Deep-Sea Research I 50 (2003) 301–315 Instruments and Methods An automated submersible flow cytometer for analyzing pico- and nanophytoplankton: FlowCytobot Robert J. Olson*, Alexi Shalapyonok, Heidi M. Sosik Woods Hole Oceanographic Institution, Woods Hole, MA 02543, USA Received 19 July 2002; received in revised form 18 December 2002; accepted 18 December 2002 Abstract Flow cytometry is a valuable tool for the analysis of phytoplankton and other suspended particles because of its speed and quantitative measurements, but the method’s oceanographic application has been limited by the need to take discrete water samples for analysis on board ship or in the laboratory. For this reason, we have developed an automated flow cytometer (FlowCytobot) that can operate in situ and unattended. The new instrument utilizes a diode-pumped 532 nm laser and can measure light scattering and fluorescence of particles as small as Synechococcus cells. For operation at the LEO-15 mooring site off New Jersey, it is connected to shore by power and communications cables, and is controlled by a microcomputer whose programming can be loaded remotely. The sampling rate is adjustable; we have used from 12.5 to 50 ml min 1 . Integrated signals from each particle (two light scattering angles and two fluorescence emission bands) are transmitted to a shore-based computer, where they are accessible by Internet and can be examined in real time. FlowCytobot was deployed at LEO-15 from late July to early October 2001, where it operated continuously (aside from occasional power or communications interruptions at the node) without outside intervention. Even after 2 months of in situ operation, FlowCytobot’s measurements were similar to those of a conventional flow cytometer, as shown by analysis of a discrete water sample taken at the location of the sample inlet. In addition to documenting seasonal and event-scale changes in size distributions and population abundances in the pico- and nanophytoplankton, FlowCytobot will be useful for examining diel cycles in light scattering and pigment fluorescence of cells in situ that may allow estimation of rates of production by different phytoplankton groups. r 2003 Elsevier Science Ltd. All rights reserved. Keywords: Phytoplankton; Flow cytometry; Mooring; Time series; Fluorescence; Scattering 1. Introduction Detailed knowledge of the composition and characteristics of the particles suspended in the sea is crucial to an understanding of the biology, optics and geochemistry of the oceans. The composition and size distribution of the phyto- plankton community, for example, help determine the flow of carbon and nutrients through an ecosystem (Chisholm, 1992), and can be important indicators of change in coastal environments subject to anthropogenic disturbances such as nutrient loading and pollution (Cloern, 2001). Flow cytometry, which provides rapid and quantitative measurements of individual sus- pended microscopic particles, has proved a *Corresponding author. Tel.: +1-508-289-2565; fax: +1- 508-457-2169. E-mail address: [email protected] (R.J. Olson). 0967-0637/03/$ - see front matter r 2003 Elsevier Science Ltd. All rights reserved. doi:10.1016/S0967-0637(03)00003-7
Transcript
Deep-Sea Research I 50 (2003) 301–315
Instruments and Methods
An automated submersible flow cytometer for analyzingpico- and nanophytoplankton: FlowCytobot
Robert J. Olson*, Alexi Shalapyonok, Heidi M. Sosik
Woods Hole Oceanographic Institution, Woods Hole, MA 02543, USA
Received 19 July 2002; received in revised form 18 December 2002; accepted 18 December 2002
Abstract
Flow cytometry is a valuable tool for the analysis of phytoplankton and other suspended particles because of its
speed and quantitative measurements, but the method’s oceanographic application has been limited by the need to take
discrete water samples for analysis on board ship or in the laboratory. For this reason, we have developed an automated
flow cytometer (FlowCytobot) that can operate in situ and unattended. The new instrument utilizes a diode-pumped
532 nm laser and can measure light scattering and fluorescence of particles as small as Synechococcus cells. For
operation at the LEO-15 mooring site off New Jersey, it is connected to shore by power and communications cables,
and is controlled by a microcomputer whose programming can be loaded remotely. The sampling rate is adjustable; we
have used from 12.5 to 50ml min�1. Integrated signals from each particle (two light scattering angles and two
fluorescence emission bands) are transmitted to a shore-based computer, where they are accessible by Internet and can
be examined in real time. FlowCytobot was deployed at LEO-15 from late July to early October 2001, where it operated
continuously (aside from occasional power or communications interruptions at the node) without outside intervention.
Even after 2 months of in situ operation, FlowCytobot’s measurements were similar to those of a conventional flow
cytometer, as shown by analysis of a discrete water sample taken at the location of the sample inlet. In addition to
documenting seasonal and event-scale changes in size distributions and population abundances in the pico- and
nanophytoplankton, FlowCytobot will be useful for examining diel cycles in light scattering and pigment fluorescence
of cells in situ that may allow estimation of rates of production by different phytoplankton groups.
r 2003 Elsevier Science Ltd. All rights reserved.
Keywords: Phytoplankton; Flow cytometry; Mooring; Time series; Fluorescence; Scattering
1. Introduction
Detailed knowledge of the composition andcharacteristics of the particles suspended in the seais crucial to an understanding of the biology,optics and geochemistry of the oceans. The
composition and size distribution of the phyto-plankton community, for example, help determinethe flow of carbon and nutrients through anecosystem (Chisholm, 1992), and can be importantindicators of change in coastal environmentssubject to anthropogenic disturbances such asnutrient loading and pollution (Cloern, 2001).Flow cytometry, which provides rapid andquantitative measurements of individual sus-pended microscopic particles, has proved a
0967-0637/03/$ - see front matter r 2003 Elsevier Science Ltd. All rights reserved.
doi:10.1016/S0967-0637(03)00003-7
valuable tool for studies of cells in the size rangeB0.5–30 mm (Olson et al., 1991, 1993; Vaulot et al.,1995; Vaulot and Marie, 1999; Reckermann andColijn, 2000; Li and Dickie, 2001). In a flowcytometer, several optical measurements are madeas each particle in a water sample passes through afocused laser beam. Light scattering signalsprovide information about the distributions ofparticle size and composition, while fluorescencedata allow discrimination between phytoplanktonand other particles, and identification of majorphytoplankton groups. Time series of flow cyto-metric measurements have contributed to ourunderstanding of phytoplankton species succes-sion (Olson et al., 1990a; DuRand et al., 2001; Liand Dickie, 2001) and growth processes (DuRandand Olson, 1998; Shalapyonok et al., 1998; Andr!eet al., 1999; Jacquet et al., 2001; Shalapyonok et al.,2001) and of the effects of phytoplankton growthon bulk water optical properties (DuRand andOlson, 1996).Although flow cytometry has provided new
insights about pico- and nanoplankton, its usehas been limited by the need to take discrete watersamples for analysis on board ship or in thelaboratory. This means that the sampling resolu-tion, frequency and duration of studies are limitedby the availability of ship time and wire time.Continuous, extended time series studies will allowus to investigate the responses of an ecosystem toenvironmental changes on several scales, includingthe diel cycle of light and dark, events such asstorms and upwelling, and seasonal progressions.For these reasons, we have developed a submer-sible flow cytometer, FlowCytobot, which canoperate in situ and unattended.FlowCytobot’s design is similar to that of
laboratory-based flow cytometers in that a sea-water sample is injected into the center of a sheathflow of particle-free water, which serves to confineall the particles to the center of the flow cell (andthus to uniform illumination by a focused laserbeam). Because we originally assumed that such aflow system would be too easily contaminated ordisturbed to work in the marine environment forextended periods, our first design incorporated asimple ducted flow of raw seawater in which theanalysis region was optically defined by intersect-
ing orthogonal laser beams: only particles whichpassed through both beams simultaneously wereanalyzed. We found that such an approach wasworkable, but the complexities and compromises itentailed persuaded us to return to the ‘‘conven-tional’’ fluid focusing approach. FlowCytobotdiffers from laboratory flow cytometers in that itis contained in a watertight pressure housing, butmore significantly, it operates continuously andautonomously, under the direction of a micro-computer whose programming can be modified bya remote operator. Programmable operationsinclude data acquisition and transfer to shore,adjustment of sampling frequency and rate ofinjection, injection of internal standard beads,flushing the flow cell or sample tubing withdetergent, backflushing the sample tubing toremove potential clogs, adding sodium azide tothe sheath reservoir to prevent biofouling of theinternal surfaces, and adjustment of the lasersteering mirror.FlowCytobot is similar to another autonomous
instrument, CytoBuoy (Dubelaar et al., 1999), inthat it recycles sheath fluid and uses a diode-pumped laser, but it differs in important ways.FlowCytobot is linked to shore by power andcommunications cables, while CytoBuoy is batterypowered and transmits data to shore by radio.These features allow CytoBuoy more flexibility asto location, but limit its duty cycle and datatransmission rate. The number of ocean observa-tories suitable for deployment of instruments likeFlowCytobot is small at present (we are aware of3), but we anticipate a growing network of suchsites, in open ocean as well as coastal waters(Glenn et al., 2000b).The LEO-15 observatory includes two perma-
nent underwater nodes with ports for providing insitu instruments with power and data connectionsto a shore lab. A variety of continuous measure-ments are available at the nodes (although formost of our deployment only bottom temperatureand wave height were being measured), andmeteorological and other environmental measure-ments are available from the shore station (Glennet al., 2000a). The observatory is an ideal locationto study effects of environmental forcing onplankton community structure. Southwesterly
R.J. Olson et al. / Deep-Sea Research I 50 (2003) 301–315302
winds along the coast cause recurrent upwelling tooccur at LEO-15 during the summertime, withconsequent nutrient enrichment and phytoplank-ton blooms. Suspended particles (from bothphytoplankton growth and resuspension of sedi-ment) can increase in concentration during theseupwelling episodes (Schofield et al., 2002); uponcessation of upwelling (due to changing winds),water column stratification and remineralizationprocesses can deplete dissolved oxygen (Pearceet al., 1982), damaging benthic organisms andfisheries. Storms may also interrupt these processesby re-mixing the water column. During theevolution of a bloom, species succession has beenobserved, with a diatom-dominated crop duringupwelling giving way to dinoflagellates uponstratification (Kerkhof et al., 1999); presumablythese kinds of changes in community compositionwill be reflected in cell size distributions as well.
2. Methods and materials
2.1. Instrument overview
FlowCytobot is based on a 532 nm solid-statelaser for excitation, combined with a quartz flowcell and photomultiplier detectors for light scatter-
ing and fluorescence. A sampling valve systemselects from ambient seawater, and reservoirs ofsolutions containing detergent or standard micro-spheres for calibration. Sheath water is recircu-lated during operation. The self-containedunderwater system includes signal processingelectronics and a computer for sample controland data acquisition. Power supply to the instru-ment, real-time data transmission to a shore-basedcomputer, and user-initiated communication tochange instrument status were accomplished viathe cables to the permanent underwater node atthe sampling site.
2.1.1. Fluidics
Seawater is drawn to the instrument housing(Fig. 1) through a 2mm copper screen (to elim-inate large particles) by a SeaBird pump on theoutflow side (B1 lmin�1). Inside the housing, aprogrammable syringe pump with a 6-way dis-tribution valve (Kloehn, Inc.) samples this flowthrough an 80 mm Nitex mesh on the end of0.5mm ID PEEK tubing. The sample is pumpedand injected into the center of a sheath of particle-free (0.2 mm-filtered) seawater flowing at a rate of5mlmin�1 through a flow cell with dimensions180 mm� 400 mm. The rate of sample injection isadjusted so that the particles in the sample pass
Fig. 1. Schema of fluidics system. The distribution valve at the syringe pump allows access to several reservoirs inside the instrument.
Beads are injected periodically to monitor performance, sodium azide is added to the sheath fluid to prevent internal fouling, and
detergent can be added to the flow cell and tubing (during this operation, the sheath pump is stopped and the laser is blocked by a
hydraulically operated shutter).
R.J. Olson et al. / Deep-Sea Research I 50 (2003) 301–315 303
one at a time through a laser beam; at present weinject sample seawater with a 0.25-ml syringe at12.5–50 ml min�1. Sheath fluid (seawater) is re-circulated through a 0.2 mm cartridge filter by aminiature gear pump (MicroPump model 188 withPEEK gears and 1.6mm ID PEEK tubing); theexcess volume due to injection of sample overflowsto the outside of the housing.
2.1.2. Optics and signal processing
The laser (532-nm, 100mW diode-pumped solidstate laser, Coherent, Inc.) beam, which is diver-ging in the horizontal direction, is focused by aspherical lens (20-mm focal length) to provide anelliptical beam spot with vertical and horizontaldimensions of 5 mm� 100 mm (Fig. 2). As eachparticle passes through the beam, it scatters laserlight in the forward and side directions, and mayemit red fluorescence from chlorophyll and orangefluorescence from phycoerythrin. This light iscollected by lenses and directed by dichroic filtersand mirrors to four independent photomultipliertubes (PMTs) with appropriate optical filters, andconverted to voltage signals by preamplifierswhose design follows that of the Coulter EPICSflow cytometer (R. Auer, pers. comm.). Signals are
integrated during the time that they are above anadjustable threshold level. The logic circuitry canbe configured to allow any of the signals to triggerdigitization and storage of the integrated signalsfrom all four detectors; at present we usechlorophyll fluorescence to trigger acquisition.The instrument was constructed on an optical
bench (12 in� 24 in) using off-the-shelf compo-nents, except for the signal processing and powersupply boards, which were custom designed(Fig. 3). The flow cell (modified for pressures upto 130 psi by machining o-ring grooves for largero-rings between the flow cell and its housing) andthe fluorescence collection lens were from aFACScan flow cytometer (BD Biosystems). Theforward light scattering lens was from a CoulterEPICS flow cytometer. Optical mounts wereobtained from Newport Corp. and Thor Labs,Inc.; optical filters (532DF10 for scattered laserlight, 680DF40 for chlorophyll, and 574DF40 forphycoerythrin fluorescence) and dichroics (630 nmshort pass, 550 nm long pass) were from OmegaOptical and Andover Optical. To detect green andorange light we used miniature modular PMTsfrom Hamamatsu (HC140-A); for chlorophyllfluorescence, which requires high red sensitivity,we used a Hamamatsu R1477 side-on tube (withHC123-01 integrated socket-HV supply). ThePMT signals were linearly amplified; to increasethe dynamic range of the measurements, a pair ofamplifiers, with 30-fold difference in gains, wasused for each signal. After integrating the signalsto 14-bit precision and choosing the appropriatesignal from each pair, we obtain about 4 decadesof useful dynamic range. This allows us to measuresignals from Synechococcus (B1 mm) up toB10 mm phytoplankton cells.
2.1.3. Control system
All functions of the instrument are controlled byan on-board microcomputer (Tattletale 8, OnsetComputer Corp.), according to a program loadedfrom a shore-based computer. The shore computercan be operated locally or by remote control overthe Internet (using PCAnywhere software and amodem-controlled power switch). The data aredisplayed in real time as 2-parameter dot plots formonitoring performance. Because we found that
Fig. 2. Schema of optical system showing light path of the
excitation laser beam and collection of scattered (forward and
side angles) and fluoresced light of the wavelengths indicated, in
relation to the flow cell. Water samples containing particles are
injected into the central channel of the flow cell as described in
Fig. 1.
R.J. Olson et al. / Deep-Sea Research I 50 (2003) 301–315304
connecting to the shore-based computer viaPCAnywhere sometimes interfered with datatransfer from the instrument, we use a Webcamera to observe the shore-based computermonitor remotely for routine checks when nointervention is planned.
2.1.4. Data analysis
For each particle, eight channels of signal datawere stored (four parameters at two gain settingseach), with a millisecond-resolution time stamp foreach 200-event data transfer. The data wereanalyzed using software written in MATLAB(The Mathworks, Inc.). First, we calculated thevolume of seawater analyzed as a function of time,taking into account periods when no data werebeing acquired (re-filling the sampling syringe andtransferring data to shore) and merging the high-and low-gain data for each parameter. Next weobtained the number and properties of thestandard beads in the samples in which theyoccurred. The data from the rest of the sampleswere then classified into one of several phyto-plankton populations. Phycoerythrin (PE)-positivecells (Synechococcus or cryptophytes) and PE-
negative cells (encompassing all other phytoplank-ton) were classified on the basis of orangefluorescence. Within these groups, a customizedclustering algorithm (utilizing side scattering andchlorophyll fluorescence data for each cell) wasused to distinguish Synechococcus from crypto-phytes, and up to three groups of ‘‘eukaryoticphytoplankton’’. The distinction between largeand small eukaryotic phytoplankton groups wasnot always obvious, so the use of the terms‘‘picoeukaryotes’’ and ‘‘nanoeukaryotes’’ is onlyapproximately correct for the data presented here.
2.2. Simple ducted flow with intersecting laser
beams
We were initially concerned that disturbances inflow (e.g., from partial clogging or bubbles) wouldbe a recurrent problem during unattended opera-tion, so we explored the use of a simple ductedflow of seawater through the flow cell as analternative to that of hydrodynamic focusing ofthe sample stream in a particle-free sheath stream.In this configuration, the Micro Pump pulled rawseawater through the flow cell at 5mlmin�1, and
Fig. 3. Optics, fluidics, and electronics are mounted in a frame that rests on rubber wheels inside a 16 in diameter aluminum tube
(removed here). At the top of the instrument, the syringe pump and bead reservoir are visible; on the left end is the bulkhead with
sampling, data, and power connections; and at the right end are the signal conditioning electronics and computer. The optical
components are in the center.
R.J. Olson et al. / Deep-Sea Research I 50 (2003) 301–315 305
two tightly focused diode laser beams (Lasiris,50mW, 780 and 830 nm, respectively) werefocused on the center of the flow cell (along withthe third beam from the 532-nm laser, which wasless tightly focused) to define the sensing region(Fig. 4). Only when light scattering signals from allthree lasers occurred simultaneously (which meantthat the particle in question had passed throughthe central, uniform, part of the green laser beam),were the signals from a given particle acquired.
2.3. Data quality
Flow cytometric data can be influenced by manyfactors other than the frequency and character-istics of the sample particles, including electronicnoise, optical misalignment, and biased sampling.The capability to monitor the instrument duringoperation is therefore critical; the capability tomake adjustments during operation is also desir-able. FlowCytobot’s operating mode includesperiodic analyses of standard fluorescent plasticbeads that serve to monitor optical alignment andstream flow in the flow cell. A suspension ofbeads (1 mm, red-fluorescing; Molecular Probes) in
a 120-ml reservoir (a spring-loaded plastic syringe)is sampled several times in succession at pre-programmed intervals (typically every 20 h), andanalyzed analogously to the seawater samples.Because the beads eventually settle in the storagereservoir, we mixed the reservoir by attaching amagnet to the syringe pump arm and placing amagnetic stirring bar in the syringe; the stirring barwas dragged back and forth through the beadsuspension with every syringe move.Analysis of beads from an internal reservoir will
not reveal problems with the seawater samplingsystem. This would require mixing beads with theseawater outside the instrument, which is beyondthe capabilities of the present instrument. Toprevent (or ameliorate) clogging of the seawatersample tube (or its 80-mm Nitex screen), thesampling program incorporates backflushing ofthe seawater sample tubing, as well as soaking it indetergent during the period when beads are beingsampled.To evaluate the performance of the instrument
in actual use, we carried out a parallel samplingfor analysis by conventional laboratory flow cyto-metry, on September 27, 2001 (when FlowCytobot
Fig. 4. Schema of flow cytometer layout during tests of an optically defined sensing region. (A) Cross-sectional view of the flow cell,
where the intersection of two IR lasers defines a sensing region in the center of a third, 532 nm, laser beam. All three beams are in the
same plane, with particles flowing upward through the flow cell channel. Data are acquired only from particles passing through all
three beams simultaneously, ensuring that signal collection is triggered only when particles are in the central, uniform part of the green
beam. (B) Layout of the optical and detection systems. For simplicity, not all lenses, dichroic mirrors and detectors are shown.
R.J. Olson et al. / Deep-Sea Research I 50 (2003) 301–315306
had been in operation at LEO-15 for 2 months). Asample obtained from 5-m depth at the LEO-15site using a Niskin bottle was fixed with 0.1%glutaraldehyde and stored in liquid nitrogen, andwas later analyzed at Woods Hole OceanographicInstitution (WHOI) with a modified CoulterEPICS flow cytometer (Green et al., 2003).
2.4. Size calibration
To enable us to estimate the size of phytoplank-ton cells, we calibrated FlowCytobot’s lightscattering measurements against measurements ofcell volume as determined with a Coulter Multi-sizer, for 11 monospecific laboratory cultures ofphytoplankton, ranging in diameter from B1 to10 mm (as in Shalapyonok et al. 2001).
2.5. Deployment at LEO-15
The Longterm Ecosystem Observatory at 15m(LEO-15) consists of two unmanned seafloorobservatories 1.5 km apart, approximately 9 km
off the central coast of New Jersey, and is designedto collect long-term oceanographic data with hightemporal resolution (Glenn et al., 2000a). In situinstruments are deployed at the LEO site andconnected to a fiber optic data/power link thattransfers data, in real time, back to the shorestation.For deployment, FlowCytobot was mounted in
an aluminum frame, which was clamped by diversinto a platform anchored (by four pipes driveninto the sediment) a few meters from node ‘‘B’’(Fig. 5). Adjacent to the frame, a subsurface floatwith separate anchor supported a sample collec-tion tube (1
2in diameter Tygon) that was held at the
desired depth (5m at present) by attaching it tothe subsurface float line. Electrical connection tothe node is by separate power supply andcommunications cables with wet mate-able con-nectors and Kellums grips. We used the 120V DCpower available at the Guest Auxiliary Connectorand the RS232 communications available at theGuest Main Connector. The raw data fromFlowCytobot was transferred to shore after every
Fig. 5. Configuration of FlowCytobot at the LEO-15 mooring site off New Jersey. Inset: FlowCytobot in its frame, after testing off the
WHOI dock.
R.J. Olson et al. / Deep-Sea Research I 50 (2003) 301–315 307
200 events, at 9600 baud. Typical data acquisitionrates were 2Mbh�1, representing B105 cellsanalyzed in an hour. The data was stored on adedicated computer, and periodically transferredover the Internet to the laboratory at WHOI forprocessing.For tests off the WHOI dock or in the
laboratory, power was supplied to FlowCytobotand communications were carried out via a ‘LEOnode simulator’ constructed by C. van Alt atWHOI.
3. Results and discussion
3.1. Exploration of a simple ducted flow system
As an alternative to fluid focusing and the use ofparticle-free sheath fluid to force all sampleparticles through the center of the laser beam, weinvestigated an approach using a simple ductedflow of raw seawater and an optically definedsensing region (see Fig. 4). Our results indicatedthat such an approach is feasible but requiresrelatively complex data analysis involving assump-tions about particle properties. Specifically, theGaussian intensity profiles of the laser beams usedto define the sensing region cause the samplingvolume, and the distribution of particle sizesdetected, to be a function of the light scatteringproperties of the particles. For example, while asmall particle (i.e., with small light scattering) mustpass through the central, most intense part of theIR beam to produce a signal above threshold, alarger particle may do so even if it passes throughthe outer edge of the beam. To obtain accurate cellconcentrations, then, a scattering-dependent cor-rection must be applied to the data. We empiri-cally derived a correction algorithm by analyzingknown mixtures of standard particles, and foundthat it was successful for correcting mixtures ofdifferent-sized phytoplankton (Fig. 6).In addition, however, we found that a whole-
seawater sample stream caused problems with theraw data when particles were very abundant. Cellsignals often included light scattering from non-target particles present outside of the analysisregion (but still in the main laser beam). These
100 150 200 2500
0.01
0.02
0.03
0.04
0.05
Side Scattering Channel
Fra
ctio
n of
bea
ds d
etec
ted
0.5 µm
1 µm
2 µm
4 µm
6 µm
0.1 1 100
500
1000
1500
2000
2500
Side Scattering, 1µm bead units
Cel
ls m
l -1
cha
nnel
-1
EPICS
Nannochloris
Dunaliella
1 100
100
200
300
400
Nannochloris
Dunaliella
Side Scattering, 1µm bead units
Cel
ls m
l -1 c
hann
el -1
bef
ore
corr
ectio
n
Before Correction After Correction
FlowCytobot
0
0.5
1
1.5
2
x 104
Cel
ls m
l -1 c
hann
el -1
afte
r co
rrec
tion
Fig. 6. With a simple ducted flow and optically defined
sampling region, FlowCytobot’s detection efficiency was size
dependent (top panel). A correction algorithm was obtained by
analyzing known concentrations of beads of different sizes.
Cultures of phytoplankton of different sizes (Dunaliella, 8mm;Nannochloris, 2.5mm) were analyzed with the conventional flowcytometer (EPICS, middle panel), and with FlowCytobot using
an optically defined sampling region (bottom panel); the large
cells were detected with higher frequency than the small cells.
After applying the bead-derived correction, cell concentrations
from FlowCytobot (4600 and 34,000 cellml�1 for Dunaliella
and Nannochloris) were similar to those from the conventional
flow cytometer (5800 and 39,000 cellml�1).
R.J. Olson et al. / Deep-Sea Research I 50 (2003) 301–315308
additions to the signals were usually small (pre-sumably from bacteria or detritus, which are verynumerous in coastal waters) but they caused thelight scattering of small cells such as Synechococ-
cus to be overestimated, and effectively limited thelower size of particles that could be analyzed. Thisproblem could be reduced in laboratory tests bydiluting the seawater sample with filtered seawater(data not shown), but this is not a practicalsolution for in situ sampling.Because of this problem with the raw seawater
approach (and because of its complexity ingeneral), we returned to the ‘‘conventional’’ flowcytometric approach of injecting sample seawaterinto a filtered sheath stream.
3.2. Comparison of FlowCytobot and a laboratory
flow cytometer
FlowCytobot is constructed in large part fromconventional flow cytometer components, so it isnot surprising that the performance of the twokinds of instruments is similar, as shown byparallel analyses of standard fluorescent beadsand natural seawater samples. In laboratory tests,counting standard microspheres at concentrationsup to 5� 105 particlesml�1, the two instrumentsgave similar results (Epics Count=1.08*FlowCy-tobot Count, r2 ¼ 0:99; n ¼ 7). FlowCytobot’sanalysis rate at the highest concentration tested(at a water sampling rate of 0.05mlmin�1)corresponds to B150 signals s�1. To test effectson FlowCytobot of extended operation in the field,we compared its results with those of a watersample from approximately the same location andtime, but analyzed by laboratory flow cytometry.Cell concentrations of populations defined byclustering on the basis of light scattering andfluorescence characteristics were similar for thetwo instruments (Fig. 7): EPICS and FlowCytobotgave results of 6500 and 6200, 540 and 300, and11,200 and 8300 cell ml�1 for Synechococcus, cryp-tophytes, and ‘‘other eukaryotic phytoplankton’’,respectively. We cannot explain why all threepopulations were less numerous according toFlowCytobot, but we note that in the test shownhere the two instruments were not analyzingexactly the same water sample; the EPICS results
are from a single preserved aliquot from a Niskinbottle sample, while the FlowCytobot results arefrom three 0.25-ml samples analyzed in situ overthe course of an hour.The cell-specific optical measurements are not
directly comparable between the two instrumentsbecause of design differences. FlowCytobot’s532 nm excitation light is more efficiently absorbedby the antennae pigments of Synechococcus (atleast in coastal strains with low-phycourobilinphycoerythrin) than that from the 488-nm laser inthe EPICS. In contrast, accessory pigments ofmost eukaryotes absorb 532-nm light less effi-ciently than 488-nm light. This causes the chlor-ophyll fluorescence of Synechococcus as measuredby FlowCytobot to be high relative to that of theeukaryotes (and suggests that Synechococcus cellsare easily detected by FlowCytobot). Conversely,while FlowCytobot appears able to easily measurethe small eukaryotes in coastal waters, it is not wellsuited for very small cells that lack phycoerythrinor carotenoid accessory pigments, such as open-ocean Prochlorococcus, which have very lowabsorption at 532 nm. Measuring such cells withFlowCytobot probably will require a blue solid-state laser with higher output than is presentlyavailable.A less obvious difference in the flow cytometric
signatures from the two instruments, that of therelative positions of the cells and beads in terms oflight scattering, is presumably caused by differinglight scattering collection angles (FlowCytobot’sside light scattering detector integrates over alarger angular distribution than that of the EPICS)in combination with the specific volume scatteringfunctions of cells and plastic beads. Calibration ofmeasurements of light scattering with CoulterMultisizer measurements of cell volume suggeststhat FlowCytobot light scattering signals can beused to estimate cell size with confidence (Fig. 8).A power law function explained 99% of thevariance between cell volume and side angle lightscattering.
3.3. LEO-15 deployment
FlowCytobot was deployed at LEO-15 from lateJuly to early October 2001. Beads from an internal
R.J. Olson et al. / Deep-Sea Research I 50 (2003) 301–315 309
reservoir were analyzed approximately daily tomonitor instrument performance (Fig. 9). A gra-dual decline in both concentration and mean beadoptical properties was observed during the firstmonth of the deployment, followed by a precipi-tous decline during the week of September 13; onSeptember 17 we re-aimed the laser beam byremote control, which restored the optical signalsnearly to their original values. Beads sinking oradhering to the walls of the reservoir may beresponsible for the decline in bead concentration,but we cannot be sure. Likewise, we cannot be surewhat caused the decline in sensitivity; it could havebeen caused by a shift in flow of the sample corestream, although the fact that the bead propertiesremained stable for many days after adjustment ofthe laser beam suggests that flow was not unstableand rather that the beam itself had shifted.
EPICS flow cytometer (laboratory)
Red
Flu
ores
cenc
e
100
101
102
103
104
105
FlowCytobot (in situ)
100
101
102
103
104
0
100
200
300
400
500
Side Light Scattering
Fre
quen
cy
1 µm beads
CryptophytesOther EukaryotesSynechococcus
102
103
104
105
106
Side Light Scattering
1 µm beads
(A) (B)
(C) (D)
Fig. 7. Analyses of phytoplankton at LEO-15 measured by a Coulter EPICS flow cytometer (A, C) and by FlowCytobot (B, D). A
discrete sample collected from the depth of FlowCytobot’s sample intake at 12:00 on September 27, 2001, was analyzed with a modified
EPICS flow cytometer (Green et al., 2003). The results are compared to those from FlowCytobot during the 1 h time period
encompassing the Niskin sampling. The data are plotted in log units to show cells ranging in size from 1mm (Synechococcus) to
>10mm (cryptophytes and other eukaryotes). A and B are 2-parameter plots of all the particles with chlorophyll fluorescence, with
lighter shading indicating higher concentrations of cells. Populations of cryptophytes, Synechococcus, and eukaryotic phytoplankton
were discriminated as described in the text and their light scattering distributions presented separately in C and D. As expected, the
appearance of the flow cytometric signatures is not identical (see text for details). The legend in C also applies to D.
10-2
10 -1
100
101
102
10 -1
100
101
102
103
Side Scattering (relative to beads)
Cou
lter
volu
me
( µl
)
Volume = 9.1553(Side Scattering1.1088)
R2 = 0.988
Fig. 8. Relationship between phytoplankton cell volume as
measured with a Coulter Multisizer and side light scattering as
measured by FlowCytobot. A power law function explained 99%
of the variance between cell volume and side angle light scattering.
R.J. Olson et al. / Deep-Sea Research I 50 (2003) 301–315310
Laboratory tank tests indicate that large changesin water temperature (B10�C) can affect laseralignment, although on several occasions suchchanges in temperature were observed with noobvious effects on performance (data not shown).
The limiting factor in FlowCytobot’s mooredoperation was wear and eventual leaking of thepiston seal in the syringe used to move samplewater. We believe this began after 2 months ofcontinuous operation, suggesting that replacement
07_Aug 17_Aug 27_Aug 06_Sep 16_Sep 26_Sep0
0.5
1
Bea
d P
rope
rtie
s
Date in 2001
Red FluorescenceSide ScatteringOrange FluorescenceForward ScatteringConcentration
Fig. 9. Concentration and mean optical properties of internal standard beads analyzed during deployment at LEO-15.
0
2
4
6x 10
5
Synechococcus
0
1
2
3x 10
5
Picoeukaryotes
0
1
2
x 105
Nanoeukaryotes
Cel
ls m
l-1
07_ Aug 17_ Aug 27_ Aug 06_Sep 16_ Sep 26_ Sep0
1000
2000
3000
4000Cryptophytes
Date in 2001
Fig. 10. Cell concentrations of different phytoplankton groups at LEO-15 as a function of time. Each datum represents an hourly
mean value. Gray regions indicate night. Note that the distinction between large and small eukaryotic phytoplankton groups was not
always obvious, and that the low numbers of cryptophytes present after the first week of the deployment often made measurements of
this population unreliable.
R.J. Olson et al. / Deep-Sea Research I 50 (2003) 301–315 311
of the syringe at intervals on this order willprobably be necessary during sustained operation.A second anticipated problem, that of sample
contamination by cell growth in the Tygon tubingbringing water down to the instrument, wasapparently not serious, based on our comparisonwith an independent water sample analysis. Athird potential problem, fouling inside the instru-ment (flow cell, PEEK tubing, and filter cartridge),was apparently prevented effectively by the addi-tion of sodium azide to the recirculating sheathfluid (final concentration B0.02%) and/or deter-gent treatments and backflushing of the sampletubing (see Fig. 1).The optical signals for phytoplankton cells were
normalized to the nearest bead sample, since we
believe these declines were caused by shifts in laserillumination or flow stream position, which wouldaffect cells as well as beads. (We have not appliedan adjustment to the cell concentration data; theobserved changes in cell concentrations were farlarger than those in bead concentrations so thiswould be a relatively small adjustment). Exceptduring the event around September 17, the declinein bead concentration was probably not causeddirectly by declining optical sensitivity; the redfluorescence of the beads is several-fold higherthan the detection threshold.Large changes in cell concentration (B2 orders
of magnitude) were noted for all phytoplanktongroups (Fig. 10), which could be due to physicalmixing and advection of different water masses at
0
0.05
0.1 Synechococcus
0
0.2
0.4Picoeukaryotes
0
2
4
6
8Nanoeukaryotes
Mea
n C
ell S
ide
Sca
tterin
g (r
elat
ive
to b
eads
)
07_Aug 17_Aug 27_Aug 06_Sep 16_Sep 26_Sep0
10
20
30
40Cryptophytes
Date in 2001
Fig. 11. Mean side light scattering (relative to 1mm beads) of different phytoplankton groups as a function of time. Each datum
represents an hourly mean value. Gray regions indicate night. Note that the distinction between large and small eukaryotic
phytoplankton groups was not always obvious, and that the low numbers of cryptophytes present after the first week of the
deployment often made measurements of this population unreliable.
R.J. Olson et al. / Deep-Sea Research I 50 (2003) 301–315312
the sampling site. Changes in mean cell opticalproperties of each group were much smaller thanfor cell concentrations, on the order of 2-fold(Fig. 11), as expected for well-defined populations.In addition, closer examination reveals distinct dielpatterns, especially in light scattering (Fig. 12).These patterns presumably reflect cell growth anddivision, as discussed elsewhere (Olson et al.,1990b; DuRand and Olson, 1996; Shalapyonoket al., 1998; Jacquet et al., 2001); in bothSynechococcus and eukaryotic phytoplankton,mean cell light scattering increased during theday and decreased at night. The decrease some-times began earlier in the case of Synechococcus,consistent with the finding that cell division inSynechococcus occurs in daylight hours (Water-bury et al., 1986), earlier than at least some other
kinds of phytoplankton (Vaulot and Marie, 1999;Jacquet et al., 2001; Binder and DuRand, 2002).The large declines in cell concentrations that
occurred in September were accompanied by watercolumn mixing that may have reduced cell growthrates through light limitation (Sosik et al., 2003).The increases in cell light scattering during thesame time period could be related to such loweredgrowth rates, but could also reflect changingspecies composition.
4. Conclusion
Although there are several aspects of FlowCy-tobot that can be improved (e.g., we hope toreduce its size, increase its sampling rate, and
Fig. 12. Mean side light scattering (relative to 1mm beads) of different phytoplankton groups at LEO-15 during the week of July 29 to
August 5, 2001, and solar radiation (Wm�2, bottom panel) measured at a meteorological tower on shore. Each datum represents an
hourly mean value. Gray regions indicate night. Communications problems between FlowCytobot and the shore station caused data to
be lost around 1 August.
R.J. Olson et al. / Deep-Sea Research I 50 (2003) 301–315 313
improve its reliability), the deployment at LEO-15demonstrates that in situ flow cytometric measure-ments of phytoplankton are practical, and that thisapproach can provide quantitative informationover an unprecedented range of time scales. Theobserved diel patterns in cell size can reveal growthrates of the phytoplankton even though thepatterns in cell concentration are dominated bynon-biological mechanisms such as water massexchange (Sosik, et al., submitted), and shouldhelp us to understand the dramatic changes incell populations observed on longer time scales.Longer deployments, in concert with more com-prehensive environmental and hydrographic mea-surements, are now needed.
Acknowledgements
This work was supported by NSF grants OCE-9416551, 9907002, 0119915, DOE grant DE-FG02-95-ER61982, ONR grant N00014-93-1-1171, and NOAA/NURP grant NA06RU0139.We thank Tom Hurst and Glenn McDonald forelectrical and mechanical engineering, and RosePetrecca and the LEO team for logistical support.
