyanin was extracted in 20 mM sodium acetate buffer (pH 5.5) following three freeze-thaw cycles at -20 &ordm;C and on ice, respectively. The extract was centrifuged and then measured spectrophotometrically at 620 nm with correction at 650 nm (Demarsac and Houmard 1988). Chlorophyll-a (Chl-a) was extracted overnight at -20 &ordm;C in 90percent acetone and then measured spectrophotometrically with acid correction (Tett et al. 1975).For toxin analysis, whole water samples were lyophilized, resuspended in 5percent acetic acid, separated by solid phase extraction (SPE; Bond Elut C18 column, Varian), and eluted in 50percent methanol as previously described (Harada et al. 1988). Microcystin (MC) variants of leucine (L), arginine (R), and tyrosine (Y) were detected and quantified at the Wisconsin State Lab of Hygiene (SLOH) using liquid chromatography electrospray ionization tandem mass spectroscopy (API 3200, MSorMS) after separation by HPLC (Eaglesham et al. 1999). We report only MCLR concentrations since MCYR and MCRR were near the limit of quantification for the sampling period (0.01 &micro;g L-1).In situ N2 fixation measurementsN2 fixation rates were measured, with some modifications, following the acetylene reduction assay (Stewart et al. 1967). A fresh batch of acetylene was generated each day before sampling by combing 1 g of calcium carbide (Sigma Aldrich 270296) with 100 mL ddH2O. Following sample collection, 1 L of water was concentrated by gentle filtration onto a 47 mm GForF filter in the field. The filter was then gently washed into a 25 mL serum bottle using the lake water filtrate (final volumes 10 mL aqueous, 15 mL gas). Samples were spiked with 1 mL of acetylene gas and incubated in situ for two hours. The assay was terminated with 5percent final concentration trichloracetic acid and serum bottles were transported back to the lab. For each sampling period, rates were controlled and corrected for using a series of the following incubated acetylene blanks: 1) 1 mL of acetylene in filtrate alone, 2) 1 mL of acetylene in a killed sample, and 3) 1 mL of acetylene in ddH2O. Ethylene formed was measured by a gas chromatograph (GC; Shimadzu GC-8A) equipped with a flame ionization detector (FID), Porapak N column (80or100 mesh, 1or8OD x 6), and integrator (Hewlett Packard 3396) with N2 as the carrier gas (25 mL min-1 flow rate). Molar N2 fixation rates were estimated using a 1:4 ratio of N2 fixed to ethylene formed (Jensen and Cox 1983). All N2 fixation values are reported as integrated photic zone rates of &micro;g N L-1 hr-1.DNA extraction and processing of PC-IGS fragmentDNA was extracted from frozen filters using a xanthogenate-phenol-chloroform protocol previously described (Miller and McMahon 2011). For amplification of the phycocyanin intergenic spacer (PC-IGS) region, we used primers PCalphaR (5-CCAGTACCACCAGCAACTAA-3) and PCbetaF (5-GGCTGCTTGTTTACGCGACA-3, 6-FAM-labelled) and PCR conditions that were previously described (Neilan et al. 1995). Briefly, each 50 &micro;l reaction mixture contained 5 &micro;l of 10X buffer (Promega, Madison, WI), 2.5 &micro;l of dNTPs (5 mM), 2 &micro;l of forward and reverse primers (10 &micro;M), 2 &micro;l of template DNA, and 0.5 &micro;l of Taq DNA polymerase (5 U &micro;l-1). Following precipitation with ammonium acetate and isopropanol, the DNA pellet was resuspended in ddH2O and digested for 2 hrs at 37 &ordm;C using the MspI restriction enzyme, BSA, and Buffer B (Promega, Madison, WI). The digested product was precipitated and then resuspended in 20 &micro;L of ddH2O. 2 &micro;L of final product was combined with 10 &micro;L of formamide and 0.4 &micro;L of a custom carboxy-x-rhodamine (ROX) size standard (BioVentures, Inc).Cyanobacterial PC-IGS community fingerprinting and cell countsWe analyzed the cyanobacterial community using an automated phycocyanin intergenic spacer analysis (APISA) similar to the automated ribosomal intergenic spacer analysis (ARISA) previously described (Yannarell et al. 2003). Briefly, this cyanobacterial-specific analysis exploits the variable PC-IGS region of the phycocyanin operon (Neilan et al. 1995). Following MspI digestion, the variable lengths of the PC-IGS fragment can be used to identify subgenus level taxonomic units of the larger cyanobacterial community (Miller and McMahon 2011). The MspI fragments were sized using denaturing capillary electrophoresis (ABI 3730xl DNA Analyzer; University of Wisconsin Biotechnology Center (UWBC)). For each sample, triplicate electropherogram profiles were analyzed using GeneMarker&reg; (SoftGenetics) software v 1.5. In addition, a script developed in the R Statistics Environment was used to distinguish potential peaks from baseline noise (Jones and McMahon 2009, Jones et al. 2012). Relative abundance data output from this script were created using the relative proportion of fluorescence each peak height contributed per sample. Aligned, overlapping peaks were binned into subgenus taxonomic units (Miller and McMahon 2011). These taxa were named based on the genus and base pair length of the PC-IGS fragment identified (e.g. For Mic215, Mic = Microcystis and 215 = 215 base pair fragment). Fragment lengths were matched to an in silico digested database of PC-IGS sequences using the Phylogenetic Assignment Tool (https:ororsecure.limnology.wisc.eduortrflpor).The NTL-LTER program collects biweekly phytoplankton samples between April and September for cell counts and detailed descriptions of the field and laboratory protocols are available online at http:ororlter.limnology.wisc.edu. When indicated, biomass has been converted to mg L-1 using the biovolume calculated during the cell count process and assuming a density equivalent to water.
Version Number
22

Microbial Observatory at North Temperate Lakes LTER Time series of bacterial community dynamics in Lake Mendota 2000 - 2009

Abstract
With an unprecedented decade-long time series from a temperate eutrophic lake, we analyzed bacterial and environmental co-occurrence networks to gain insight into seasonal dynamics at the community level. We found that (1) bacterial co-occurrence networks were non-random, (2) season explained the network complexity and (3) co-occurrence network complexity was negatively correlated with the underlying community diversity across different seasons. Network complexity was not related to the variance of associated environmental factors. Temperature and productivity may drive changes in diversity across seasons in temperate aquatic systems, much as they control diversity across latitude. While the implications of bacterioplankton network structure on ecosystem function are still largely unknown, network analysis, in conjunction with traditional multivariate techniques, continues to increase our understanding of bacterioplankton temporal dynamics.
Core Areas
Dataset ID
298
Date Range
Maintenance
completed
Metadata Provider
Methods
Surface water samples were collected from Lake Mendota, WI, USA, and analyzed by automated ribosomal intergenic spacer analysis as described previously (Shade et al., 2007). From 2000 to 2009, a total of 34 spring, 53 summer and 34 autumn observations were made. Thirty-two environmental variables were collected at the same location by the North Temperate Lakes Long Term Ecological Research program (lter.limnology.wisc.edu)
Short Name
MEMOTY
Version Number
18

Microbial Observatory at North Temperate Lakes LTER Six Bogs Microbial Communities 2009

Abstract
Population dynamics are influenced by drivers acting from outside and from within an ecosystem. Extrinsic forces operating over broad spatial scales can impart synchronous behavior to separate populations, while internal, system-specific drivers often lead to idiosyncratic behavior. Here we demonstrate synchrony in community-level dynamics among phytoplankton and bacteria in six north temperate humic lakes. The influence of regional meteorological factors explained much of the temporal variability in the phytoplankton community, and resulted in synchronous patterns of community change among lakes. Bacterial dynamics, in contrast, were driven by system-specific interactions with phytoplankton. Despite the importance of intrinsic factors for determining bacterial community composition and dynamics, we demonstrated that biological interactions transmitted the signal of the regional extrinsic drivers to the bacterial communities, ultimately resulting in synchronous community phenologies for bacterioplankton communities as well. This demonstrates how linkages between the components of a complex biological system can work to simplify the dynamics of the system and implies that it may be possible to predict the behavior of microbial communities responsible for important biogeochemical services in the landscape.
Core Areas
Dataset ID
292
Date Range
-
Metadata Provider
Methods
See protocols of North Temperate Lakes Microbial ObservatorySampling Techniques: Integrated epilimnionDNA extraction protocol: FastPrep DNA extraction kitBinning protocol: ARISA_v4.2.RCapillary Instrument (from Biotech Center): ABI 3730xLPCR DNA standardization protocol: By volume of DNA extract (1 ul per reaction)PCR thermocycler protocol: RISAASH protocol: 2 min at 94 C, [30 s at 94, 45 s at 55, 1 m at 72, (Repeat 29X)], 1 m at 72, Hold at 4
NTL Keyword
Short Name
6BOG03
Version Number
21

Heterotrophic Bacterial Community Patterns in Lake Mendota

Part of this research is about long-term heterotrophic bacterial community patterns in Lake Mendota, Wisconsin. Heterotrophic bacteria are responsible for nutrient cycling in aquatic systems. These preliminary abundance data indicate seasonal patterns in bacterial taxa (OTU’s). We will perform time-series analysis with these data together with environmental variables (water chemistry and meteorological factors) in order to investigate drivers of the bacterial community ...

Linking Nutrient Cycling to Cyanobacterial Community Structure and Succession in Lakes

Lake Mendota is an eutrophic lake that harbors an abundant and diverse array of bloom-forming cyanobacteria (also called blue-green algae). The cyanobacterial community is highly variable, contains numerous nitrogen (N2) fixing and non-N2 fixing genera, and has multiple genotypes capable of forming ephemeral, and possibly toxic, blooms. Nutrients play an integral role in structuring the cyanobacterial community, but it is unclear how phosphorus (P), nitrogen (N), and trace metal limitation might influence seasonal to decadal community dynamics ...

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