LAKE SUPERIOR PHOTOTROPHIC PICOPLANKTON: NITRATE ASSIMILATION
MEASURED WITH A CYANOBACTERIAL NITRATE-RESPONSIVE BIOREPORTER
AND GENETIC DIVERSITY OF THE NATURAL COMMUNITY
Natalia Valeryevna Ivanikova
A Dissertation
Submitted to the Graduate College of Bowling Green State University in partial fulfillment of the requirements for the degree of
DOCTOR OF PHILOSOPHY
May 2006
Committee:
George S. Bullerjahn, Advisor
Robert M. McKay
Scott O. Rogers
Paul F. Morris
Robert K. Vincent Graduate College representative
ii
ABSTRACT
George S. Bullerjahn, Advisor
Cyanobacteria of the picoplankton size range (picocyanobacteria) Synechococcus and
Prochlorococcus contribute significantly to total phytoplankton biomass and primary production in marine and freshwater oligotrophic environments. Despite their importance, little is known about the biodiversity and physiology of freshwater picocyanobacteria. Lake Superior is an ultra- oligotrophic system with light and temperature conditions unfavorable for photosynthesis.
Synechococcus-like picocyanobacteria are an important component of phytoplankton in Lake
Superior. The concentration of nitrate, the major form of combined nitrogen in the lake, has been increasing continuously in these waters over the last 100 years, while other nutrients remained largely unchanged. Decreased biological demand for nitrate caused by low availabilities of phosphorus and iron, as well as low light and temperature was hypothesized to be one of the reasons for the nitrate build-up. One way to get insight into the microbiological processes that contribute to the accumulation of nitrate in this ecosystem is to employ a cyanobacterial bioreporter capable of assessing the nitrate assimilation capacity of phytoplankton. In this study, a nitrate-responsive biorepoter AND100 was constructed by fusing the promoter of the
Synechocystis PCC 6803 nitrate responsive gene nirA, encoding nitrite reductase to the Vibrio fischeri luxAB genes, which encode the bacterial luciferase, and genetically transforming the resulting construct into Synechocystis. The transcription of luciferase in the transformant is regulated by the availability of nitrate in the sample. Therefore, the bioluminescent signal produced by the bioreporter reflects the nitrate assimilation capacity of the cell. The dynamic range of the bioreporter response was found to be between 1 and 100 µM nitrate. The results of a series of bioreporter assays conducted on preserved water samples collected from several stations iii in Lake Superior in May and September 2004 suggest that low availability of phosphorus is the major factor that constrains nitrate depletion in the lake with low seasonal or spatial variability.
In addition, iron was found to be a secondary limiting factor, whose effect is evident only of phosphorus is added to the sample. During the period of isothermal mixing, light was shown to significantly reduce nitrate depletion in the lake. Overall, the bioreporter AND100 is a suitable model for elucidating the factors that regulate nitrate depletion by phytoplankton in natural waters. However, understanding the physiology of the natural cyanobacterial assemblages in the lake helps to prove the validity of the bioreporter approach. Since the information on the endemic Lake Superior phytoplankton is very scarce, an initial characterization of the genetic diversity of cyanobacteria in the lake was conducted. High throughput sequencing of a library of cyanobacterial 16S ribosomal DNA clones amplified by PCR from DNA isolated from the lake water resulted in 368 successful reactions. In a neighbor-joining tree the majority of the 16S rDNA sequences clustered within the “picocyanobacterial clade” that consists of both freshwater and marine Synechococcus and Prochlorococcus picocyanobacteria. Two new groups of picocyanobacteria LSI and II that do not cluster within any of the known freshwater picocyanobacterial clusters were the most abundant (> 50% of the sequences) in the samples collected from pelagic Lake Superior stations. Conversely, at station KW located in a nearshore urban area, only 4% of the sequences belonged to these clusters, and the remaining of the sequences reflected the freshwater biodiversity described previously. In addition, several picocyanobacterial strains were isolated from Lake Superior between years 2004 and 2005.
Despite their low representation in the environmental clone library, the physiological characterization of these strains may reveal adaptations to unique conditions that exist in Lake
Superior. iv
ACKNOWLEDGEMENTS
First of all, I want to thank my advisor Dr. George S. Bullerjahn for his support and
guidance during the three and a half years that I spent in Bowling Green. Thank you George for providing me with an opportunity to work in your lab and encouraging me to think independently. I would like to thank Dr. Robert M. McKay, who helped me to learn the basics of
the science of limnology, which I had a very vague idea about when I first came to Bowling
Green. I also would like to thank my other committee members: Dr. Scott O. Rogers, Dr. Paul F.
Morris, and Dr. Robert K. Vincent. Thank you Dr. Rogers for letting me use your equipment. I
would like to acknowledge the Captain and crew of the R/V Blue Heron for their assistance in
collection of samples and Michael Twiss and Christel Hassler (Clarkson University) and Rob
Sherrell and Eleni Anagnostou (Rutgers University) for sharing their dissolved iron and SRP data, respectively, used in Chapter 3 of the thesis. I want to thank people in George and Mike’s labs Maria Baranova, Audrey Cupp, Linda Popels, Ramakrishna Boyanapali, David Porta and
Mamoon Al-Raishadat for creating a friendly atmosphere in the lab and Armeria Vicol for teaching me many useful tips.
I also would like to acknowledge my friends that I met here in BG and who also worked
in George’ lab Nadejda Vintonenko and Kerry Brinkman. Special thanks to my boyfriend Anton
V. Kulikov for tolerating me while I was writing this thesis. And, of course, I want to thank my
parents Galina Mazgutovna Gataulina and Valerii Vasylevich. Ivanikov for letting me become
who I am and my entire family for their everlasting love and support.
v
TABLE OF CONTENTS
Page
CHAPTER 1. INTRODUCTION…………………………………………………………………1
Freshwater picocyanobacteria: diversity…………………………………………………..4
Freshwater cyanobacteria: populational dynamics………………………………………..7
Lake Superior as an example of an extremely oligotrophic system……………………..11
Lake Superior and accumulation of nitrate………………………………………………12
Potential factors limiting primary productivity in Lake Superior………………………..14
Use of cyanobacterial bioreporters to measure nutrient bioavailability…………………16
Regulation of cyanobacterial mitrogen assimilation genes……………………………...19
The importance of studying the endemic picoplankton of Lake Superior……………….22
References………………………………………………………………………………..29
CHAPTER 2. CONSTRUCTION AND PHYSIOLOGICAL CHARACTERIZATION OF A
CYANOBACTERIAL BIOREPORTER CAPABLE OF ASSESSING NITRATE
ASSIMILATORY CAPACITY IN FRESHWATERS…………………………………………..41
Introduction………………………………………………………………………………………41
Materials and methods…………………………………………………………………………...42
Media and growth conditions…………………………………………………………….42
Construction of the PnirA::luxAB promoter fusions…………………………………….43
Characterization of the AND100A and AND100B promoter fusions and the AND100
bioreporter………………………………………………………………………………..45
Water collection from Lake Superior…………………………………………………....46
Monitoring nitrate depletion in bioreporter assays………………………………………46 vi
Results……………………………………………………………………………………………47
Nitrate-Dependent Activation of AND100 Bioluminescence…………………………...47
Factors influencing AND100 nitrate-dependent luminescence in BG-11 media………..50
Induction of bioluminescence during nitrate assimilation……………………………….52
Use of the AND100 bioreporter to assess nitrate assimilation in field samples…………53
Discussion………………………………………………………………………………………..55
Utility of the bioreporter assay…………………………………………………………..55
Application of the AND100 reporter to Lake Superior………………………………….56
Comparison to other cyanobacterial N bioreporters……………………………………..57
Concluding remarks – future prospects………………………………………………….58
References………………………………………………………………………………………..60
CHAPTER 3. NITRATE UTILIZATION IN LAKE SUPERIOR IS IMPAIRED BY LOW
NUTRIENT (P, Fe) AVAILABILITY AND SEASONAL LIGHT LIMITATION…………….65
Introduction………………………………………………………………………………………65
Materials and methods…………………………………………………………………………...67
Media and growth conditions…………………………………………………………….67
Sample collection………………………………………………………………………...68
Nitrate assimilation in Lake Superior water: nutrient effects……………………………69
Nitrate assimilation in Lake Superior water: light flux………………………………….70
Monitoring nitrate depletion in bioreporter assays………………………………………70
Measurement of alkaline phosphatase activity…………………………………………..71
Results……………………………………………………………………………………………71 vii
Physico-chemical characteristics of Lake Superior……………………………………...71
Nitrate assimilation in Lake Superior water: nutrient effects - The AND100…………...74
Nitrate assimilation in Lake Superior water: light flux………………………………….77
Discussion………………………………………………………………………………………..79
References………………………………………………………………………………………..86
CHAPTER 4. THE PHYLOGENETIC DIVERSITY OF LAKE SUPERIOR
CYANOBACTERIA…………………………………………………………………………….91
Introduction………………………………………………………………………………………91
Materials and Methods…………………………………………………………………………...93
Sample collection………………………………………………………………………...93
Isolation of cyanobacterial strains from Lake Superior………………………………….94
DNA extraction…………………………………………………………………………..95
PCR amplification………………………………………………………………………..95
Construction of clone libraries…………………………………………………………...96
DNA sequencing…………………………………………………………………………96
Phylogenetic analysis…………………………………………………………………….96
Results……………………………………………………………………………………………97
Discussion………………………………………………………………………………………109
References………………………………………………………………………………………114
viii
LIST OF FIGURES
Figure Page
CHAPTER 1
1 A). The in vivo absorption spectra of Prochlorococcus (strain MED4) and marine
Synechococcus (strain WH8102).
B). Typical vertical distributions of Prochlorococcus and Synechococcus in the oceanic
water column…………………………………………………………………………….4
2 A phylogenetic tree of cyanobacterial 16S rDNA sequences……………………………8
3 Graphic representation of the historical trend of increasing nitrate/nitrite concentrations
In Lake Superior………………………………………………………………………...13
4 Nitrate assimilation system in cyanobacteria……………………………………………………..15
5 Organization of a bioreporter organism………………………………………………….17
6 Interactions between nitrogen and carbon regulation in cyanobacteria………………….20
7 Maximum-likelihood tree of the picophytoplankton clade…………………...………….27
CHAPTER 2.
1 Structure of the Synechocystis PCC 6803 nirA gene promoter………………………….44
2 Elements of the promoter probe vector pILA……………………………………………45
3 Bioluminescence of Synechocystis PCC 6803 strains transformed with nirA promoter
constructs………………………………………………………………………………...48
4 Bioluminescence of Synechocystis sp. reporter strain AND100………………………....49
5 Effect of ammonium addition on nitrate induced bioluminescence in AND100………...50
6 Effect of light intensity on nitrate induced bioluminescence in And100………………...51
7 Coincident induction of luminescence and nitrate uptake……………………………….52 ix
8 Measurement of nitrate in Lake Superior samples by AND100 luminescence………….53
9 Time course of AND100 luminescence in water sampled from pelagic station ON2…...54
CHAPTER 3.
1 Bioreporter response to water sampled from open lake station WM…………………….75
2 Bioreporter luminescence in water sampled from open lake station CD-1……………...76
3 Bioreporter response to water sampled at nearshore-offshore transects (HN, EH,
ON)…………………………………………………………………………………….………...78
4 Bioreporter response to water sampled at stations SB and KW…………………………80
5 Meta analysis of effect sizes in all experimental runs…………………………………...81
6 Effect of light treatment on bioreporter response………………………………………..82
CHAPTER 4. THE PHYLOGENETIC DIVERSITY OF LAKE SUPERIOR
CYANOBACTERIA INFERRED FROM 16S rDNA SEQUENCES
1 Neighbor-joining tree of 16S rDNA sequences from the epilimnion at station CD1..….98
2 Neighbor-joining tree of 16S rDNA sequences from the DCM at station CD1………..100
3 Neighbor-joining tree of 16S rDNA sequences from station CD1 collected during the
isothermal mixing………………………………………………………………………102
4 Neighbor-joining tree of 16S rDNA sequences from stations CD1 and KW that cluster
within the Lake Superior clusters LSI and LSII………………………………………..104
5 Neighbor-joining tree of 16S rDNA sequences from station KW……………………...106
6 Clusters of freshwater picocyanobacteria and other cyanobacterial groups presented in the
16S rDNA data set obtained in this study………………………………………………108
x
LIST OF TABLES
Table Page
1 Physico-chemical characteristics of Lake Superior hydrographic stations during 2004...72
2 Soluble reactive phosphorus (SRP) and alkaline phosphatase (Apase) activities measured
in Lake Superior in 2004…………………………………………………………………73
1
CHAPTER 1. INTRODUCTION
Fifty percent of the global primary production on Earth is carried out by phytoplankton
(Ting et al. 2002). Cyanobacteria (“blue-green algae”) are the most ubiquitous and widely distributed phytoplankters. The taxon Cyanobacteria (“Cyanophyta”) is comprised by a group of ancient phototrophic prokaryotic organisms that belong to the Bacteria domain and are characterized by the ability to carry out oxygenic photosynthesis. They are thought to have played an important role in the establishment of the aerobic atmosphere on Earth approximately
3.5 billion years ago. By their molecular phylogeny and the organization of photosynthetic apparatus, cyanobacteria are more closely related to the chloroplasts of eukaryotic algae and higher plants than to other photosynthesizing bacteria (Giovannoni et al. 1988). It is generally accepted that the ancestors of cyanobacteria were involved in single or multiple endosymbiotic events resulting in the appearance of photosynthetic eukaryotes. Thus, cyanobacteria are a model for the study of the origins of oxygenic photosynthesis on Earth.
One of the striking features of this group of oxygenic photoautotrophs is their ability to adapt to a conspicuously wide range of environments, which can be partially explained by their long evolutionary history (Ting et al, 2002). Cyanobacteria are common in the phytoplankton of the coastal and pelagic areas of the ocean, brackish ecosystems, tropical and temperate lakes, as well as in temperate soils, hot springs and arid deserts (Garcia-Pichel et al. 1998; Stockner et al.
2000; Paerl, 2000; Ward and Castenholz, 2000; Whitton, 2000). Over the course of evolution, cyanobacteria have developed survival strategies that allow them to thrive in extreme conditions.
The strategies include spatial or temporal separation of nitrogen fixation and photosynthetic oxygen evolution to protect the oxygen sensitive nitrogen fixation machinery (Paerl, 1990), regulation of buoyancy to resist vertical mixing of the water column and remain in the well 2
illuminated surface waters (Walsby, 1972), chromatic adaptation to adjust to different
wavelengths of light (Palenik, 2001), a unique pigment composition that enables them to
photosynthesize at extremely low irradiances (Ting et al. 2002), photoprotection mechanisms
(Castenholz and Garcia-Pichel, 2000), as well as effective nutrient uptake kinetics that enable
them to dominate ultra-olirotrophic environments (Stockner et al. 2000; Paerl, 2000) .
The ability to grow at the limits of life helps cyanobacteria dominate vast nutrient and/ or
light deficient segments of the world’s oceans and large lakes in terms of primary production and
biomass. Nitrogen-fixing cyanobacteria Trichodesmium and Richelia bloom in nitrogen deplete ultraoligotrophic oceans (Villareal, 1992; Carpenter, 1983). A significant portion of oceanic primary production is conducted by the autotrophic picoplankton (APP), a group of phytoplankton composed mainly of cyanobacteria that range in size from 0.2 to 2µM
(picocyanobacteria). By various estimates, 32-80% of photosynthesis in the subtropical and tropical Atlantic and Pacific can be attributed to the marine picocyanobacteria Synechococcus and Prochlorococcus (Goericke and Welshmeyer, 1993; Li, 1983). These tiny unicellular cyanobacteria generally do not fix N2, but their increased surface to volume ratio allows them to survive at extremely low nutrient concentrations present in these oceanic areas. The smaller cell
B size allows for a more efficient light absorption. Indeed, the assimilation number Pm and initial slope α of the photosynthesis-irradiance curve of natural phytoplankton assemblages from the chlorophyll maximum of the mid-Atlantic were higher for picoplankton-size fraction than for the remaining phytoplankton (Platt et al 1983). At the same time, the picoplankton photosynthesis is
saturated at lower irradiances, and they are more susceptible to photoinhibition (Platt et al. 1983;
Glover et al. 1985). In addition, as an adaptation to low irradiances they have acquired a unique
pigment composition that allows Prochlorococcus and Synechococcus to share the nutrient rich 3
subsurface layer of the water column. A characteristic feature of Prochlorococcus species is the
presence of divinyl chlorophylls a and b and monovinyl chlorophyll b, whose absorption maxima
(Figure 1, A) are shifted towards the shorter wavelengths of light compared to the typical algal
and cyanobacterial monovinyl chlorophyll a (Chisholm et al. 1988), which is consistent with the predominance of Prochlorococcus in the deep blue-green enriched segments of the water column
(100-200m) (Olson et al. 1990; Moore, 2002; Partensky, 1999; Fuller et al. 2003). The major light-harvesting pigments of the marine Synechococcus are monovinyl chlorophyll a and phycoerythrin, a phycobilin with the blue-shifted absorption maximum (Amax = 565-575nm),
compared to that of phycocyanin (Amax = 615-640nm), which is more typical for cyanobacteria
growing in the shallower freshwater lakes (Ting et al. 2002). The two major chromophores of
Synechococcus phycoerythrin are phycoerythrobilin (PEB, Amax = ≈550nm), and phycoeurobilin
(PUB, Amax = ≈490nm)(Figure 1, A)(Stockner et al. 2000). Synechococcus cyanobacteria typically occupy the upper layer of the subsurface zone, and their cell density exceeds that of
Prochlorococcus at the surface of the water column and in coastal waters; however, these two groups generally coexist throughout the water column (Fuller et al. 2003; Ferris and Palenik,
1998; Partensky et al. 1999; Rocap et al. 2003; Zinser et al. in press)(Figure 1, B). The phenomenon of niche-differentiation in oceanic picocyanobacteria has received much attention during the past two decades. Until the advent of epifluorescent microscopy in the late 1970s, picocyanobacteria were simply overlooked due to the larger cell-biased sampling techniques.
However, since the discovery of marine Synechococcus (Waterbury et al. 1979), and
Prochlorococcus (Chisholm et al. 1988), in the euphotic zone of oligotrophic oceans, many studies have been focused on their genetic and phenotypic diversity, as well as their spatial
4
Figure 1: A).The in vivo absorption spectra of Prochlorococcus (strain MED4) (green) and marine Synechococcus (strain WH8102) (pink). In Synechococcus, the 493 nm and 544 nm absorption peaks are attributable primarily to the its major light harvesting pigments phycourobilin and phycoerythrobilin, respectively. The divinyl chlorophyll (Chl) a and b pigments of Prochlorococcus absorb maximally in the blue region (447 nm,~485 nm). The red peak of Synehcococcus (680nm) is attributable to monovinyl Chl a. Thus, the red peak of Prochlorococcus divinyl Chl a (673 nm) is shifted approximately 7 nm towards the blue region of the spectrum compared with the monovinyl Chl a (680 nm) of Synechococcus (both absorption spectra have been normalized to a value of one at this red peak). Thus, Prochlorococcus is more efficient at absorbing blue wavelengths of light that Synechococcus, which absorbs more in the green area of the spectrum. B). Typical vertical distributions of Prochlorococcus (orange triangles) and Synechococcus (pink squares) at a station in the subtropical Atlantic (32°08´ N, 70°02´ W) during the summer (10 June, 1996) shows Prochlorococcus cell concentrations exceeding those of Synechococcus, particularly deeper (80–120 m) in the water column. Cell concentrations were measured by flow cytometry using a modified FACScan (Becton Dickinson). Approximate depths of the open ocean water column that are enriched with blue-green and blue wavelengths of light are shown. Adapted from Ting et al., 2003.
5 distribution and seasonal dynamics in the oceanic water column. Such phenomena are largely controlled by light and nutrient gradients (reviewed in Ting et al. 2002 and Scanlan and West,
2002). Whether such niche differentiation occurs among APP is not yet understood.
Freshwater picocyanobacteria: diversity
In contrast, the information on the biodiversity and the populational dynamics of the freshwater picocyanobacteria with regard to the factors controlling phytoplankton growth and productivity is relatively scarce (Stockner and Antia, 1986; Callieri and Stockner, 2002). A great body of research has been focused on the bloom-forming freshwater cyanobacteria of the genera
Anabaena, Nostoc, Oscillatoria, Aphanizomenon, Nodularia and Microcystis ubiquitous in warm, nutrient rich lakes, rivers and man-made water storage systems, where they decrease water quality and can cause damage by producing hepato- and neurotoxins that can be potentially poisonous to wildlife, livestock and humans (reviewed by Oliver and Ganf, 2000). Freshwater picocyanobacteria that contribute substantially to primary production in large and deep oligotrophic lakes have received much less attention than the bloom-formers (Fahnenstiel and
Carrick, 1992; Nagata et al. 1994; Nagata et al. 1996; Stockner and Shortsheed, 1994).
The freshwater picocyanobacteria range in size from 0.2 to 3µM (Stockner et al. 2000;
Callieri and Stockner, 2002) and can be colonial or single celled. The colonial picocyanobacteria have been known to limnologists since the beginning of the XXth century due to their abundance in warm meso- and eutrophic lakes and the relatively large size of the colonies (Stockner et al.
2000). The single celled picocyanobacteria are the dominant group of the freshwater APP. The major method for the detection and enumeration of single celled picocyanobacteria is epifluorescent microscopy, and most of the research on the single celled APP occurred during 6 the last three decades (Stockner and Antia, 1986; Fahnenstiel and Carrick, 1992; Callieri and
Stockner, 2002).
The dominant picoplankton pigments are characterized by different fluorescence profiles allowing for detection and enumeration of major groups differing by their pigment composition
(Ting et al. 2002). Phycoerythrin-rich cyanobacteria emit orange-red fluorescence under green excitation and yellow-orange fluorescence under blue excitation, and thus can be easily distinguished from phycocyanin-rich cyanobacteria and chlorophyll-rich eukaryotic APP, which are characterized by purple-red and red emission under green and blue light respectively
(Fahnenstiel and Carrick, 1992). The majority of APP in lakes Huron and Michigan fall into the phycoerythrin-rich category (Fahnenstiel and Carrick, 1992; Nagata et al. 1996). Similar results were obtained in a study of Lake Superior picoplankton, where orange fluorescent chroococcoid picocyanobacteria were the predominant organisms in the <3µM fraction (Fahnenstiel et al.
1986). The dominance of each pigment type is related to light quality and quantity in different layers of the water column (Voros et al. 1998). Phycoerythrin-rich picoplankton generally dominates large and deep oligotrophic lakes with clear water and low light attenuation
-1 coefficient Kd (< 0.55m ), whereas phycocyanin-rich cells are more common in shallow
-1 eutrophic lakes with higher Kd (>2.25 m )(Postius and Ernst, 1999).
Species composition of the APP has received considerable attention in the past two decades (Stockner and Antia, 1986; Stockner et al. 2000; Callieri and Stockner, 2002). The major colonial genera are Aphanocapsa, Aphanothece, Chroococcus, Coelospherum, Cyanodictyon,
Merismopedia, Snowella and Tetrarcus. Their representatives can be found in a wide range of conditions from warm eutrophic to oligotrophic, but mostly in nutrient rich meso- and eutrophic lakes (Callieri and Stockner, 2002). The three genera that comprise the single celled group are 7 the freshwater Synechococcus, Cyanobium and Cyanothece, with Synechococcus being the most abundant and, physiologically and genetically diverse genus (Stockner and Antia, 1986;
Fahnenstiel et al. 1986; Fahnenestiel and Carrick, 1992; Callieri and Stockner, 2002). The freshwater Synechococcus and Cyanobium species together with the marine Synecochococcus and Prochlorococcus form a bootstrap-supported “picocyanobacterial clade” separated from the rest of the cyanobacterial radiation, and these four groups dominate the APP of the freshwater, marine and brackish ecosystems (Figure 2)(Urbach et al. 1998; Honda et al. 1998; Ernst et al.
2003; Crosbie et al. 2003). The eukaryotic fraction of the APP is generally outnumbered by an order of magnitude by the picocyanobacterial fraction, and is composed mostly of green algae
(Chlorophyta) and diatoms (Bacillariophyta), and to a lesser degree cryptomonads
(Cryptophyta), chrysomonads (Chrysophyta) and dinoflagellates (Dinophyta) (Stockner and
Antia, 1986; Callieri and Stockner, 2002).
The separation of the cyanobacterial component of the APP into colonial and single celled groups is imperfect since some of the single celled species form loosely aggregated colonies (Stockner et al. 2000). Recently, Ernst et al. (1996) have reported the presence of regularly ordered glycoproteins forming S-layers on the cell surface of picocyanobacteria from
Lake Constance. Such S-layers can serve as a base for colony formation (Callieri and Stockner,
2002), which is thought to help picocyanobacteria resist grazing by dinoflagellates, one of the major factors regulating their abundance. Presumably, the external polysaccharide layer of the colonies is avoided by grazers (Klut and Stockner, 1991). The increased occurrence of APP colonies during the periods of ultra-oligotrophy in the late summer and early fall in some temperate lakes led to the suggestion that they might represent an adaptive response to severe nutrient stress (Fahnenstiel and Carrick, 1992; Klut and Stockner, 1991). The interactions 8
Picoplankton clade sensu Urbach et al. 1998
Freshwater
picocyanobacteria
Figure 2. A phylogenetic tree constructed from 16S rDNA sequences depicts the close relationship between Prochlorococcus and marine Synechococcus, which together with freshwater picocyanobacteria Synechococcus and Cyanobium form the “picocyanobacterial clade” sensu Urbach et al. (1998), well separated from the remaining of the cyanobacterial radiation. Numbers at nodes indicate bootstrap support values. Adapted from Ting et al. 2002
9
between single cells within the colony allow for a more efficient nutrient recycling, and the
decreased buoyancy of the colonies might help the APP to occupy the nutrient rich subsurface
waters of the euphotic zone (Klut and Stockner, 1991).
Freshwater cyanobacteria: populational dynamics
The seasonal succession of the APP in oligotrophic dimictic lakes includes a spring
abundance peak, which corresponds to the onset of stratification, followed by the summer
decline, and a second peak in the early fall. It is generally accepted that picocyanobacteria and
picoeukaryotes out-compete other phytoplankton in the light limited environment of large lakes
during spring isothermal mixing due to their exceptional ability to grow at low irradiances,
compared to the larger cells (Stockner et al. 2000; Callieri and Stockner, 2002). Further, after the
onset of stratification, grazing by nano- and microzooplankton and limited nutrient
bioavailability are the major causes of the decline of the spring peak (Stockner and Shortsheed,
1994; Callieri and Stockner, 2002). During the two abundance peaks, different populations of
picocyanobacteria dominate the APP, likely in response to seasonal changes in nutrient and light
availability (Fahnenstiel and Carrick, 1992; Ernst et al. 1995).
There is no clear pattern for the vertical distribution of the APP, and their abundance
peaks were recorded in the metalimnion and higher hypolimnion of Lakes Huron and Michigan
(Fahnenstiel and Carrick, 1992) in the metalimnion of Lake Baikal (Nagata et al. 1994), in the epilimnion of Lake Kinneret, Israel (Malinsky-Rushansky et al 1995) and in the surface waters of Lake Biwa, Japan (Nagata et al 1996). The above illustrates the increased ability of the APP to adapt to various light levels.
As mentioned above, cyanobacteria and photosynthesizing eukaryotes of the picoplankton size range dominate the phytoplankton in oligotrophic lakes. The relative 10
contribution of the APP to the total primary production varies between lakes. The numbers range from 17% in lakes Huron and Michigan (Fahnenstiel and Carrick, 1992), to 40-54% in Lake
Superior (Fahnenstiel et al. 1986) 80% in Lake Baikal (Nagata, 1994), 23% in Lake Biwa
(Nagata et al. 1996) and 29-53% in eleven oligotrophic lakes in Canada (Stockner and Shorteed,
1994). Stockner (1991) proposed a model according to which the contribution of the APP to primary production and total phytoplankton biomass decreases with increasing phosphorus availability. In a study of eight New Zealand lakes, Petersen (1991) showed an inverse dependence between the trophic status and the contribution of APP to total primary production.
Sondergaard (1991) in his study on seven Danish lakes showed that, although Chl (chlorophyll) concentrations corresponding to the APP fraction of the biomass were similar between lakes, their relative contribution was higher in the lakes with a lower trophic status. Voros et al. (1991) studied 32 lakes ranging from shallow eutrophic to deep oligotrophic subalpine lakes and found that the contribution of the APP to total Chl concentrations were more than 70% in lakes with
Chl lower than 10 µg L-1 and less than 10 % in lakes with Chl exceeding 100 µg L -1. However,
there is considerable seasonal and vertical variation in the APP primary production and biomass,
which in the case of a small data set can lead to erroneous conclusions on the APP importance
for total primary production when several lakes are compared (Fahnenstiel and Carrick, 1992;
Stockner and Callieri, 2001). Nevertheless, the general trend remains with the APP being a most
ubiquitous component of phytoplankton in nutrient deplete waters. A component of this
dissertation is to examine the seasonal progression of APP in Lake Superior to help understand
their population dynamics (Chapter 4).
11
Lake Superior as an example of an extremely oligotrophic system
Lake Superior is a large water body with the most extensive surface area of any
freshwater lake in the world. It is the second largest in volume (after Lake Baikal in
southwestern Siberia) and contains approximately 10% of the world’s surficial freshwater. The
lake is highly oligotrophic with very stable water chemistry due to the geology and geomorphology of the lake drainage area. The chemical composition of Lake Superior water is rather stable with low concentrations of nearly every chemical element. Almost the entire drainage basin of the lake is located within the very ancient (2500-3000 billion years old)
Canadian Crystalline Shield with chemically stable igneous and metamorphic rocks (Weiler,
1978). Most of the lake water supply comes from precipitation falling onto the watershed.
Approximately 50% of the precipitation that falls on the terrestrial watershed evaporates. The remaining precipitation comes into the lake by means of numerous, but short tributaries, which transport the water to the lake quickly. Thus, the contact time during which the chemically resistant mineral substance of the riverbeds can be dissolved is relatively short. Furthermore, since about 40% of the basin is covered by the lake surface, a considerable portion of the total basin precipitation falls directly onto the lake, diluting the “saturated” drainage water significantly, so that the chemical composition of the Lake Superior water is close to that of rainwater (Matheson and Munawar, 1978).
Besides that, the basin is thinly populated with an average of 10 people km-2. Human
development within the basin is concentrated in the two major industrial centers, Duluth on the
western tip of the lake and Thunder Bay in Canada. Ninety five percent of the land basin is
covered with forests and there is very little agricultural activity in the basin. Consequently, there 12 have been no significant changes in the lake water composition caused by human actions
(Matheson and Munawar, 1978).
Concentration of major ions and nutrients in Lake Superior remained constant over the last 100 years. Calcium, magnesium and chloride were unchanged since 1885. Sodium and potassium were not changed since 1940, but the earlier higher values were probably due to the differences in analytical methods used before and after 1940. Nutrient levels, including phosphate, sulfate and silica were constant since the beginning of the last century (Weiler, 1978).
Lake Superior and accumulation of nitrate
Unlike other nutrients, nitrate exhibits a century long steady exponential increase (Figure
3), which corresponds to an annual increase in nitrate of about 2%. Weiler (1978) was the first to report the historical trend of nitrate accumulation in Lake Superior between years 1906 and
1976. Later, Bennet (1986), in his paper focused on nitrification of Lake Superior, fit an exponential function to the historical nitrate data spanning the time interval from 1906 until
1976. By extrapolating the exponential relationship beyond the period of observations, he built an exponential function for the nitrate increase in the lake covering the time period between 1880 and 2000. He calculated the rate of the nitrate build-up in the lake to be 2% per year in the form of nitrate each year; thus, resulting in a six-fold increase over a time interval of 100 years.
According to Bennet (1986), atmospheric nitrogen loading is the major source of the nitrate accumulation in the lake. However, Bennet’s model fails to explain the magnitude of the nitrate increase over a relatively short time. Considering the hydraulic flushing, an increase in nitrogen loading requires the time interval equal to the nitrogen turnover time to manifest itself in the lake nitrogen concentration. For Lake Superior, the nitrogen turnover time is more than 50 13
years, which implies a six-fold increase in loading must have occurred a long time ago to cause a
six-fold increase in the lake nitrogen concentration.
Figure 3. Graphic representation of the historical trend of increasing nitrate/nitrite concentrations for the time period from 1900 to 2002 (Sterner, R.W. unpublished)).
Although atmospheric nitrogen deposition is likely the main source of the nitrogen input
into the lake there is probably more than one factor that contributes to such a large change in a
major biologically active chemical element. One of the reasons this build-up can be attributed to
the decrease in the biotic demand of nitrogen, caused by other environmental factors. The diminished biological uptake of nitrogen can lead to its accumulation in the lake and thus can
also account for the observed nitrogen build-up as well as the atmospheric loading. 14
Potential factors limiting primary productivity in Lake Superior
Historically, low availability of phosphorus was considered to be the major limiting
nutrient in large oligotrophic lakes (Schindler, 1977; Nalewajko, 1980; Nalewajko and Voltolina,
1986; Millard, 1996; Guildford, 2000). At the same time, owing to prolonged periods of
isothermal mixing and low Zeu/Zm ratio, the phytoplankton are likely to be light limited in such
lakes especially during the mixing period. Indeed, Millard et al. 1996 showed that in spring, P
uptake rates in Lake Ontario are lower than in summer due to a lower biomass, and light is the
primary limiting factor, but in the onset of thermal stratification in May-June, P deficiency starts to increase throughout the lake and reaches its maximum in July/August (Millard et al. 1996).
Further, Guildford et al. 2000 showed that the phytoplankton of Lake Superior were under severe
P deficiency, compared to Lake Malawi, which has similar size and morphology, but the
different climates impose different water circulation patterns resulting in different nutrient and
light regimes. In addition, in Lake Malawi, phytoplankton were adapted to higher irradiances
(Guildford et al. 2000). Another study on Lake Superior showed that stratified and inshore areas
are more P limited, whereas unstratified and offshore regions are more light limited (Nalewajko
and Voltolina, 1986). Fahnenstiel et al suggest that since light, temperature and nutrient supplies
are often at suboptimal levels during spring mixing in Great Lakes, the three factors are likely act
in combination. Indeed, only simultaneous amendments with light and phosphorus lead to the
maximal phytoplankton growth (Fahnenstiel et al. 2000).
It has been shown that phosphorus availability can influence nitrate assimilation capacity
in cyanobacteria (Hu et al. 2000); which is expected since ATP is the energy source for the
nitrate and nitrite uptake reactions, a required step in the nitrate assimilation pathway (Figure
4)(Flores et al. 2005). Further, light driven photosynthetic reactions provide the ATP the and 15
reducing power in the form of ferredoxin for this pathway (Figure 4)(Flores et al. 2005). Indeed,
evidence exists for a compensatory mechanism between light and nitrate limitation in diatoms
(Ree and Gotham, 1981). Light limitation can prevent Synechococcus linearis from assimilating the limiting nutrient (Healey, 1984). Finally, light intensity influences the ability of
Synechococccus PCC 7942 to remove nitrate from groundwater (Hu et al. 2000).
Figure 4. Nitrate assimilation system exampled on freshwater cyanobacteria Synechococcus elongates. The ABC- type transporter for nitrate/nitrite is located at the cytoplasmic membrane (CM). The enzymes nitrate reductase (Fd- Nar) and nitrite reductase (Fd-Nir) use of ferredoxin (Fd) photosynthetically reduced at the thylakoids as electron donor. Ammonium resulting from nitrate reduction is incorporated into amino acids by the glutamine synthetase/glutamate synthase (GS/GOGAT) pathway (see below). Approximate values for the affinity constants of the permease (Ks) and the reductases (Km) are indicated. From Flores et al. 2005
In addition to phosphorus and light limitation, there is evidence for low availability of
iron in Laurentian Great Lakes (Twiss et al. 2000; Sterner et al. 2004; McKay et al. 2005). Iron is
an important component of the photosynthetic apparatus and nitrogen fixation machinery, and
photosynthetically reduced ferredoxin provides electrons for the nitrate reduction reactions. Low
iron bioavailability is widely recognized as a limiting factor for phytoplankton in the high- 16
nutrient low chlorophyll (HNLC) areas of the ocean (Coale et al. 1996; Boyd et al. 2004). The
large-scale iron fertilization experiments in the HNLC regions of the Southern Ocean, iron
stimulated the nitrate uptake by phytoplankton in situ (Coale et al. 1996; Boyd et al. 2004). In
Lake Superior, the effect of iron was demonstrated in phosphorus amendment experiments,
where it limited growth stimulated by added phosphorus (Sterner et al. 2004). Thus, low
availability of iron can constrain the phytoplankton capacity to use other available nutrients.
Considering its role in nitrate reduction and photosynthesis, iron stress is likely to affect the
nitrate assimilatory capacity of the phytoplankton in Lake Superior.
Hence, there may be a paradoxical situation in Lake Superior, whereby phytoplankton cannot assimilate nitrate despite its sufficient amount in the water. One of the ways to get insight into the microbiological processes that contribute to nitrate production and removal within the lake is to assess the bioavailability of nitrate and the role of other nutrients and physical factors in altering the picoplankton capacity to assimilate nitrate. Chapters 2 and 3 describe series of experiments designed in order to understand such factors by employing a nitrate-sensing cyanobacterial bioreporter.
Use of cyanobacterial bioreporters to measure nutrient bioavailability
Modern analytical techniques for the estimation of nutrient levels in natural habitats
allow for a rapid and precise detection of virtually any chemical in a broad concentration range.
However, these methods fail to determine the bioavailable fraction of a nutrient versus its total
concentration in an environmental sample. In contrast, the application of genetically engineered
whole cell biosensors provides information on the bioavailability of a nutrient. Therefore, they can be used in combination with analytical methods for environmental monitoring (Belkin, 2003;
Bachmann, 2003). 17
The term “whole cell biosensor” typically implies a genetically altered prokaryotic or eukaryotic cell capable of producing a detectable signal in response to the presence or absence of a certain chemical or group of chemicals in the media (Figure 5) (Belkin, 2003; Bachmann,
2003). In such a cell, the promoter of a gene, whose expression is regulated by the chemical under study, fused to a reporter gene and an antibiotic resistance marker. This construct is introduced into the genome of the host organism by means of genetic transformation. This allows for the expression of the reporter gene in response to decreased or increased bioavailabilty of the substrate that regulates the promoter. The most commonly used reporter genes are gfp encoding for the Green Fluorescent Protein (GFP) and luxAB encoding for the bacterial luciferase enzyme
(Kunert et al. 2000; Gillor et al. 2002; Shao et al. 2002; Mbeunki et al. 2002; Durham et al.
Figure 5. Organization of a bioreporter organism. In ‘lights off’ assays (a), the concentration of the chemical in question is estimated from the degree of inhibition of a ‘normally on’ activity. In ‘lights on’ assays (b), a quantifiable molecular reporter is fused to specific gene promoters, known to be activated by the target chemical(s). (from Belkin, 2003)
18
2002; Gillor et al. 2003; Ivanikova et al. 2005). The measurable signals reflecting changes in the
bioavailable concentration of the chemical under study are GFP fluorescence and luminescence
in the case of luciferase.
Cyanobacteria have often been employed for the construction of biosensors because they
represent an ecologically important group of photoautotrophs and can be easily genetically
transformed. luxAB and gfp based recombinant plasmids for the incorporation into the
chromosomes of unicellular cyanobacteria Synechococcus sp. PCC 7942 and Synechocystis sp.
PCC 6803 are now available making the construction of bioreporters based on these strains very
straightforward.
Over the last decade, the use of genetically engineered cyanobacterial biosensors has
been described by different research groups (Belkin, 2003; Bachmann, 2003). A series of papers were focused on the development of bioreporters for the detection of environmental pollutants
(Erbe et al. 1996; Applegate et al. 1998; Willardson et al. 1998 and Shao et al. 2002). Others described the construction of cyanobacterial strains capable of sensing bioavailable nutrient concentrations and their application for environmental monitoring. In attempt to provide a tool for the monitoring of cyanobacterial blooms, the nitrogen regulated promoter of the nblA gene, responsible for phycobilisome degradation in nitrogen deplete conditions. was fused to the luxAB gene and introduced into Synechocystis PCC 6803. The resulting strain was used for the assessment of nutrient bioavailability in water to predict the formation of blooms (Mbeunki et al.
2002). In our laboratory, a Synechococcus PCC 7942 bioreporter strain for the detection of bioavailable Fe was constructed by fusing the Fe responsive isiA promoter to the luxAB gene from Vibrio fischeri (Durham et al. 2002). The biosensor was used to assess iron limitation in the
Great Lakes (Durham et al. 2002, Porta et al. 2003; McKay et al. 2005). Gillor et al. (2002) fused 19 the promoter of the alkaline phosphatase gene phoA to Vibrio harveyi luxAB gene and introduced the fusion into Synechococcus PCC 7942. The resulting strain was used for monitoring of phosphorus bioavailability in lake Kinneret, Israel (Gillor et al. 2002). A bioluminescent nitrogen sensing strain was constructed by the promoter fusion of the glnA gene, regulated by the availability of combined nitrogen and the luxAB gene and used it to measure the bioavailable nitrogen concentration in the same lake (Gillor et al. 2003).
One of the objectives of this work was to design a cyanobacterial strain capable of sensing the bioavailable nitrate and use it for monitoring the nitrate assimilation capacity by phytoplankton in Lake Superior. The bioreporter is based on a freshwater cyanobacterial strain
Synechocystis PCC 6803, which was selected as the host organism for this work due to several reasons. First, it was the only cyanobacterial strain whose entire genome was sequenced at the time when the work was started allowing for simple PCR-mediated cloning of any DNA sequence of interest (Kaneko et al. 1996). Further, luxAB and gfp based promoter probe vectors pILA and pIGA for the homologous recombination into the genome of Synechocystis PCC 6803 were previously developed by Kunert et al. (Figure 2 in Chapter 2)(2000). Finally, it is a well- characterized strain in terms of physiology and gene regulation (Herrero et al. 2001).
Regulation of cyanobacterial mitrogen assimilation genes
To develop a reliable bioreporter for nitrate utilization, a thorough understanding of the regulatory mechanisms is required. In cyanobacteria, the expression of the genes, which are responsible for nitrogen uptake is controlled by both the global nitrogen regulator NtcA, a member of the CRP (Catabolic Repressor Protein) family of bacterial transcriptional factors and the signal transducer PII (Herrero et al. 2001). The assimilation of many nitrogen species requires their sequential reduction to ammonium using the electrons of photosynthetically 20
reduced ferredoxin, a Fe containing protein. Then, ammonium is incorporated into carbon
skeletons via the glutamine synthetase (GS)/glutamate synthase (GOGAT) reactions known as
GS-GOGAT pathway (Figure 7). GS catalyzes ATP dependent amidation of glutamate to yield glutamine. GOGAT catalyzes the sequential reaction, in which the amido group of glutamine is transferred to the molecule of 2-oxoglutarate, yielding two molecules of glutamate (Figure 7).
Under the conditions of ammonium deficiency and in the presence of nitrate as a sole nitrogen
source, NtcA positively regulates the transcription of the glnA gene encoding the GS enzyme and
a number of genes involved in assimilation of alternative nitrogen sources (Muro-Pastor et al.
2001).
Figure 6. Interactions between nitrogen and carbon regulation in cyanobacteria. 2-OG, 2- oxoglutarate; NtcA, global nitrogen regulator; glnB, gene encoding the PII protein; Nar, nitrate reductase; Nir, nitrite reductase; GS, glutamine synthetase; GOGAT, glutamate synthase; Fdred : reduced ferredoxin . (From Tandeau de Marsac et al. 2001).
It has recently been shown that cyanobacteria sense nitrogen status of the cell by the
intracellular concentration of 2-oxoglutarate, an intermediate of the TCA cycle (Figure 7). In
Synechocystis PCC 6803, nitrogen deficiency is perceived through the increased level of this 21 catabolite (Muro-Pastor et al. 2001), and it increases the affinity of the Synechococcus PCC 7942
NtcA protein to the promoter of the glnA gene in vitro (Vasquez-Bermudez et al. 2002). Thus, activation of expression by NtcA induced by nitrogen starvation depends on the carbon status of the cell. The level of 2-oxoglutarate also controls the activity of another nitrogen regulator PII.
Under ammonium replete conditions, the dephosphorylated form of PII post-translationally inhibits the nitrate/nitrite uptake system. In Synechococcus PCC 7942 the level of PII phosphorylation positively correlates with the increase of the intracellular concentration of 2- oxoglutarate. Binding of 2-oxoglutarate to PII results in a conformational change in the protein leading to its phosphorylation by the PII kinase (Figure 7)(Tandeau de Marsac et al. 2001). It should be noted that, since cyanobacteria lack a 2-oxoglutarate dehydrogenase (Smith et al.
1967) the main metabolic function of 2-oxoglutarate is to serve as a substrate for the incorporation of ammonium into carbon skeletons. This makes this catabolite a particularly suitable signal molecule, the level of which reflects the nitrogen: carbon ratio in the cell (Muro-
Pastor et al. 2001).
In addition to nitrogen control, both NtcA and PII are involved in the regulation of carbon assimilation genes (Figure 7)(Muro-Pastor et al. 1996). The expression of both proteins in turn is controlled by the electron transport through the photosynthetic electron transport chain (Alfonso et al. 2001; Garcia-Domingues and Florencio, 1997). Therefore, besides the ferredoxin dependent reduction of nitrate and nitrite needed for their assimilation, there are many mechanisms connecting nitrogen uptake and light induced carbon assimilation.
The nitrate/nitrite regulated promoter of the Synechocystis PCC 6803 nirA gene encoding for a nitrite reductase was employed for the construction of a nitrite/nitrate sensing bioreporter.
The promoter region contains consensus sequences for the NtcA and NtcB regulatory proteins. 22
Whereas, NtcA modifies the transcription of nitrogen assimilation genes with respect to the availability of combined nitrogen, the NtcB protein, which belongs to the LysR family of transcriptional activators was shown to enhance the transcription of the nitrite assimilation genes in the presence of this substrate as a nitrogen source. In Synechococcus PCC 7942, NtcB increases the positive effect of NtcA on the transcription of nirA gene in nitrite containing media, but its activity is not essential for the expression of nirA in low nitrogen media (Maeda, et al.1998; Aichi and Omata, 1997). In contrast, in Synechocystis PCC 6803, it activates transcription in the presence of nitrite/nitrate in concert with NtcA and its activity is required for the nirA expression in nitrogen deplete media (Frias et al. 2000; Aichi et al. 2001).
The NtcB dependent positive effect of nitrite on the transcription from the nirA promoter is a key component to the functioning of the bioreporter described in this dissertation. When exposed to nitrate containing media, the Synechocystis cells harboring the nirA:luxAB fusion emit light due to the transcription of the luxAB gene from the nirA promoter in response to the presence of nitrite, and the Synechocystis nirA:luxAB promoter fusion was used to monitor the availability of nitrite or nitrate derived from the reduction of nitrite in water samples. After the physiological characterization of the nitrite/nitrate biosensor in the laboratory, the optimal conditions for measuring the bioavailable concentration of nitrate were determined, and the biosensor was exposed to the water samples from Lake Superior.
The importance of studying the endemic picoplankton of Lake Superior
The Synechocystis PCC 6803 based nitrate bioreporter is a model for elucidating the factors that regulate nitrate depletion by phytoplankton in natural waters. The response of the bioreporter in the Lake Superior water provides insight into the conditions faced by natural phytoplankton in this ecosystem. Cyanobacteria of the picoplankton size range constitute a 23
significant if not dominant fraction of Lake Superior phytoplankton (Fahnenstiel et al. 1986;
Hicks and Pascoe, 2001). As mentioned earlier, Synechocystis is a physiologically and genetically well characterized cyanobacterial strain (Herrero et al. 2001), and is one of the strains that can be easily genetically transformed using promoter-probe vectors developed by
Hagemann’s lab (Kunert et al. 2000). However, the strain clusters outside the well bootstrap supported picocyanobacterial clade in a cyanobacterial tree of 16S rDNA (Figure 2)(Urbach et al. 1998; Honda et al. 1998; Robertson et al. 2001). Nevertheless, by the cell size of ≈ 3µM,
Synechocystis is at the upper border of the picoplankton category; therefore, its physiological responses to stress caused by low availabilities of light and nutrients are expected to be in many ways similar to those of cyanobacterial picoplankton. All the above makes Synechocystis a plausible candidate for the construction of a nitrate bioreporter that can be used to study aspects of nitrate drawdown in Lake Superior. However, the ultimate goal of these studies is to apply this strategy to the natural picoplankton assemblage in lake Superior. Understanding the physiology of the endemic species will help affirm the validity of the bioreporter approach in their ecosystem.
The information on Lake Superior phytoplankton community is scarce. The mean phytoplankton biomass in Lake Superior is extremely low and the lake was classified as ultra- oligotrophic based on the comparison with other Laurentian Great Lakes and a number of
European lakes (Munawar and Munawar, 1978). In 1973, the total phytoplankton biomass was fluctuating seasonally between 1 and 1.4 mg/m3 chlorophyll a with very little spatial variability
in the pelagic part of the lake. The absence of pronounced temporal or vertical trends in
phytoplankton abundance and primary production was also noticed by Fahnenstiel et al (1986),
who sampled throughout the year in 1979 and in September 1983. Lake Superior APP (< 3µM) 24
were responsible for 40-54% of total C uptake in 1979 and 1983, with the orange fluorescing chroococcoid cyanobacteria < 1µM in diameter accounting for 16-24 % in 1983 (Fahnenstiel et al. 1986). In September 1983, the abundance of chroococcoid picocyanobacteria of < 1µM was
32- 42*103 cells/mL with the total 44- 61*103 cells/mL autofluorescing cells (Fahnenstiel et al.
1986).
Species composition of Lake Superior phytoplankton was described by Munawar and
Munawar (1978). The lake was characterized by high species diversity, more than 285 taxa were identified, many of them had not been reported before. Diatoms appeared to be the dominant group (31% of the total number of species), followed by chlorophytes (22%), chrysomonads(20%), cyanobacteria (12%), cryptomonads (8%) and dinoflagellates (6%). The most common diatoms were Cyclotella stelligera and C.comta, which are considered to be indicators of oligotrophy. The cyanobacterial community appeared to be dominated by filamentous forms such as Oscillatoria limnetica, Oscillatoria sp., O. minima, Lyngbya sp., L. lymnetica, Anabaena pulchra, Anabaena sp. Oscillatoria limnetica, a phycoerythrin-rich
filamentous cyanobacterium was one of the dominant phycoplankton species in May, June and
July. Some of the colonial picoplankton genera such as Aphanothece sp., Aphanocapsa sp.,
Chroococcus sp. and Merismopedia sp. were also detected, with no indication of unicellular
Synechococcus-like picocyanobacteria (Munawar and Munawar, 1978). Conversely, Fahnenstiel
et al. (1978) report on high abundances of phycoerythrin-rich chroococcoid picocyanobacteria in
both epilimnion and hypolimnion of Lake Superior in September 1983. Similar results were
obtained by Hicks and Pascoe (2001) in their comparative study of the Laurentian Great Lakes
picoplankton using 16S rRNA based hybridizations and direct cell counts. As mentioned earlier,
unicellular Synechococcus-like picoplankton is an important if not dominant part of 25 phytoplankton in oligotrophic lakes all over the world, including the Laurentian Great Lakes
(Caron et al. 1985; Fahnenstiel and Carrick, 1992; Klut and Stockner, 1991; Wehr, 1992;
Stockner and Shortsheed, 1994; Postius and Ernst, 1999). The apparent absence of this group of the APP from lake Superior in the 1973 study is probably due to the biased sampling techniques used in that study.
Overall, the biodiversity of Lake Superior phytoplankton, especially its picocyanobacterial component remains poorly investigated and needs more attention. Compared to the other Laurentian Great Lakes, this enormous water body is the least disturbed by human activities, has unique water quality and probably the most preserved phytoplankton community
(Weiler, 1978; Munawar and Munawar, 1978). Over the last two decades, many reports have been focused on the molecular approach for studying the bacterioplankton and phytoplankton composition of the ocean (Schmidt et al. 1991; Worden et al. 1999; West and Scanlan, 1999;
Fuller et al. 2003; Field et al. 2003; Venter et al. 2004; Zinser et al. in press). PCR amplification of 16S rDNA sequences extracted form the seawater revealed an extremely high diversity of oceanic microbial life (Giovannoni et al. 1990; Ward et al. 1990). In the case of picoplankton, these methods are especially useful since many of these organisms are extremely difficult to bring in culture, and, traditional culturing techniques tend to underestimate true species diversity
(Schmidt et al. 1991; Scanlan and West, 2002).
As mentioned earlier, phycoerythrin-rich Synechococcus cyanobacteria dominate the
APP of transparent oligotrophic lakes (Callieri and Stockner, 2002), whereas in the open ocean, they coexist with chlorophyll b containing Prochlorococcus (Ting et al. 2002). The former genus
Synechococcus includes genetically and physiologically diverse, unicellular coccoid cyanobacteria < 3µM in diameter that divide by binary fission and occupy a wide range of 26
environments besides the oligotrophic oceans and lakes (Rippka et al. 1979), including hot
springs (Miller and Castenholz, 2000) and hypersaline environments (Garcia-Pichel et al. 1998).
Synechococcus-like cells are difficult to classify by standard microscopic techniques due to their small size and morphological similarity (Postius and Ernst, 1999). Herdman (1979) noticed significant differences in the G+C content among members of the Synechococcus genus, suggesting that it is not a natural taxon. The current thinking is that the genus Synechococcus is not monophyletic, and it was divided in a number of groups based on the G+C content, habitat
(Waterbury and Rippka, 1989), as well as pigment composition and 16S rDNA and cpcAB
(phycocyanin) intergenic spacer phylogeny (Urbach et al, 1998; Garcia-Pichel et al. 1998; Honda et al. 1999; Robertson et al. 2001). Based on the analysis of a number of cyanobacterial 16S rDNA sequences, Urbach et al (1992) defined a new picocyanobacterial clade, which included marine and freshwater picocyanobacteria and separated from the rest of the cyanobacterial radiation with high bootstrap support (Figure 2). All Synechococcus-like and Prochlorococcus picocyanobacterial strains isolated so far clustered within this clade (Urbach et al. 1998; Ting et al. 2002; Katano et al. 2000; Crosbie et al. 2003; Ernst et al. 2003)(Figure 7), and it retains the high bootstrap values in trees of cyanobacterial rpoC1 genes (large subunit of the RNA polymerase enzyme) (Palenik and Swift, 1996), as well as the cpcAB (phycocyanin) (Robertson et al. 2001) and 16S-23s rDNA gene spacers (Ernst et al. 2003).
The fourth chapter of this dissertation focuses on the phylogenetic analyses of Lake
Superior biodiversity studied by constructing and sequencing a 16S rDNA library of sequences amplified by PCR (Polymerase Chain Reaction) with cyanobacteria specific primers and DNA collected from a number of sites in Lake Superior. The vast majority of the 16S rDNA sequences in the library clustered within the picocyanobacterial clade with 100% bootstrap support. Among 27
Figure 7. Maximum-likelihood tree of the picophytoplankton clade sensu Urbach et al. (1998), inferred from 16S rRNA gene sequences (1,383 nt positions). Terminal branches display isolate and GenBank accession numbers. Bootstrap values of <50% are not shown. Minimum and mean (parentheses) pairwise percent similarities are shown on the right-hand side of each group label. The cluster designations are in accordance with Ernst et al. (2003). From Crosbie et al. 2003. 28
several picocyanobacterial subclusters present in the library, some appeared to be cosmopolitan
with members isolated from various marine and freshwater environments in different parts of the world. In addition, a new “Lake Superior” subcluster was detected that may represent a new
ecotype of Synechococcus. At the same time, four picocyanobacterial strains were isolated from the lake between years 2004 and 2005 and their phylogenetic relatedness to known picocyanobacteria was determined based on the analysis of their 16S rDNA sequences. The significance of these findings for further studies on Lake Superior picoplankton biodiversity and
populational dynamics with respect to spatiotemporal changes in light and nutrient
bioavailability is discussed.
29
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41
CHAPTER 2. CONSTRUCTION AND PHYSIOLOGICAL CHARACTERIZATION OF A
CYANOBACTERIAL BIOREPORTER CAPABLE OF ASSESSING NITRATE
ASSIMILATORY CAPACITY IN FRESHWATERS
The results presented in this chapter were published as:
Ivanikova N.V; McKay R.M.L and G.S. Bullerjahn. 2005. Construstion and Characterization of a Cyanobacterial Bioreporter Capable of Asssessing Nitrate Assimilatory Capacity in
Freshwaters. Limnol. Oceangr.: Methods 3: 86 –93.
Introduction
Cyanobacteria are a dominant component of phytoplankton in marine and freshwater oligotrophic systems (Stcokner et al. 2000) where primary production is frequently limited by nutrient availability. Whereas availability of phosphate is traditionally considered as the major factor limiting growth in freshwater ecosystems (Schindler 1977; Hudson et al. 2000), pools of other elements may be depleted, or their availability limited due to speciation effects. With respect to the Laurentian Great Lakes, various studies have documented evidence for low levels of iron (Nriagu et al. 1996; Twiss et al. 2000; Sterner et al. 2004), nitrate (MacGregor et al.
2001) and silicate (Schelske et al. 1986), suggesting that several elements in addition to phosphate warrant consideration as possible limiting factors.
A recently developed approach for the quantification of nutrient availability in freshwater environments is the use of cyanobacterial whole cell luminescent bioreporters (Bachmann 2003;
Belkin 2003). Whereas rapid and reliable chemical protocols are available to measure absolute levels of specific nutrients in water samples, bioreporters provide data on the capacity of the biota to acquire and assimilate these nutrients. Recombinant bioluminescent cyanobacterial 42
strains have been successfully applied in monitoring iron (Durham et al. 2002; Porta et al. 2003)
and phosphate (Gillor et al. 2002) availability in freshwater. In this study, we constructed a
Synechocystis sp. strain PCC 6803 bioluminescent reporter strain to assess nitrate/nitrite bioavailability in freshwater environments. The construct employs the promoter of the nitrite reductase gene, nirA, fused to the bacterial luciferase genes, luxAB. The nirA promoter is under
positive control by two transcription factors, NtcA and NtcB, that together yield elevated
transcription when bioavailable nitrate or nitrite is present in the medium (Frias et al. 2000; Aichi
et al. 2001). The strain, designated AND100, exhibits NtcA/B-dependent bioluminescence under
conditions that favor nitrate/nitrite assimilation, and the intensity of luminescence is a measure of
nitrate/nitrite uptake. Combined with additional sensors that respond to ammonium (Gillor et al.
2003), the capacity to assimilate various nitrogen species can be evaluated in freshwater systems.
Since in most freshwater systems, nitrate concentrations exceed those of nitrite by more than an order of magnitude (Mortonson and Brooks 1980), the bioreporter can be viewed primarily as a sensor for nitrate bioavailability. As such, this strain will be particularly useful in experiments designed to address factors influencing nitrate utilization by phytoplankton.
Materials and Methods
Media and Growth Conditions
For routine laboratory growth of Synechocystis sp. PCC6803, BG-11 medium (Allen
1968; as described at www-cyanosite.bio.purdue.edu) was employed throughout, except that the
concentration of NaNO3 was reduced to yield a N:P ratio of 10. Experimental manipulation of
nitrate concentration was achieved by adding NaNO3 to nitrate-free BG-11 at concentrations
ranging from 1 to 1000 µM. To maintain a constant osmotic strength of the medium, equimolar
amounts of NaCl were added as appropriate to replace NaNO3. Additionally, the ferric 43
ammonium citrate stock was replaced with equimolar FeCl3, to avoid interference in those
experiments where exogenous ammonium was added. Kanamycin was added to 30 µg mL-1 to
select for the drug resistant marker in the nitrate bioreporter strain AND100. All cultures were bubbled with air and grown at 22 oC in constant light (50 µmol quanta m-2 s-1) provided by cool-
white fluorescent lamps. Growth of batch cultures was routinely monitored at daily intervals by
measuring light scattering at 750 nm (OD750).
Construction of the PnirA::luxAB promoter fusions
The functional components of the nirA promoter (PnirA) includes a consensus sequence
(GTAN8TAC) for binding of a CAP-type transcriptional regulator, NtcA, and a motif
(ATN11AT), constituting a binding site for a LysR family protein, NtcB (Fig. 1). It has been
shown by Northern Blotting that transcription of the nirA gene is up-regulated by NtcA in
ammonium depleted conditions, and NtcB is thought to serve as an enhancer of nirA
transcription in the presence of nitrate or nitrite (Aichi et al. 1997; Frias et al. 2000; Aichi et al.
2001).
The pILA recombinant plasmid vector described by Kunert et al. (2000) allows the fusion
of PstI and KpnI adapted promoter fragments upstream from the Vibrio harveyi luxAB genes
encoding bacterial luciferase (Figure 2). Following plasmid construction and retrieval of
plasmid clones from Escherichia coli DH5α, genetic transformation of Synechocystis sp.
PCC6803 yields the insertion of the promoter::luxAB fusion into the chromosome by homologous recombination. The availability of the complete Synechocystis sp. PCC 6803 genomic sequence (review, Kaneko and Tabata 1997; Nakamura et al. 1998) allows the rapid cloning of any promoter sequence following PCR amplification.
44
NtcB-binding motif NtcA-binding motif -10 element 5’-ctaaatgcgtaaactgcatatgccttcgctgagtgtaatttacgttacaaattttaacgaaacgggaaccctatattgatctctac-3’
Figure 1. Elements of the Synechocystis sp. PCC 6803 nirA promoter driving luxAB expression in bioreporter strain AND100. The 3’ end of the sequence corresponds to the 3’ end of the PCR amplicon cloned into plasmid pILA.
In order to confirm the in vitro results by an in vivo transcription assay, we inserted the
NtcA and NtcB responsive elements of the nirA promoter upstream of the luxAB genes in the
pILA plasmid (Figures 1 and 2). Specifically, 304bp and 94bp fragments corresponding to NtcB
and NtcA responsive elements respectively were amplified by PCR using the following primers
(the PstI and KpnI sites for the forward and bacPDard primers respectively are underlined):
5’- TGTAGGAAAACAACTGCAGAATGCTGC-3’ (NtcB, forward);
5’- AGGTACCGCATATGCAGTTTACGCA-3’ (NtcB, bacPDard);
5’- TGCTGCAGCCTTGGCTGAGTGTAATTTA – 3’ (NtcA, forward);
5’ – CAACGGTACCAGCCAGATAACAGTAGAGAT – 3’ (NtcB, bacPDard).
PCR was performed for 30 cycles of the following temperatures: 94 oC, 1 min; 55 oC, 2 min; 72
oC, 3 min. Following ligation of the KpnI-PstI digested PCR products into pILA, transformation
of Synechocystis sp. PCC6803 yielded strain AND100 following selection on kanamycin BG-11
plates. For the construstion of the bioreporter, a 380bp fragment including the entire nirA
promoter was amplified by PCR with the following primers (the KpnI site underlined):
5’-TGTAGGTACCCAACCTCAGAATGCTGC-3’ (forward), and
5’-CAACGGTACCAGCCAGATAACAGTAGAGAT-3’ (reverse), using the PCR and ligation conditions described above.
45
Figure 2. Promoter probe vector pILA developed by Kunert et al (2000). Fragments of the nirA promoter were inserted upstream from the Vibrio fischeri luxAB genes using PstI and KpnI restriction sites. Adapted from Kunert et al 2000.
Characterization of the AND100A and AND100B promoter fusions and the AND100 bioreporter
Nitrate-dependent luminescence of AND100 was characterized in modified BG-11 media
containing NaNO3 amendments ranging from 1-100 µM. Prior to assaying luminescence in
media or field samples, cells were prepared by first growing AND100 cultures to late
exponential phase (OD750nm ~ 1.0) in low nitrate BG-11. Cells were harvested by centrifugation
at 4,000 x g for 5 min, washed twice in nitrate-free BG-11 and resuspended to a final OD750nm of
0.1 in lake water or BG-11 of defined nitrate concentration. Luminescence of AND100 cultures
was measured with a Femtomaster FB14 luminometer (Zylux Corp., Maryville, TN) immediately
following the addition of 20 µL of methanol containing 27 mM n-decyl aldehyde, a substrate for
bacterial luciferase, to 2 mL of the sample. Whereas direct addition of n-decyl aldehyde to a
Synechococcus sp. PCC7942 bioreporter yielded transient luminescence, suggesting toxicity
(Porta et al. 2003), Synechocystis sp. PCC6803 exhibited a strong and stable luminescent 46
response under these conditions. Thus, the AND100 bioreporter can be assayed more quickly,
avoiding a long incubation in aldehyde vapors as is required for the Synechococcus sp.
constructs. Luminescence, normalized to OD750nm of the sample, was averaged from readings
observed from four replicates.
Water Collection From Lake Superior
Epilimnetic water (5 m depth) was collected from stations ON-2 (46o 58.00’ N, 89o 21.50’ W;
12 September 2002 and 20 May 2004) and HN-210 (47o 15.49’ N, 88o 07.99’ W; 30 July 2001),
both located in waters offshore from the Keweenaw Peninsula, using a trace metal clean
pumping system (Field and Sherrell 2003; Sterner et al. 2004). Water pumped from the
epilimnion was passed through a 0.45 µm capsule filter and collected in acid-cleaned polycarbonate bottles. Samples were either frozen (HN-210 and ON-2 from 2001 and 2002, respectively), or immediately tested with the bioreporter in the shipboard laboratory (ON-2 sample from 2004). All frozen samples were routinely thawed immediately prior to the bioreporter assay.
Monitoring Nitrate Depletion in Bioreporter Assays
Assessment of nitrate uptake by the AND100 bioreporter was achieved by measuring nitrate
depletion from water sampled at station ON-2 during the course of a bioreporter assay. Nitrate
concentrationwas monitored by using a probe fitted with a biochamber containing denitrifying
- bacteria defective in nitrous oxide reductase (NOx probe; Unisense, Aarhus Denmark). Nitrate
reduction by bacteria in the biochamber yielded nitrous oxide which was detected via a Clark-
type electrode coupled to a picoammeter (PA2000; Unisense). Electrode polarization was
performed according to the manufacturer’s instructions. The probe was calibrated to detect
micromolar nitrate by constructing a standard curve obtained following incremental spiking of 47
ON-2 water with 1, 2, 5 and 10 µM NaNO3. At several time points during a shipboard bioreporter assay, 10 mL aliquots were withdrawn and nitrate concentration measured using the probe.
Results
Nitrate-Dependent Activation of AND100 Bioluminescence
In cyanobacteria, the global nitrogen regulator NtcA is stricktly required for the expression of nitrate/nitrite assimilation genes in all investigated strains (Herrero, 2001). In contrast, the LysR family regulator, NtcB is involved in nitrogen control at different stringency levels. In Synechocystis PCC 6803, Northern blots with the nirA probe showed that NtcB activates transcription of the nirA gene in the presence of nitrate/nitrite, and it is required for
NtcA-dependent activation in low ammonium medium (Frias et al. 2000; Aichi et al. 2001). The results of the in vivo examination of nirA transcription with the employment of nirA promoter constructs described above are in agreement with the in vitro studies. Both NtcA and NtcB- responsive elements of the promoter (Figure 1) are required for the down-regulation of transcription in ammonium replete media (Figure 3, A) and the nitrate reposive activation of transcription (Figure 3, B). Therefore, we used the entire nirA promoter for the construction of the nitrate-responsive bioreporter (Figure 1).
Addition of the AND100 bioreporter to BG-11 media containing different concentrations of nitrate showed increased luminescence in response to added nitrate with clear differences resolved between 1-50 µM nitrate (Fig. 4). The time course for nitrate-dependent luminescence yielded a maximum after 4-7 h of incubation, followed by a decline. The transient nature of the luminescent response was likely due to ammonium-dependent NtcA nutritional repression 48
50
40 Col 13 Col 18 ) Col 23 -1
750 30
20 (RLU*OD Bioluminescence
10
A 0 100µM 1000µM 100 µM 1000 µM 100 µM1000 µM A
1000 Col 13
) Col 18
-1 Col 23 800 750
600
400 (RLU*OD Bioluminescence 200
0 B 1µM 100µM 1 µM 100 µM 1 µM 100 µM
Figure 3. Bioluminescence of Synechocystis PCC 6803 strains transformed with nirA promoter constructs. AND100, ANDA100 and ANDB100 contain constructs with NtcA and NtcB resposnive elements of the nirA promoter (ANDA100 and ANBD100 respectively) of full promoter (AND100). The strain AND100 was consequently used for the development of the bioreporter. The strains were incubated for 72 h in BG11 medium containing different ammonium concentrations (A), or for 7 h in BG11 with different nitrate levels (B). The numbers on X axis indicate ammonium (A) or nitrate (B) concnetrations. Luminescence was normalized against optical density (750 nm). Error bars represent standard deviations (n=4). 49
120
100
80
60
40
20
0
luminescence (% of maximum) 0 2 4 6 8 10 12 14 exposure time (h)
Figure 4. Bioluminescence of Synechocystis sp. reporter strain AND100. Late log phase cells grown in BG11 (modified as described in the text) were transferred at the initial time to BG11 with various concentrations of NaNO3 (z - [1µM], - [10 µM], S - [25 µM], { - [50 µM], - [100 µM]). Luminescence was normalized against optical density (750 nm). Data are presented as percent of maximal luminescence obtained in 100 µM NaNO3 (2419 +/-19 RLU×OD750 – 1). Error bars represent standard deviations (n=4).
resulting from the intracellular accumulation of ammonium following nitrate reduction (Aichi et al. 2001). Indeed, the addition of methionine sulfoximine (MSX), an inhibitor of ammonium assimilation, to AND100 incubated in 100 µM nitrate, abolished the decline phase seen at 8 h
(data not shown). Treatment with MSX resulted in constitutive derepression of nitrate/nitrite dependent nirA transcription as reported previously (Aichi et al. 2001).
Examining the bioreporter response after 6 h exposure, a dose-response curve revealed a threshold for nitrate-dependent luminescence in the range of 1 - 10 µM nitrate (Fig. 4). Dose- response curves were routinely constructed at the time points varying between 5 - 7 hours, depending on the kinetics of induction of luminescence during the course of the assay. Given that spring survey nitrate concentrations in the upper Great Lakes typically fall within the range 50 of 20 - 30 µM (U.S. EPA 2004), the response of our bioreporter is appropriate for assessing nitrate availability in these freshwater systems.
Factors influencing AND100 nitrate-dependent luminescence in BG-11 media.
Due to the dual control of PnirA by NtcA and NtcB, the output of the AND100 bioreporter is likely affected by the speciation of nitrogen. The NtcA protein yields transcriptional activation under nitrogen deficiency, but nutritional repression coincident with ammonium assimilation (Herrero et al. 2001). Reflecting this, induction of luminescence in
100µM nitrate was fully repressed by an equimolar addition of ammonium (Fig. 5). Addition of ammonium to a concentration one-tenth that of nitrate yielded transient repression (Fig. 5), reflecting the physiological preference for ammonium over nitrate as a source of nitrogen.
120
100
80
60
40
20
0 0123456789
luminescence (% of maximum) exposure time (h)
Figure 5. Effect of ammonium addition on nitrate induced bioluminescence in AND100. Late log phase cells grown in decreased N BG11 were transferred at the initial time to BG11 containing [100 µM] NaNO3. At the 5 hour time point, various amounts of NH4Cl were added to the samples ({ - final concentration of NH4Cl [100 µM], S - [10 µM], - [1µM], z- no NH4Cl added). Luminescence was normalized against optical density (750 nm). Data are presented as percent of maximal luminescence obtained when ammonium was not added to the sample (1390 ± 49 RLU× OD750 – 1). Error bars represent standard deviations (n=4).
140 51
120
100
80
60
40
20
0 012345678910
luminescence (% of maximum) luminescence (% of exposure time (h)
Figure 6. Effect of light intensity on nitrate induced bioluminescence in And100. Late log phase cells grown in decreased N BG11 were transferred at the initial time to BG11 containing [100 µM] NaNO3. z- 50 µmol quanta * m-2 s-1, { - 30 µmol quanta × m-2 s-1, T- 15 µmol quanta × m-2 s-1, r - Vµmol quanta * m-2 s-1. Data are presented as percent of maximal luminescence obtained at 50 µmol quanta × m-2 s-1 (2991± 499 RLU× OD750 – 1). Error bars represent standard deviations (n=4).
Transient repression in 10 µM ammonium was most likely due to uptake of ammonium, yielding decreased luminescence, followed by derepression of luminescence when ammonium became depleted from the medium by assimilation. The observed repression of PnirA-dependent gene expression at 10 µM ammonium was consistent with other reports demonstrating repression in
cyanobacteria at similar ammonium concentrations (Flores et al. 1980; Dortch, 1990).
In addition to photosynthetically-derived reducing power needed to reduce nitrate to
ammonium during assimilation, more recent studies have shown that NtcA-dependent activation
of nitrogen assimilatory genes requires α-ketoglutarate as a coinducer (Tanigawa et al. 2002;
Vasquez-Bermudez et al. 2003). Taking this into account, photosynthetic light reactions and
carbon fixation together likely influence the activation of transcription during nitrogen limitation.
Thus, we tested the induction of luminescence in 100 µM nitrate at several light intensities.
Nitrate-dependent transcription occurred only in the light, and increased with increasing light 52 intensity (Fig. 6). Such data support the observation that light and nitrate limitation in cyanobacteria and eukaryotic algae exhibit a synergistic relationship (Rhee and Gotham 1981;
Healey 1985). The light-dependent response exhibited by AND100 is potentially useful owing to the fact that light can limit phytoplankton growth in lakes such as Lake Superior during periods of both vernal holomixis (Nawelajko and Voltolina 1986) and summer stratification
(Nalewajko et al. 1981).
Induction of bioluminescence during nitrate assimilation.
As a result of the dual nitrate/nitrite regulation of the PnirA promoter, bioluminescence should be closely coupled temporally to the assimilation of nitrate in the medium. To test whether the onset of luminescence can be correlated with depletion of nitrate from the medium, a nitrate-specific biosensor electrode was employed to monitor nitrate depletion during the course of a bioreporter )
-1 20 600
18 750 16 500 14 12 400 10 8 300 6 4 200 2 nitrate consumed (µM) 0 100
01234567 luminescence (RLU*OD
exposure time (h)
Figure 7. Coincident induction of luminescence and nitrate uptake. Lake Superior water samples from pelagic station ON-2 were assayed with the AND100 bioreporter, and nitrate uptake measured together with bioluminescence. { - nitrate consumed (µM), z - bioluminescence (RLU/OD750). Error bars represent standard deviations (n=3). 53 )
-1 2000
750 1800 1600 1400 1200 1000 800 600 400 200 0 luminescence (RLU*OD 0 102030405060 - [NO3 ] µM
Figure 8. Measurement of nitrate in Lake Superior samples by AND100 luminescence. Bioluminescence of AND100 seeded into water samples from pelagic stations HN-210 and ON-2 are compared to luminescence values in BG-11 media of known nitrate concentration. z - AND100 luminescence in BG11 containing 1, 10, 20, 30, 40, 50 µM NaNO3, U- AND100 luminescence in unamended ON-2 water; S- AND100 luminescence following addition of 10 nM Fe and 2 mM phosphate; - AND100 luminescence in unamended HN-210 water. Error bars represent standard deviations (n=4).
assay with Lake Superior water collected from pelagic station ON-2. Indeed, nitrate consumption and the induction of luminescence followed the same kinetics (Fig. 7).
Use of the AND100 bioreporter to assess nitrate assimilation in field samples.
Lake Superior water collected from pelagic stations ON-2 and HN-210 was tested with the bioreporter to investigate whether the strain could be used to assess nitrate assimilation capacity.
A calibration curve yielded a linear response for nitrate concentrations ranging from 10 – 50 µM
(r2 = 0.966), and seeding lake water with the bioreporter yielded a luminescent response following 5 - 6 h of incubation (Fig. 8). Plotting the bioluminescence onto the calibration curve 54 ) -1
700 750 600 500 400 300 200 100 0 01234567
luminescence (RLU*OD exposure time (h)
Figure 9. Time course of AND100 luminescence in water sampled from pelagic station ON2. Curves represent the following conditions: z - no addition; S - addition of 2 mM P; {- addition of 10 nM Fe; - addition of both P and Fe. Error bars represent standard deviations (n=4).
provided an apparent nitrate concentration of 19 µM at station ON-2 and 25 µM at station HN-
210. Since the actual nitrate concentrations at ON-2 and HN-210 were 22.5 µM and 37 µM, respectively, we note that the bioreporter underestimated the true nitrate level, suggesting that nitrate drawdown by the bioreporter was impaired in these samples. By contrast, amendment of water sampled from ON-2 with 2 µM potassium phosphate and 10 nM ferric chloride resulted in an enhanced luminescent response yielding an apparent nitrate concentration of 23 µM, nearly identical to the chemically derived value (Fig. 8). 55
Examining further the influence of iron and phosphate on AND100 bioluminescence in
lake samples, the bioreporter was used to assay ON-2 water amended by iron and phosphate
individually, and in combination (Fig. 9). This demonstrated that bioluminescence over 6 h
exposure time was enhanced only when P and Fe were amended together, suggesting a co-
limitation of these nutrients as a factor constraining nitrate utilization.
Discussion
Utility of the bioreporter assay.
In this paper, we describe a novel cyanobacterial bioreporter capable of assessing the
nitrate assimilatory capacity of freshwater picoplankton. The data reported here indicate that the
AND100 bioreporter can be used to yield a signal of suitable sensitivity and reproducibility from
which bioavailable nitrate can be quantified. The strain yields nitrate/nitrite-responsive
induction of bioluminescence due to the action of the NtcA/B transcriptional activators. The
onset of luminescence and nitrate uptake is tightly coupled, thus the intensity of the luminescent
signal can be viewed as a measure of nitrate assimilation. Notably, the dynamic range of the
AND100 bioreporter is appropriate for measuring nitrate levels that typically occur in the Great
Lakes. Whereas we recognize that a bioreporter constructed in Synechocystis sp. PCC 6803
may not be fully representative of the diversity of photosynthetic picoplankton of the Great
Lakes, the AND100 strain can be viewed as a prototype in which detailed characterization can be
carried out prior to expanding the technology to more ecologically relevant phototrophs.
The bioreporter assay can be viewed as an alternative method to measure nitrogen uptake
in aquatic systems. Traditional techniques typically employ the use of stable isotopes (15N) to calculate flux of nitrogenous compounds (Dugdale and Wilkerson 1986). Such techniques depend upon measuring the uptake and incorporation of 15N by the biota present in the water 56
sample. Since the method is both sensitive and dependent on the natural biological activity
resident in the water sample, stable isotope labeling can provide useful reproducible measures of nitrogen uptake (Dugdale and Wilkerson 1986). Disadvantages include the modest expense of
15N substrates and the high cost of mass spectrometry, contamination of natural abundance 15N,
and the time required to analyze the samples (often weeks or months). Additionally, separating
heterotrophic vs. algal uptake with 15N is possible but may be difficult under oligotrophic
conditions (J. Finlay, personal communication). The AND100 bioreporter, while not an
ecologically relevant strain, provides measures of nitrate utilization that are rapid, inexpensive,
reproducible, and are likely indicative of nitrogen assimilation by phototrophs.
Application of the AND100 reporter to Lake Superior.
Over the past 100 years, the nitrate concentration in Lake Superior has increased 6-fold.
Whereas atmospheric deposition of nitrogen is thought to be the main source of the nitrate that
has accumulated in the lake (Bennett 1986), there are likely many factors contributing to such a
large change in a major biologically active chemical element. Nitrate may accumulate in Lake
Superior as a result of low biotic demand. Alternatively, one or more environmental factors may
constrain the ability of phytoplankton to use nitrate in the lake. Owing to the complex seasonal
and synergistic relationships between light and nutrient availability in the Great Lakes
(Nalewajko et al. 1981; Nawelajko and Voltolina 1986; Millard et al. 1996; Fahnenstiel et al.
2000), the AND100 bioreporter exhibits performance characteristics under varying light regimes
and nutrient status that are suitable to assess the influence of these factors on nitrate
consumption. The reporter strain thus provides a proxy for the physiological responses of the
endogenous cyanobacteria, whose nitrogen assimilatory functions are likely similarly regulated
by light levels, nitrogen speciation and bioavailability of both phosphate and iron. Indeed, the 57
pilot experiments reported here provide evidence that phosphate and iron together constrain
nitrate utilization in Lake Superior, because the AND100 strain underestimated chemically-
derived nitrate levels unless supplemented with both of these nutrients (Fig. 7), These data are
supported by a recent study showing that low availability of iron constrains even modest
increases in growth response of endemic phytoplankton following amendment of water collected
from Lake Superior with phosphate (Sterner et al. 2004). An extensive temporal and spatial
survey of Lake Superior combining both traditional bottle amendment and bioreporter assays
will be important in sorting out the individual contributions of light and nutrient limitation to the
events leading to the long-term nitrifying of Lake Superior.
Comparison to other cyanobacterial N bioreporters.
The properties of the AND100 strain differ in many respects from two cyanobacterial
nitrogen bioreporters previously described (Mbeunki et al. 2002; Gillor et al. 2003). These
bioreporters are luxAB fusions employing the Synechocystis sp. PCC6803 nblA (Mbeunkui et al.
2002) and Synechococcus sp. PCC 7942 glnA promoters (Gillor et al. 2003), controlling the
genes encoding a phycobilisome degradation regulator and glutamine synthetase, respectively.
Whereas the dynamic ranges of these strains were similar to AND100, the luminescent response
was induced upon nitrogen deficiency, not during nitrogen utilization as described in this paper.
Secondly, the responses of the Synechococcus sp. PglnA and Synechocystis sp. PnblA bioreporters were considerably slower, yielding dose-dependent luminescence on the order of 15
– 25 h (Mbeunkui et al. 2002; Gillor et al. 2003). Additionally, the glnA strain yielded dose- dependent responses to a wide variety of N species ranging from nitrate, ammonium, urea and glutamine (Gillor et al. 2003), and nblA expression was responsive to nitrate and ammonium
(Mbeunkui et al. 2002). Whereas such broader spectrum responses may be very useful 58
properties for the measurement of total nitrogen bioavailability, the nitrate/nitrite specificity of
the AND100 bioreporter provides a means for determining the bioavailability of specific
nitrogen species, especially when used in concert with the PglnA reporter. Indeed, the PglnA
reporter has been used to document low total nitrogen bioavailability along a west-to-east
transect in Lake Erie (Wilhelm et al. 2003). In this context, the AND100 bioreporter likely could
provide further insights by focusing on the potential for nitrate utilization in the Great Lakes.
The positive induction of the AND100 luminescent response will allow one to measure the onset of nitrate utilization as light levels are manipulated and nutrients are amended to Lake Superior samples. By comparison, the properties of the GSL nitrogen bioreporter, whose
bioluminescence is under repression by elevated nitrogen, would be less suitable for such an
experiment. Overall, the AND100 strain affords a direct method for determining the role of both
chemical and physical factors in regulating nitrate uptake by the endemic phytoplankton.
Concluding remarks – future prospects.
Another potential application for the AND100 strain has been suggested based on recent
studies examining the use of cyanobacteria in bioremediation efforts aimed at reducing nitrate in
drinking water (Hu et al. 2000). Indeed, Synechococcus sp. PCC 7942 has been proposed as a
remediatory strain capable of reducing nitrate levels in contaminated reservoirs. Notably,
bioassay experiments demonstrated enhanced depletion of nitrate following amendment with
both phosphate and a trace metal mixture (Hu et al. 2000). A bioremediation strategy modified
by employing strain AND100 would yield a nitrate-dependent real-time bioluminescent signal,
providing a means by which the water treatment system could be optimized to maximize nitrate
consumption. 59
Lastly, current studies are focusing on the development of more sophisticated bioreporter
strains capable of yielding multiple signals. For example, the availability of iron and phosphorus
regulated promoters (Durham et al 2002; Gillor et al. 2002), along with reporter genes expressing
luciferase and GFP derivatives, will allow the construction of a multichannel sensor strain reporting on bioavailable nitrogen, phosphorus and iron via spectrally resolvable outputs. Once
such strains are characterized, the long-term goal is to improve gene transfer techniques so that
this technology can be mobilized into more ecologically relevant marine and freshwater
cyanobacterial strains.
60
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65
CHAPTER 3. NITRATE UTILIZATION IN LAKE SUPERIOR IS IMPAIRED BY LOW
NUTRIENT AVAILABILITY (P, Fe) AND SEASONAL LIGHT LIMITATION
Introduction
Over the past 100 years, nitrate levels in Lake Superior have increased six-fold and now range between 20-30 µmol L-1 throughout the lake (Fig. 3, Chapter 1); Weiler 1978; Bennett
1986; McManus et al. 2003). The reasons behind the accumulation of nitrate in Lake Superior
are unknown. While it is clear that atmospheric deposition of reactive nitrogen has increased in
some regions at least 5- to 10-fold over preindustrial conditions (Galloway et al. 2003), patterns
in regional nitrate ion wet deposition are hard to reconcile with the observed century-long
accumulation of nitrate in Lake Superior. Lake Superior is generally upwind of most sources of
nitrogen (N) polluted air, and it’s long hydraulic residence time and N turnover time indicate
great inertia in the biogeochemical system.
The inability of phytoplankton to utilize this bulk source of N has led us to examine the
factors that constrain nitrate utilization in the lake. Phosphorus (P) is principally involved in
nutrient limitation in the lake (Sterner et al. 2004), but additional chemical and physical factors
may further constrain the utilization of nitrate in Lake Superior. Iron (Fe) is a redox element
essential for both photosynthetic energy transduction (Raven et al. 1999) and nitrate assimilation
(Raven 1988). Dissolved Fe, however, is low throughout much of Lake Superior with open lake
concentrations rarely exceeding 6 nmol kg-1 (Nriagu et al. 1996; Sterner et al. 2004; McKay et al.
2005). Thus, low availability of P and Fe may interact to limit nitrate drawdown. Nutrient
bioassays have confirmed the P-limited character of Lake Superior and have further
demonstrated that P-stimulated growth is constrained by low Fe availability (Sterner et al. 2004). 66
Water column irradiance is also expected to impact the ability of phytoplankton to use
nitrate. Nitrate assimilation is light dependent in cyanobacteria and eukaryotic algae (Rhee and
Gotham 1981; Healey 1985; Hu et al. 2000). In addition to photosynthetically-derived reducing
power needed to reduce nitrate to ammonium during assimilation, recent studies have
demonstrated that NtcA-dependent activation of N assimilatory genes requires a pool of fixed
carbon (α-ketoglutarate) as a coinducer (Tanigawa et al. 2002; Vasquez-Bermudez et al. 2003).
Taking this into account, photosynthetic light reactions and carbon fixation together likely
influence the activation of transcription during N assimilation.
Lake Superior is the deepest of the Laurentian Great Lakes and has been characterized as a light-limited environment during the period of prolonged mixing that precedes thermal stratification (Nalewajko et al. 1981; Nalewajko and Voltolina 1986; Guildford et al. 2000).
Whether phytoplankton are impaired in their ability to assimilate nitrate during this time has not been previously addressed. Determining the impact of nutrients and light on nitrate depletion from conventional bioassays is not straightforward. Nitrate drawdown is often negligible, even in bottles amended with P and Fe, as a result of low ambient incubation temperatures in concert with low phytoplankton biomass in Lake Superior (< 1 µg chlorophyll L-1). Amendment studies
can also introduce artifacts that may confound interpretation of results. For example, bottle
enrichment assays interrupt mixing and light gradients and increases in phytoplankton biomass
may yield altered water chemistry over the long duration (24 h or more) of the assay (Carpenter
1996).
We have recently developed a cyanobacterial bioreporter capable of assessing nitrate
assimilatory capacity in freshwaters (Ivanikova et al. 2005). Specifically, the assay employs a
genetically engineered cyanobacterium, Synechocystis sp. PCC6803, which bears a 67
transcriptional fusion between the promoter of the gene encoding nitrite reductase (PnirA) and
the Vibrio sp. bacterial luciferase genes, luxAB. This construct, named AND100, yields
bioluminescence during nitrate utilization, and the luminescence yield is an indirect
measurement of the rate of nitrate assimilation (Ivanikova et al. 2005). Since picocyanobacteria
represent at least 20% of the phytoplankton productivity in Lake Superior (Fahnenstiel et al.
1986) and contribute from 22-50% of the total chlorophyll (McKay et al. 2005), the AND100 nitrate reporter strain can be viewed as a proxy for this size class of phytoplankton. In this study, we analyze the performance of the cyanobacterial bioreporter in Lake Superior water amended with nutrients and under light regimes that mimic seasonal mixing depths to assess the importance of nutrient limitation and irradiance as factors influencing nitrate utilization in this ecosystem.
Materials and Methods
Media and growth conditions
For construction of the nitrate bioreporter strain AND100, wild-type Synechocystis sp.
PCC6803 was transformed with the modified pILA plasmid carrying the PnirA::luxAB promoter fusion, as previously described (Ivanikova et al. 2005). For routine growth of strain AND100,
BG-11 medium (Allen 1968; as described at www-cyanosite.bio.purdue.edu) with nitrate concentration reduced to 2.3 mmol L-1 (low nitrate BG-11; Ivanikova et al. 2005) was employed
throughout. Kanamycin was added to 30 µg mL-1 to select for the drug resistant marker in
AND100. All cultures were bubbled with air and grown at 25 °C in constant light (50 µmol quanta m-2 s-1) provided by cool-white fluorescent lamps. Growth of batch cultures was
routinely monitored at daily intervals by measuring light scattering at 750 nm (OD750).
68
Sample collection
Samples were collected from 13 hydrographic stations during three research cruises on
Lake Superior, North America, during 2004 on the R/V Blue Heron (Table 1). The surveys
included periods of vernal holomixis (May 2004) as well as late summer stratification
(September 2004). In addition, station CD-1 was revisited in late October 2004 prior to autumnal mixing. At each station, sampling was preceded by a conductivity-temperature-depth cast (Table
1).
From most stations, water samples were collected from discrete depths using a metal- clean in situ pumping system (Field and Sherrell 2003; Sterner et al. 2004). Water from stations
Sterner B and Portage Deep, as well as from the south entry of the Keweenaw Waterway, was sampled using an acid-clean Teflon-coated Go-Flo bottle. Water from all stations was passed through a 0.45 µm cartridge filter and collected in acid-cleaned polycarbonate bottles prior to freezing. Frozen samples were routinely thawed immediately prior to the bioreporter assay.
Nitrate in lake water samples was measured using an Alpkem autoanalyzer (precision
0.72% at 10 µmol L-1) whereas soluble reactive phosphorus (SRP) was measured using a
freshwater version (Anagnostou 2005) of the magnesium hydroxide co-precipitation (MAGIC)
method (Karl and Tien 1992). Application of this method carried a detection limit of 0.2 nmol L-
1 with precision of ca. 12% and 5% at the 1 nmol L-1 and 3 nmol L-1 SRP levels, respectively.
Dissolved Fe was measured by Zeeman-corrected graphite furnace atomic absorption
spectrophotometery (Model 4110; PerkinElmer) as described elsewhere (Porta et al. 2003). Total
chl was measured by fluorometry after Welschmeyer (1994).
69
Nitrate assimilation in Lake Superior water: nutrient effects
Bioreporter cells were prepared by first growing AND100 cultures to late exponential
phase (OD750nm ~ 1) in low nitrate BG-11 medium. Cells were harvested by centrifugation at
4,000 × g for 15 min, washed twice in nitrate-, P- and Fe-free BG-11 and resuspended to a final
OD750nm = 0.1 in lake water or BG-11 of defined nitrate concentration. Samples were then
incubated at 25 °C with continuous gyrotary shaking (100 rpm). For most assays, irradiance was
maintained at 50 µmol quanta m-2 s-1, a light flux shown to yield maximum rates of nitrate
assimilation using the cyanobacterial bioreporter (Ivanikova et al. 2005). Luminescence of
AND100 cultures was measured with a Femtomaster model FB14 luminometer (Zylux Corp.)
immediately following the addition of 20 µL of methanol containing 27 mmol L-1 n-decyl
aldehyde substrate (Sigma Chemical Co.) to 2 mL of the sample. Luminescence, normalized to
OD750nm of the sample, was averaged from triplicate samples. For nutrient amendment
experiments, FeCl3, K2HPO4 and Na2EDTA were added to the water samples prior to assaying to
achieve final concentrations of 10 nmol kg-1, 8 µmol L-1 and 15 nmol L-1, respectively.
Bioreporter response in each assay was normalized to the maximum luminescence value
obtained after 7 h incubation. Data were tested using two-way ANOVA using log-transformed
values to stabilize the variance. Effect sizes (sensu Sterner et al. 2004) were calculated for each experimental run. “Plus” effects are the difference in measured bioreporter activity between treatments with nutrients added singly compared to controls with no amendments. “Minus” effects are the difference in bioreporter activity between treatments with all nutrients added compared to treatments where all nutrients but the one of interest were added. Minus effects measure the effect of a nutrient treatment in the presence of other amended nutrients.
70
Nitrate assimilation in Lake Superior water: light flux
In experiments where the effect of light on nitrate assimilation by the bioreporter was analyzed, different light fluence rates were achieved by applying one or more layers of 3 mm
black mesh as a neutral density filter. The mean water column irradiance (I) of the mixed layer in
-KT -1 Lake Superior was calculated using the formula I = [E0 (1-e )] [KT] (Riley 1957), where E0 is the mean solar flux at the surface of the lake integrated over 24 hours, K is the vertical light extinction coefficient and T is the depth of mixing. The term E0 at Lake Superior stations CD1 on
18 May and 14 September, 2004 and WM on 19 May and 15 September, 2004 was calculated
assuming a cloud-free atmosphere (Fee et al. 1990; as described at
http://sciborg.uwaterloo.ca/research/uwaeg/). Light extinction coefficients for various sectors
of Lake Superior were taken from Schertzer et al. (1978).
Monitoring nitrate depletion in bioreporter assays
Nitrate depletion from water samples during the course of bioreporter assays was
monitored using a probe fitted with a biochamber containing denitrifying bacteria lacking
- detectable nitrous oxide reductase activity (NOx biosensor; Unisense A/S) as described
previously (Ivanikova et al. 2005). The probe was calibrated to detect micromolar
concentrations of nitrate by constructing a standard curve obtained following incremental spiking
-1 of water collected from Sta. CD-1 (5 m, May 2004) with 1, 2, 5 and 10 µmol L of NaNO3. Ten- mL aliquots withdrawn before and after the bioreporter assay were subsequently tested with the
- NOx biosensor. The rate of nitrate depletion was normalized to cell counts obtained by
microscopy.
71
Measurement of alkaline phosphatase activity (APase; E.C. 3.1.3.1.)
Unfiltered water was dispersed to triplicate methacrylate cuvettes (2.5 mL) and incubated
with 40 µmol L-1 4-methyl umbelliferyl phosphate (Sigma) in darkness at ambient ship
laboratory temperature (ca. 20 °C). Sodium bicarbonate (4 mmol L-1) was substituted for Lake
Superior water in substrate controls whereas quench standards were prepared using unfiltered
lake water and 1 µmol L-1 of 4-methylumbelliferone (Sinsabaugh et al. 1997). Enzyme activities
were calculated using a reference standard containing 1 µmol L-1 of 4-methylumbelliferone.
APase-catalyzed fluorescence was determined using a TD-700 laboratory fluorometer (Turner
Designs) equipped with a near-UV lamp and a methylumbelliferyl filter set (ex: 300-400 nm;
em: 410-610 nm). Enzyme activity was normalized to a chl-specific value.
Results
Physico-chemical characteristics of Lake Superior
During May, the water column at most open lake stations was isothermal (2-4 °C) whereas modest thermal structure was evident at several nearshore (< 3 km from shore) sites
(Table 1). Chl a biomass did not exceed 2 µg L-1 at nearshore sites and was generally < 1 µg L-1
at pelagic stations (Table 1). Picophytoplankton (0.2 – 2 µm) comprised the dominant size-
fraction in May accounting for 24-61% (median: 48%) of total chl a.
During September, thermal stratification was evident at all stations with surface
temperatures ranging between 10.3 – 12.7 °C (Table 1). Chl a was < 1.5 µg L-1. As in May, the
picophytoplankton size fraction was dominant. By contrast, 2 stations sampled in the Keweenaw
Waterway, a system that bisects the Keweenaw Peninsula, showed elevated chl a biomass (> 6
µg L-1) in which microphytoplankton (> 20 µm) and nanophytoplankton (2 – 20 µm) size- fractions were dominant. 72
Lakewide, average surface water nitrate levels were consistently > 22 µmol L-1 and were
ca. 10% higher in May (mean: 25.81 µmol L-1) compared to September (mean: 23.08 µmol L-1)
(unpaired two-tailed t-test, p < 0.001). Compared to Lake Superior, nitrate levels within the
Keweenaw Waterway were markedly reduced, ranging between 10-11 µmol L-1 during sampling
in September. Vertical profiles at two stations (WM and CD-1) during September showed
evidence for modest surface depletion of nitrate (Table 1) as has been demonstrated previously
for Lake Superior (McManus et al. 2003).
Table 1. Physio-chemical characteristics of Lake Superior hydrographic stations during 2004. Nitrate concentration was determined using an Alpkem autoanalyzer and using the cyanobacterial bioreporter. n.d., not determined. - Date zm Depth T Chl a [NO3 ] Bioreporter -1 -1 - -1 Station Station Coordinates (m) (m) (°C) (µg L ) (µmol L ) [NO3 ] (µmol L ) WM 47.33° N, 89.80° W 5/18 181 5 2.4 0.82 26.16 21.7 ± 1.2 9/15 5 12.7 0.91 22.30 18.41 ± 1.1 9/15 30 7.3 1.78 24.33 23.48 ± 5.3 9/15 100 3.9 n.d. 25.01 26.72 ±8.5 CD-1 47.30° N, 91.67° W 5/18 249 5 2.7 0.86 26.97 24.13 ± 1.8 9/14 5 12.0 1.49 22.05 20.77 ± 2.7 9/14 15 11.4 1.16 21.83 22.34 ± 3.7 9/14 50 5.3 0.51 24.80 27.84 ± 3.6 10/21 15 7.3 0.08 n.d. n.d. 10/21 30 6.5 0.40 n.d. n.d. 10/21 50 5.3 0.23 n.d. n.d. Sterner B 46.81° N, 92.13° W 5/20 28 5 5.5 1.60 24.72 26.37 ± 0.9 9/14 5 12.8 1.38 24.50 22.41 ± 0.5 EH-001 47.56° N, 88.39° W 5/19 98 5 2.6 0.88 27.09 19.91 ± 4.3 EH-009 47.57° N, 88.21° W 5/19 246 5 2.4 0.86 25.61 20.52 ± 1.5 ON-1 46.91° N, 89.29° W 5/20 17 5 7.0 1.82 24.95 24.31 ± 2.4 ON-2 46.97° N, 89.36° W 5/20 71 5 3.8 1.37 26.55 24.36 ± 2.4 HN-010 47.26° N, 88.56° W 5/19 12 5 7.0 1.76 24.14 18.72 ± 1.5 HN-210 47.41° N, 88.74° W 5/19 162 5 2.6 0.93 26.16 20.74 ± 1.5 Bingman 47.01° N, 88.34° W 9/16 59 5 10.3 0.60 23.37 21.03 ± 1.6 McKay South 46.95° N, 88.39° W 9/16 64 5 10.7 0.89 23.17 20.14 ± 4.4 PD 46.99° N, 88.44° W 9/16 n.d. 5 n.d. 6.16 10.13 14.24 ± 0.9 Portage Deep 47.06° N, 88.50° W 9/16 11 5 18.0 6.41 11.15 14.56 ± 1.5 73
WM, Western Mid-lake; CD, Castle Danger; EH, Eagle Harbor; ON, Ontonagon; HN, Hancock
North; PD, Keweenaw Waterway; zm, maximum depth
Table 2. Soluble reactive phosphorus (SRP) and alkaline phosphatase (APase) activities measured in Lake Superior during 2004. Units of APase are given as nmol methylumbelliferyl- phosphate hydrolyzed µg chl-1 h-1. n.d., not determined Station Date Depth (m) APase SRP1 (nmol µg chl-1 h-1) (nmol L-1) CD-1 05/18/04 5 0 n.d. 09/14/04 5 42.12 ± 6.8 3.5 ± 0.9 09/14/04 15 52.70 ± 2.0 5.0 ± 1.9 WM 05/18/04 5 0 n.d. 09/15/04 5 18.94 ± 2.2 1.0 ± 0.2 09/15/04 30 22.16 ± 0.8 1.7 ± 0.4 McKay South 09/16/04 5 22.69 ± 1.0 1.2 ± 0.2 Bingman 09/16/04 5 25.94 ± 3.6 1.4 ± 0.5 1 Taken from Anagnostou (2005)
In contrast to elevated levels of nitrate, SRP was severely depleted with a median surface water
concentration of 1.3 nmol L-1 during sampling in September (Table 2). Consistent with this,
APase activity was high during September with rates characteristic of a severely P-deficient
algal community (sensu Healey and Hendzel 1980) as has been demonstrated previously for
Lake Superior during the stratified period (Rose and Axler 1998; Guildford et al. 2000; Sterner et
al. 2004). By contrast, negligible APase activity was observed in May (Table 2), consistent with
previous reports showing low-to-negligible APase activity in the lake during the period of vernal
mixing (Rose and Axler 1998; Sterner et al. 2004). Although SRP was not determined for
stations CD-1 and WM in May, average SRP measured elsewhere in the lake at this time was ca.
100 nmol L-1 (unpublished). 74
Dissolved Fe displayed the highest variability of the three nutrients measured, ranging in
May from 0.5 nmol kg-1 at station EH-001 to 62 nmol kg-1 at station ON-1 (C. Hassler, M.R.
Twiss and S. Havens, unpublished data). Although both of these stations are considered
nearshore, they differ markedly in terms of their bathymetry and the extent to which they are
impacted by coastal processes. In particular, station ON-1 is impacted by the Ontonagon River
that serves as a major source of suspended solids delivered to the lake, the transport of which is
sometimes evident as a large plume visible for several kilometers from shore (Churchill et al.
2003).
Nitrate assimilation in Lake Superior water: nutrient effects
The AND100 Synechocystis sp. PCC 6803 nitrate reporter strain was seeded into filtered
water from each station and luminescence was measured following amendment of samples with
P and Fe, both individually and in combination. Since light emission from the AND100 reporter strain correlates to the rate of nitrate assimilation (Ivanikova et al. 2005), the degree to which nutrient addition influences nitrate utilization can be directly assessed.
The AND100 bioreporter frequently underestimated the nitrate concentration in Lake
Superior samples (Table 1). This was most apparent with surface water (5 m) samples where, with the exception of a single station (Sterner B: May 2004), the bioreporter underestimated the nitrate concentration by 3-27% (median: 13%) (paired two-tailed t-test, p < 0.0001). This result
was not unexpected, however, because lake water chemistry regularly yields conditions
preventing maximum rates of nitrate uptake.
There was but little seasonal variation in the bioreporter response at open lake station
WM (Fig. 1). We observed a significant main effect of P in all assays and the bioreporter 75
yielded maximal response in the presence of both added P and Fe. This pattern of response
suggests a P-Fe co-limitation consistent with previous bioassay results (Sterner et al. 2004).
Station CD-1, although only 5 km from shore, is situated along a deep trench off the
Minnesota shoreline and possesses many features (bathymetry, chl biomass) of an open lake
station. There was a nearly universal response to added P at this site (Fig. 2), with only the
surface water sample assayed in September lacking significance of the main effect of P. Fe
again was a secondarily important resource, with several significant P × Fe interaction terms and
Figure 1. Bioreporter response to water sampled from open lake station WM. Nutrient amendments were 10 nmol kg-1 Fe and 8 µmol L-1 P where indicated. In all experiments, bioreporter luminescence was normalized to the maximum value obtained for the assay after 7 h. Statistical significance of the main effect of P, the main effect of Fe, or their interaction (P × Fe) is indicated (*: p<0.05; **p<0.01). one significant Fe main effect (Fig. 2). To a first approximation, the responses at CD-1 (Fig. 2)
and WM (Fig. 1) were similar. 76
The nitrate bioreporter elicited no obvious pattern related to distance from shore in samples collected during May (Fig. 3, A-C). Water from nearshore stations HN-010 (Fig. 3A),
ON-1 (Fig. 3B) and EH-001 (Fig. 3C) each revealed significant P effects and different forms of
Fe effects (Fig. 3A-C). The effect of nutrient amendment was less pronounced at offshore stations ON-2 (Fig. 3B) and EH-009 (Fig. 3C). Both HN and ON sites had significant responses to P alone.
Figure 2. Bioreporter luminescence in water sampled from station CD-1. Nutrient amendments were 10 nmol kg-1 Fe and 8 µmol L-1 P where indicated. Significance reported as in Fig. 2 (no factors were significant in September, 5 m).
77
In September, we compared the effect of nutrient addition between a site located in
Portage Lake (Portage “Deep”), part of the Keweenaw Waterway and station Bingman located in
Keweenaw Bay. Station Bingman revealed a positive main effect of P (Fig. 4). By contrast,
amending water sampled from station Portage Deep demonstrated that nitrate assimilation was
not constrained by nutrient deficit, since no increase in luminescence could be seen following
addition of P or Fe (Fig. 4). Supporting this observation, the nitrate bioreporter did not
underestimate the concentration of nitrate measured at this station (and nearby station Keweenaw
Waterway, located near the south entry to the waterway) using conventional chemical methods
(Table 1). Further, that nitrate measured at these stations was less that half the concentration measured in the lake proper is suggestive of nitrate utilization at these sites compared to sites in the lake.
To gain an overall indication of the strength of P and Fe in stimulating nitrate uptake, we calculated mean plus and minus effect sizes over all experimental runs (Fig. 5). Effect sizes for P were larger than Fe effect sizes. Further, Fe had a clear study-wide statistical significance in the presence of supplemented P. Its effect in the absence of supplemented P was equivocal in this particular test.
Nitrate assimilation in Lake Superior water: light flux
We calculated the average mixing depth irradiance over 24 h during late May at stations
CD-1 and WM, and compared bioreporter luminescence in water samples at the spring irradiance level with optimal light intensities required for nitrate utilization. The 24 h integrated irradiance calculated for station CD-1 (10 µmol quanta m-2 s-1) was suboptimal for maximum bioreporter
luminescence, indicating that 78
79
Figure 3. Bioreporter response to water sampled at nearshore-offshore transects (HN, EH and ON). Nutrients were added to 10 nmol kg-1 Fe and 8 µmol L-1 P where indicated. Significance reported as in Fig. 2.
nitrate assimilation was constrained by low light during the period of vernal mixing (Fig. 6). By
contrast, the light flux calculated for vernal mixing at station WM (25 µmol quanta m-2 s-1) was sufficient to yield maximum nitrate assimilation rates. Photon flux rates calculated for late summer at both stations (> 100 µmol quanta m-2 s-1) yielded saturating light conditions for nitrate
- utilization (Fig. 6). As determined by the NOx biosensor, the nitrate assimilation rates at 10 vs.
-2 -1 - 6 -1 -1 - 6 -1 -1 50 µmol quanta m s were 1.9 µmol NO3 10 cell h and 4.6 µmol NO3 10 cell h , respectively. The rate at 10 µmol quanta m-2 s-1, which was 42% of the rate at 50 µmol quanta
m-2 s-1, closely matched the bioluminescence of the lower light treatment relative to that measured at higher light (39%, Fig. 6) and further affirmed the use of cellular bioluminescence by strain AND100 as a measure of the rate of nitrate assimilation. Thus, the low light field encountered during spring can limit the capacity of the bioreporter to assimilate nitrate.
Discussion
We hypothesized that nitrate utilization by the endemic phytoplankton would be constrained primarily by deep mixing, and hence light limitation, in May and by nutrient (P and
Fe) deficit in September. The effect of light on nitrate utilization was demonstrated using experimental conditions that mimicked mean mixed layer irradiances for spring and summer at two locations. We previously demonstrated a light flux of 50 µmol quanta m-2 s-1 to yield
maximum rates of nitrate assimilation using the cyanobacterial bioreporter AND100 (Ivanikova
et al. 2005). As demonstrated in the present study, the threshold below which nitrate
80
Figure 4. A comparison of bioreporter response between water sampled in the Keewenaw Waterway and the open waters of Keewenaw Bay (Bingman). Nutrients were added to 10 nmol kg-1 Fe and 8 µmol L-1 P where indicated. Significance reported as in Fig. 2.
assimilation was found to be impaired was between 10 - 25 µmol quanta m-2 s-1. That is, a mean
mixed layer irradiance of 25 µmol quanta m-2 s-1 as calculated for station WM in May was found
to be saturating with respect to nitrate utilization whereas 10 µmol quanta m-2 s-1, the mean mixed layer irradiance calculated for station CD-1, resulted in an impaired ability to use nitrate.
The effect of light, however, was likely greater than that described here, as the photon fluence rates adopted for this study assumed no light attenuation by cloud cover. Thus, the light intensities represent idealized maximum values encountered by phytoplankton, yet spring
81
Figure 5. Meta-analysis of effect sizes in all experimental runs (Mean ± 95% CI). P amendments stimulated nitrate utilization both in the absence (+P) and in the presence (-P) of added Fe. Fe stimulated nitrate utilization in the presence of amended P (-Fe effect). Effects of Fe in the absence of supplemented P (+Fe) were not statistically significant, but were close to the conventional 0.05 level. P had a larger effect on nitrate utilization than did Fe.
irradiances would routinely be lower, yielding lower nitrate assimilation rates. Furthermore, the interactions of light and temperatures below 15 ºC could not be accurately assessed by the
Synechocystis sp. PCC6803 bioreporter, whose metabolism and growth is impaired at the low
(ca. 4 ºC) temperatures encountered during spring in Lake Superior (cf. Fahnenstiel et al. 2000). 82
Figure 6. Effect of light treatment on bioreporter response. Water samples collected during May, 2004 from stations CD-1 and WM were seeded with the nitrate bioreporter and luminescence was measured following 7 h incubation at the calculated light fluxes representing integrated spring mixing and summer stratification.
Overall, these data lend agreement with other studies suggesting that seasonally, light exerts a measurable role in constraining biological production in Lake Superior (Nalewajko and
Voltolina 1986; Guildford et al. 2000).
Inconsistent with our hypothesis was the observed positive effect of nutrient amendment on nitrate utilization by the cyanobacterial bioreporter in May. The results from several studies, including our own, suggest that phytoplankton exhibit negligible- to low P deficiency during 83 vernal mixing in Lake Superior (Halfon 1984; Nalewajko and Voltolina 1986; Rose and Axler,
1997; Sterner et al. 2004). This evidence comes from several parameters including nutrient amendment bioassay, assay of community alkaline phosphatase activity and seston molar C:P stoichiometry. Likewise, recent evidence suggests a Fe-replete environment exists for the phytoplankton community during vernal mixing in the lake (McKay et al. 2005). Using a Fe- responsive cyanobacterial bioreporter in concert with an immunochemical approach specific for diatoms, we demonstrated Fe sufficient conditions existing at nearshore and most open lake sites sampled during May 2001 (McKay et al. 2005).
Despite the expectations of P- and Fe-sufficient conditions existing in May, nitrate utilization by the bioreporter was stimulated at all sites following addition of P. At five of these sites, addition of Fe further enhanced the P-stimulated response. Although we previously demonstrated algal growth response to P and Fe when added to a sample collected from the isothermal water column of open lake station EM in June 2000, the response was not totally unexpected given that both SRP (23 nmol L-1) and dissolved Fe (3.4 nmol L-1) were low at this location (Sterner et al. 2004). In the present study, however, lakewide SRP during May was ca.
100 nmol L-1 whereas dissolved Fe was also elevated, in excess of 50 nmol L-1 at several nearshore stations (HN-010, ON-1). Despite this, the nitrate bioreporter consistently responded to added P, and Fe enhanced the P-stimulated response of the nitrate bioreporter at five of the eight sites, including each of the nearshore sites. With respect to Fe, this specific result indicates that Fe bioavailability does not always and reliably relate to the concentration of dissolved Fe, perhaps due to differences in the type (Hutchins et al. 1999) and the refractory nature (Maranger and Pullin 2003) of organic Fe-complexing ligands. 84
Additional insight into the effects of added nutrients on nitrate utilization is provided by
Hu et al. (2000) who investigated the use of Synechococcus PCC7942 for the treatment of
nitrate-contaminated groundwater. When Synechococcus was incubated with groundwater
containing 1.53 mmol L-1 nitrate, depletion of nitrate from the groundwater was negligible when only ambient P (160 nmol L-1) was included in the assay. Upon further amendment with P,
however, depletion of nitrate from the groundwater proceeded at increasing rates with increasing added P (Hu et al. 2000). From this, it was determined that the P concentration required for half- maximal rate of nitrate uptake was 15 µmol L-1, which was higher than the 9 µmol L1 needed to
achieve half-maximal rates of growth. Thus, it appears that nitrate utilization can be enhanced
when P is added beyond that required to stimulate growth.
It appears that there exists an interplay between light and nutrients that may regulate algal
growth and the concomitant assimilation of nitrate during the period of vernal mixing in Lake
Superior. Evidence in support of this comes from Rhee and Gotham (1981) who demonstrated
that algal growth rates can be maintained under suboptimal light as a result of a compensatory
relationship between light and nutrients. Likewise, Fahnenstiel et al. (2000) demonstrated an
interaction between light and nutrients in controlling phytoplankton growth in the Great Lakes
during spring isothermal mixing. In that study, only modest increases in phytoplankton growth
were reported when either light or nutrient deficit was alleviated. Only when both parameters
were provided at saturating levels was maximal growth obtained.
Unlike the condition in May, light did not limit the assimilation of nitrate in September
when the lake was thermally-stratified. At both stations where a light effect was assessed, the
calculated integrated mixed layer light flux exceeded the threshold light fluence rate required for
maximal nitrate utilization. Rather, as predicted, P- and Fe deficit, alone or in combination, 85 constrained nitrate utilization by the cyanobacterial bioreporter. This was consistent with the vanishingly low concentrations of SRP measured in surface waters of Lake Superior during
September 2004 and support the observation that during summer thermal stratification, the picophytoplankton in the lake are primarily limited by low P availability as has been demonstrated previously for this size class (Sterner et al. 2004) and for the total phytoplankton community in Lake Superior (Nalewajko and Voltolina 1986; Rose and Axler 1997; Guildford et al. 2000; Sterner et al. 2004). That Fe addition might enhance the P-stimulated assimilation of nitrate by the bioreporter is consistent with the bioassay experiments reported by Sterner et al.
(2004).
86
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91
CHAPTER 4. THE PHYLOGENETIC DIVERSITY OF LAKE SUPERIOR
CYANOBACTERIA INFERRED FROM 16S rDNA SEQUENCES
Introduction
The autotrophic picoplankton (APP) are the major primary producers in the vast oligotrophic segments of the ocean and large transparent lakes (Ting et al. 2002; Callieri and
Stockner, 2002). They account for up to 90% of the total phytoplankton biomass, and up to 80% of the total carbon fixation in certain oceanic areas (Li et al. 1983). The APP of both marine and freshwater ecosystems is composed predominantly of cyanobacteria < 3µM in size (referred hereafter as “picocyanobacteria”). In the ocean, phycoerythrin (PE) - rich marine Synechococcus coexist with chlorophyll b containing Prochlorococcus, whereas the APP of oligotrophic lakes is dominated by the PE - rich freshwater Synechococcus (Ting et al. 2002; Fahnenstiel and Carrick,
1992; Postius and Ernst, 1999). Different ecotypes of Synechococcus and Prochlorococcus are adapted to different light and nutrient regimes that exist in the euphotic zone of the ocean (Ting et al. 2002; Zinser et al. in press). Most likely, spatiotemporal gradients of physical and chemical conditions cause differential vertical distribution and seasonal succession of ecotypes in the marine (Moore et al. 1998; Ferris and Palenik, 1998; West and Scanlan, 1999; Rocap et al. 2003;
Zinser et al. in press) and freshwater environments (Ernst et al. 1995; Postius and Ernst, 1999).
Owing to the importance of the APP abundance and photosynthetic activity for global primary production and biomass, a great body of research was focused on the genetic and physiologic biodiversity and niche-partitioning between different picocyanobacterial ecotypes in the ocean
(Zinser et al. in press); however, the freshwater APP have received much less attention (Callieri and Stockner, 2002). 92
Traditional cultivation methods are biased towards larger phytoplankton and PC-rich cyanobacteria that represent only a minor fraction of the APP; and thus, tend to underestimate the true APP ubiquity (Crosbie et al. 2003a). Further, due to their small size and apparent phenotypic uniformity, physiologically and genetically diverse Synechococcus are hard to classify by conventional microscopy (Rippka et al. 1979; Robertson et al. 1999). Molecular phylogeny of the ribosomal operon DNA sequences has proven to be useful for studying cyanobacterial biodiversity as it can resolve differences between morphologically similar strains
(Honda et al. 1998; Robertson et al. 1999; Ernst et al. 2003; Crosbie et al. 2003a and b). In a 16S rDNA tree, both marine and freshwater unicellular picocyanobacteria cluster within the
“picocyanobacterial clade”, which separates from the rest of the cyanobacterial radiation with
100% bootstrap support (Urbach et al. 1998; Ernst et al. 2003; Crosbie et al. 2003b). The phylogenetic analysis of 16S rDNA is also used for studying the natural APP assemblages. PCR- based amplification of picoplankton 16S rDNA sequences from water samples allows direct analysis of the APP community, avoiding biased culturing techniques (Urbach et al. 1998;
Honda et al. 1998; Robertson et al. 1999; Schmidt et al. 1991; Field et al. 1997; West and
Scanlan, 1999; Fuller et al. 2003).
In this study, we for the first time characterize the phylogenetic diversity of cyanobacterial 16S rDNA sequences from Lake Superior, a large ultra-oligotrophic water body with the most extensive surface area of any freshwater lake in the world. PE-rich picocyanobacteria contribute significantly to total phytoplankton biomass and primary production in Laurentian Great lakes, including Lake Superior (Caron et al. 1985; Fahnenstiel et al. 1986; Fahnenstiel and Carrick, 1992). Despite their importance, the biodiversity of the Great
Lakes APP is poorly understood. In order to initially characterize the genetic structure of the 93
picoplankton community in Lake Superior, we constructed and analyzed a library of
cyanobacterial 16S rDNA sequences amplified by PCR using DNA isolated from lake water and
cyanobacteria-targeted primers. The results of the phylogenetic analysis of the library suggest the
presence of two novel “Lake Superior” clusters of 16S rDNA sequences within the
picocyanobacterial clade sensu Urbach et al. (1992). In addition, four picoplankton strains were
isolated from the lake between years 2004 and 2005. Their phylogenetic relatedness to known
picocyanobacterial strains was determined by analysis of 16S rDNA sequences.
Materials and methods
Sample collection
The samples were collected during two research cruises in the South Western arm of
Lake Superior in May and Sepetmebr 2004. In May, during isothermal mixing water was
collected from a depth of 5m at stations Sterner B (SB), Castle Danger 1(CD-1) and Western
Midlake (WM) (for station coordinates see Table 1 in Chapter 3). In September 2004, when the
water column was stratified, water was collected from the epilimnion and DCM (Deep
Chlorophyll Maximum) from stations CD-1 (5m and 15m respectively) and WM (5m and 30m
respectively), and from the epilimnion (5m depth) from stations SB and Portage Deep (PD).
Water from all stations except for SB and PD was collected using a trace metal clean pumping
system (Sterner et al. 2004). Water from stations SB and PD was sampled using an acid-clean
teflon-coated Go-Flo bottle. Water from all stations was passed through 0.45 µm cartridge filters, which were then placed into1.6 ml eppendorf tubes containing TE buffer (10mM Tris-HCL, pH.7.5, 1 mM EDTA-Na2) and stored at -20°C for DNA extraction. 94
Isolation of cyanobacterial strains from Lake Superior
Many authors have mentioned the importance of the colony forming cyanobacteria for the total APP abundance in lakes (Caron, 1985; Klut and Stockner, 1990; Callieri and Stockner,
2002; Fahnenstiel and Carrick, 1992). We skipped the filtration step used in many of the previous studies in order to avoid losing a significant fraction of colonial picocyanobacteria,
because their ability to pass through the 1-5 µM pore size filters typically used to select for the
APP can be variable and unpredictable (Leppard et al. 1987). Strains LS0417, LS0503 and
LS0504 were isolated by direct plating of lake water onto 1.2% agarose plates enriched with
BG11 medium (Allen 1968; as described at www.cyanosite.bio.purdue.edu) to select for
cyanobacteria and 250 µg L-1 cycloheximide to inhibit the growth of eukaryotic cells. The plates
were incubated under continuous illumination with 5-10 µmol quanta m-2 s-1. Strain LS0417 was
isolated from the water sample collected in September 2004 from the epilimnion from station
Bingman (for station coordinates and location map see Materials and Methods and Figure 1 in
Chapter 3). Strains LS0503 and LS0504 were isolated from the surface waters collected in May
2005 during cruise from station SB. Whole water was collected by acid-rinsed Go-flo bottles and drawn through the filters, which were immediately placed onto the plates, and the plates were stored in the dark until the end of the cruise. Strain LS0427 was obtained by amendment of surface water collected from station CD1 in May 2004 with 30 µM NaNO3, 8 µM K2PO3, 10nM
-1 FeCl3 and 250 µg L cycloheximide. After four weeks of incubation under continuous
illumination with 5-10 µmol quanta m-2 s-1, the culture was centrifuged at 6000 rpm for 15 minutes to collect picocyanobacteria and the sediment was spread onto BG 11/cycloheximide plates as described above. When single colonies of PC-rich (strains LS0417, LS0503 and
LS0427) and PE-rich (LS0503) picocyanobacteria were formed on plates, they were transferred 95
into liquid BG11 media and grown under the same light conditions. After several rounds of retransferring into fresh BG11, all cultures became unialgal, but still were contaminated with heterotrophic bacteria.
DNA extraction
For the extraction of DNA from environmental samples, each filter was aseptically cut into slices and placed into 50ml Falcon tubes. Three ml of STE buffer (10mM Tris-HCl, pH 8.0,
0.1M NaCl, 1mM EDTA-Na2) were added to the tubes with lysozyme to a final concentration of
3mg*mL-1. The tubes were incubated with shaking for 2h at 37°C. Further, 300 µL of SDS
(10%, pH 7.0) were added to the samples and incubated at 37°C for 1h, 95°C for 15 minutes, -
70°C for 15 minutes and 37°C for 15 minutes. The tubes were then subjected to two rounds of
phenol-chloroform extraction and the DNA was precipitated with 96% ethanol and resuspended in 50µL of TE buffer. DNA from the isolated cyanobacterial strains was extracted by the phenol free method as described at http://www.molbiol.ru/protocol/24_01.html.
PCR amplification
Oxygenic phototroph specific primers 106F: 5’CGGACGGGTGAGTAACGCGTGA 3’
and 789R: 5’ GACTACAT/AGGGGTATCTAATCCCA/TTT 3’(Nubel et al. 1997) were used to amplify 16S rDNA from DNA preparations. PCR amplifications were performed in 50µL volume containing 5µL of 10X PCR reaction buffer (500mM KCl, 100mM Tris-HCl (pH 9.0),
1% Triton X-100), 5µL of the DNA preparation, 200µM concentrations of deoxynucleoside triphophates, 0.2 nM primers and 0.25 µL of Taq DNA polymerase (Promega). The PCR reactions were carried out in the BIO-RAD thermal cycle, catalogue # 170-6700. The amplification steps included 94°C for 5 minutes, followed by 30 cycles of 94°C for 1 m, 58°C for 2 minutes and 72°C for 3 minutes. In order to increase the efficiency of the following TOPO 96 reaction, a final of 30 minutes at 72°C was added to ensure the PCR products are 3’ polyadenylated. The same PCR and ligation conditions with the TOPO vector were used for the amplification of 16S rDNA of isolated cyanobacterial strains.
Construction of clone libraries
The pCR 2.1 - TOPO vector (Invitrogen) was used to clone the PCR amplicons as described in the user manual. TOP10F’ chemically competent Escherichia coli cells from
(Invitrogen) were transformed with the TOPO cloning reaction and 100µg/l ampicillin containing LB (Luria Bertani) plates were used to select for transformants. The colonies were screened for positive clones by colony PCR with the primers used for initial amplification. The amplification mixture was the same as was used for the initial amplification, except that colonies of transformed Escherichia coli were used as templates. Positive colonies were stored in 25% glycerol at -70°C for subsequent sequencing.
DNA sequencing
High-throughput sequencing of Escherichia coli cultures transformed with TOPO vector bearing inserts of environmental 16S rDNA was performed at the sequencing center of the
Clemson University Genomic Institute. Four 96-well plates containing glycerol stocks were frozen at -70°C prior to shipping to Clemson. Sequencing was performed in an ABI 3730XL 96- capillary sequencer in one direction using 2 pM per reaction of M13 reverse sequencing primer
(Invitrogen) for the pCR 2.1 TOPO vector.
Phylogenetic analysis
Sequences were aligned using the alignment program CLUSTALX 1.83 (Higgins and
Sharp, 1988). The phylogenetic trees for each sampling site were constructed from 615 97
unambiguously aligned bases by neighbor joining method using MEGA3.1 (Kumar et al. 2004)
software.
Results
In order to assess the genetic diversity of cyanobacteria in Lake Superior, we sequenced
16S rDNA genes amplified by PCR of total DNA collected from several stations in Lake
Superior with the 106F and 781F primers specific to cyanobacteria and plastids (Nubel et al.
1996). The samples were collected from 5m at stations CD1, WM, SB during spring isothermal mixing in May 2004, and from the epilimnion and DCM at stations CD1 and WM, and the epilimnion at stations SB and PD during thermal stratification in September 2004. The station
map is presented in Chapter 3, figure 1 (Chapter 3). High throughput sequencing of 480
sequences in one direction resulted in 368 successful reactions. Out of the entire pool of 368
sequences, 41 did not cluster within the oxygenic phototroph lineage in a neighbor-joining tree, and 29 clustered ouside the cyanobacterial radiation (data not shown). The majority of the sequences that did not cluster within the oxygenic phototroph lineage were from the May, 2004
libraries.
The remaining 298 sequences that did cluster within the cyanobacterial radiation were
divided into 9 groups (libraries) according to 9 sampling sites: CD1, May, 5m; CD1, September,
5m; CD1, September, 15m; WM, May, 5m; WM, September, 5m; WM, September, 30m; SB,
May, 5m; SB, September, 5m and PD, September, 5m. The phylogenetic analysis of the
epilimnion library from CD1 is presented in figure 1. Included in the analysis are strains LS0417,
LS0427, LS0503 and LS0504 were isolated from pelagic (LS0427, LS0417) and nearshore
(LS0503, 0504) stations in Lake Superior during years 2004 and 2005. Other strains are
98
LS342 CD1 Sep 5m 4-E6 LS355 CD1 Sep 5m 4-F7 LS372 CD1 Sep 5m 4-G9 CD1, September, LS361 CD1 Sep 5m 6-G12 LS347 CD1 Sep 5m 4-E11 Epilimnion (5m) LS351 CD1 Sep 5m 4-F3 LS344 CD1 Sep 5m 4-E8 LS339 CD1 Sep 5m 4-E3 LS354 CD1 Sep 5m 4-F6 LS363 CD1 Sep 5m 4-G3 LS371 CD1 Sep 5m 4-G8 LS341 CD1 Sep 5m 4-E5 LS352 CD1 Sep 5m 4-F4 LS340 CD1 Sep 5m 4-E4 LS350 CD1 Sep 5m 4-F2 LSI (Lake Superior group I) LS357 CD1 Sep 5m 4-F9 LS362 CD1 Sep 5m 4-G2 99.4 LS377 CD1 Sep 5m 4-H5 LS388 CD1 Sep 5m 5-A4 89 LS360 CD1 Sep 5m 4-F12 LS384 CD1 Sep 5m 4-H12 LS383 CD1 Sep 5m 4-H11 87 LS345 CD1 Sep 5m 4-E9 LS382 CD1 Sep 5m 4-H10 LS356 CD1 Sep 5m 4-F8 91 LS376 CD1 Sep 5m 4-H4 LS378 CD1 Sep 5m 4-H6 LSII (Lake Superior group II) 91 77 LS389 CD1 Sep 5m 5-A5 LBP1 Lake Biwa Japan 99.7 MW6C6 Lake Mondsee Austria 86 MW32B5 Lake Mondsee Austria Group H MW73B4 Lake Hallstattersee Austri MW74D3 Lake Hallstattersee Austria MW4C3 Lake Mondsee Austria Group B 98 LS373 CD1 Sep 5m 4-G10 BO8807 Lake Constance Central Europe (Subalpine cluster I) S.rubescens Lake Zurich Switzerland LM94 Lake Maggiore Italy 77 ARC11 Lake Erie MH305 Lake Mondsee Austria 99 LBB3 Lake Biwa Japan 99 LBG2 Lake Biwa Japan Lake Biwa cluster 75 LS0427 Lake Superior 99 MW97C4 Lake Mondsee Austria Group I P211 Bylot Island tundra pond Marine Synechococus sp 98 Prochlorococcus sp. 97 92 MH301 Lake Mondsee Austria MH301 cluster LS381 CD1 Sep 5m 4-H9 LS353 CD1 Sep 5m 4-F5 PCC7920 pond Finland LS0503 Lake Superior 98 LS0417 Lake Superior Cyanobium gracile 86 BO984127 Lake Constance Central Europe PCC6904 stream California USA cluster PCC6307 lake water Wisconsin Synechococcus PCC7942 Synechocystis PCC6803 99 LS365 CD1 Sep 5m 4-G5
0.02 99
Figure 1. 16S rDNA neighbor-joining tree of the major clusters of picocyanobacteria described in Ernst et al 2003 and Crosbie et al. 2003, with an addition of four Lake Superior isolates (LS0417, 0427, 0503, 0504), 32 environmental clones from the epilimnion of Lake Superior pelagic station CD1 (LS337-389) obtained in this study and strains Synechococcus PCC7942 and Synechocystis 6803 that are not in the picoplankton clade. Clusters that included LS clones are highlighted in color and the cluster labels are in bold. The tree was inferred from 615 bases of the 16S rDNA. Numbers at nodes indicate the percent of bootstrap frequency (1000 replicates) obtained by MEGA 3.1 using the Kimura-2 parameter model of nucleotide substitution. Bootstrap values < 75% are not shown. Average pairwise percent similarities are shown for Lake Superior strains LSI and LSII. 16S rDNA sequences of previously known strains were obtained from Gene Bank.
Cyanobium and Synechococcus-like freshwater isolates, as well as marine
Synechococcus and Prochlorococcus, which together constitute the major clusters of the picocyanobacterial clade. The cluster designations are in accordance with Robertson et al. 2001 with modifications by Ernst et al. 2003 and Crosbie et al. 2003. Sequences labeled LS337-389 are environmental clones obtained in this study. Identical sequences from the library or from strains isolated from the same lake were not included the neighbor-joining tree. In spite of the fact that, partial length 16S rDNA sequences were used in this study, all major picocyanobacteria clusters described in previous studies, even though prior studies analysed near complete 16S
rDNA sequences (Ernst et al. 2003; Crosbie et al. 2003) were recovered by our analysis and
retained high bootstrap values (figure 1). Thirty one out of 32 unique sequences clustered within
the picocyanobacteria clade sensu Urbach et al. (1998) with 99% bootstrap support. The majority
of the sequences clustered within two new picocyanobacterial groups, LS I and II (Lake Superior
clusters I and II), with the average pairwise sequence similarities of 99.4% and 99.7%
respectively. The two groups are closely related to each other and group H, sensu Crosbie et al.
(2003), which consists of a number of PE-rich isolates from Lake Mondsee, Austria and a PE-
rich strain LPB1, isolated from Lake Biwa, Japan. However, the sequences formed two
independent clusters that did not include any of the strains isolated from other oligotrophic lakes. 100
CD1, September, LS465 CD1 Sep 15m 5-G9 LS475 CD1 Sep 15m 5-H7 DCM (15m) LS453 CD1 Sep 15m 5-F9 LS451 CD1 Sep 15m 5-F7 LSI (Lake Superior group I) 95 LS462 CD1 Sep 15m 5-G6 99.5 LS440 CD1 Sep 15m 5-E8 84 LS476 CD1 Sep 15m 5-H8 LS477 CD1 Sep 15m 5-H9 LS472 CD1 Sep 15m 6-H10 LS456 CD1 Sep 15m 5-F12 LSII (Lake Superior group II) LS447 CD1 Sep 15m 5-F3 94 99.7 89 70 LS446 CD1 Sep 15m 5-F2 MW6C6 Lake Mondsee Austria 70 MW32B5 Lake Mondsee Austria Group H LBP1 Lake Biwa Japan LS452 CD1 Sep 15m 5-F8
88 LS478 CD1 Sep 15m 5-H10 LS461 CD1 Sep 15m 5-G5 LS463 CD1 Sep 15m 5-G7 LS464 CD1 Sep 15m 5-G8 88 MW73B4 Lake Hallstattersee Austria MW74D3 Lake Hallstattersee Austria Group B MW4C3 Lake Mondsee Austria (Subalpine cluster BO8807 Lake Constance Central Europe I) LS443 CD1 Sep 15m 5-E11 LS448 CD1 Sep 15m 5-F4 LM94 Lake Maggiore Italy S.rubescens Lake Zurich Switzerland LS449 CD1 Sep 15m 5-F5 LBB3 Lake Biwa Japan 99 LBG2 Lake Biwa Japan Lake Biwa cluster 72 ARC11 Lake Erie MH305 Lake Mondsee Austria MH301 Lake Mondsee Austria
98 LS457 CD1 Sep 15m 5-G1 MH301 cluster LS442 CD1 Sep 15m 5-E10
100 PCC7920 pond Finland LS0417 Lake Superior 99 PCC6307 lake water Wisconsin Cyanobium gracile 91 BO984127 Lake Constance Central Europe cluster PCC6904 stream California USA LS0503 Lake Superior MW97C4 Lake Mondsee Austria 70 MW99B6 Lake Mondsee Austria 100 Group I LS0427 Lake Superior P211 Bylot Island tundra pond 98 81 Marine Prochlorococcus Marine Synechococcus Synechococcus99 PCC7942 Synechocystis PCC6803 99 LS450 PD Sep 15m 5-F6
0.02 101
Figure 2. 16S rDNA neighbor-joining tree of the major clusters of picocyanobacteria described in Ernst et al 2003 and Crosbie et al. 2003, with an addition of four Lake Superior isolates (LS0417, 0427, 0503, 0504), 23 environmental clones from the DCM of Lake Superior pelagic station CD1 (LS440-378) obtained in this study and strains Synechococcus PCC7942 and Synechocystis 6803 that do not cluster within the picoplankton clade. Clusters that included LS clones are highlighted in color and the cluster labels are in bold. The tree was inferred from 615 bases of the 16S rDNA. Numbers at nodes indicate the percent of bootstrap frequency (1000 replicates) obtained by MEGA 3.1 using the Kimura-2 parameter model of nucleotide substitution. Bootstrap values < 70% are not shown. Average pairwise percent similarities are shown for Lake Superior clusters LSI and LSII.
Only 3 of the picocyanobacterial sequences did not cluster within groups LSI and LSII. LS373 was in the Subalpine cluster I (group B sensu Crosbie et al. 2003), which consists of PE-rich isolates from several oligotrophic lakes in Europe, LS 381 grouped with a PE-rich isolate
MH301 from Lake Mondsee, Austria, which remained unclustered in the 16S rRNA tree by
Crosbie et al. 2003. Another picocyanobacterial sequence (LS353) did not cluster with any of the known picocyanobacteria. Sequence LS365 was outside the picoplankton lineage, and appeared to be closely related to the 16S rDNA of Synechocystis PCC 6803 (figure 1).
The 16S rDNA sequences from the DCM at CD1, similarly, formed two new clusters LSI and LSII (average pairwise sequence similarities 99.5% and 99.7% respectively) within the picoplankton clade, that were closely related, but well separated from group H (figure 2).
However, fewer sequences clustered within LSI, and there were more sequences in the Subalpine
cluster I. Two sequences clustered with the MH301 group (LS457, LS442), and two
picoplankton sequences remained unclustered (LS452, LS478). As in the case of the epilimnion
library from CD1, one sequence (LS450) clustered with Synechocystis PCC 6803 16S rDNA
outside the picoplankton lineage.
LSI and II clusters were also present on the trees obtained for the epilimnion libraries
from WM and SB, and the DCM library from WM (data not shown). The same trend with fewer 102 CD1, May, LS200 CD1 May 5m 3-A8 LS203 CD1 May 5m 3-A11 (5m) LS210 CD1 May 5m 3-B6 LSI (Lake Superior group I) 95 LS189 CD1 May 5m 6-F11 99.7 LS205 CD1 May 5m 3-B1 90 LS198 CD1 May 5m 3-A6 LS217 CD1 May 5m 3-C1 LS169 CD1 May 5m 6-E3 94 LS218 CD1 May 5m 3-C2 LSII (Lake Superior group II) 62 LS182 CD1 May 5m 6-F4 75 99.7 LS206 CD1 May 5m 3-B2
LBP1 Lake Biwa Japan 73 MW32B5 Lake Mondsee Austria Group H 84 69 MW6C6 Lake Mondsee Austria MW73B4 Lake Hallstattersee Austria MW74D3 Lake Hallstattersee Austria LS186 CD1 May 5m 6-F8 97 MW4C3 Lake Mondsee Austria Group B LS174 CD1 May 5m 6-E8 (Subalpine cluster 100 S.rubescens L. Zurich Europe I) BO8807 Lake Constance Central Europe LM94 Lake Maggiore Italy LS190 CD1 May 5m 6-F12 99 LBB3 Lake Biwa Japan LBG2 Lake Biwa Japan Lake Biwa cluster 100 ARC11 Lake Erie 71 LS204 CD1 May 5m 3-A12 MH305 Lake Mondsee Austria LS0427 Lake Superior 68 MW97C4 Lake Mondsee Austria 100 MW99B6 Lake Mondsee Austria Group I 69 92 P211 Bylot Island tundra pond 99 Marine Prochlorococcus Marine Synechococcus 99 99 MH301 Lake Mondsee Austria LS213 CD1 May 5m 3-B9 MH301 cluster
71 LS168 CD1 May 5m 6-E2 PCC7920 pond Finland 96 LS0417 Lake Superior 88 BO984127 Lake Constance Central Europe 90 PCC6307 lake water Wisconsin Cyanobium gracile PCC6904 stream California USA cluster LS0503 Lake Superior Synechococcus PCC7942 Synechocystis PCC6803 LS170 CD1 May 5m 6-E4 LS0504 Lake Superior 100 OKO3 Lake Okutama Japan 99 Limnotrix redekei CCAP1443/1 l
80 Oscillatoria limnetica MR1
0.02 103
Figure 3. 16S rDNA neighbor-joining tree of the major clusters of picocyanobacteria described in Ernst et al 2003 and Crosbie et al. 2003, with an addition of four Lake Superior isolates (LS0417, 0427, 0503, 0504), 18 environmental clones from station CD1, collected from 5 m in May, 2004 (LS168-218), and strains Synechococcus PCC7942, Synechocystis 6803, O. limnetica and L. redekei that are not in the picoplankton clade. Clusters that included LS clones are highlighted in color and the cluster labels are in bold. The tree was inferred from 615 bases of the 16S rDNA. Numbers at nodes indicate the percent of bootstrap frequency (1000 replicates) obtained by MEGA 3.1 using the Kimura-2 parameter model of nucleotide substitution. Bootstrap values < 60% are not shown. Average pairwise percent similarities are shown for Lake Superior clusters LSI and LSII.
LSI sequences in the DCM library, compared to the epilimnion was observed at WM. Among other CD1 September clusters, MH301 and Subalpine cluster I were presented in each September sample except for SB.
As mentioned earlier, libraries constructed from the spring samples contained fewer cyanobacterial sequences than did the fall libraries. Figure 3 presents a neighbor-joining tree of the cyanobacterial sequences from the spring library from CD1. The distribution of sequences among picocyanobacterial clusters resembles that of the fall libraries, with fewer sequences in LSI and more Subalpine cluster I sequences compared to the epilimnion libraries. Unlike the
LSII cluster from the fall trees, LSII had moderate bootstrap support. However, in a neighbor- joining tree of LSI and II sequences from independent libraries from CD1 and PD, all LSII sequences clustered together with 70% bootstrap (figure 4). One picocyanobacterial sequence
(LS168) grouped with the members of the Cyanobium gracile cluster, which consists of a number of PE and PC-rich strains isolated from various locations all over the world and strains
LS0503 and LS0417 isolated from water samples collected from stations SB in May 2004 and
Bingman in September, 2004 respectively. Another clone in the spring library (LS170) clustered with 100% bootstrap support outside the picoplankton clade together with the PE-rich
filamentous cyanobacteria Oscillatoria limnetica and Limnothrix redekei, as well as PE-rich LS342 CD1 Sep 5m 4-E6 LS355 CD1 Sep 5m 4-F7 104 LS341 CD1 Sep 5m 4-E5 LS372 CD1 Sep 5m 4-G9 LS371 CD1 Sep 5m 4-G8 LS347 CD1 Sep 5m 4-E11 LS361 CD1 Sep 5m 6-G12 LS377 CD1 Sep 5m 4-H5 LS354 CD1 Sep 5m 4-F6 LS351 CD1 Sep 5m 4-F3 LS360 CD1 Sep 5m 4-F12 LSI (Lake Superior group LS339 CD1 Sep 5m 4-E3 LS344 CD1 Sep 5m 4-E8 I) LS362 CD1 Sep 5m 4-G2 LS388 CD1 Sep 5m 5-A4 LS384 CD1 Sep 5m 4-H12 LS350 CD1 Sep 5m 4-F2 LS340 CD1 Sep 5m 4-E4 LS357 CD1 Sep 5m 4-F9 LS363 CD1 Sep 5m 4-G3 LS217 CD1 May 5m 3-C1 LS352 CD1 Sep 5m 4-F4 LS453 CD1 Sep 15m 5-F9 LS189 CD1 May 5m 6-F11 LS10 PD Sep 5m 7-A10 LS198 CD1 May 5m 3-A6 LS451 CD1 Sep 15m 5-F7 LS205 CD1 May 5m 3-B1 LS440 CD1 Sep 15m 5-E8 LS476 CD1 Sep 15m 5-H8 LS200 CD1 May 5m 3-A8 LS203 CD1 May 5m 3-A11 LS345 CD1 Sep 5m 4-E9 LS22 PD Sep 5m 7-B10 LS477 CD1 Sep 15m 5-H9 LS465 CD1 Sep 15m 5-G9 LS382 CD1 Sep 5m 4-H10 LS383 CD1 Sep 5m 4-H11 70 LS472 CD1 Sep 15m 6-H10 LS210 CD1 May 5m 3-B6 LS475 CD1 Sep 15m 5-H7 LS356 CD1 Sep 5m 4-F8 LS462 CD1 Sep 15m 5-G6 LS376 CD1 Sep 5m 4-H4 LS456 CD1 Sep 15m 5-F12 LS218 CD1 May 5m 3-C2 LS378 CD1 Sep 5m 4-H6 LSII (Lake Superior group 70 LS182 CD1 May 5m 6-F4 LS446 CD1 Sep 15m 5-F2 II) LS447 CD1 Sep 15m 5-F3 LS389 CD1 Sep 5m 5-A5 LBP1 Lake Biwa Japan 80 MW6C6 Lake Mondsee Austria Group H MW32B5 Lake Mondsee Austria Synechococcus PCC7942 0.01 105
Figure 4. Neighbor-joining tree of Lake Superior environmental clones that form new pelagic lake Superior clusters LSI and I collected from CD1 and PD, and a closely related picocyanobacterial group H (Crosbie et al. 2003). The tree was inferred from 615 bases of the 16S rDNA. Numbers at nodes indicate the percent of bootstrap frequency (1000 replicates) obtained by MEGA 3.1 using the Kimura-2 parameter model of nucleotide substitution. Bootstrap values < 70% are not shown. Average pairwise percent similarities are shown for Lake Superior clusters LSI and LSII.
isolates OK03 and LS0504, from lakes Okutama (Japan) and Superior (this study) respectively
(this cluster is hereafter referred as O. limnetica group). The latter two strains have the cell diameter of approximately 1 µM and form short chains of 3 to 4 cells; and, therefore, are not strictly unicellular (Katano et al. 2000; this study). Thus, these two strains belong to the picoplankton category by their cell size, but cannot be classified as Synechoccoccus (Katano et al. 2000). The SB and WM libraries from May contained sequences from LSI and II, subalpine cluster I, MH301 cluster as well as two more sequences from the O.limnetica group (data not shown).
Clusters LSI and II, appear to be the most abundant groups of Lake Superior cyanobacterial 16S rDNA sequences in our data set. Both groups are closely related to group H sensu Crosbie et al. 2003, but form independent clusters supported by high or moderate bootstrap percentages (figures 1, 2 and 3). A neighbor-joining tree of LSI and II clones from CD1 and PD is shown on figure 4. The two LS clusters are separated from group H, and have moderate bootstrap support values and differ by an average of 0.6% (LSI) and 0.3%(LSII) in pairwise sequence comparisons.
Unlike the cyanobacterial 16S rDNA sequences from SB and pelagic stations CD1 and
WM, only 2 out of 30 unique sequences from the epilimnion at station PD clustered with the
Lake Superior cluster, LSI, and cluster LSII was not presented in the library (figure 5). Instead,
LM94 Lake Maggiore Italy 106 LS26 PD Sep 5m 7-C2 S.rubescens Lake Zurich Switzerland CD1, September, LS15 PD Sep 5m 7-B3 BO8807 Lake Constance Central Europe Epilimnion (5m) MW73B4 Lake Hallstattersee Austria MW74D3 Lake Hallstattersee Austria Group B LS8 PD Sep 5m 7-A8 LS13 PD Sep 5m 7-B1 62 (Subalpine cluster I) MW4C3 Lake Mondsee Austria LS18 PD Sep 5m 7-B6 LS33 PD Sep 5m 7-C9 LS6 PD Sep 5m 7-A6 PDI (PD cluster I) LS17 PD Sep 5m 7-B5 99 LS7 PD Sep 5m 7-A7 99.8 LS50 PD Sep 5m 7-E2 LS16 PD Sep 5m 7-B4 99 LS22 PD Sep 5m 7-B10 LSI (Lake Superior group I) LS10 PD Sep 5m 7-A10 LBP1 Lake Biwa Japan 99.8 66 MW32B5 Lake Mondsee Austria 71 MW6C6 Lake Mondsee Austria LS23 PD Sep 5m 7-B11 68 LS52 PD Sep 5m 7-E4 Group H LS9 PD Sep 5m 7-A9 LS44 PD Sep 5m 7-D8 LS27 PD Sep 5m 7-C3 LS37 PD Sep 5m 7-D1 LS32 PD Sep 5m 7-C8 LS46 PD Sep 5m 7-D10 Lake Biwa cluster 83 LBG2 Lake Biwa Japan LBB3 Lake Biwa Japan MH305 Lake Mondsee Austria 99 LS45 PD Sep 5m 7-D9 72 LS11 PD Sep 5m 7-A11 ARC11 Lake Erie LS12 PD Sep 5m 7-A12 MH301 Lake Mondsee Austria LS5 PD Sep 5m 7-A5 100 99 MH301 cluster 69 LS53 PD Sep 5m 7-E5 LS43 PD Sep 5m 7-D7 LS19 PD Sep 5m 7-B7 PCC7920 pond Finland LS0417 Lake Superior 97 PCC6307 lake water Wisconsin Cyanobium gracile 90 BO984127 Lake Constance Central Europe 77 PCC6904 stream California USA cluster LS0503 Lake Superior 95 LS38 PD Sep 5m 7-D2 LS34 PD Sep 5m 7-C10 PDII (PD cluster II) LS0427 Lake Superior 71 99.7 MW97C4 Lake Mondsee Austria 100 MW99B6 Lake Mondsee Austria Group I P211 Bylot Island tundra pond 99 78 Marine Prochlorococcus Marine Synechococcus 99 Synechococcus PCC7942 Synechocystis PCC6803
0.02
107
Figure 5. 16S rDNA neighbor-joining tree of the major clusters of picocyanobacteria described in Ernst et al 2003 and Crosbie et al. 2003, with an addition of four Lake Superior isolates (LS0417, 0427, 0503, 0504), 30 environmental clones from station PD, collected from 5 m in Septemebr, 2004 (LS1-53), and strains Synechococcus PCC7942 and Synechocystis 6803 hat are not in the picoplankton clade. Clusters that included LS clones are highlighted in color and the cluster labels are in bold. The tree was inferred from 615 bases of the 16S rDNA. Numbers at nodes indicate the percent of bootstrap frequency (1000 replicates) obtained by MEGA 3.1 using the Kimura-2 parameter model of nucleotide substitution. Bootstrap values < 60% are not shown. Average pairwise percent similarities are shown for Lake Superior clusters LSI, PDI and PDII.
two PD specific clusters named PDI and II with average sequence similarities of 99.8 and 99.7 respectively were present and did not include any known cyanobacterial strains. The bootstrap value of 99% provided a strong support for the monophyly of these clusters. Further, members of each of the major freshwater picocyanobacterial clusters described in previous studies except for
C. gracile cluster and group I sensu Crosbie et al. 2003 were presented in the PD library (figure
5). In addition, a new cluster MH305, which previously consisted of a single PE-rich strain
MH305 (Crosbie et al. 2003), contained two PD sequences (LS11 and 45) and a PC-rich Lake
Erie isolate ARC11 (Cupp and Bullerjahn, unpublished).
Figure 6 shows the overall distribution of 16S rDNA clones obtained in this study among different lineages within the cyanobacterial radiation. One striking feature of this data set is the apparent difference in the genetic diversity of cyanobacteria between the nearshore station PD and other sampling sites, including pelagic stations CD1 and WM, and the nearshore station SB.
Lake Superior cluster I is ubiquitous at CD1, WM and SB (minimum 50% of the clones), whereas at PD the LSI group accounted for only 4% of the sequences. Further, cluster LSII is absent from the PD library, but has representatives at all pelagic stations and SB. Conversely, picocyanobacterial clusters MH305, group H sensu Crosbie, Lake Biwa cluster, and PD clusters I and II are only present at PD. The major Lake Superior cluster LSI is more abundant in the 108 O.limnetica cluster Synechocystis PCC 6803 group unclustered picocyanobacteria MH301 cluster MH305 cluster Group H (Crosbie et al, 2003) Lake Biwa cluster C. gracile cluster PD cluster I PD cluster II Subalpine cluster I 120 LSI LSII
100
80
60 % of clones % of 40
20
0 PDSep5 SBSep5 SBMay5 CDSep5 CDSep15 CDMay5 WMSep5 WMSep30 WMMay5
Figure 6. Clusters of the picocyanobacterial clade and other cyanobacterial groups (O. limnetica and Synechocystis PCC 6803) presented in the 16S rDNA data set obtained in this study. Cluster designations are in accordance with Ernst et al, 2003 and Crosbie et al, 2003. Clusters LSI, LSII, PDI and PDII were described in this study. Sample information (station name, month and the samling depth) is presented on the X axis.
mixed layer during the fall, than in the deeper DCM layer or in the surface waters during the spring. O.limnetica cluster was only present in the spring libraries, as was the C.gracile cluster.
Lake Superior strains LS0504 and LS0503 that cluster within the two groups respectively were also isolated in culture from the spring water samples. 109
Discussion
The work presented here was initiated as a first attempt to genetically characterize the cyanobacterial component of the natural APP assemblages in Lake Superior. The vast majority
of Lake Superior cyanobacterial 16S rDNA clones obtained in the present study belonged to the
robust picoplankton clade sensu Urbach et al. (1998), which consists of both marine and
freshwater picocyanobacteria. Crosbie et al. (2003b) defined seven clusters within the nonmarine
subdivision of the picoplankton clade (Figure 9 in Chapter 1). Certain freshwater clusters are
restricted to a particular ecological niche, e.g. the cluster of Antarctic strains, or geographical
location, e.g. group E sensu Crosbie et al. (2003b) (Lake Biwa, Japan) (Figure 9 in Chapter 1). In
contrast, other clusters appear to be cosmopolitan with members isolated from distant locations
and lakes of different limnological characteristics. The examples of such clusters include
Cyanobium gracile cluster and group H sensu Crosbie et al. (2003b) (Figure 9 in Chapter 1).
Here, we present evidence for the existence of new freshwater picocyanobacterial clusters LSI
and II, which are probably specific to Lake Superior, within the freshwater group of
picocyanobacteria. LS clusters I and II were supported by relatively high bootstrap values and
appeared to be closely related to group H sensu Crosbie et al (2003), which consists of a number
of PE-rich isolates from deep subalpine Lake Mondsee (Austria), as well as the PE-rich strain
LBP1, isolated from the mesotrophic Lake Biwa (Japan). The LSI and II clusters were well
represented at the pelagic stations and SB, but were nearly absent from the nearshore PD.
Instead, the picocyanobacterial community at PD appeared more diverse than the pelagic
community and consisted of members of the C. gracile cluster, Subalpine cluster I, Lake Biwa
cluster sensu Ernst et al. (2003), group H, as well as two new PD specific clusters PDI and PDII.
The pelagic Lake Superior is an extremely oligotrophic system where the combination of 110
limnological conditions creates a unique environment where the phytoplankton are severely
limited by low concentrations of phosphorus and iron, as well as light and temperature regimes
unfavorable for photosynthesis (Fahnenstiel et al. 2000; Sterner et al. 2004; McKay et al. 2005;
Chapter 3) .The evident differences in the picocyanobacterial community strusture between the
pelagic south-western arm of Lake Superior and the shallow nearshore station PD located in an
urban area of the lake in the vicinity of Houhgton, Michigan, allows us to suggest the existence
of an ecotype of Synechococcus, which is adapted to the specific conditions in the pelagic lake.
Whether the ecotype is unique to Lake Superior or if the representatives of LSI and LSII clusters
are present elsewhere in lakes with similar environemtal conditions remains uncertain untill more
16S rDNA sequence information on other lakes becomes available.
LS I and II were the most highly represented clusters in libraries from the pelagic stations
CD1 and WM, as well as the nearshore station SB. Even though the abundance of a certain genotype in the ecosystem can not be inferred from the representation of the genotype in the
clone library, due to the biasing introduced by the sampling methods and PCR, the absolute
dominance of LSI and II clusters in the clone library suggests that these clusters constitute a
significant fraction of the APP in Lake Superior. One way to provide more evidence for the
presence of the new clusters in the natural APP assemblages is to conduct a similar phylogenetic
study using a different biodiversity marker. The employment of protein coding genes for
studying biodiversity allows differentiation between genotypes that appear identical when 16S
rDNA sequences are used. One candidate for such analysis is the ntcA gene encoding for the
global nitrogen regulator NtcA in cyanobacteria (Lindell et al, 2005). The advantages of the ntcA
gene for the genetic diversity studies include its specificity for cyanobacteria and the presence of
highly conserved patches encoding for functional domains in the ntcA sequence that can be used 111 as priming sites for PCR. In addition, all known cyanobacterial strains possess a single ntcA copy in their genome (Lindell et al. 2005; Penno et al. in preparation). It has been shown recently that the ntcA gene provides a higher resolution than 16S rDNA for differentiating between marine
Synechococcus and Prochlorococcus strains (Penno et al. in preparation). In addition, the ntcA gene expression can be used as an indicator of nitrogen status of cyanobacteria, as its expression is induced during nitrogen stress (Lindell and Post, 2001). This will enable us to use the ntcA gene for both genetic and physiological characterization of cyanobacteria in Lake Superior. In addition, the phycocyanin operon sequences, namely the intergenic spacer between the cpcB and
A genes (cpcBA-IGS) has been succefully employed in previous phylogenetic studies (Robertson et al. 2001; Crosbie et al. 2003b). The operon is present solely in cyanobacteria, and the phylogeny of the non-coding intergenic spacer helps to resolve differences between closely related strains. Crosbie et al. (2003b) used the cpcBA-IGS sequences for the phylogenetic analysis of isolated freshwater picocyanobacteria. The employment of this gene for the genetic characterization of Lake Superior samples would make the comparison with Crosbie’s clusters more adequate.
We have isolated several cynobacterial strains from Lake Superior and analyzed their phylogenetic relatedness to known cyanobacteria. None of the isolates clustered within the LSI and II clusters of other groups well represented in the library. Strain LS0504 was closely related to Oscillatoria limnetica, a PE-rich filamentous strain, which was shown to dominate the cyanobacterial component of Lake Superior phytoplankton in the spring and early summer
(Munawar and Munawar, 1978). LS0504 is not stricktly unicellular as it forms chains of 3 two 4 cells, similarly to another PE-rich picocyanobacterium OK03, which is also related to O. limnetica (Katano et al. 2001). The latter authors suggested that it might represent a genus of 112
picocyanobacteria distinct from Synechococcus spp. Two sequences from the clone libraries
from May exhibited a high degree of similarity to LS0504 and O. limnetica, which suggests that
members of this group thrive in the lake during the isothermal mixing. However, our primary
goal was to isolate the most common members of the Lake Supeior APP community. The results
of the phylogenetic analysis suggest the predominance of PE-rich cyanobacteria in the lake.
Despite the fact that grouping of picocyanobacteria based on pigment composition is not always
consistent with phylogenetic clustering (Robertson et al. 2001; Ernst et al. 2003), subalpine
cluster I and group B, which are the most closley related to LSI and II of all other groups of freshwater APP, consist entirely of PE-rich strains (Figure 9, Chapter 1). Moreover, Fahnenstiel
et al. (1986) reported on the dominance of PE-rich Synechococcus-like cells in the epilimnion
and hypolimnion of Lake Superior in September 1983. All the above strongly suggests that PE-
rich Synechococcus are the dominant pigment group in the lake. Recently, Crosbie et al. (2003a)
were able to rapidly establish isolates of PE-rich picocyanobacteria from five subalpine lakes in
Austria using single cell sorting by flow-cytometry. We are planning on using a similar cell
sorting technique on Lake Superior APP. Despite the low representation of the PC and PE-rich
isolates in the library, the physiological characterization of these strains along with members of
LSI and II clusters, which we are planning to isolate in the furture, may reveal common physiological adaptations to the unique Lake Superior environment.
Finally, studying the diversity and physiology of the endemic picoplankton of Lake
Superior can aid in the interpretation of the bioreporter experiments, in which Synechocystis PCC
6803 was used as a proxy for the physiological responses of the LS cyanobacteria. Although the vast majority of the cyanobacterial 16S rDNA sequences recovered in this study are not genetically related to Synechocystis and clustered within the picoplankton clade sesnu Urbach et 113 al. (1998), two sequences grouped together with Synechocystis in a well bootstrap supported cluster (Figures 3 and 6). This suggests that Synechocystis-like organisms may be thriving in the specific conditions that exist in the lake, even though these cyanobacteria are not likely to be a dominant phytoplankton group. The presence of such organisms in Lake Superior helps justify the choice of the model organism for the bioreporter experiments.
114
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