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Expanding Single Particle Mass Spectrometer Analyses for the Identification of Microbe Signatures in Sea Spray Aerosols Camille M Sultana, Hashim Al-Mashat, and Kimberly Ann Prather Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.7b00933 • Publication Date (Web): 28 Aug 2017 Downloaded from http://pubs.acs.org on September 4, 2017

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Analytical Chemistry

Expanding Single Particle Mass Spectrometer Analyses for the Identification of Microbe Signatures in Sea Spray Aerosols Camille M. Sultana1, Hashim Al-Mashat1, Kimberly A. Prather1,2,* 1

Department of Chemistry and Biochemistry, University of California, San Diego, La

Jolla, CA 92093-0314; 2

Scripps Institution of Oceanography, University of California, San Diego, La Jolla, CA

92093; 1

ABSTRACT: Ocean-derived microbes in sea spray aerosols (SSA) have the potential to

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influence climate and weather by acting as ice nucleating particles in clouds. Single

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particle mass spectrometers (SPMS), which generate in situ single particle composition

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data, are excellent tools for characterizing aerosols under changing environmental

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conditions as they can provide high temporal resolution and require no sample

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preparation. While SPMS have proven capable of detecting microbes, these instruments

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have never been utilized to definitively identify aerosolized microbes in ambient sea

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spray aerosols. In this study, an aerosol time-of-flight mass spectrometer was used to

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analyze laboratory generated SSA produced from natural seawater in a marine aerosol

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reference tank. We present the first description of a population of biological SSA mass

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spectra (BioSS), which closely match the ion signatures observed in previous terrestrial

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microbe studies. The fraction of BioSS dramatically increased in the largest supermicron

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particles, consistent with field and laboratory measurements of microbes ejected by

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bubble bursting, further supporting the assignment of BioSS mass spectra as microbes.

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Finally, as supported by analysis of inorganic ion signals, we propose that dry BioSS

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particles have heterogeneous structures, with microbes adhered to sodium chloride

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nodules surrounded by magnesium-enriched coatings. Consistent with this structure,

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chlorine-containing ion markers were ubiquitous in BioSS spectra and identified as

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possible tracers for distinguishing recently aerosolized marine from terrestrial microbes.

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(INTRODUCTION START)

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Microbial cells ejected in sea spray aerosols (SSA) by bubble bursting at the

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ocean surface1–7 are of interest because of their potential to act as ice nucleating particles

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(INP)8–13 within clouds. However, common offline methods used to detect and enumerate

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aerosolized microbial cells have poor temporal resolution and often require a significant

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investment of time in sample collection, preparation, and analysis. Therefore these

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traditional offline techniques are not well suited to monitoring microbes in the

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atmosphere. To capture changes in aerosol composition, ground-based and aircraft

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studies require high temporal resolution measurements on the order of seconds to minutes.

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In addition, knowledge of the surface composition of individual particles is critical for

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understanding their ice nucleating capabilities.14–16 However, with bulk collection

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methods commonly employed for offline microbial analyses, such as impingers or filters,

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information on the chemical morphology of microbe-containing particles is not

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maintained.

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Single particle mass spectrometers (SPMSs) have been shown to be able to detect

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aerosolized microorganisms, providing real-time, single particle, size resolved, chemical

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composition data without requiring any sample preparation.17–19 SPMS studies of isolated

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aerosolized standards of microbes and plant detritus all report similar mass spectra (MS)

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indicative of cellular material, rich in potassium, phosphate, and a number of organic

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nitrogen ion markers.17–21 However, MS with such cellular signatures have only been

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identified in one study of an ambient aerosol population22 and a small number of studies

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of insoluble residues in precipitation and cloud water samples,22–25 which have been

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attributed to terrestrial microbial sources. Identifying MS generated from microbe-

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containing particles within an SSA population is analytically challenging as ion markers

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often considered characteristic of cellular single particle MS are also generated by

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chemical species dissolved in seawater. This study uses isolated SSA to identify a narrow

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set of likely single particle biological mass spectra (BioSS) that can be used in future

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attribution studies of microbes or microbe fragments in the atmosphere.

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Isolated SSA was produced from natural seawater in a marine aerosol reference

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tank (MART) and analyzed with aerosol time-of-flight mass spectrometry (ATOFMS). In

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this study, identified BioSS signatures are consistent with phosphate- and potassium-rich

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MS reported in previous SPMS studies of terrestrial microbes. We also show the first

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application of data analyses utilizing particle size and ion signal dependence on total ion

53

intensity and laser pulse energy to further confirm BioSS mass spectra as microbe-

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comtaining SSA particles. In addition, using this information, details on the structure of

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BioSS particles are proposed and studied as a function of changing seawater chemical

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and biological composition.

57 58

EXPERIMENTAL SECTION

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MART Induced Phytoplankton Bloom and SSA Generation

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60 L of coastal Pacific seawater was collected from the ocean surface at Scripps Pier (La Jolla, CA; 32°51´56.8"N: 117° 15´38.48"W; 275 m offshore) on 9/10/13 18:00.

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The ocean seawater chlorophyll-a concentration, water temperature, and salinity were 2.9

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mg/m3, 19.9 °C, and 33.5 PSU at the time of collection. The seawater was added to a 100

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L MART system without treatment or filtering and allowed to equilibrate to room

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temperature. Details of particle generation and phytoplankton bloom initiation have been

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discussed extensively previously, however a brief summary is given here.26 Beginning on

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9/11/2013, SSA particles were generated in the MART using the pulsed plunging

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waterfall technique described in detail previously, with a 4 second waterfall duty cycle.

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After initial generation of SSA particles from the untreated seawater, a diatom growth

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medium commonly known as Guillard’s f medium (ProLine Aquatic Ecosystems) (Table

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S-1) was added to promote phytoplankton growth, and then SSA particles were again

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generated. Phytoplankton growth was also stimulated by high definition fluorescent tubes

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(5700 K, Full Spectrum Solutions, Model #205457) mounted to the MART and operated

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continuously throughout the experiment. After 9/11/2013, SSA particles were not

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produced until 9/16/2013 as the MART water recirculation system has been found to

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inhibit phytoplankton growth during early periods of a phytoplankton bloom. Once a

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threshold chlorophyll-a concentration was reached, SSA particles were generated and

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sampled daily. Silica gel diffusion dryers were utilized to reduce the relative humidity of

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the sampled air to ~15%.

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Measurement of Bulk Seawater Biological Activity

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Bulk seawater was collected daily from the MART. In vivo measurements of

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chlorophyll-a fluorescence were made immediately after collection using a custom built,

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portable fluorometer calibrated using chlorophyll-a from Anacystis nidulans (Sigma

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Aldrich, C6144) in acetone. Water for DOC analysis was filtered (0.7 µm Whatman GF/F,

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Z242489) into cleaned and combusted 40 mL glass vials and then immediately acidified

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with two drops of trace metal-free 12N HCl to an approximate pH of 2. Samples were

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stored protected from light at room temperature until analysis using the high-temperature

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combustion method (Shimadzu Instruments). Heterotrophic bacteria were enumerated via

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flow cytometry (Beckman-Coulter Altra) stained with Hoechst 34442 (1 µg/ml, final

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concentration) (Method S-1).

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Measurement of SSA Composition via ATOFMS

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ATOFMS was utilized to measure in real time the size-resolved chemical

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compositions of dried individual SSA particles with vacuum aerodynamic diameters (dva)

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between 0.5 – 4.5 µm. Detailed descriptions of ATOFMS have been published previously

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and only a brief discussion is given here. Aerosol particles are drawn into the instrument

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through a converging nozzle inlet and accelerated to their size-dependent terminal

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velocities. Aerosol particles transit two continuous wave laser beams (532 nm) and the

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calculated particle velocity is converted to vacuum aerodynamic diameter. A Q-switched

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Nd:YAG laser pulse (266 nm wavelength, 8 ns, 700 µm spot size,) desorbs and ionizes

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each particle’s chemical components which are then detected by a dual-polarity reflectron

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time-of-flight mass spectrometer. A laser pulse energy (LPE) of 1.1-1.3 mJ was utilized

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every day of SSA sampling. In addition on specific days throughout the bloom the energy

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of the laser pulse energy was varied between 0.2-1.2 mJ.

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Summary of Single Particle Data Analyses

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A total of 453,217 mass spectra were collected over the course of the experiment.

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All ATOFMS single particle data were imported into MATLAB and analyzed using a

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Flexible Analysis Toolkit for the Exploration of SPMS data (FATES).27 Peak

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assignments were made referencing the current literature and correspond to the most

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likely ion produced at a specific mass-to-charge ratio (m/z). No clustering algorithms

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were used to group data, rather the data set was visually explored at the single particle

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mass spectral level utilizing guiFATES, a user-guided visual analytical graphical user

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interface within FATES. Utilizing this tool, a set of MS was identified with signatures

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similar to previous detailed descriptions of terrestrial bacterial SPMS mass spectra.19,28–32

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Based on the characteristics of these initially identified MS, a decision tree was

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developed (Figure S-1) to objectively discriminate a narrow set of ion signatures

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generated by likely microbe or microbe-fragment containing particles (BioSS) from the

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greater SSA population. Markers for potassium (39K+), phosphate (63PO2-, 79PO3-),

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organic nitrogen (74N(CH3)4+, 146C5H8NO4-, -66), and organic (m/z -40, -41) species, all

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detected previously in cellular SPMS ion signatures, were utilized to select for BioSS

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mass spectra. Thresholds for the maximum relative signals from inorganic salt species

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common in seawater, such as magnesium, calcium, sodium, and iron, were set for the

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BioSS class (Figure S-1). The addition of the diatom growth medium immediately

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increased the relative signal from potassium, phosphate, iron, and calcium ion markers,

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but did not discernably influence the relative signals from the organic and organic

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nitrogen ion markers utilized in the discrimination of BioSS (Figures S-2, S3). The

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number fractions of BioSS was 0.014±0.03 and 0.011±0.03 (standard error calculated

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assuming a binomial distribution) before and after the growth medium addition,

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respectively. Thus, the BioSS class as defined successfully discriminated against

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potassium and phosphate-rich MS generated directly by the addition of growth medium.

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Total positive ion intensity represents the sum of all positive ion signals for a

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single mass spectrum from 0 to 300 m/z, and is reported on an arbitrary scale of 0 to 100.

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To generate relative ion values, positive and negative MS were normalized separately by

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either the total positive or total negative ion intensity, respectively. Relative ion signals

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that were utilized to bin MS are listed in Table S-2.

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RESULTS and DISCUSSION

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Description of SSA Microbial Mass Spectra (BioSS)

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Using the criteria described in the last section and Figure S-1, MS likely produced

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by microbial, microbe-containing, or microbe-fragment containing SSA particles (BioSS)

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were identified within the SSA population based upon close similarity to previous

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descriptions of cellular spectra generated from SPMS studies of nebulized terrestrial

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bacteria.19,28–32 For simplicity, throughout this work “microbe-containing particle” is

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utilized to refer to particles with both intact cells or cell fragments. The term “marine

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microbes” encompasses a diverse range of species including viruses, heterotrophic

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bacteria, cyanobacteria, and eukaryotes. While strong potassium and phosphate ion

146

signals are ubiquitous in microbial SPMS mass spectra, it is important to note that the

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complete ion signatures for terrestrial and marine microbial SPMS mass spectra exhibit

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wide variations.17–19,32 As such, it is likely that some ion signatures generated from

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ejected marine microbes may fall outside the BioSS class as defined in this study.

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Over the course of the experiment, only ~2% of all SSA mass spectra were

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classified as BioSS, reaching a maximum of ~14% on 9/17/2013 and then falling and

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remaining below 1% after 9/22/2013. All BioSS identified had significant signals from

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phosphate (63PO2-,79PO3-, 97H2PO4-) and potassium (39,41K+). Most also had 42CNO-, 26CN-,

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and

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important to note that in this work, BioSS is treated as a single particle type generated by

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a population of microbe-containing particles. However a great deal of variation between

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the MS exists. Two characteristic MS illustrating the range of BioSS signatures are

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shown in Figure 1. These should not be considered representative of distinct particle

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types but rather the two extremes of a continuum of BioSS mass spectra (Figure S-4). A

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detailed list of common ion markers is provided in Table S-3. To help eliminate noise,

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these MS are made up of an average of 28 (Figure 1a) and 64 (Figure 1b) single particle

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mass spectra.

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35,37

Cl- ion markers with a range in signal responses from additional ions. It is

In Figure 1a, the BioSS signature is characterized by intense signals from

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129,131,133

MgCl3- and relatively large organic nitrogen markers (90C4N3-, 107C4N4H3-,

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117

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which in prior studies have been assigned to the ionization of amino acids.19,28,29

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Additional signal from ion markers -66 and -71 are present which have been noted in

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single cell SPMS studies, but not specifically assigned.21,28,29,31 In some cases, BioSS

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were identified with a positive ion mass spectrum, very similar to Figure 1a but lacking

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negative ion signal. The BioSS signature in Figure 1b is characterized by relatively more

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intense signals from 42CNO-, 26CN- and ion markers -40, -41, -64, and -65 in the negative

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mass spectrum but with diminished signals from -129,131,133MgCl3-, 97H2PO4-, and most

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other positive and negative organic ion markers detailed in Figure 1a. Single particle

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mass spectra similar to Figure 1b consistently generate a set of well-correlated (Figure S-

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5) low intensity positive ion markers (104, 120, 141, 157, 175, 197, 213, 224, 275) some

C5N4H-, 146C5H8NO4-, 59N(CH3)3+, 74N(CH3)4+) in both the positive and negative MS

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of which have been assigned (104K2CN+,120K2CNO+) or noted (157, 175, 213) previously.

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28,29,32–34

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detritus35 lack signals from chlorine ions or chlorine-containing ion clusters except when

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cultured in salt rich media or aerosolized from a salt solution.17,18 Almost all BioSS

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identified in this study contained signal from 35,37Cl- and many also had signals from

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chlorine-containing ion clusters such as 129,131,133MgCl3-, 223,225,227,229Mg2Cl5-, 81,83Na2Cl+,

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and 113,115K2Cl+. This suggests that signals from chlorine-containing ions could be unique

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markers used to distinguish ocean-derived from terrestrial microbial spectra in marine

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influenced air masses. However, atmospheric processing of sea spray aerosols can lead to

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chloride depletion within the particle,36,37 so these ion markers may potentially only be

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generated by freshly produced microbe-containing SSA particles.

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BioSS and Particle Size Dependence

All previously reported SPMS analyses of standards of microbial cells and plant

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The number fraction of BioSS categorized particles relative to all MS generating

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particles increased with size, growing over an order of magnitude from 0.2% (0.5-1 µm)

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to 12% (4-4.5 µm) over the size range of the ATOFMS (Figure S-6). This is consistent

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with field measurements which have detected bacteria predominantly in large

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supermicron SSA particles.38 The authors know of no quantitative comparisons of

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bacterial ejection rates from water into droplets within the size range of the ATOFMS.

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However, published bacterial enrichment factors plummet exponentially from 50 to 20

195

µm in wet droplets generated by bubble bursting.7,6 It is hypothesized that with

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continuing decreasing droplet size microbes will continue to be less effectively

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transferred into the aerosol phase due to the physical mechanism of SSA production.5

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For comparison, the size dependent number fraction was also calculated for all

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remaining particles, excluding BioSS, with at least 0.05 or 0.1 relative ion signals from

200

both potassium (39K+) and phosphate (79PO3-+63PO2-), referred to as KPhos5 or KPhos10

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classes, respectively. These are similar phosphate and potassium thresholds that are

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utilized in combination with an array of organic nitrogen markers to define BioSS (Figure

203

S-1). Representative MS for all non-BioSS classes are provided in Figure S-7 and S-8.

204

KPhos5 and KPhos10 made up 16% and 5% of all SSA mass spectra, and the number

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fraction for these potassium and phosphate-rich particles remains flat over the instrument

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size range (Figure S-6). The number fraction for KPhos5 mass spectra with also 0.05

207

relative ion signal from the sum of 26CN- and 42CNO-, markers for organic nitrogen that

208

have been previously utilized to classify biological particles,23,24,39 also did not increase

209

with size. While common in BioSS mass spectra, 26CN- and 42CNO- ion markers were not

210

utilized to define this class. Because these non-BioSS classes do not display any size

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dependence, it suggests the chemical components generating the phosphate, potassium,

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and organic nitrogen ion signals were transferred as dissolved species from the seawater

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into the aerosol phase rather than associated with cells or particulates.

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The number fraction for KPhos10 mass spectra with at least 0.1 relative ion signal

215

from the sum of organic nitrogen ion markers, 26CN- and 42CNO-, did increase with size

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from 0.5 to 3 µm, though this class only made up ~0.1% of all SSA mass spectra. These

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MS are potentially microbial, however most were excluded from BioSS because their

218

iron or calcium signal exceeded the maximum thresholds (Figure S-1) implemented to

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eliminate the influence of the diatom growth medium addition. As discussed in the

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following section, the overall BioSS ion signatures are highly dependent on the total

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positive ion intensity (TPII). For this reason, applying a simple threshold, which appears

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to discriminate effectively against the majority of generic SSA mass spectra, does not

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effectively capture the BioSS class. For BioSS with relatively high TPII (>40), 70% of

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the MS had potassium (39K+), organic nitrogen (26CN-+42CNO-), and phosphate (63PO2-

225

+79PO3-) relative ion signals all greater than 0.1. However, only 30% of BioSS with

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relatively low TPII met these thresholds. This is the first utilization of particle size in

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SPMS analysis to distinguish between SSA-containing particulates versus dissolved ions.

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The novel results stemming from this approach highlight the importance of careful data

229

treatment when trying to identify cellular spectra within a SSA or marine aerosol

230

population. Even relatively strong signals from ion markers such as

231

and

232

markers are extremely common in SSA populations (Figure S-9).

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Dependence of SSA BioSS Signatures on Total Ion Intensity and Laser Pulse Energy

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SPMS studies of well-characterized and chemically and morphologically uniform

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aerosol particles have illustrated how differences in laser fluence yield variations in mass

236

spectral signatures due to changes in both the ionization processes and the degree of

237

particle desorption.40–43 For particles with similar composition, the total ion intensities of

238

MS generally increase when particles encounter higher laser fluence.40,42 However,

239

analyses utilizing total ion signal or variable laser pulse energies have never been

240

leveraged previously to help discriminate or confirm a distinct particle type within a

241

larger chemically complex aerosol population. Due to the nominally Gaussian beam

242

profile and hot spots in the desorption/ionization laser utilized in this study,17,42 the laser

243

fluence that each particle experiences upon ionization is variable even when the total

244

pulse energy is relatively constant.

39

K+,

PO3-,

79

26

CN-

42

CNO- cannot be used solely as indicating a microbial ion signature, as these ion

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All BioSS identified for the entire experiment, generated at 1.22+-0.04 mJ laser

246

pulse energy, were grouped by TPII. Subsequently, the distributions of relative ion

247

signals for a variety of m/z (Table S-2) were calculated for all BioSS within these TPII

248

bins (Figure 2 and Figure S-10). While this analysis utilizes TPII as a proxy for laser

249

fluence, this assumption was further confirmed by directly varying the laser pulse energy

250

from 0.2 to 1.2 mJ on September 17th. BioSS were binned based upon relative signals

251

from the ions previously described. The results for the lowest (0.21+-0.03) and highest

252

(1.28+-0.06) laser pulse energies are shown in Figure 3 and for all laser pulse energies in

253

Figure S-11. Except for m/z -90, the distribution of all relative ion signals examined for

254

the low and high pulse energies mimics the distribution for the low and high ion

255

intensities respectively. This supports the use of total positive ion signal as a proxy for

256

laser fluence for BioSS.

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BioSS with low (0-5) TPII or generated utilizing using low laser pulse energy

258

more frequently have high relative ion signals from m/z +74 (74N(CH3)4+), -90 (90C4N3-),

259

and -146 (146C5H8NO4-) compared to BioSS with high (35-100) TPII (Figure 2a-c) or

260

generated with high pulse energy (Figure 3a-c). The opposite trend is observed for the

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sum of m/z -26 and -42 (26CN-, 42CNO-), -66, and the sum of +104 and +120 (104K2CN+,

262

120

263

total ion intensity compared to low total ion intensity (Figure 2d-f and Figure 3d-f). It is

264

likely that trends in these ion markers, indicative of amino acids, with respect to laser

265

fluence are simply a result in changes in the fragmentation of the molecules, rather than

266

illustrative of differences in the chemical species desorbed from the particle.31,44 The

267

trends in most of the relative ion signals described here (m/z +74, -26, -42, -66, -90, -146)

K2CNO+) for which large relative ion signals are more common for BioSS with high

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can be directly compared to and are entirely consistent with prior reports on the influence

269

of laser fluence on bacterial cell single particle mass spectra and further confirm BioSS as

270

indeed generated from microbial containing particles.30,31

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Utilizing BioSS Signatures and Total Ion Intensity to Probe the Structure of

272

Microbe-Containing SSA Particles

273

BioSS mass spectral signals due to -Mg negative ion clusters (129,131,133MgCl3,

-

274

223,225,227,229

Mg2Cl5), -Cl (35,37Cl-), and +Na (23Na+,46Na2, 81,83Na2Cl+, 139,141,143Na2Cl+) ion

275

markers also had a strong dependence on total positive ion intensity and laser pulse

276

energy. BioSS with low TPII more frequently had high (>0.15) relative signal from -Mg

277

negative ion clusters. In contrast, at very high TPII (>75) the number fraction of +Na and

278

-Cl-rich (>0.15) MS making up BioSS increased dramatically (Figure 4a). While

279

chlorine-containing ion markers (35,37Cl-, 129,131,133MgCl3, -223,225,227,229Mg2Cl5, 81,83Na2Cl+)

280

have never been noted in microbial or biological SPMS mass spectra, except when

281

cultured in salt rich media, they are common in SSA mass spectra.26,45,46 This suggests

282

that these inorganic ion signals largely originate from chemical species present in the

283

microbe-containing SSA particle but are not the ion signature generated by the microbial

284

cell. It has been frequently noted that the laser pulse energies commonly utilized in

285

SPMS result in incomplete desorption of supermicron particles.43,47–51 The BioSS total

286

ion intensity distribution is similar across the ATOFMS size range (0.5-4.5 µm) and only

287

shifts slightly to higher values with increasing size (Figure 4b). Assuming spherical

288

particles and complete particle desorption and ionization, the total ion intensity should

289

have a third order dependence on diameter, which would result in a 700-fold increase in

290

ion yield from 0.5 to 4.5 µm (dva). The minimal increase in ion yield with particle

13



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291

diameter suggests that desorption of biological SSA particles is not complete over the

292

range of laser fluences used in this study.

293

Coupling the trends in total ion intensity and -Mg, -Cl, and +Na ion signals

294

allows us to offer a conceptual picture of the structure of BioSS SSA particles. First, it is

295

well documented that dried seawater and model salt solution droplets exhibit a chemical

296

spatial heterogeneity with a core rich in sodium chloride while the outer layer is enriched

297

in organics and all minor inorganic components.52–58 Microbes are likely ejected in

298

droplets of seawater, that upon drying will chemically segregate in the same manner with

299

microbes adhered to sodium chloride rich nodes, surrounded by a magnesium-rich

300

coating. Theoretical studies of laser desorption/ionization processes indicate that

301

desorption propagates from the surface of the laser illuminated particle face.59,60

302

Therefore if desorption of the microbe-containing SSA particle is incomplete, the

303

orientation of the particle within the laser beam will affect the mass spectrum generated.

304

The laser beam could hypothetically illuminate the microbe face of the particle and

305

generate little to no signal from sodium chloride in the shadow of the microbe. BioSS

306

would only have relatively more intense signal from sodium chloride when much more

307

complete desorption and ionization of the total particle occurs generating higher ion

308

yields. In addition when very low degrees of desorption and ionization occurs, the mass

309

spectrum could be rich in signal from the magnesium abundant coating relative to signal

310

associated with ionization of the microbial cell. This is in good agreement with previous

311

studies of supermicron SSA particles; low laser pulse energies generate low intensity MS

312

with high magnesium signal relative to sodium due to the enrichment of magnesium at

313

the particle surface and concentration of sodium within the core.61,62

14


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314


While there is strong evidence that BioSS identified in this study are generated by

315

microbe-containing SSA particles, it is apparent that the BioSS mass spectral class

316

represents a continuum which at the extremes is increasingly similar to either very lightly

317

are strongly desorbed typical SSA particles composed largely of sea salts and dissolved

318

organic species. For this study, explicit limitations (Figure S-1) on contributions from

319

typical sea salt species such as sodium and magnesium were subjectively chosen for the

320

BioSS class. Future studies will focus on refining the structural paradigm above to more

321

conclusively understand variability of the inorganic composition and resultant ion signals

322

for marine microbes.32,63–65 However, the model presented here is the first to illustrate

323

that many microbe-containing SSA particles may generate MS with little to no microbial

324

ion signatures. Therefore, the number fraction of BioSS likely represents a lower bound

325

for the total number of microbe-containing SSA particles.

326

Influence of Seawater Chemistry on BioSS signatures

327

The fraction of BioSS was determined over the course of the phytoplankton

328

bloom and found to reach a maximum (~14%) close to the first peak in both the

329

heterotrophic bacteria and chlorophyll-a and before the rise in total organic carbon in

330

seawater (Figure 5). Previous studies of SSA particles generated during phytoplankton

331

blooms show that as the bloom progresses and the dissolved organic carbon content

332

increases in seawater, dry supermicron SSA particles show increasingly thick organic and

333

magnesium-rich coatings surrounding sodium chloride cores.26,46 More detailed

334

descriptions on the influence of induced phytoplankton blooms on the chemistry of the

335

broader SSA population can be found in previous publications.26,66–69 ATOFMS data in

336

this study indicate that the magnesium-rich coatings, proposed in the previous section to

15



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Page 16 of 29

337

coat the biological SSA particles, also increased in thickness over the course of the

338

phytoplankton bloom. As already noted, BioSS with high -Mg (129,131,133MgCl3,

339

223,225,227,229

340

the phytoplankton bloom progressed the fraction of -Mg-rich (>0.15) BioSS increased.

341

Also for each day, BioSS mass spectra were grouped by TPII and the number fraction of

342

-Mg-rich BioSS, within each TPII range, was calculated and normalized by the maximum

343

-Mg-rich number fraction each day. This distribution for -Mg-rich BioSS shifted to higher

344

TPII values over the course of the experiment (Figure 5). Higher total positive ion

345

intensities of -Mg-rich BioSS suggest that more of the magnesium-rich coating had to be

346

desorbed and ionized before reaching the microbial cell. This also suggests that very

347

thick organic and magnesium coatings of dry microbe-containing SSA particles could

348

possibly prevent the generation of recognizable BioSS signatures. This consideration is

349

more critical in the examination of dense laboratory generated phytoplankton blooms

350

where the dissolved organic carbon content of the seawater is much higher than

351

commonly found in the natural marine environment.

-

Mg2Cl5) relative signal generally had relatively low total ion intensities. As

352 353

CONCLUSION

354

Identification and quantification of microbes originating from seawater will allow

355

future studies to better understand their role as ice nuclei within clouds. However, while

356

it has been shown that microbes are ejected in sea spray aerosols,1–7 MS with

357

characteristic microbial signatures have never been uniquely identified within SPMS SSA

358

datasets. This is the first report to distinguish BioSS, likely microbe MS, from the

359

abundant SSA mass spectra with significant potassium and phosphate ion signals likely

16


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360

resultant from dissolved chemical species. Reported in this study is an array of

361

identifying size and mass spectral characteristics for SSA BioSS that will support the

362

identification of microbe and microbe fragment-containing SSA particles in future

363

laboratory and field studies. We utilize these ATOFMS results to propose that dry SSA

364

generating BioSS are likely particles containing a microbial cell adhered to a sodium

365

chloride node encompassed by a magnesium-rich coating. Such in situ descriptions of

366

microbial SSA are rare as details of the structure of SSA are lost utilizing impinger or

367

filter collection techniques commonly employed with offline analysis of aerosolized

368

microbes. Finally, the chlorine and chlorine-containing ion clusters ubiquitous in the SSA

369

BioSS population are the first ion markers proposed to be useful in distinguishing

370

terrestrial from ocean-derived aerosolized microbes in marine influenced air masses.

371

In addition the analytical techniques applied herein while specifically employed

372

for the identification of microbe-containing SSA particles could be applied to the wider

373

examination of SSA, ambient, and other chemically complex aerosol populations. Our

374

work suggests that particle size can be utilized to help discriminate mass spectral types

375

generated by SSA containing insoluble residues beyond microbes, such as dust or soot. In

376

addition we introduce mass spectral signature dependence on total ion intensity as a

377

useful tool to support the classification of distinct particle types within a realistic mixed

378

aerosol population. This technique is especially valuable as it can be applied to existing

379

SPMS datasets and does not require explicit variable laser pulse energy experiments. The

380

expansion of SPMS data analyses beyond the grouping of particles by comparison of

381

mass spectral signatures could not only improve the robustness of scientific conclusions

382

but also expand the limits of knowledge discovery within the field.

17



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383

ASSOCIATED CONTENT

384

Supporting Information Online location of data set; Details on the flow cytometry

385

method; Concentration of nutrients added to the MART; m/z values used in the ion signal

386

analysis; Ion markers common to the representative MS in Figure 1; Decision tree

387

utilized to discriminate BioSS; Average MS before and after growth medium addition;

388

Relative ion signal distribution before and after growth medium additions; Continuum of

389

BioSS single particle MS; Covariance matrix for BioSS positive ion signals; Number

390

fraction of particle types by size; Representative MS of Kphos (not BioSS); Scatter plot

391

of phosphate and potassium ion signal; Distribution of relative ion signals for BioSS

392

grouped by total ion intensity; Distribution of relative ion signals for BioSS grouped by

393

laser pulse energy.

394

AUTHOR INFORMATION

395

Corresponding Author

396

*Phone: +1 858 822 5312. E-mail: [email protected].

397

ACKNOWLEDGEMENTS

398

This work was supported by the National Science Foundation through the Centers of

399

Chemical Innovation Program via the Center for Aerosol Impacts on Chemistry of the

400

Environment (CHE-1305427). The authors would like to thank all collaborators involved

401

in the MART microcosm study, notably C. Lee and D. B. Collins. The authors would also

402

like to thank Grant Deane for helpful discussions.

403

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A.; Qin, Z.; Cappa, C. D.; Bertram, T. H.; Tivanski, A. V.; Stone, E. A.; Prather, K. A.; Grassian, V. H. Chem 2017, 2, 655–667.

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570

Figure 1

571 572 573 574 575 576 577 578 579

Figure 1. Two representative dual-polarity mass spectra illustrating the continuum of SSA ion signatures identified as BioSS. Some mass spectra were characterized by (a) a number of relatively intense positive and negative organic nitrogen markers, particularly m/z +59, +74 and -146, or (b) a series of less intense peaks above +100 (highlighted in inset). To help eliminate noise, these are averages of 28 (a) and 64 (b) single particle mass spectra.

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Figure 2

581 582 583 584 585 586 587

Figure 2. Distributions of relative ion signals for BioSS with either low (961 total BioSS mass spectra) or high (5253 total BioSS mass spectra) total positive ion intensity. Data is shown for m/z +74 (a), -90 (b), -146 (c), the sum of -26 and -42 (d), -66 (e), and the sum of +104 and +120 (f). Results shown are for all BioSS generated during the experiment with 1.22+-0.04 mJ laser pulse energy.

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588

Figure 3

589 590 591 592 593 594

Figure 3. Distributions of relative ion signals on September 17th for BioSS generated with either low (130 total BioSS mass spectra) or high (271 total BioSS mass spectra) laser pulse energies. Data is shown for m/z +74 (a), -90 (b), -146 (c), the sum of -26 and 42 (d), -66 (e), and the sum of +104 and +120 (f).

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Figure 4

596 597 598 599 600 601 602

Figure 4. (a) The fraction of BioSS, grouped by total positive ion intensity (TPII), with large -Cl, +Na, or -Mg relative ion signals. The number of BioSS within each ion intensity range are also shown. (b) The TPII distribution of BioSS grouped by particle diameter. The legend indicates the total number of BioSS particles within each size range. Results shown are for all BioSS generated during the experiment.

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Figure 5

605 606 607 608 609 610 611 612 613 614

Figure 5. Temporal trends of (a) chlorophyll-a (Chl-a), heterotrophic bacteria (HB), and dissolved organic carbon (DOC) concentrations in seawater as well as (b) the total number of BioSS and number fraction relative to all SSA mass spectra. In addition, for each day (b) the number fraction of -Mg-rich BioSS relative to all BioSS and (c) the number fraction of -Mg-rich BioSS within each total positive ion intensity range, normalized to the maximum -Mg-rich number fraction for each day . Results shown are for mass spectra generated with the ATOFMS operating at 1.22+-0.04 mJ laser pulse energy.

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Expanding Single Particle Mass Spectrometer ... - ACS Publications

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