University Policy IT-04.02-11/18 TO: the University of West Florida

University Policy IT-04.02-11/18

TO: The University of West Florida Community

FROM: Dr. Martha D. Saunders, President

SUBJECT: UWF Information Security and Privacy Policy

Responsible Office: Information Technology Services

I. Purpose:

The University of West Florida (UWF) takes seriously its obligation to respect and protect the privacy of its students, alumni, faculty and staff, and to safeguard the confidentiality of information important to UWF's mission and vision. This commitment is in accordance with legislated or contractual obligations concerning the use and control of protected or private information. As the custodian of protected and private information, UWF recognizes the importance of safeguarding information resources from loss, misuse, unauthorized access or modification.

This policy is not intended to replace or supersede provisions for protected or private information that are dictated by legislation or contractual provisions.

II. Who Does this Govern and Who Needs to Know this Policy?

This Privacy Policy applies to all faculty, staff, students, affiliates, prospective students, contractors and sub-contractors, and associated parties who interact with UWF systems to process, transmit, or store UWF information classified as protected or private on:

A. UWF-owned computing systems, telecommunication systems, and network assets.

B. Personally owned computing/storage devices and telecommunication devices.

C. Computing, storage, telecommunications, or network services procured from third-party vendors including cloud and colocation services. University units who maintain physical locations or conduct services outside of the United States of America are also responsible for meeting applicable local, national, or regional privacy rules or regulations for those sites.

III. Information Classification and Definition of Terms:

A. Classification-

For the purpose of this policy, information will be classified as follows:

1. The Protected classification encompasses information deemed confidential under federal or state law or applicable regulations, UWF contractual obligations, or privacy considerations such as the combination of names with respective Social Security Numbers.

2. The Private classification encompasses information for which the unauthorized disclosure may have moderate adverse effects on the university's reputation, resources, services, or individuals. This is the default classification, and should be assumed when there is no information indicating that information should be classified as public or protected.

3. The Public classification encompasses information for which disclosure to the public poses negligible or no risk to the UWF's reputation, resources, services, or individuals. In addition, certain legislation may specify select information as public.

B. Definitions-

1. Personal identifiable information (PII) means any information relating to an individual or identifiable natural person. An identifiable person is one who can be identified, directly or indirectly – in particular, by reference to an identification number or to one or more factors specific to his or her physical, physiological, mental, economic, cultural or social identity.

2. Education records are those records that contain information directly related to a student and which are maintained by an educational agency or institution or by a party acting for the agency or institution. See UWF Regulation 3.0.17 for more information regarding educational records at UWF.

3. Personal Health Information (PHI) refers to demographic information, medical history, test and laboratory results, insurance information and other information that is collected by a health care professional to identify an individual and determine what type of care that individual should receive.

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4. Data Trustees are the Executive Vice President and the Heads of each Division at UWF; they are responsible for the major categories of university data for their respective areas.

5. Information Systems Coordinating Group (InfoSys) members are endorsed by a Data Trustee to manage a subset of data. The designated member is responsible for the accuracy, privacy, and integrity of a university data subset.

6. University Unit refers to a school or college and any departments or divisions which are a subdivision of a college or school; centers, facilities, labs, libraries, or program within a college or school, or as an independent entity; offices; associations; and administrative units.

C. Information Privacy Principles-

1. Protected or Private information must be safeguarded.

2. Employ the agreed upon conditions with third-party entities.

3. Collect only protected or private information needed to support a business process.

4. Keep protected and private information no longer than required by law or business need.

D. Consequences-

Disciplinary action for violating this policy could be taken under the UWF's current Standards for Disciplinary Action for the violation of a provision of a UWF Policy.

IV. Policy Statement:

A. Resources-

1. Departmental Information Security Representative (DISRep). Each University unit bears the responsibility to identify and classify the unit’s information and to ensure the following standards are followed for information classified as protected or private. DISReps are also expected to carry out a particular set of responsibilities:

i. Maintaining the information identification and classification documentation of unit protected or private information assets.

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ii. Assessing the unit's electronic and physical controls for information classified as protected or private to ensure they meet legislated or contracted requirements. iii. Ensuring unit staff is trained on this policy, and specific legislated or contracted privacy requirements. iv. Ensuring that each unit staff member who handles protected or private information sign an employee statement of understanding regarding confidentiality. v. Working with legal resources to ensure contracts or agreements contain terms to stipulate adherence to UWF policy, legislation, or contractual safeguarding provisions when protected or private information is processed, transmitted or stored by a third-party vendor.

B. Training-

UWF will make available to the DISRep, and the university in general, standardized information privacy training. This training will provide appropriate privacy training for all Faculty, Staff and students.

C. Forms-

Employee statement of understanding regarding confidentiality.

D. Procedures-

IT Security and Privacy Incident Response and Reporting Procedures.

E. Guidelines-

1. UWF Information Classification Guidelines.

2. Guidelines for the use of personal cloud computing services for UWF Business.

F. Access and Use-

1. Authorized Users of Protected or Private Information. Access to UWF information classified as protected or private requires appropriate authorization:

i. It is the responsibility of the designated trustee or DISRep to authorize access to protected or private information to users or entities as required for them to perform their assigned job duties, to complete a business process, or by contractual obligation.

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ii. For an individual not employed by UWF or third parties who are authorized to view protected or private information as part of a regulatory, academic, or business function, the sharing UWF unit must have a signed Employee Statement of Understanding Regarding Confidentiality on file for individuals or UWF data sharing terms and conditions for third parties. Additionally, background checks may be required prior to granting access to UWF protected or private information.

iii. The individual whose protected or private information is produced or displayed is authorized to access that information unless restricted by legal or contractual obligations.

iv. Legal or regulatory requirements may impact who is authorized to view UWF protected or private information access.

G. Confidentiality Statement and Privacy Training-

1. Signed Employee Statement of Understanding Regarding Confidentiality and training are required for UWF personnel with authorization to access or process protected or private information:

i. Each UWF position requiring access to protected or private information must be reflected in the position description.

ii. For each person requiring access to protected or private information, signed Employee Statement of Understanding Regarding Confidentiality must be maintained on file unit and be available for audit. This information may be stored in a digital or paper format.

iii. Employees designated as having access to select protected information may be required to acknowledge confidentiality controls necessary to meet specific legal or contractual privacy requirements.

iv. Each unit must train its employees on the requirements to safeguard protected or private information. This training should occur prior to employee access of protected or private information or as required by legislation or contractual obligation

v. As verification of participation, each University unit must maintain rosters of participants in online or in-person privacy training in an electronic or paper format.

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H. Approved Transfer of Protected or Private Information-

1. The following actions involving protected or private information must be authorized by the responsible Dean, Director, Department Head, or designee and related approval documentation or contract/agreement maintained on file at the unit’s central office:

i. Transferring protected information between UWF computing resources and third-party vendors or service providers.

ii. Allowing system and network administrators to access protected information to perform an approved action to mitigate a system problem or as part of an incident response to a privacy breach investigation.

2. Coordinate with the UWF Legal Office in the event of receiving a valid subpoena, warrant, legal order, to meet a legal or contractual order for the transfer of protected information.

I. Third-party Access to Protected or Private Information-

1. UWF may choose to contract with a third-party for the collection, storage, or processing of information, including protected or private information. The third- party may offer services in the form of hosting, outsourcing, or private/public cloud computing services.

2. If UWF decides to contract a third-party for the processing of protected or private information, this must be regulated in a written agreement, in which the rights and duties of UWF and the third-party contractor in addition to any subcontractors engaged by the primary third-party contractor are specified. A third-party contractor shall be selected that will guarantee the technical and organizational security/privacy measures required in this privacy policy and provide sufficient guarantees with respect to the protection of the information.

3. A third-party contractor should also be contractually obligated to process protected or private information only within the scope of the contract and the directions of UWF. Processing of protected or private information may not be undertaken for any other purpose.

J. Physical Security Access Restrictions-

1. Offices and storage facilities that maintain protected or private information locally must:

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i. Ensure that all protected or private information in hardcopy or electronic form is secure in their work area at the end of the day and when they are expected to be gone for an extended period.

ii. Computer workstations processing, transmitting, or storing protected or private information must be secured by locked rooms when the workspace is unoccupied.

iii. Any protected or private information should be removed from the desk and locked in a drawer when the desk is unoccupied and at the end of the work day if the room cannot be secured.

iv. File cabinets containing protected or private information must be kept closed and locked when not in use or when not attended.

v. Keys used for access to resources holding protected or private information must not be left at an unattended desk.

vi. Passwords may not be left on sticky notes posted on or under a computer, nor may they be left written down in an accessible location.

vii. Printouts containing protected or private information should be immediately removed from the printer in unsecured areas.

viii. Upon disposal, documents containing protected or private information should be shredded or placed in the locked confidential disposal bins. Electronic media containing protected or private information that is no longer needed should be physically destroyed (e.g., shred, degauss, crushed) or wiped by electronic methods to render the information unreadable and unrecoverable as stipulated in National Institute of Standards and Technology-Special Publication 800-88 Revision 1 Guidelines for Media Sanitization.

ix. Whiteboards containing protected or private information should be erased unless they are in secured areas. In addition, whiteboards with protected or private information should not be facing external windows unless blinds are drawn down to prevent unauthorized viewing of content.

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x. Portable computing devices containing protected or private information such as laptops phones, tablets, CDROMs, DVDs, USB flash drives should be secured in locked rooms, file cabinets, or locked drawers after normal work hours.

2. Additional physical privacy controls may also be required by law or contractual obligation for specific information items.

K. Use of Biometric Technologies-

University units implementing biometric technologies must ensure they meet any relevant privacy and biometric laws and regulations as they may relate to the acquisition and retention of biometric information. In addition, the university unit must ensure that its use meets a defined business need with auditable procedures to secure the biometric information and privacy of the enrollees.

L. Online Collection of Protected and Private Information-

1. Campus units that collect protected or private information on their public or Intranet web pages must ensure technical controls provide encryption of protected information communicated between a user's browser and a web-based application through the use of secure protocols (e.g., HTTPS, TLS/SSL, etc.). In addition, any storage of protected or private data on publicly accessible servers must be encrypted. University websites collecting protected or private information requires a link to the UWF Privacy Policy.

2. Prospective students, current students, faculty, staff, and interested parties residing outside of the United States and providing protected or private information electronically to UWF understand this information will be transferred to the U.S. where it will be processed and stored under U.S. privacy standards or by applicable framework agreements.

V. Standards for Specific Information Types:

A. Public Records-

UWF faculty, staff, and contracted business partners must ensure the safekeeping of public records that have archival, administrative, or legal value. The UWF records management policy (FIN-03.02-02/14) linked under the Public Records Management website contains specific responsibilities for the retention, storage, disposal, and archival of UWF records. Archived information classified as protected or private information

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must be maintained with the same safeguarding controls, such as encryption, that are legislated or contracted for production systems.

B. Student Educational Records-

1. The Family Educational Rights and Privacy Act (FERPA) (20 U.S.C. § 1232g; 34 CFR Part 99) is a Federal law that ensures access and protects the privacy of student education records. Florida Statute 1002.225 requires UWF to protect applicant records and student education records, in accordance with FERPA.

i. The disclosure of education records maintained by an educational institution. ii. Access to these records.

2. UWF has defined certain components of a student’s education record as “Directory Information.” “Directory Information” means information contained in an education record of a student that would not generally be considered harmful or an invasion of privacy if disclosed. These items are classified as Public information unless a student has chosen to restrict their directory information through the Privacy section in their MyUWF account, which places a privacy hold on the student's account including “Directory Information.” Students who wish to have their privacy flag removed from their permanent academic record must contact the Office of the Registrar in writing or may submit the change online through MyUWF. UWF regulation 3.017 contains the current information designated as educational records at UWF.

3. EU General Data Protection Regulation. The European Union General Data Protection Regulation is a privacy law that applies to the personal identifiable information collected in or from the European Union (EU), or that is related to goods or services offered in the EU. The GDPR requires that UWF process personal data lawfully, fairly and in a transparent matter. The personal data collected by UWF must be collected for specified, explicit and legitimate purposes.

4. UWF collects or processes personal data for:

i. Legitimate interests pursued by UWF or third parties in providing education, employment, research and development, and community programs.

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ii. For the performance of a contract.

iii. Compliance with legal obligations to which UWF is subject.

5. UWF is taking measures to protect personal identifiable information that is subject to the GDPR.

C. Social Security Numbers-

1. UWF collects and stores Social Security Numbers (SSNs) as needed and as permitted by law. University units and their employees are only permitted to collect or store SSNs when necessary to meet a state or federal requirement or the unit has obtained written approval from the President, Provost, Vice President, General Counsel, IT Security Team, or designated approver to meet an official business process.

2. UWF requires all entities maintain privacy controls over SSNs to meet legal, contractual, or good privacy practice requirements including:

i. UWFIDs are to be used instead of SSNs for routine university business.

ii. Collection, storage, or processing of SSNs is restricted to UWF automated systems that serve the Enterprise Resource Planning (ERP) student, financial, and human resource systems.

iii. SSNs must not be stored on UWF-owned, personal computing devices, or transferred to vendor storage services including cloud computing resources, unless appropriate management approval and execution of an information sharing agreement is granted for mission-critical UWF business activities.

iv. SSNs must not be stored on UWF-owned or personal portable storage devices or mobile computing devices.

v. SSNs or partial SSNs should never be displayed in areas such as public locations where it is not possible to restrict access to only those approved to view SSNs.

vi. Any approved business process requiring the transfer of electronic documents containing SSNs over internal UWF network, Internet, or a

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wireless carrier’s network requires the encryption of the transferred documents between the users computing device and UWF information processing equipment.

vii. Any required mailing of paper documents containing SSNs must be done in a manner that reduces the risk of displaying SSNs before the document is opened.

D. Gramm-Leach-Bliley Financial Modernization Act of 1999 (GLB)-

1. UWF generates, receives and stores many financial documents and records classified as protected. This includes, but is not limited to, information about the awarding and issuance of loans to students, and the collection of payments from students, parents, patients and customers via check, money order, wire transfer, Automated Clearing House (ACH) and credit/debit card. GLB (Public Law 106- 102) applies to any record handled or maintained by - or on behalf of - UWF or its affiliates that contains protected financial information about a student or other third-party who has a relationship with UWF.

2. GLB safeguarding provisions pertain to any record containing protected financial information whether in paper, electronic or other form, which is handled or maintained by or on behalf of the UWF or its affiliates. For these purposes, the term protected financial information shall mean any information (i) a student or other third-party providers in order to obtain a financial service from UWF, (ii) about a student or other third-party resulting from any transaction with UWF involving a financial service, or (iii) otherwise obtained about a student or other third-party in connection with providing a financial service to that person. In particular, safeguarding provisions of this policy and the UWF’s security policy (i) ensure the security and confidentiality of covered records, (ii) protect against any anticipated threats or hazards to the security of such records, and (iii) protect against the unauthorized access or use of such records or information in ways that could result in substantial harm or inconvenience to customers.

3. All UWF contracts with providers who are responsible for processing, transferring, or storing GLB-protected UWF information will be required, under the terms of the contract, to stipulate implemented safeguards that adhere to, and are in compliance with, the provisions of the Gramm-Leach-Bliley Act.

E. Branded Credit/Debit Card Transactions-

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UWF will collect and use information obtained from branded credit/debit card transactions (VISA, MasterCard, American Express, and Discover) only for business purposes upon approval by the UWF Controller’s Office. The credit card information will be safeguarded in a confidential manner as defined in the PCI DSS Compliance section of the UWF Compliance and Ethics, and as specified in the merchant agreements as contractual obligations. Such obligations include compliance with the Payment Card Industry – Data Security Standard (PCI DSS).

F. Research Information-

University units conducting research must be aware of appropriate privacy restrictions for information transmitted, stored, or processed as part of research projects. Research projects are also a required component of a University unit’s yearly data classification, risk assessment, and risk mitigation planning. Legal privacy restrictions include, but are not limited to, the Health Insurance Portability and Accountability Act (HIPAA), International Traffic in Arms Regulations (ITAR), The Belmont Report (1979) and 2.1 Code of Federal Regulations Title 45 Part 46: The Common Rule concerning the protection of human subjects, other federal or state legal requirements, and contractual research information privacy restrictions. In addition, University units must protect the privacy of protected or private research information with appropriate information privacy and security controls such as those published by the National Institute of Standards and Technology (NIST), ISO, or Federal Information Security Management Act (FISMA). Required information privacy and security controls extend to any device used to transmit, store or process protected or private research information.

VI. Privacy Violations and Incident Reporting

A. Privacy violations occur when a UWF student, staff, contractor or faculty member violates this policy, specific legal privacy requirements, or contractual obligations. For the purpose of this policy there are there are three primary classifications of privacy violations at UWF:

1. Incidental disclosure which occurs when an unauthorized party overhears or sees protected or private information during a permitted use or disclosure in a work space.

2. Accidental disclosure occurs when privacy control weaknesses allow unauthorized access to protected or private information. Privacy control weaknesses include human error or a fault in privacy control procedures that leads to a loss of ability to limit access to protected or private information to only authorized users.

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Diversity and Distribution of Ecotypes of the Aerobic Anoxygenic Phototrophy Gene pufM in the Delaware Estuaryᰔ† Lisa A. Waidner and David L. Kirchman* College of Marine and Earth Studies, University of Delaware, Lewes, Delaware 19958

Received 15 October 2007/Accepted 2 May 2008

The diversity of aerobic anoxygenic phototrophic (AAP) bacteria has been examined in marine habitats, but the types of AAP bacteria in estuarine waters and distribution of ecotypes in any environment are not well known. The goal of this study was to determine the diversity of AAP bacteria in the Delaware estuary and to examine the distribution of select ecotypes using quantitative PCR (qPCR) assays for the pufM gene, which encodes a protein in the light reaction center of AAP bacteria. In PCR libraries from the Delaware River, pufM genes similar to those from Beta-(Rhodoferax-like) or Gammaproteobacteria comprised at least 50% of the clones, but the expressed pufM genes from the river were not dominated by these two groups in August 2002 (less than 31% of clones). In four transects, qPCR data indicated that the gammaproteobacterial type of pufM was abundant only near the mouth of the bay whereas Rhodoferax-like AAP bacteria were restricted to waters with a salinity of <5. In contrast, a Rhodobacter-like pufM gene was ubiquitous, but its distribution along the salinity gradient varied with the season. High fractions (12 to 24%) of all three pufM types were associated with particles. The data suggest that different groups of AAP bacteria are controlled by different environmental factors, which may explain current difﬁculties in predicting the distribution of total AAP bacteria in aquatic environments.

Several groups of bacteria potentially have the capacity to Congregibacter litoralis sp. strain KT71 (15). Phylogenetic anal- derive extra energy from light while assimilating organic mat- yses of pufM and other photosynthesis genes suggested that ter for carbon and energy (13). Among potential photohetero- uncultured AAP bacteria related to Rhodobacter are abundant trophs are the aerobic anoxygenic photosynthetic (AAP) bac- in the Delaware estuary (37). Additionally, 16S rRNA analyses teria. The abundance of these bacteria varies greatly among indicate that Rhodobacter-like bacteria are capable of inhabit- aquatic regimes (0 to 20% of total bacterial abundance) (8, 21, ing estuarine waters with a wide range of salinities (10). One 23, 28, 31), with estuaries having some of the highest estimates type of riverine AAP bacterium is related to strictly freshwater (28, 38). The reasons for this high variation are not clear, Betaproteobacteria, such as Roseateles depolymerans (34) and although environmental factors, such as nutrient status (21), members of the Rhodoferax clade (11). Although the diversity light, and particles (38), have been hypothesized to control of AAP bacteria is starting to become clear, we know little AAP bacterial communities. The distribution of specific groups about estuarine ecotypes or about the distribution of ecotypes of AAP bacteria, which has not yet been examined in depth, in any environment. may provide some clues. The aim of this work was to examine freshwater and estua- Culture-dependent and -independent studies suggest that rine ecotypes of pufM genes from uncultivated AAP bacteria there are habitat-specific types of AAP bacteria. Culture-de- in the Delaware Estuary. In the Delaware, as in other estuar- pendent studies found isolates typical of marine and saline ies, the Betaproteobacteria are abundant and active in freshwa- habitats (18), and a recent examination of metagenomic clones ter, the Alphaproteobacteria dominate saline habitats, and the from the Global Ocean Sampling revealed differences in the Gammaproteobacteria are evenly distributed throughout the composition of AAP bacterial communities between estuarine salinity gradient (5, 7, 11). We hypothesized that the distribu- and oceanic regimes (41), although only a single location in the tion of specific types of AAP bacteria in the estuary would be estuaries was examined. In oceanic and coastal waters, AAP similar to that of phylogenetic groups defined by rRNA genes. bacteria belong to the alpha-3 and alpha-4 subclasses of To determine the dominant types of AAP bacteria, clone li- Alphaproteobacteria (Roseobacter and Erythrobacter) (2, 20, 25), braries of pufM genes and transcripts from the Delaware River and PCR and metagenomic clones from coastal waters (4, 16) and Bay were constructed. Three ecotypes of pufM were tar- contain pufM DNA sequences closely related to those of a geted using specific quantitative PCR (qPCR) primer pairs, gammaproteobacterium in the OM60 clade (6) and to those of and the abundances of these ecotypes were examined throughout the salinity gradient of the estuary. We found that two of these ecotypes occupied specific ecological regimes repeatedly * Corresponding author. Mailing address: University of Delaware, over several years, regardless of season. College of Marine and Earth Studies, 700 Pilottown Road, Lewes, DE 19958. Phone: (302) 645-4375. Fax: (302) 645-4007. E-mail: kirchman @udel.edu. MATERIALS AND METHODS † Supplemental material for this article may be found at http://aem Sampling and environmental parameters. Samples were obtained on six .asm.org/. cruises from the main stem of the Delaware estuary at an approximately 1-m ᰔ Published ahead of print on 9 May 2008. depth. Nutrient concentrations were determined using a Perstorp flowthrough

4012 VOL. 74, 2008 DISTRIBUTION AND DIVERSITY OF ESTUARINE AAP BACTERIA 4013

TABLE 1. Primers used in cloning and ecotype-speciﬁc qPCR of pufMa

Length Temp Target Samples Forward primer Reference Reverse primer Reference (bp)b (°C)c All pufM genes River, Dec. 2001 pufLF (CTKTTCGACTTC 24 pufM750R (CCCATGGT 1 1,500 58 TGGGTSGG) CCAGCGCCAGAA) All pufM genes River, Aug. 2002 pufLF 24 pufM750R 1 1,500 58 All pufM genes River, Aug. 2002 pufM557F (CGCACCTGG 1 pufM750R 1 233 58 cDNA ACTGGAC) All pufM genes Bay, Aug. 2002 pufM557F 1 pufM_WAW (AYNGCR 40 277 56 AACCACCANGC CCA) Rhodoferax-like pufM All qPCR samples RfxF2 (TGGACGGCCGC This study RfxR2 (GCTCAATTTCG This study 156 60 genes ATTCTCA) CGTTCACCACCAA) Rhodobacter-like pufM All qPCR samples RbaF1 (TGGACGAACCT This study RbaR1 (CAACTCGCGG This study 152 50 genes GTTCAGC) TCGCC) gammaproteobacterial All qPCR samples DelMGF1 (ACCGCCGCC This study DelMGR1 (CTAGCTCC This study 151 57 pufM genes TTCTCCAT) CGATCGCCACC ATA) 16S rRNA genes, all All qPCR samples BACT1369F (CGGTGAAT 36 PROK1541R (AAGGAG 36 192 60 bacteria ACGTTCYCGG) GTGATCCRGCC GCA)

a The sequence of each primer is next to the name in parentheses. b PCR product length in base pairs. c Annealing temperature.

analyzer using colorimetric assays as described previously (26). Temperature, 1), the reactions were examined by gel electrophoresis to confirm that no product oxygen, and salinity (expressed as unitless values on the practical salinity scale) was generated in the no-RT control and that the correct-sized product was were measured using a CTD 911 Plus device (SeaBird Electronics, Bellevue, amplified. The three RT-PCRs were pooled and cloned as described above. WA). Detailed data on temperature, oxygen, salinity, chlorophyll, and nutrient All clone libraries were screened for inserts by colony PCR with the M13 and calculated seston concentrations are provided in Table S1 in the supplemen- primer sequences flanking the pCR2.1 cloning site. Amplification was carried out tal material. with 30 cycles at 94°C for 30 s, 55°C for 30 s, and 72°C for 30 to 90 s. After they In December 2001, DNA was isolated from free-living bacterioplankton of the were checked by gel electrophoresis, PCR products were purified using the Delaware River as described previously (9). In August, October, and November QiaQuick centrifugation method and eluted in 30 ␮l of elution buffer (Qiagen). 2002 and July 2004, the bacterial size fraction was isolated from whole water by The clones from the August 2002 river cDNA and bay DNA libraries were sequential filtration through 3.0- and 0.8-␮m polycarbonate filters (147-mm sequenced using BigDye 3.1 (Applied Biosystems, CA) on a Spectrumedix 24- diameter; Poretics). In March 2005, the bacterial size fraction was isolated as capillary SCE2410 apparatus. The pufLM products from the December 2001 and described previously (38). DNA was extracted with phenol-chloroform and fur- August 2002 libraries were sequenced from purified plasmid DNA using both the ther purified using the IsoQuick nucleic acid extraction kit (ISC Bioexpress, M13F and M13R primers. Kaysville, UT) or by cetyltrimethylammonium bromide extraction. Samples in- Sequences were analyzed and edited using the SeqMan program (DNAStar, tended for RNA purification were preserved in RLT buffer with ␤-mercaptoeth- Madison, WI). Libraries of pufLM were checked for chimeric clones using the anol (Qiagen, Germantown, MD) and frozen in liquid nitrogen. Total RNA was Bellerophon program (17). To detect chimeric clones in the pufM libraries, purified on RNeasy minicolumns according to the manufacturer’s recommenda- sequence alignments of the full-length and C-terminal and N-terminal regions tions (Qiagen). were constructed. Phylogenetic trees were generated from the three alignments Clone libraries of pufM. Four pufM libraries were constructed with nucleic and manually compared for differences in branch patterns. Sequences of indi- acids from surface waters of the Delaware estuary (Table 1). Three samples for vidual clones that did not branch as expected based on the full-length alignment library construction were obtained from the river (40o7.6ЈN, 74o48.4ЈW), 198 km were inspected for chimera formation. From each library, five clones or fewer from the mouth of the estuary, and the bay library sample was from surface water were rejected as chimeras. The estimated diversities of the clones (Chao I) in the 9 km from the mouth of the estuary (38o6.5ЈN, 75o6.0ЈW). Amplification condi- libraries were determined using the DOTUR software package (27). Comparative tions consisted of 30 cycles of denaturation (94°C for 30 s), annealing at tem- sequence analyses were performed using the Megalign (DNAStar), MEGA 3.1 (22), peratures given in Table 1 for 30 s, and extension at 72°C. Extension times for the BLAST-X, version 2.2.9 (3), and batch BLAST-X (GreenGenes [greengenes 1,500-bp pufLM and 200- to 300-bp pufM fragments were 1 min and 30 s, .lbl.gov]) software programs. respectively. All reaction mixtures contained final concentrations of reagents as qPCR of pufM ecotypes. Three primer sets were designed to amplify specific ϫ follows: 1 PCR buffer, 2.5 mM MgCl2, 0.2 mM of each deoxynucleoside ecotypes of pufM in qPCR reactions (Table 1). The first type, Rhodoferax-like triphosphate, 0.02 U/␮l Taq (Promega), 0.1 ␮M of each primer (MWG, Ger- pufM, was designed to target genes in hypothesized representative freshwater many), and 50 to 200 ng template DNA. Each library was generated from a pool AAP bacteria. The primers were designed to match exactly to sequence coding of three reaction mixtures which was concentrated on Microcon columns (mo- for the N-terminal end of the DelRiverFos06H03 product (37). The second lecular weight cutoff, 10,000) by centrifugation at 1,000 ϫ g for 5 min. Pooled primer pair, Rhodobacter-like pufM, was designed against an estuarine type of products were electrophoresed through SeaKem agarose (BioWhittaker, Fred- pufM in the fosmid clone DelRiverFos13D03 (37). The last set, the Delaware erick, MD), excised, and cloned into vector pCR2.1 (Invitrogen, Carlsbad, CA) marine group, was designed to target a dominant group (37%) of pufM genes in as per the manufacturer’s instructions for cloning directly from low-melting-point the Delaware Bay library (August 2002) constructed in this study. To determine agarose. the abundances of all bacteria in whole water and free-living bacterial fractions, cDNA from the August 2002 river RNA was generated using Superscript II qPCR was performed using the BACT1 primer pair as described by Suzuki et al. reverse transcriptase (RT) (Invitrogen), primed with the reverse primer (36). Template inhibition was checked by performing qPCR assays on serially pufM750R (Table 1). The RNA was treated with DNase I (Invitrogen) at 24°C as diluted environmental DNA samples. Regardless of the DNA purification per the manufacturer’s recommendations. The DNA-free RNA was divided into method, the efficiency of amplification ranged from 82 to 88%, as determined by four reaction mixtures which included all reagents except the RT. Template the slope of the regression of logfold DNA dilution with threshold cycle values. denaturation and priming were performed as per the manufacturer’s recommen- Amplification of all pufM genes was done under the following conditions: 10 dations. Three reaction mixtures then received 5 U each of the RT, and the min of denaturation and activation of the enzyme at 95°C, followed by 40 cycles fourth reaction mixture was the no-RT control. First-strand synthesis was at 42°C of denaturation at 95°C (15 s), annealing at the temperatures specified in Table for 20 min. Following PCR amplification with pufM557F and pufM750R (Table 1 (45 s), and extension and detection at 72°C (45 s). Reactions targeting the 16S 4014 WAIDNER AND KIRCHMAN APPL.ENVIRON.MICROBIOL.

TABLE 2. Composition and diversity of pufM PCR and RT-PCR grouped at the 97%-similarity levels as recommended for pro- libraries from the Delaware estuary in December 2001 a tein-encoding genes (27). The four libraries were composed of and August 2002 21 to 33 groups, with coverage ranging from 57 to 79%. The Total No. of % Chao I richness estimates for these four libraries were not Library no. of Chao I groups Coverageb statistically different from each other (Table 2). clones We compared the Delaware River and Bay clones to known December 2001 river 76 33 57 65 (43, 129) pufM genes using BLASTX (Table 3). The December river August 2002 river 95 23 76 37 (26, 79) library was dominated by clones (88% of all clones) closely August 2002 river RNA 96 21 79 31 (22, 74) August 2002 bay 107 26 76 61 (36, 152) related to pufM of DelRiverFos06H03, which is hypothesized to be representative of freshwater AAP Betaproteobacteria a Groups were defined at 3% amino acid sequence divergence. The Chao I (37). The August river DNA library also contained pufM genes index was calculated using the DOTUR software program. Numbers in parentheses are 95% confidence limits. related to the betaproteobacterial DelRiverFos06H03 and b Percent coverage was calculated with the formula ͓1 Ϫ (n/N)͔ϫ100, where other freshwater pufM genes from Lake Fryxell. Approxi- n is the number of singleton clones and N is the total number of sequences. mately half of the August river pufM genes were related to the pufM gene of the cultured gammaproteobacterium Congregi- bacter litoralis KT71 (15), but the average similarity of the rRNA gene were conducted for 30 cycles of amplification. All products were detected by an Applied Biosystems 7500 PCR system using Sybr green I fluo- amino acid sequences was only 92% (Table 3). The genes rescence. Amplification reactions contained the following: 1ϫ brilliant Sybr similar to Rhodobacter and Rhodobacter-like pufM genes, in- green master mix (Stratagene, La Jolla, CA), 80 pg/␮l DNA, 0.096 ␮M (each) cluding that of the hypothesized estuarine type in fosmid clone ␮ primer, and water to a 12.5- l final reaction volume. All reactions were com- DelRiverFos13D03 (37), comprised less than 5% of the cloned pleted with a dissociation step to check for nonspecific amplification. Standards were purified fosmid and plasmid clones. The Rhodobacter-like and pufM genes in both river DNA libraries (Table 3). Rhodoferax-like pufM standards were DelRiverFos13D03 and DelRiverFos06H The composition of the river cDNA library was similar to 03, respectively. The standard for the Delaware marine group (gammaproteobac- that of its DNA counterpart except that the gammaproteobacterial pufM) was plasmid clone DB_2E03 from the general pufM library con- terial gene did not dominate (Table 3). Approximately 30% of structed from the August 2002 bay sample. The plasmid was linearized with NotI the pufM transcripts in the river sample were closely related to restriction endonuclease (New England Biolabs, Ipswitch, MA), electrophoresed through agarose, and purified with the GeneClean spin system (Bio101). All DelRiverFos06H03 pufM, with a corresponding average amino standard DNA concentrations were determined using PicoGreen (Invitrogen) acid similarity of 94% (Table 3), and another 20% were similar fluorescence. Standard reaction mixtures contained approximately 10 to 106 to Lake Fyxell pufM genes. Only 4% of pufM in cDNA clones Ϫ Ϫ Ϫ Ϯ copies and resulted in lines with slopes of 3.4 to 3.8 (average, 3.6 0.2), was similar to estuarine DelRiverFos13D03 pufM. Genes most corresponding to an average amplification efficiency of 90% Ϯ 6%. The standard DNA for the 16S rRNA gene analysis was genomic DNA from Escherichia coli similar to those of the Gammaproteobacteria comprised ap- strain EPI300 (Epicentre, Madison, WI). Reactions targeting 16S rRNA genes proximately 14% of the cDNA library. contained 103 to 108 copies of standard DNA. In contrast to the river DNA libraries, the August bay DNA To confirm the specificities of the Rhodoferax pufM primer sets, 24 PCR library was dominated by genes similar to the pufM genes from products from representative samples of the entire estuary were cloned and the Monterey Bay BAC clone EBAC000-29C02 (37% of all sequenced as described above. The pufM genes amplified by the Rhodoferax-like pufM qPCR primers were on average 88% similar to DelRiverFos06H03 (data clones) and Congregibacter litoralis KT71 (32%) (Table 3). The not shown). To test the specificity of the gammaproteobacterial pufM primer pufM genes in Delaware Bay clones similar to the pufM gene in pair, MG1-F/R, 12 PCR products using this primer pair and DNA from the the Monterey Bay BAC clone ranged in similarity from 84 to Delaware Bay (9 km from the mouth of the estuary) collected in August 2002 98%, with an average of 95% (Table 3). Products of the Con- were cloned and sequenced. All tested clones were 92 to 95% similar to pufM of HTCC2080 and 94 to 98% similar to the dominant type of marine pufM in the gregibacter-like pufM genes were on average 95% similar at the Delaware Bay (data not shown). Specificity of the Rhodobacter primer set was amino acid level. The remaining 27% of the bay library was tested by comparing the sequences of primers RbaF1 and RbaR1 to those of 426 composed of clones with genes similar to the pufM genes from pufM sequences from the Delaware estuary, Sargasso, Mediterranean, and Red cultured representatives in the alpha-3 and alpha-4 (Roseo- seas, Monterey Bay, and isolates in the Rhodobacter, Roseobacter, and Erythro- bacter and Erythrobacter) subclasses of the Proteobacteria.In bacter genera (see Table S2 in the supplemental material). The best matches to the forward primer (Ͼ78% similar with no mismatches at the 3Ј end) were the bay library, no pufM gene was related to that of the estu- Rhodobacter-like pufM genes from the DNA and RNA libraries from the Dela- arine DelRiverFos13D03 fosmid clone, and there were no ware Bay and River and the pufM genes of the Oregon Coast isolate R2A163 freshwater representatives in this library. (35), Rhodobacter blasticus, and the Southern Ocean Roseobacter isolate SO3 We further examined the relationships of the Delaware es- (25). The reverse primer matched well to Rhodobacter-like pufM genes from the DNA and RNA libraries from the Delaware Bay and River and to the pufM tuary pufM genes and transcripts with other pufM genes by genes of Rhodobacter capsulatus, Rhodobacter blasticus, and Rhodobacter spha- constructing a phylogenetic tree with dominant members of eroides, as well as to those of Roseobacter isolates R2A163 and OCH114, Ro- the Delaware estuary libraries (Fig. 1). The tree contained a seobacter denitrificans, Roseobacter litoralis, and Roseobacter isolate BS90. cluster of Rhodoferax-like freshwater pufM sequences, com- Nucleotide sequence accession numbers. The sequences of all pufM clones prised of Delaware River pufM genes and transcripts as well as were deposited in GenBank under the accession numbers EU191236 to EU191609. pufM sequences from Lake Fryxell (19). The remaining clusters in the tree contained pufM genes from cultured and uncultured representatives isolated from marine and coastal en- RESULTS vironments. One group contained pufM genes similar to those Diversity and composition of Delaware estuary pufM librar- of the alpha-3 (Rhodobacter- and Roseobacter-like) and alpha-4 ies. We constructed three pufM libraries from bacterial nucleic (Erythrobacter-like) subgroups of Proteobacteria. The hypothe- acids from the freshwater end of the Delaware estuary and one sized estuarine type of pufM, DelRiverFos13D03 fosmid clone, from the mouth of the bay (Table 2). Protein sequences were and river DNA and cDNA clones fell in this group. The pufM VOL. 74, 2008 DISTRIBUTION AND DIVERSITY OF ESTUARINE AAP BACTERIA 4015

TABLE 3. BLAST analysis of Delaware estuary pufMa

%of Avg % Library Top BLASTX hit Accession no. Phylogenetic groupb clones identityc December 2001 river DelRiverFos06H03 AAX48200 Beta 88 99 Roseateles depolymerans BAB19668 Beta 4 94 Lake Fryxell c1 AAO62372 Alpha-1 3 96 Lake Fryxell c7 AAO62378 Alpha-3 1 100 Rhodobacter blasticus BAA22642 Alpha-3 193 Thiocapsa roseopersicina CAD66535 Gamma 1 93 Thiocystis gelatinosa BAA22650 Gamma 1 90

August 2002 river Congregibacter litoralis KT71 ZP_01104362 Gamma 51 92 DelRiverFos06H03 AAX48200 Beta 16 98 Lake Fryxell c1 AAO62372 Alpha-1 15 93 Lake Fryxell c8 AAO62379 Alpha-1 8 89 Blastomonas sp. strain NT12 BAA25728 Alpha-4 7 95 Rhodobacter blasticus BAA22642 Alpha-3 295 DelRiverFos13D03 AAX48162 Alpha-3 198

August 2002 river cDNA DelRiverFos06H03 AAX48200 Beta 30 94 Lake Fryxell c1 AAO62372 Alpha-1 19 94 Blastomonas natatoria BAA25728 Alpha-4 14 90 Congregibacter litoralis KT71 ZP_01104362 Gamma 14 92 Roseiﬂexus sp. strain RS-1 ZP_01355478 Green non-sulfur 7 72 DelRiverFos13D03 AAX48162 Alpha-3 498 Jannaschia sp. strain CCS1 YP_508114 Alpha-3 4 94 Roseococcus thiosulfatophilus AAL57746 Alpha-1 3 86 Porphyrobacter neustonensis BAA25904 Alpha-4 3 93 Lake Fryxell c8 AAO62379 Alpha-1 1 92 Rhodobacter veldkampii BAC54030 Alpha-3 1 92

August 2002 bay EBAC000–29C02 AAM48603 Gamma 37 95 Congregibacter litoralis KT71 ZP_01626201 Gamma 32 95 Rhodobacter blasticus BAA22642 Alpha-3 21 89 Roseobacter sp. strain SYOP2 AAT79391 Alpha-3 3 98 Porphyrobacter sanguineus BAA25723 Alpha-4 3 87 Jannaschia sp. strain CCS1 YP_508114 Alpha-3 2 95 Blastomonas sp. strain NT12 BAA77030 Alpha-4 1 90 Hawaii envhot3 AAL02391 Gamma 1 95

a All pufM genes were compared to database sequences (January 2007) using BLASTX. Sequences similar to those boldfaced in the table were targeted by qPCR in this study. b Phylogenetic group assignment of each top BLAST hit was based on 16S rRNA for cultured bacteria and on pufM for uncultured bacteria. Alpha, beta, and gamma refer to subclasses of the Proteobacteria. Lake Fryxell clone 1 and 7 pufM phylogenetic afﬁliations were assigned to the alpha-1 and alpha-3 subclasses of Proteobacteria (19). The pufM gene in clone EBAC000-29C02 was assigned to the Gammaproteobacteria (15). c Average pufM product percent amino acid identity to the top BLASTX hit for all clones in each library is noted. clones from the August 2002 bay and March 2005 turbidity from either end of the estuary (Table 3), but genes related to maximum (66 km from the mouth of the bay) samples also pufM from DelRiverFos13D03 and other Rhodobacter-like clustered with these sequences. The last cluster of pufM genes, pufM genes made up approximately 10% of the August river the Delaware marine group, was composed of genes from cDNA library. Additionally, since Rhodobacter species are as- Delaware Bay clones and from the hypothesized gammapro- sociated with particles (12) and a large proportion of estuarine teobacterial Monterey Bay bacterial artiﬁcial chromosome AAP bacteria are associated with particles (38), we hypothe- (BAC) clones, EBAC000-29C02 and -65D09. The Delaware sized that pufM genes in this clade would be abundant through- marine group cluster also contained the pufM gene from the out the estuary. gammaproteobacterium HTCC2080, isolated from oligotro- The third ecotype targeted by qPCR, the Delaware marine phic oceanic waters (6), and a pufM clone from San Pedro group, was a dominant pufM sequence in the Delaware Bay Channel (SPOTS1). library, comprising 37% of the clones (Table 3), and was sim- Quantitative mapping of pufM ecotypes. To examine the ilar to genes from Monterey Bay BAC clones and the gamma- distribution of pufM genes along the salinity gradient of the proteobacterium HTCC2080 (6). It was distinct, however, from estuary, we designed qPCR primers to target three major the second-most-abundant gammaproteobacterial pufM gene groups of pufM genes hypothesized to be abundant in the in the Delaware Bay library. This pufM clade, comprising 32% estuary (Table 1). One was the pufM gene of the fosmid clone of the Delaware Bay clones, was a loose cluster of genes that DelRiverFos06H03, thought to be representative of freshwater were on average 95% similar to pufM of Congregibacter litoralis. AAP bacteria (37). The second type, Rhodobacter-like, was This type of pufM gene was not targeted by qPCR, since these hypothesized to be ubiquitous throughout the estuary. This sequences did not fall in a tight cluster. ecotype comprised less than 5% of the clones in DNA libraries Two of the pufM types varied consistently with salinity in the 4016 WAIDNER AND KIRCHMAN APPL.ENVIRON.MICROBIOL.

FIG. 1. Relationships of pufM genes in the Delaware River and Bay. Delaware clones from the river (DelRiver), turbidity maximum (Del TurbMax) and bay (DelBay) are in bold. Lake Fryxell clones are abbreviated “LF.” Alpha-, beta-, and gammaproteobacterial clusters are designated on the basis of the 16S rRNA gene. ␣-2, ␣-3, and ␣-4 refer to subclasses of Alphaproteobacteria. Delaware cDNA clones are indicated (cDNA). Fosmid clones described previously (38) are marked DelRiverFOS. Ecotypes targeted by qPCR are indicated by arrows (100% match of primers to fosmid or plasmid sequences). The scale bar represents 5 nucleotide substitutions per 100 positions. Chloroﬂexus aurantiacus was the outgroup. VOL. 74, 2008 DISTRIBUTION AND DIVERSITY OF ESTUARINE AAP BACTERIA 4017

FIG. 2. Distribution of two pufM ecotypes normalized to pg of total DNA in the Delaware estuary. Ecotypes targeted by qPCR were Delaware marine group (gammaproteobacterial) (A) or Rhodoferax-like (betaproteobacterial) (B) pufM genes. Error bars show the standard errors for four qPCRs. The average salinity for all four transects is plotted in panel B. The percentage of bacteria was calculated assuming 2 fg DNA per bacterial cell.

Delaware estuary (Fig. 2). The Delaware marine group was through the salinity gradient (Fig. 3). This pufM gene was more restricted to waters with a salinity of Ͼ11 (Fig. 2A). The abun- abundant in the lower-salinity waters of the estuary (125 km to dance of this pufM gene covaried significantly with salinity (r ϭ 200 km from the mouth) during October and November 2002 0.57; P Ͻ 0.001; n ϭ 49) and was inversely correlated to nitrate (Fig. 3A), whereas in August 2002 and July 2004, the concentrations (r ϭϪ0.69; P Ͻ 0.001; n ϭ 27). At the mouth Rhodobacter-like pufM gene was more abundant in the higher- of the bay in 2002, this gene ranged from 50 to 125 copies/pg salinity stations (Fig. 3B). In the riverine section of the estuary, of total bacterial DNA, corresponding to 0.25 to 0.63% of Rhodobacter-like pufM genes were not as abundant as Rhod- bacteria, assuming 2 fg DNA per bacterial cell. This pufM gene oferax-like pufM, reaching only 120 copies/pg DNA or about was not detected at significant levels in July 2004. In contrast, 0.6% of all bacteria (Fig. 3A). The abundance was not signif- the Rhodoferax-like pufM ecotype was restricted to waters with icantly correlated with nutrient concentrations (r Ͻ 0.31; P Ͼ a salinity of Ͻ5, and its abundance was inversely correlated 0.05; n ϭ 27) or chlorophyll (r ϭ 0.12; P Ͼ 0.05; n ϭ 38). with salinity (r ϭϪ0.65; P Ͻ 0.001; n ϭ 49) and chlorophyll We estimated the contribution of these three ecotypes to the (r ϭϪ0.41; P Ͻ 0.01; n ϭ 39) regardless of the season (Fig. bacterial community as a whole and to the AAP bacterial 2B). Additionally, this freshwater pufM sequence positively community. In the entire data set, the sum of the three types of correlated with nitrate (r ϭ 0.51; P Ͻ 0.01; n ϭ 27) and AAP bacteria comprised up to 1.6% of bacteria, with an aver- phosphate concentrations (r ϭ 0.58; P Ͻ 0.01; n ϭ 27). In three age of 0.14% (calculated from data in Fig. 2 and 3), assuming transects, maximum abundances of Rhodoferax-like pufM were one copy of pufM per genome and two 16S rRNA genes or 2 similar to those of the marine group, ranging from 40 to 150 fg DNA per bacterial cell (14, 28). These estimates were also copies/pg, which corresponds to 0.2 to 0.75% of the total bac- compared to the total AAP bacterial abundance estimated terial community. In August 2002, this type was not abundant previously (38) by pufM qPCR (Table 4). In five cruises, the even in the least-saline stations, reaching only 20 copies/pg three types of pufM comprised on average 5.7% of all bacteria (Fig. 2B). The hypothesized estuarine Rhodobacter-like pufM containing the pufM gene (Table 4). In the middle portions of gene was ubiquitous in the estuary but did not vary consistently the estuary, the contribution of the three pufM types to the 4018 WAIDNER AND KIRCHMAN APPL.ENVIRON.MICROBIOL.

FIG. 3. Distribution of Rhodobacter-like pufM ecotypes, normalized to pg of total DNA, in the Delaware estuary in autumn (A) or summer (B). Error bars, each based on the standard error for four qPCRs, are smaller than the symbols. Dashed vertical lines in panel B delineate the ﬁve regions of the estuary: LB, lower bay (0 to 25 km); MB, midbay (25 to 70 km); ETM, turbidity maximum (70 to 115 km); UrbR, urban river (115 to 175 km); UR, upper river (175 to 215 km). The percentage of bacteria was calculated assuming 2 fg DNA per bacterial cell. total bacterial and AAP bacteria community averaged about Particle-associated pufM genes. To determine if speciﬁc 0.08% and 4.3%, respectively. In the lower bay and upper river, groups of AAP bacteria were associated with particles, we the three types of AAP bacteria examined in this study were estimated abundances of particle-attached pufM-containing more abundant and comprised 12 and 8% of the AAP bacterial bacteria by subtracting values in the free-living fraction from community, respectively (Table 4). those of the corresponding whole water during a transect in

TABLE 4. Contributions of three ecotypes to total AAP bacterial communities in the Delaware estuarya

% of bacteria (ϮSE) containing pufM Regionb (nc) Rhodobacter-like Rhodoferax-like Marine group Sum Lower bay (7) 3.1 (0.15) 0.0049 (0.006) 8.8 (0.21) 12.0 (4.6) Midbay (15) 3.9 (0.11) 0.044 (0.25) 2.0 (0.13) 6.0 (1.7) Turb. max. (9) 2.8 (0.20) 0.19 (0.037) 0.017 (0.0018) 3.1 (1.2) Urban river (18) 1.9 (0.06) 1.5 (0.11) 0.0047 (0.0067) 3.5 (0.72) Upper river (6) 2.8 (0.031) 5.0 (0.058) 0.00010 (0.000014) 7.8 (2.6) Entire estuary (55) 2.9 (0.55) 1.1 (0.79) 1.7 (2.9) 5.7 (0.90)

a The Rhodobacter-like, Rhodoferax-like, and marine group (gammaproteobacterial) pufM genes were compared to the total AAP bacterial community by normalizing to total pufM abundance (36). “Sum” is the total of the three percentages. b Regions were deﬁned as in reference 37 by distance from the mouth of the bay: lower bay (0 to 25 km), Midbay (25 to 70 km), turbidity maximum (Turb. max.) (70 to 115 km), urban river (115 to 175 km), or upper river (175 to 215 km). c n, number of samples in each region from ﬁve cruises (August, October, and November 2002, July 2004, and March 2005). VOL. 74, 2008 DISTRIBUTION AND DIVERSITY OF ESTUARINE AAP BACTERIA 4019

ferax-like types, respectively (calculated from data in Fig. 4). These percentages do not differ signiﬁcantly (analysis of variance, P Ͼ 0.05) and are also not statistically different from 39% Ϯ 18%, the average percentage of total AAP bacteria associated with particles in the Delaware Estuary (38).

DISCUSSION The goal of this study was to examine relationships among estuarine AAP bacteria and to determine if ecotypes inferred from phylogenetic analyses varied systematically within the salinity gradient of the estuary. We hypothesized that the distribution of AAP bacterial types would follow the patterns of bacterial groups previously determined using the 16S rRNA gene. Groups of freshwater, brackish, and marine ecotypes of pufM sequences were determined by phylogenetic analyses, and these patterns were confirmed by qPCR abundance estimates through the estuary. In contrast to our initial hypothesis, the distribution of the three types of pufM genes did not coincide entirely with the patterns of Alpha-, Beta-, and Gamma- proteobacteria typically observed in studies of rRNA genes in estuaries. Salinity probably influenced the distribution of the betaproteobacterial Rhodoferax-like AAP bacteria in the estuary. The hypothesized freshwater pufM genes clustered with pufM genes from organisms originally isolated from low-salinity environments, such as Rhodoferax and Roseateles, and from uncultured bacteria from the Delaware River and Lake Fryxell. In this study, Rhodoferax-like pufM genes were restricted to waters with a salinity of Ͻ5. These data are supported by the obser- vation that Rhodoferax-like pufM genes are restricted to estuarine or freshwaters in the Global Ocean Sampling data set (41). The distribution of this group of pufM genes is consistent with the distribution of Betaproteobacteria in the Delaware and other estuaries (5, 7, 11). This restriction to low-salinity waters, however, may be in part explained by the inverse relationship between nutrient concentrations and salinity in the Delaware (r ϭϪ0.75; P Ͻ 0.001; n ϭ 27) and other estuaries (39). FIG. 4. Distribution of three pufM ecotypes in whole water and the free-living bacterial fraction in March 2005. Abundance of Delaware Unexpectedly, our qPCR results indicated that the abun- marine group (A), Rhodobacter-like (B), or Rhodoferax-like (C) pufM dance of the gammaproteobacterial AAP bacteria covaried genes was normalized to 16S rRNA gene abundance. The percentage with salinity. Studies using 16S rRNA gene clone libraries or of bacteria was calculated assuming two 16S rRNA gene copies per fluorescence in situ hybridization indicate that the Gammapro- bacterial cell. teobacteria do not vary systematically with salinity (7, 10). The distribution observed in this study may be related to the trophic status of these waters (as indicated by nitrate concentra- 2005 (Fig. 4). The variation of the three pufM types in the total tions), not just salinity. In the Delaware estuary, the positive community throughout the estuary in 2005 was similar to that relationship between gammaproteobacterial AAP bacteria and for pufM in the free-living fraction in 2002 and 2004 (Fig. 2 and salinity may be due in fact to nitrate, because there is an 3). However, in contrast to previous transects, Rhodoferax-like inverse relationship between nitrate concentrations and salin- pufM was more abundant than the other two ecotypes. The ity in the estuary (r ϭϪ0.75; P Ͻ 0.001; n ϭ 27). estimated fraction of bacteria comprising the three pufM Additionally, different groups of gammaproteobacterial ecotypes was 10-fold less in 2005 than in 2002 to 2004, in part AAP bacteria may be adapted to different trophic conditions. due to how the bacteria were collected (whole water or GF/D AAP bacteria in the OM60 clade of Gammaproteobacteria filtration versus 0.8-␮m polycarbonate filtration). About 80 km appear to be comprised of two groups based on individual gene from the mouth of the bay (Fig. 4), particle-associated AAP phylogeny and synteny, and these groups occupy distinct hab- bacteria were a very large fraction of the total, probably be- itats (41). In the Delaware estuary, there were two types of cause of high particle concentrations (38). But overall, the gammaproteobacterial pufM genes, which are similar to pufM average (Ϯ standard error) percentages of particle-associated genes in other estuarine and coastal communities. The first pufM genes were 22% Ϯ 36%, 12% Ϯ 31%, and 24% Ϯ 38% type, the most abundant one in the Delaware Bay library, is for the Delaware marine group, Rhodobacter-like, and Rhodo- similar to the pufM gene from the gammaproteobacterium 4020 WAIDNER AND KIRCHMAN APPL.ENVIRON.MICROBIOL.

HTCC2080 (6) and the Monterey Bay BAC clone EBAC000- in coastal and estuarine environments. Particle attachment by 65D09 (4) (Fig. 1). This type accounts for 37% of the pufM AAP bacteria may even be common in the open ocean, since in genes amplified by the Delaware marine group qPCR primers the Sargasso Sea, the estimated AAP abundance was twofold (Table 3). The second type, related to Congregibacter litoralis lower in free-living bacterioplankton (Ͻ0.8 ␮m) than in the 3- (15), comprised a large portion of the pufM genes and mRNA to 20-␮m fraction (41). transcripts from the Delaware River and approximately The qPCR assays targeted three pufM types hypothesized to one-third of pufM clones from the Delaware Bay. Unfortu- be ecologically interesting based on the clone library results nately, the average percent similarity of Delaware estuary and a previous fosmid library study of AAP bacteria (37). In pufM genes to the C. litoralis pufM gene was low (Table 3), total, the three groups examined by qPCR comprised on aver- resulting in this cluster being too loose to be examined by a age only 5.7% of all pufM genes in the estuary, much lower single qPCR assay. than what we expected based on the clone library results. This The qPCR data indicated that the Rhodobacter-like ecotype difference may reflect the well-known problems with trying to covaried with salinity and that there was a seasonal influence use clone library results for quantitative analyses, and it also on this relationship. This seasonal difference is not explained suggests a higher diversity of AAP bacteria than what was by nitrate, since nitrate concentrations are always highest in captured in the four PCR libraries constructed for this study. the urban river and at the turbidity maximum of the estuary, This study was the first to examine how specific types of AAP regardless of season (29). Instead, it may be partly explained by bacteria vary with respect to environmental parameters such as the broad range of Rhodobacter- and Roseobacter-like AAP salinity and nutrients. The distribution of the betaproteobac- genes amplified by this primer set. The nucleotide sequences of terial pufM types within the estuary as determined by qPCR the forward and reverse Rba qPCR primers match, on average, was consistent with what we expected based on its phylogenetic 64 and 86%, respectively, to nucleotide sequences of represen- affiliation. However, the estuarine distribution of the alpha-3- tative Rhodobacter and Roseobacter pufM genes (see Table S2 proteobacterial Rhodobacter-like and gammaproteobacterial in the supplemental material). Subgroups of bacteria in the pufM genes did not coincide with what had previously been Rhodobacter group, particularly those related to Sagittula stel- observed in studies using the 16S rRNA gene. Further inves- lata and Ruegeria spp., vary systematically with season and tigations into the distribution and activity of these and other inorganic nitrogen and particulate organic matter concentra- types of AAP bacteria, such as those containing the gamma- tions in a salt marsh creek (12), although pufM genes have not proteobacterial pufM genes, may provide further clues to po- been found in cultured representatives of these bacterial sub- tentially diverse ecological adaptations by AAP bacteria. groups. More data on AAP bacteria in the Rhodobacter clade are needed. ACKNOWLEDGMENTS Other environmental factors probably influence the survival We thank Vanessa Michelou, Ogugua Anene-Maidoh, and the cap- of specific groups of AAP bacteria in the estuary. Light atten- tain and crew of the R/V Cape Henlopen and R/V Hugh R. Sharp for uation in the turbidity maximum of the Delaware estuary is assistance with sample collection. Chris Sommerfield and Jon Sharp high, and low light availability may negatively influence some provided valuable support as chief scientists of cruises in the Delaware AAP bacteria. This, along with increasing allochthonous nu- estuary. This work was supported by DOE grant DE-FG02-97ER62479 and trient loads, may in part explain the low abundance of the NSF MCB-0453993. Delaware marine group in the Delaware River. This group may be representative of AAP bacteria that are adapted to more REFERENCES oligotrophic, clearer waters, such as those of coastal areas and 1. Achenbach, L. A., J. Carey, and M. T. Madigan. 2001. Photosynthetic and open oceans (6, 15). Additionally, top-down factors, such as phylogenetic primers for detection of anoxygenic phototrophs in natural environments. Appl. Environ. Microbiol. 67:2922–2926. grazing, could also preferentially remove certain ecotypes, 2. Allgaier, M., H. Uphoff, A. Felske, and I. Wagner-Do¨bler. 2003. 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Table S1. Environmental parameters of the Delaware estuary samples described in Waidner and Kirchman (2008 AEM). Distance Seston Temp. Chl a Oxygen Nitrate+Nitrite NH4 PO4 (km) Date (mg/L) Salinity (deg C) (µg/L) (µg/L) (µM) (µM) (µM) 9 8/31/02 31.60 23.0 2.9 7.1 1.60 0.16 45 8/31/02 5.86 20.10 24.4 3.5 7.3 30.00 0.08 66 8/31/02 12.76 15.70 24.8 3.0 7.5 65.24 5.10 0.12 82 8/31/02 13.00 11.60 25.6 3.0 7.6 106.93 19.40 0.64 100 8/31/02 30.99 6.50 24.6 3.9 7.9 145.10 50.50 1.84 121 8/28/02 26.12 27.0 5.0 7.8 136 8/28/02 45.11 0.58 27.3 6.2 7.9 128.30 46.00 3.37 142 8/28/02 34.95 27.1 5.1 7.9 158 8/28/02 15.60 0.24 27.0 3.1 7.9 86.93 38.80 2.59 178 8/28/02 27.0 3.0 7.9 198 8/28/02 13.73 0.12 27.7 4.7 7.8 82.10 16.10 1.47 9 10/22/02 1.35 30.96 17.4 3.7 8.0 3.57 8.75 1.23 18 10/22/02 4.44 28.49 16.5 2.8 8.2 7.35 9.00 1.33 38 10/22/02 4.48 24.94 16.9 2.5 8.3 22.90 8.15 1.88 45 10/22/02 6.87 20.99 15.7 5.3 8.6 44.89 6.35 2.18 66 10/22/02 22.14 10.56 16.2 0.9 9.1 105.21 1.63 2.95 100 10/22/02 70.29 1.19 16.4 0.8 9.7 176.40 2.45 3.65 121 10/21/02 40.45 0.14 16.0 0.9 9.9 128.52 11.14 3.23 151 10/21/02 20.50 13.4 0.5 10.4 174 10/21/02 20.02 0.06 12.3 0.3 10.7 56.49 3.74 1.30 210 10/21/02 14.58 11.3 0.3 11.0 9 11/6/02 16.34 12.2 8.4 9.0 29 11/6/02 9.35 28.00 12.2 17.1 9.0 11.68 3.43 0.84 45 11/6/02 12.00 19.50 11.1 5.5 9.7 64.08 6.48 2.29 66 11/3/02 30.77 13.80 11.5 3.0 10.0 110.50 5.28 2.90 82 11/3/02 69.63 7.70 11.6 2.8 10.4 174.00 8.43 3.28 121 11/3/02 41.05 0.11 10.9 2.1 10.8 157.25 6.65 3.24 136 11/2/02 39.71 0.10 10.9 1.7 11.1 129.75 34.13 3.15 142 11/2/02 30.02 0.10 10.8 2.1 11.1 123.00 31.90 3.01 158 11/2/02 17.30 0.08 10.8 1.3 11.2 87.30 25.60 2.24 170 11/2/02 18.50 0.08 10.7 1.2 10.9 83.60 22.35 2.17 178 11/2/02 39.92 0.08 9.7 1.5 11.4 81.83 7.73 1.76 198 11/1/02 25.87 0.08 9.0 1.0 11.6 81.15 6.13 1.60 9 7/9/04 0.12 30.75 19.1 0.2 7.7 66 7/9/04 35.97 11.12 26.2 0.5 7.6 100 7/9/04 25.88 3.16 26.6 0.7 7.9 136 7/8/04 13.27 0.15 26.8 0.6 8.0 158 7/8/04 17.29 0.13 26.4 0.8 8.0 198 7/8/04 9.95 0.12 27.3 1.0 7.9 9 3/7/2005 28.72 3.3 9.4 28 3/7/2005 88.66 22.55 3.3 10.4 47 3/8/2005 127.86 15.68 3.0 10.6 66 3/8/2005 91.14 12.04 3.1 10.6 78 3/8/2005 46.73 7.11 3.5 10.5 112 3/8/2005 10.91 0.18 3.6 10.5 121 3/8/2005 12.12 0.16 3.5 10.5 131 3/8/2005 11.10 0.17 3.6 10.4

Supplemental Table S2 Waidner and Kirchman

Supplemental Table S2. Specificity of Rhodobacter-like pufM primers for qPCR. The forward and reverse primer sequences were aligned with 397 and 425 sequences respectively from the Delaware estuary, Sargasso, Mediterranean, and Red seas, Monterey Bay, and Rhodobacter, Roseobacter, and Erythrobacter isolates. The sequences are ordered top to bottom with respect to PCR priming efficacy of the primer sequences. A dot at the position indicates an exact match to the primer.

Supplemental Table S2 for

Waidner, L. A., and D. L. Kirchman. 2008. Diversity and distribution of ecotypes of the aerobic anoxygenic phototrophy gene pufM in the Delaware estuary. Appl. Environ. Microbiol. 74:4012-4021.

Diversity and distribution of three distinct ecotypes of the aerobic anoxygenic phototroph gene, pufM Supplemental Table S2 Waidner and Kirchman

5' 3' Percent match to WHOLE 6 BASES AT 3 BASES AT RbaF1 primer TGGACGAACCTGTTCAGC PRIMER 3' END 3' END translation WTNL FS DelRiverFos13D03 ...... 100 100 100 bacterium_R2A163 .....C...... 94 100 100 St2DecG07 ...... C...... 94 100 100 cDNA-1E8 .....C.....C...... 89 100 100 cDNA-1H1 .....C.....C...... 89 100 100 cDNA-3D9 .....C.....C...... 89 100 100 cDNA-3E6 .....C.....C...... 89 100 100 ST2AUG38 .....C.....T...... 89 100 100 DB_1E03 .....C.C.GC...... 78 100 100 DB_2B02 .....C.C.GC...... 78 100 100 Rhodobacter_blasticus .....C...AAC...... 78 100 100 ST2AUG06 .....C...AAC...... 78 100 100 ST2AUG42 .....C...AAC...... 78 100 100 cDNA-1A9 .....C...TATG...A. 67 67 67 cDNA-1B4 .....C...TATG...A. 67 67 67 cDNA-1C7 .....C...TATG...A. 67 67 67 cDNA-1C9 .....C...TATG...A. 67 67 67 cDNA-1G5 .....C...TATG...A. 67 67 67 cDNA-3A5 .....C...TATG...A. 67 67 67 cDNA-3C4 .....C...TATG...A. 67 67 67 Roseobacter_S03 .....C..T...... TC. 78 67 33 DB_2A10 ...... CCG.C....TC. 67 67 33 ST2AUG07 ...... CAGCC...TC. 61 67 33 ST2AUG44 ...... CAGCC...TC. 61 67 33 ST2AUG61 ...... CAGCC...TC. 61 67 33 ST2AUG99 ...... CAGCC...TC. 61 67 33 cDNA-1A12 ...... GCAGCC...TC. 56 67 33 cDNA-1B7 ...... GCAGCC...TC. 56 67 33 cDNA-1C6 ...... GCAGCC...TC. 56 67 33 cDNA-1H9 ...... GCAGCC...TC. 56 67 33 cDNA-3A3 ...... GCAGCC...TC. 56 67 33 cDNA-3B7 ...... GCAGCC...TC. 56 67 33 cDNA-3D2 ...... GCAGCC...TC. 56 67 33 DB_1B11 .....CGC.GCC...TC. 56 67 33 DB_1C12 .....CGC.GCC...TC. 56 67 33 DB_1D11 .....CGC.GCC...TC. 56 67 33 DB_1F11 .....CGC.GCC...TC. 56 67 33 DB_1G11 .....CGC.GCC...TC. 56 67 33 DB_1H11 .....CGC.GCC...TC. 56 67 33 DB_2A04 .....CGC.GCC...TC. 56 67 33 DB_2A07 .....CGC.GCC...TC. 56 67 33 DB_2A11 .....CGC.GCC...TC. 56 67 33 DB_2A12 .....CGC.GCC...TC. 56 67 33 DB_2B08 .....CGC.GCC...TC. 56 67 33 DB_2C02 .....CGC.GCC...TC. 56 67 33 DB_2C06 .....CGC.GCC...TC. 56 67 33

Diversity and distribution of three distinct ecotypes of the aerobic anoxygenic phototroph gene, pufM Supplemental Table S2 Waidner and Kirchman

5' 3' Percent match to WHOLE 6 BASES AT 3 BASES AT RbaF1 primer TGGACGAACCTGTTCAGC PRIMER 3' END 3' END translation WTNL FS DB_2C09 .....CGC.GCC...TC. 56 67 33 DB_2C11 .....CGC.GCC...TC. 56 67 33 DB_2D06 .....CGC.GCC...TC. 56 67 33 DB_2D10 .....CGC.GCC...TC. 56 67 33 DB_2E02 .....CGC.GCC...TC. 56 67 33 DB_2E03 .....CGC.GCC...TC. 56 67 33 DB_2E06 .....CGC.GCC...TC. 56 67 33 DB_2E08 .....CGC.GCC...TC. 56 67 33 DB_2F04 .....CGC.GCC...TC. 56 67 33 DB_2F10 .....CGC.GCC...TC. 56 67 33 DB_2G04 .....CGC.GCC...TC. 56 67 33 DB_2H01 .....CGC.GCC...TC. 56 67 33 DB_2H07 .....CGC.GCC...TC. 56 67 33 DB_2H09 .....CGC.GCC...TC. 56 67 33 cDNA-1C4 .....CGCGGCC...TC. 50 67 33 cDNA-1G4 .....CGCGGCC...TC. 50 67 33 cDNA-3B3 .....CGCGGCC...TC. 50 67 33 ST2AUG37 .....CGCTGCC...TC. 50 67 33 St2DecD04 .....CGCAGCT...TC. 50 67 33 St2DecD08 .....CGCAGCT...TC. 50 67 33 St2DecG08 .....CGCAGCT...TC. 50 67 33 Sar01400725 .....A..TTAT..TTC. 56 50 33 Sar01400725 .....A..TTAT..TTC. 56 50 33 cDNA-1F9 .....AGCGGC...TTC. 50 50 33 DB_2A02 .....CGCAGC...TTC. 50 50 33 DB_2A09 .....CGC.GCC..TTC. 50 50 33 DB_2G08 .....CGC.GCC..TTC. 50 50 33 DB_2H06 .....CGC.GCC..TCT. 50 50 33 eBACred25D05 .....A.CTGCA..TTC. 50 50 33 red12242701 .....A.CTGCA..TTC. 50 50 33 red13211051 .....A.CTGCA..TTC. 50 50 33 redE100P3 .....A.CTGCA..TTC. 50 50 33 cDNA-3C3 .....CGCGGCCA..TC. 44 50 33 cDNA-3E11 .....CGCTGCT..GTC. 44 50 33 red12222201 .....ACCTGCA..TTC. 44 50 33 St2DecD03 .....AGCAGCT..TTC. 44 50 33 cDNA-1A10 .....A.C.GC....TCG 61 50 0 cDNA-1B3 .....A.C.GC....TCG 61 50 0 cDNA-1E12 .....A.C.GC....TCG 61 50 0 cDNA-1F11 .....A.C.GC....TCG 61 50 0 cDNA-1G1 .....A.C.GC....TCG 61 50 0 cDNA-3A11 .....A.C.GC....TCG 61 50 0 cDNA-3A6 .....A.C.GC....TCG 61 50 0 cDNA-3B11 .....A.C.GC....TCG 61 50 0 cDNA-3C10 .....A.C.GC....TCG 61 50 0 cDNA-3C7 .....A.C.GC....TCG 61 50 0 cDNA-3D11 .....A.C.GC....TCG 61 50 0 cDNA-3D8 .....A.C.GC....TCG 61 50 0

Diversity and distribution of three distinct ecotypes of the aerobic anoxygenic phototroph gene, pufM Supplemental Table S2 Waidner and Kirchman

5' 3' Percent match to WHOLE 6 BASES AT 3 BASES AT RbaF1 primer TGGACGAACCTGTTCAGC PRIMER 3' END 3' END translation WTNL FS cDNA-3E4 .....A.C.GC....TCG 61 50 0 medS06P2 .....C.C.GC....TCA 61 50 0 ST2AUG13 ...... CAGC....TCG 61 50 0 ST2AUG60 ...... CAGC....TCG 61 50 0 ST2AUG69 ...... CAGC....TCG 61 50 0 bacterium_MBIC3951 .....C.CGGC....TCG 56 50 0 cDNA-1A5 .....C.CGGC....TCG 56 50 0 DB_1E01 .....C.CGGC....TCG 56 50 0 DB_1G02 .....C.CGGC....TCG 56 50 0 DB_2A03 ...... C.AAAC...TCG 56 50 0 DB_2B04 ...... C.AAAC...TCG 56 50 0 DB_2B11 ...... C.AAAC...TCG 56 50 0 DB_2B12 ...... C.AAAC...TCG 56 50 0 DB_2C01 ...... C.AAAC...TCG 56 50 0 DB_2C08 ...... C.AAAC...TCG 56 50 0 DB_2C12 ...... C.AAAC...TCG 56 50 0 DB_2D07 .....AGC.GC....TCA 56 50 0 DB_2D12 ...... C.AAAC...TCG 56 50 0 DB_2E11 ...... C.AAAC...TCG 56 50 0 DB_2G01 ...... C.AAAC...TCG 56 50 0 DB_2G06 .....AGC.GC....TCA 56 50 0 DB_2H11 ...... C.AAAC...TCG 56 50 0 DelRiverFos06H03 ...... GC.GCA...TCA 56 50 0 medS01P12 .....TGC.GC....TCA 56 50 0 medS06P3 .....TGC.GC....TCA 56 50 0 Rhodovulum_sulfidophilum .....C.C.GCC...TCG 56 50 0 ST2AUG01 ...... GC.GCC...TCG 56 50 0 ST2AUG100 ...... GCGGC....TCG 56 50 0 ST2AUG101 ...... GCGGC....TCG 56 50 0 ST2AUG104 ...... GCGGC....TCG 56 50 0 ST2AUG105 ...... GCGGC....TCG 56 50 0 ST2AUG33 ...... GCGGC....TCG 56 50 0 ST2AUG45 ...... GCGGC....TCG 56 50 0 ST2AUG58 ...... GCGGC....TCG 56 50 0 ST2AUG74 ...... GCGGC....TCG 56 50 0 ST2AUG75 ...... GCGGC....TCG 56 50 0 ST2AUG85 ...... GCGGC....TCG 56 50 0 ST2AUG87 ...... GCGGC....TCG 56 50 0 ST2AUG94 ...... GCGGC....TCG 56 50 0 St2DecA03 ...... GC.GCA...TCA 56 50 0 St2DecA06 ...... GC.GCA...TCA 56 50 0 St2DecA09 ...... GC.GCC...TCA 56 50 0 St2DecB06 ...... GC.GCT...TCG 56 50 0 St2DecB08 ...... GC.GCT...TCA 56 50 0 St2DecB09 ...... GC.GCT...TCA 56 50 0 St2DecB12 ...... GC.GCC...TCA 56 50 0 St2DecC04 ...... GC.GCC...TCA 56 50 0 St2DecC07 ...... GC.GCT...TCG 56 50 0

Diversity and distribution of three distinct ecotypes of the aerobic anoxygenic phototroph gene, pufM Supplemental Table S2 Waidner and Kirchman

5' 3' Percent match to WHOLE 6 BASES AT 3 BASES AT RbaF1 primer TGGACGAACCTGTTCAGC PRIMER 3' END 3' END translation WTNL FS St2DecC10 ...... GC.GCC...TCA 56 50 0 St2DecC11 ...... GC.GCC...TCA 56 50 0 St2DecD07 ...... GC.GCC...TCA 56 50 0 St2DecD12 ...... GC.GCT...TCG 56 50 0 St2DecE07 ...... GC.GCA...TCA 56 50 0 St2DecE08 ...... GC.GCA...TCA 56 50 0 St2DecF01 ...... GC.GCA...TCA 56 50 0 St2DecF03 ...... GC.GCA...TCA 56 50 0 St2DecF06 ...... GC.GCC...TCA 56 50 0 St2DecF07 ...... GC.GCC...TCA 56 50 0 St2DecF11 ...... GC.GCC...TCA 56 50 0 St2DecG02 ...... GC.GCT...TCA 56 50 0 St2DecG11 ...... GC.GCA...TCA 56 50 0 St2DecH07 ...... GC.GCT...TCA 56 50 0 cDNA-1A4 .....AGC.GCC...TCA 50 50 0 cDNA-1B1 ...... GCAGCC...TCG 50 50 0 cDNA-1B8 .....A.CAGCC...TCG 50 50 0 cDNA-1C1 .....AGC.GCC...TCA 50 50 0 cDNA-1C3 .....A.CAGCC...TCG 50 50 0 cDNA-1D5 .....C.CGGCC...TCG 50 50 0 cDNA-1E3 ...... GCAGCC...TCG 50 50 0 cDNA-1F5 .....A.CAGCC...TCG 50 50 0 cDNA-1F7 .....CGCTGC....TCG 50 50 0 cDNA-1G8 .....CGCTGC....TCG 50 50 0 cDNA-1G9 .....A.CAGCC...TCG 50 50 0 cDNA-3A10 .....C.CGGCC...TCG 50 50 0 cDNA-3A2 ...... GCAGCC...TCG 50 50 0 cDNA-3A8 .....CGCTGC....TCG 50 50 0 cDNA-3B5 .....CGCTGC....TCG 50 50 0 cDNA-3C1 .....A.CAGCC...TCG 50 50 0 cDNA-3C2 .....A.CAGCC...TCG 50 50 0 cDNA-3D12 .....C.CGGCC...TCG 50 50 0 cDNA-3E10 .....CGCTGC....TCG 50 50 0 DB_1B01 .....AGCGGC....TCA 50 50 0 DB_1B12 .....AGCGGC....TCA 50 50 0 DB_1C01 ...... GCTGCC...TCG 50 50 0 DB_1C03 .....AGCGGC....TCA 50 50 0 DB_1D03 ...... GCTGCC...TCG 50 50 0 DB_1E02 .....AGCGGC....TCA 50 50 0 DB_1F02 ...... GCGGCC...TCG 50 50 0 DB_1G03 ...... GCGGCC...TCG 50 50 0 DB_2A05 .....AGCGGC....TCA 50 50 0 DB_2A08 .....CGCGGC....CCA 50 50 0 DB_2B01 ...... GCGGCC...TCG 50 50 0 DB_2B05 ...... GCTGCC...TCG 50 50 0 DB_2B07 .....AGCGGC....TCA 50 50 0 DB_2B09 .....AGCGGC....TCA 50 50 0 DB_2C04 ...... GCGGCT...TCG 50 50 0

Diversity and distribution of three distinct ecotypes of the aerobic anoxygenic phototroph gene, pufM Supplemental Table S2 Waidner and Kirchman

5' 3' Percent match to WHOLE 6 BASES AT 3 BASES AT RbaF1 primer TGGACGAACCTGTTCAGC PRIMER 3' END 3' END translation WTNL FS DB_2D03 .....AGCGGC....TCA 50 50 0 DB_2D04 .....AGCGGC....TCA 50 50 0 DB_2D08 ...... GCGGCC...TCG 50 50 0 DB_2E05 .....AGCGGC....TCA 50 50 0 DB_2E07 .....AGCGGC....TCA 50 50 0 DB_2E10 ...... GCTGCC...TCA 50 50 0 DB_2E12 .....AGCGGC....TCA 50 50 0 DB_2F01 .....AGCGGC....TCA 50 50 0 DB_2F03 ...... GCTGCC...TCG 50 50 0 DB_2F08 ...... GCTGCC...TCG 50 50 0 DB_2G05 ...... GCTGCC...TCG 50 50 0 DB_2G09 .....AGCGGC....TCA 50 50 0 DB_2G10 ...... GCTGCC...TCG 50 50 0 DB_2G12 ...... GCTGCC...TCA 50 50 0 MBBAC29C02 .....CGC.GCC...TCG 50 50 0 MBBAC65D09 .....CGCTGC....TCG 50 50 0 Roseobacter_BS90 .....C.CGGCT...TCG 50 50 0 ST2AUG04 .....A.CAGCC...TCG 50 50 0 ST2AUG09 .....A.CAGCC...TCG 50 50 0 ST2AUG10 ...... GCTGCC...TCG 50 50 0 ST2AUG103 ...... GCGGCT...TCG 50 50 0 ST2AUG106 .....A.CAGCC...TCG 50 50 0 ST2AUG107 .....A.CAGCC...TCG 50 50 0 ST2AUG14 ...... GCGGCT...TCG 50 50 0 ST2AUG17 .....A.CAGCC...TCG 50 50 0 ST2AUG18 .....A.CAGCC...TCG 50 50 0 ST2AUG19 ...... GCTGCC...TCG 50 50 0 ST2AUG20 .....TGCGGC....TCG 50 50 0 ST2AUG22 .....A.CAGCC...TCG 50 50 0 ST2AUG23 .....A.CAGCC...TCG 50 50 0 ST2AUG24 .....A.CAGCC...TCG 50 50 0 ST2AUG25 ...... GCGGCT...TCG 50 50 0 ST2AUG29 ...... GCGGCT...TCG 50 50 0 ST2AUG30 .....A.CAGCC...TCG 50 50 0 ST2AUG31 .....A.CAGCC...TCG 50 50 0 ST2AUG32 .....A.CAGCC...TCG 50 50 0 ST2AUG34 .....A.CAGCC...TCG 50 50 0 ST2AUG35 .....A.CAGCC...TCG 50 50 0 ST2AUG36 .....A.CAGCC...TCG 50 50 0 ST2AUG39 .....CGC.GCA...TCA 50 50 0 ST2AUG40 ...... GCGGCT...TCG 50 50 0 ST2AUG41 .....A.CAGCC...TCG 50 50 0 ST2AUG43 ...... GCTGCC...TCG 50 50 0 ST2AUG47 .....A.CAGCC...TCG 50 50 0 ST2AUG48 ...... GCGGCT...TCG 50 50 0 ST2AUG49 ...... GCGGCT...TCG 50 50 0 ST2AUG50 .....A.CAGCC...TCG 50 50 0 ST2AUG51 .....A.CAGCC...TCG 50 50 0

Diversity and distribution of three distinct ecotypes of the aerobic anoxygenic phototroph gene, pufM Supplemental Table S2 Waidner and Kirchman

5' 3' Percent match to WHOLE 6 BASES AT 3 BASES AT RbaF1 primer TGGACGAACCTGTTCAGC PRIMER 3' END 3' END translation WTNL FS ST2AUG53 .....A.CAGCC...TCG 50 50 0 ST2AUG54 .....TGC.GCC...TCG 50 50 0 ST2AUG55 .....A.CAGCC...TCG 50 50 0 ST2AUG57 .....A.CAGCC...TCG 50 50 0 ST2AUG59 .....A.CAGCC...TCG 50 50 0 ST2AUG63 .....A.CAGCC...TCG 50 50 0 ST2AUG64 .....A.CAGCC...TCG 50 50 0 ST2AUG66 .....A.CAGCC...TCG 50 50 0 ST2AUG67 .....A.CAGCC...TCG 50 50 0 ST2AUG68 .....A.CAGCC...TCG 50 50 0 ST2AUG71 .....A.CAGCC...TCG 50 50 0 ST2AUG72 ...... GCGGCT...TCG 50 50 0 ST2AUG73 .....A.CAGCC...TCG 50 50 0 ST2AUG76 .....A.CAGCC...TCG 50 50 0 ST2AUG77 .....A.CAGCC...TCG 50 50 0 ST2AUG79 .....A.CAGCC...TCG 50 50 0 ST2AUG80 .....A.CAGCC...TCG 50 50 0 ST2AUG81 .....A.CAGCC...CCG 50 50 0 ST2AUG82 .....A.CAGCC...TCG 50 50 0 ST2AUG83 .....A.CAGCC...TCG 50 50 0 ST2AUG89 .....A.CAGCC...TCG 50 50 0 ST2AUG90 .....A.CAGCC...TCG 50 50 0 ST2AUG92 .....A.CAGCC...TCG 50 50 0 ST2AUG93 .....A.CAGCC...TCG 50 50 0 ST2AUG97 .....A.CAGCC...TCG 50 50 0 ST2AUG98 .....A.CAGCC...TCG 50 50 0 St2DecA01 ...... GCGGCT...TCG 50 50 0 St2DecA04 ...... GCAGCC...TCG 50 50 0 St2DecA07 ...... GCGGCT...TCG 50 50 0 St2DecA11 ...... GCGGCT...TCG 50 50 0 St2DecB05 ...... GCGGCC...TCG 50 50 0 St2DecB10 ...... GCAGCC...TCG 50 50 0 St2DecB11 ...... GCAGCC...TCG 50 50 0 St2DecD01 ...... GCAGCT...TCT 50 50 0 St2DecD05 ...... GCGGCT...TCG 50 50 0 St2DecD09 ...... GCAGCC...TCG 50 50 0 St2DecD10 ...... GCAGCT...TCG 50 50 0 St2DecD11 ...... GCAGCT...TCT 50 50 0 St2DecE04 ...... GCAGCC...TCG 50 50 0 St2DecE05 ...... GCAGCC...TCG 50 50 0 St2DecE06 ...... GCAGCT...TCG 50 50 0 St2DecE09 ...... GCTGCT...TCG 50 50 0 St2DecE10 ...... GCGGCT...TCG 50 50 0 St2DecE11 ...... GCAGCC...TCG 50 50 0 St2DecE12 ...... GCAGCC...TCG 50 50 0 St2DecF05 ...... GCAGCC...TCG 50 50 0 St2DecF08 ...... GCAGCT...TCG 50 50 0 St2DecF09 ...... GCGGCT...TCG 50 50 0

Diversity and distribution of three distinct ecotypes of the aerobic anoxygenic phototroph gene, pufM Supplemental Table S2 Waidner and Kirchman

5' 3' Percent match to WHOLE 6 BASES AT 3 BASES AT RbaF1 primer TGGACGAACCTGTTCAGC PRIMER 3' END 3' END translation WTNL FS St2DecF10 ...... GCGGCT...TCG 50 50 0 St2DecF12 ...... GCAGCC...TCG 50 50 0 St2DecG03 ...... GCAGCC...TCG 50 50 0 St2DecG05 ...... GCAGCC...TCG 50 50 0 St2DecG06 ...... GCAGCT...TCG 50 50 0 St2DecH09 ...... GCAGCT...TCG 50 50 0 cDNA-1A1 .....CGCGGCC...TCA 44 50 0 cDNA-1B12 .....CGCGGCC...TCA 44 50 0 cDNA-1C5 .....CGCGGCC...TCA 44 50 0 cDNA-1D10 .....AGCAGCC...TCT 44 50 0 cDNA-1E10 .....CGCGGCC...TCA 44 50 0 cDNA-1E11 .....AGCAGCC...TCT 44 50 0 cDNA-1E6 .....CGCGGCC...TCA 44 50 0 cDNA-1E9 .....AGCAGCC...TCT 44 50 0 cDNA-1F1 .....CGCGGCC...TCA 44 50 0 cDNA-1F2 .....AGCAGCC...TCT 44 50 0 cDNA-1F6 .....AGCAGCC...TCT 44 50 0 cDNA-1H3 .....AGCAGCC...TCT 44 50 0 cDNA-3A12 .....CGCGGCT...TCT 44 50 0 cDNA-3A9 .....AGCAGCC...TCT 44 50 0 cDNA-3B10 .....CGCGGCC...TCA 44 50 0 cDNA-3B2 .....CGCGGCC...TCA 44 50 0 cDNA-3B8 .....AGCAGCC...TCT 44 50 0 cDNA-3C11 .....CGCGGCC...TCA 44 50 0 cDNA-3C8 .....CGCGGCC...TCA 44 50 0 cDNA-3D10 .....CGCGGCC...TCA 44 50 0 cDNA-3D4 .....CGCGGCC...TCA 44 50 0 cDNA-3E1 .....CGCGGCT...TCT 44 50 0 DB_1H02 .....CGCTGCC...TCG 44 50 0 DB_2C03 .....CGCGGCC...TCG 44 50 0 DB_2H05 .....CGCGGCC...TCG 44 50 0 MBBAC24D02 .....CGCTGCT...TCG 44 50 0 MBBAC39B11 .....CGCTGCC...TCG 44 50 0 MBBAC52B02 .....CGCTGCT...TCG 44 50 0 ST2AUG08 .....CGGGGCA . . . TCA 44 50 0 ST2AUG102 .....AGCAGCC...TCG 44 50 0 ST2AUG16 .....CGCGGCA...TCA 44 50 0 ST2AUG46 .....ATCTGCA...TCG 44 50 0 ST2AUG56 .....AGCGGCT...TCG 44 50 0 ST2AUG86 .....ATCTGCA...TCG 44 50 0 ST2AUG91 .....CGCGGCA...TCA 44 50 0 St2DecB07 .....CGCGGCT...TCA 44 50 0 St2DecC01 .....CGCTGCA...TCT 44 50 0 St2DecC02 .....AGCGGCC...TCG 44 50 0 St2DecD02 .....AGCAGCC...TCG 44 50 0 St2DecD06 .....AGCGGCC...TCA 44 50 0 cDNA-1B9 ...... GC.GC...GTCG 56 33 0 cDNA-1F3 ...... GC.GC...GTCG 56 33 0

Diversity and distribution of three distinct ecotypes of the aerobic anoxygenic phototroph gene, pufM Supplemental Table S2 Waidner and Kirchman

5' 3' Percent match to WHOLE 6 BASES AT 3 BASES AT RbaF1 primer TGGACGAACCTGTTCAGC PRIMER 3' END 3' END translation WTNL FS cDNA-3A7 ...... GC.GC...GTCG 56 33 0 cDNA-3E12 ...... GC.GC...GTCG 56 33 0 Roseobacter_OCH114 ...... CAGC...TTCG 56 33 0 Roseobacter_denitrificans ...... CAGC...TTCG 56 33 0 Roseobacter_litoralis ...... CAGC...TTCG 56 33 0 cDNA-1F10 ...... GCAGC...TTCG 50 33 0 DB_2H08 .....C.CGGC...TTCG 50 33 0 medS01P3 .....A.CTGC...TTCA 50 33 0 ST2AUG95 ...... GCAGC...TTCG 50 33 0 St2DecA05 ...... GCGGC...TTCG 50 33 0 DB_1A12 .....T.TGACC..TTCA 44 33 0 DB_1B02 .....T.TGACC..TTCA 44 33 0 DB_1C02 .....C.TGACC..TTCA 44 33 0 DB_1C11 .....C.TGACC..TTCA 44 33 0 DB_1F01 .....T.TGACC..TTCA 44 33 0 DB_1F03 .....T.TGACC..TTCA 44 33 0 DB_1G01 .....C.TGACC..TTCA 44 33 0 DB_1H03 .....C.TGACC..TTCA 44 33 0 DB_2A01 .....T.TGACC..TTCA 44 33 0 DB_2B06 .....T.TGACC..TTCA 44 33 0 DB_2C05 .....T.TGACC..TTCA 44 33 0 DB_2D01 .....T.TGACC..TTCA 44 33 0 DB_2D09 .....T.TGACC..TTCA 44 33 0 DB_2E01 .....C.TGACC..TTCA 44 33 0 DB_2F02 .....T.TGACC..TTCA 44 33 0 DB_2F05 .....T.TGACC..TTCA 44 33 0 DB_2F07 .....C.TGACC..TTCA 44 33 0 DB_2F11 .....T.TGACC..TTCA 44 33 0 DB_2F12 .....T.TGACC..TTCA 44 33 0 DB_2G11 ...... GCTGCC..TTCA 44 33 0 DB_2H03 .....T.TGACC..TTCA 44 33 0 DB_2H04 .....C.TGACC..TTCA 44 33 0 DB_2H10 .....T.TGACC..TTCA 44 33 0 Sar01024194 .....A.TGAAC..TTCA 44 33 0 Sar01024194 .....A.TGAAC..TTCA 44 33 0 SarY01093008 .....A.TGAAC..TTCA 44 33 0 St2DecB04 ...... GCGGCC..TTCG 44 33 0 St2DecC03 .....AGC.GCC..TTCA 44 33 0 St2DecC05 .....TGC.GCA..TTCT 44 33 0 St2DecC06 .....TGC.GCA..TTCT 44 33 0 St2DecC08 ...... GCGGCC..TTCG 44 33 0 St2DecC09 ...... GCAGCC..TTCG 44 33 0 St2DecE03 .....TGC.GCA..TTCT 44 33 0 cDNA-1A8 .....CGCTGCT..GTCT 39 33 0 cDNA-1D3 .....CGCTGCT..GTCT 39 33 0 cDNA-1F4 .....CGCTGCT..GTCT 39 33 0 cDNA-1G11 .....CGCTGCT..GTCT 39 33 0 cDNA-1G3 .....CGCTGCT..GTCT 39 33 0

Diversity and distribution of three distinct ecotypes of the aerobic anoxygenic phototroph gene, pufM Supplemental Table S2 Waidner and Kirchman

5' 3' Percent match to WHOLE 6 BASES AT 3 BASES AT RbaF1 primer TGGACGAACCTGTTCAGC PRIMER 3' END 3' END translation WTNL FS cDNA-1H2 .....CGCTGCT..GTCT 39 33 0 cDNA-3C9 .....AGCGGCA..TTCT 39 33 0 cDNA-3E8 .....CGCTGCT..GTCT 39 33 0 ST2AUG52 .....CGCGGCC..TTCG 39 33 0 ST2AUG65 .....CGCGGCC..TTCG 39 33 0 ST2AUG88 .....CGCGGCC..TTCG 39 33 0 St2DecA02 .....AGCGGCC..TTCG 39 33 0 St2DecE01 .....AGCGGCC..TTCG 39 33 0 St2DecG09 .....AGCGGCC..TTCG 39 33 0 St2DecG10 .....AGCGGCC..TTCG 39 33 0 ST2AUG15 . . . G T C T C G G C . C . . T C G 33 33 0 St2DecC12 ....TAGCGGCC..TTCA 33 33 0 ST2AUG26 . . . G T C T C G G C A C . . T C G 28 33 0 ST2AUG78 . . . G T C T C G G C A C . . T C G 28 33 0 BACmed31B01 ...... CGGCT.ATTCT 44 17 0

Diversity and distribution of three distinct ecotypes of the aerobic anoxygenic phototroph gene, pufM Supplemental Table S2 Waidner and Kirchman

3' 5' Percent match to WHOLE 6 BASES AT 3 BASES AT RbaR1 primer (rev. compl.) GGCGACCGCGAGTTG PRIMER 3' END 3' END translation GDREL DelRiverFos13D03 ...... 100 100 100 Roseobacter_OCH114 ...... 100 100 100 cDNA-3E6 ...... 100 100 100 St2DecG07 ...... 100 100 100 cDNA-1H1 ...... 100 100 100 cDNA-1E8 ...... 100 100 100 Roseobacter_denitrificans ...... 100 100 100 cDNA-3D9 ...... 100 100 100 DB_2B02 ...... C.. 93 100 100 DB_1E03 ...... C.. 93 100 100 ST2AUG38 ...... C.. 93 100 100 Roseobacter_litoralis ...... C.. 93 100 100 Rhodobacter_blasticus ...... C.. 93 100 100 Rhodovulum_sulfidophilum ...... C.. 93 100 100 Rhodobacter_sphaeroides .....G...... C.. 87 83 100 ST2AUG06 ...... AC.. 87 100 100 DB_2H08 ...... G...C.. 87 100 100 bacterium_R2A163 ...... G...C.. 87 100 100 Rhodobacter_capsulatus .....A...... C.. 87 83 100 cDNA-1A5 ...... C.C 87 100 100 Roseobacter_BS90 ...... C.C 87 100 100 DB_1E01 ...... C.T 87 100 100 DB_1G02 ...... C.T 87 100 100 Rhodobacter_azotoformans ....TG...... C.. 80 67 100 Rhodobacter_veldkampii .....G.....AC.. 80 83 100 bacterium_MBIC3951 ...... T...C.A 80 100 100 medS01P3 .....T...... C.T 80 83 100 cDNA-1A1 .....T...... C.C 80 83 100 cDNA-3C8 .....T...... C.C 80 83 100 cDNA-1E6 .....T...... C.C 80 83 100 cDNA-3D4 .....T...... C.C 80 83 100 cDNA-3B2 .....T...... C.C 80 83 100 cDNA-1F1 .....T...... C.C 80 83 100 cDNA-1C5 .....T...... C.C 80 83 100 DB_2G11 .....T...... A.A 80 83 100 St2DecC07 .....A...... A.T 80 83 100 St2DecC05 .....A...... A.T 80 83 100 St2DecA07 .....A...... A.T 80 83 100 St2DecE09 .....A...... A.T 80 83 100 St2DecE03 .....A...... A.T 80 83 100 Roseobacter_S03 .....A...... A.T 80 83 100 St2DecB06 .....A...... A.T 80 83 100 DB_2E10 .....T...... A.T 80 83 100 DB_2H11 .....T...... A.T 80 83 100 DB_2C12 .....T...... A.T 80 83 100 DB_2A03 .....T...... A.T 80 83 100 DB_2G12 .....T...... A.T 80 83 100 MBBAC24D02 .....T...... A.C 80 83 100

Diversity and distribution of three distinct ecotypes of the aerobic anoxygenic phototroph gene, pufM Supplemental Table S2 Waidner and Kirchman

3' 5' Percent match to WHOLE 6 BASES AT 3 BASES AT RbaR1 primer (rev. compl.) GGCGACCGCGAGTTG PRIMER 3' END 3' END translation GDREL MBBAC65D09 .....T...... A.C 80 83 100 MBBAC52B02 .....T...... A.C 80 83 100 St2DecD10 .....A...... A.C 80 83 100 St2DecF09 .....A...... A.C 80 83 100 ST2AUG101 .....A...... A.C 80 83 100 ST2AUG58 .....A...... A.C 80 83 100 St2DecG06 .....A...... A.C 80 83 100 St2DecE06 .....A...... A.C 80 83 100 St2DecH09 .....A...... A.C 80 83 100 ST2AUG105 .....A...... A.C 80 83 100 ST2AUG74 .....A...... A.C 80 83 100 ST2AUG20 .....A...... A.C 80 83 100 St2DecE10 .....A...... A.C 80 83 100 cDNA-1A12 .....G...... C.C 80 83 100 cDNA-1C6 .....G...... C.C 80 83 100 cDNA-1H9 .....G...... C.C 80 83 100 cDNA-1B7 .....G...... C.C 80 83 100 St2DecA05 .....G...... A.T 80 83 100 cDNA-3C9 .....G...... A.T 80 83 100 St2DecD05 .....G...... A.C 80 83 100 St2DecG08 .....G...... A.C 80 83 100 cDNA-1D10 .....G...... A.C 80 83 100 ST2AUG60 .....G...... A.C 80 83 100 cDNA-1E9 .....G...... A.C 80 83 100 cDNA-1F10 .....G...... A.C 80 83 100 cDNA-1F2 .....G...... A.C 80 83 100 cDNA-1F6 .....G...... A.C 80 83 100 cDNA-1B1 .....G...... A.C 80 83 100 St2DecD04 .....G...... A.C 80 83 100 cDNA-3A9 .....G...... A.C 80 83 100 ST2AUG35 .....G...... A.C 80 83 100 cDNA-1H3 .....G...... A.C 80 83 100 ST2AUG95 .....G...... A.C 80 83 100 cDNA-1E3 .....G...... A.C 80 83 100 cDNA-1E11 .....G...... A.C 80 83 100 cDNA-3B8 .....G...... A.C 80 83 100 cDNA-1H7 .....G...... A.C 80 83 100 St2DecD08 .....G...... A.C 80 83 100 cDNA-3A2 .....G...... A.C 80 83 100 ST2AUG69 .....G...... A.C 80 83 100 ST2AUG13 .....G...... A.C 80 83 100 LFmorphotype_B .....G..G..AC.. 73 83 100 DB_2G08 .....T..T...C.T 73 83 100 ST2AUG37 .....A..A...C.C 73 83 100 ST2AUG54 .....G.....AG.C 73 83 100 DB_2A09 .....T..T...C.T 73 83 100 cDNA-3A8 .....A..T...A.C 73 83 100 cDNA-1F7 .....A..T...A.C 73 83 100

Diversity and distribution of three distinct ecotypes of the aerobic anoxygenic phototroph gene, pufM Supplemental Table S2 Waidner and Kirchman

3' 5' Percent match to WHOLE 6 BASES AT 3 BASES AT RbaR1 primer (rev. compl.) GGCGACCGCGAGTTG PRIMER 3' END 3' END translation GDREL cDNA-3E10 .....A..T...A.C 73 83 100 cDNA-1G8 .....A..T...A.C 73 83 100 cDNA-3B5 .....A..T...A.C 73 83 100 DB_2A12 .....T..G...C.A 73 83 100 DB_2F04 .....T..G...C.A 73 83 100 ST2AUG15 .....T..G...A.C 73 83 100 cDNA-1B8 .....G..T...G.C 73 83 100 cDNA-1G9 .....G..T...A.C 73 83 100 ST2AUG63 .....G..T...A.C 73 83 100 MedRsbBS110 .....G..T...A.C 73 83 100 ST2AUG09 .....G..T...A.C 73 83 100 ST2AUG92 .....G..T...A.C 73 83 100 ST2AUG47 .....G..T...A.C 73 83 100 ST2AUG23 .....G..T...A.C 73 83 100 ST2AUG18 .....G..T...A.C 73 83 100 ST2AUG31 .....G..T...A.C 73 83 100 ST2AUG83 .....G..T...A.C 73 83 100 ST2AUG76 .....G..T...A.C 73 83 100 ST2AUG51 .....G..T...A.C 73 83 100 cDNA-1F5 .....G..T...A.C 73 83 100 ST2AUG36 .....G..T...A.C 73 83 100 ST2AUG17 .....G..T...A.C 73 83 100 ST2AUG82 .....G..T...A.C 73 83 100 ST2AUG66 .....G..T...A.C 73 83 100 ST2AUG59 .....G..T...A.C 73 83 100 ST2AUG55 .....G..T...A.C 73 83 100 ST2AUG61 .....G..T...A.C 73 83 100 ST2AUG89 .....G..T...A.C 73 83 100 ST2AUG04 .....G..T...A.C 73 83 100 ST2AUG64 .....G..T...A.C 73 83 100 ST2AUG97 .....G..T...A.C 73 83 100 ST2AUG68 .....G..T...A.C 73 83 100 ST2AUG102 .....G..T...A.C 73 83 100 ST2AUG90 .....G..T...A.C 73 83 100 ST2AUG93 .....G..T...A.C 73 83 100 ST2AUG50 .....G..T...A.C 73 83 100 ST2AUG34 .....G..T...A.C 73 83 100 ST2AUG106 .....G..T...A.C 73 83 100 ST2AUG71 .....G..T...A.C 73 83 100 ST2AUG107 .....G..T...A.C 73 83 100 ST2AUG30 .....G..T...A.C 73 83 100 ST2AUG67 .....G..T...A.C 73 83 100 ST2AUG24 .....G..T...A.C 73 83 100 ST2AUG79 .....G..T...A.C 73 83 100 ST2AUG53 .....G..T...A.C 73 83 100 Roseobacter_BS110 .....G..T...A.C 73 83 100 ST2AUG77 .....G..T...A.C 73 83 100 ST2AUG32 .....G..T...A.C 73 83 100

Diversity and distribution of three distinct ecotypes of the aerobic anoxygenic phototroph gene, pufM Supplemental Table S2 Waidner and Kirchman

3' 5' Percent match to WHOLE 6 BASES AT 3 BASES AT RbaR1 primer (rev. compl.) GGCGACCGCGAGTTG PRIMER 3' END 3' END translation GDREL ST2AUG80 .....G..T...A.C 73 83 100 cDNA-3A12 .....G..T...A.C 73 83 100 ST2AUG57 .....G..T...A.C 73 83 100 cDNA-1C3 .....G..T...A.C 73 83 100 ST2AUG41 .....G..T...A.C 73 83 100 ST2AUG73 .....G..T...A.C 73 83 100 ST2AUG98 .....G..T...A.C 73 83 100 ST2AUG44 .....G..T...A.C 73 83 100 ST2AUG22 .....G..T...A.C 73 83 100 ST2AUG81 .....G..T...A.C 73 83 100 ST2AUG07 .....G..T...A.C 73 83 100 cDNA-3E1 .....G..T...A.C 73 83 100 cDNA-3C1 .....G..T...A.C 73 83 100 cDNA-3C2 .....G..T...A.C 73 83 100 DB_1B11 .....T..G...C.A 73 83 100 DB_2C06 .....T..G...C.A 73 83 100 DB_2A04 .....T..G...C.A 73 83 100 DB_2E02 .....T..G...C.A 73 83 100 DB_2E08 .....T..G...C.A 73 83 100 DB_2H01 .....T..G...C.A 73 83 100 DB_1C12 .....T..G...C.A 73 83 100 DB_2A11 .....T..G...C.A 73 83 100 DB_2C09 .....T..G...C.A 73 83 100 DB_2E03 .....T..G...C.A 73 83 100 DB_1F11 .....T..G...C.A 73 83 100 DB_2A07 .....T..G...C.A 73 83 100 DB_2D10 .....T..G...C.A 73 83 100 DB_2H09 .....T..G...C.A 73 83 100 DB_2E06 .....T..G...C.A 73 83 100 DB_2C11 .....T..G...C.A 73 83 100 DB_2A10 .....T..G...C.A 73 83 100 DB_2H06 .....T..G...C.A 73 83 100 DB_1D11 .....T..G...C.A 73 83 100 DB_2F10 .....T..G...C.A 73 83 100 DB_2D06 .....T..G...C.A 73 83 100 DB_2B08 .....T..G...C.A 73 83 100 DB_2H07 .....T..G...C.A 73 83 100 DB_2G04 .....T..G...C.A 73 83 100 DB_1G11 .....T..G...C.A 73 83 100 DB_2C02 .....T..G...C.A 73 83 100 DB_1H11 .....T..G...C.A 73 83 100 St2DecC01 .....G.....AA.C 73 83 100 cDNA-1F9 .....G.....AA.C 73 83 100 medS06P2 .....TA.G...C.T 67 83 100 MBBAC60D04 .....G..G..AA.T 67 83 100 MBBAC30G07 .....G..G..AA.T 67 83 100 MBBAC56B12 .....G..G..AA.T 67 83 100 ST2AUG99 .....G..T...ACC 67 83 100

Diversity and distribution of three distinct ecotypes of the aerobic anoxygenic phototroph gene, pufM Supplemental Table S2 Waidner and Kirchman

3' 5' Percent match to WHOLE 6 BASES AT 3 BASES AT RbaR1 primer (rev. compl.) GGCGACCGCGAGTTG PRIMER 3' END 3' END translation GDREL St2DecE02 .....G..T..AA.C 67 83 100 Sar01287106 . . A . . T A . A ...... 73 67 67 Sar01287106 . . A . . T A . A ...... 73 67 67 St2DecC06 . . T . . T ...... G.T 73 67 67 ST2AUG42 . . G .....G..AC.. 73 83 67 DB_1F01 . . A . . T . . G . . A . . . 73 67 67 DB_2H10 . . A . . T . . G . . A . . . 73 67 67 DB_2F12 . . A . . T . . G . . A . . . 73 67 67 DB_2F02 . . A . . T . . G . . A . . . 73 67 67 DB_2C05 . . A . . T . . G . . A . . . 73 67 67 DB_2F05 . . A . . T . . G . . A . . . 73 67 67 DB_1A12 . . A . . T . . G . . A . . . 73 67 67 DB_1F03 . . A . . T . . G . . A . . . 73 67 67 DB_2D01 . . A . . T . . G . . A . . . 73 67 67 DB_2B06 . . A . . T . . G . . A . . . 73 67 67 DB_1B02 . . A . . T . . G . . A . . . 73 67 67 DB_2F11 . . A . . T . . G . . A . . . 73 67 67 DB_2D09 . . A . . T . . G . . A . . . 73 67 67 DB_2H03 . . A . . T . . G . . A . . . 73 67 67 DB_2A01 . . A . . T . . G . . A . . . 73 67 67 cDNA-3D2 . . T . . A .....AC.. 73 67 67 cDNA-3B7 . . T . . A .....AC.. 73 67 67 cDNA-3A3 . . T . . A .....AC.. 73 67 67 St2DecG01 . . T .....G..AC.. 73 83 67 ST2AUG46 . . T . . G .....AG.. 73 67 67 ST2AUG86 . . T . . G .....AG.. 73 67 67 DB_1G01 . . A . . T . . T . . A . . . 73 67 67 DB_2E01 . . A . . T . . T . . A . . . 73 67 67 DB_1C02 . . A . . T . . T . . A . . . 73 67 67 DB_2H04 . . A . . T . . T . . A . . . 73 67 67 DB_2F07 . . A . . T . . T . . A . . . 73 67 67 DB_1C11 . . A . . T . . T . . A . . . 73 67 67 DB_1H03 . . A . . T . . T . . A . . . 73 67 67 St2DecG11 . . T . . A ...... G.T 73 67 67 Sar01024194 . . G . . . A . A .....A 73 83 67 Sar01319421 . . G . . . A . A .....A 73 83 67 Sar01024194 . . G . . . A . A .....A 73 83 67 Sar01319421 . . G . . . A . A .....A 73 83 67 BACmed31B01 . . T ...... AC.C 73 83 67 cDNA-1A4 . . G . . A ...... A.C 73 67 67 cDNA-1C1 . . G . . A ...... A.C 73 67 67 St2DecF03 . . T . . A ...... A.T 73 67 67 St2DecA01 . . T . . A ...... A.T 73 67 67 St2DecB05 . . T . . A ...... A.T 73 67 67 St2DecF01 . . T . . A ...... A.T 73 67 67 St2DecA03 . . T . . A ...... A.T 73 67 67 St2DecA06 . . T . . A ...... A.T 73 67 67 St2DecD12 . . T . . G ...... A.T 73 67 67

Diversity and distribution of three distinct ecotypes of the aerobic anoxygenic phototroph gene, pufM Supplemental Table S2 Waidner and Kirchman

3' 5' Percent match to WHOLE 6 BASES AT 3 BASES AT RbaR1 primer (rev. compl.) GGCGACCGCGAGTTG PRIMER 3' END 3' END translation GDREL St2DecC04 . . T . . G ...... A.T 73 67 67 St2DecF11 . . T . . G ...... A.T 73 67 67 St2DecD07 . . T . . G ...... A.T 73 67 67 St2DecC10 . . T . . G ...... A.T 73 67 67 St2DecA09 . . T . . G ...... A.T 73 67 67 St2DecB12 . . T . . G ...... A.T 73 67 67 St2DecC11 . . T . . G ...... A.T 73 67 67 St2DecA02 . . T . . A ...... A.C 73 67 67 bacterium_R2A84 . . T . . A ...... A.C 73 67 67 St2DecB07 . . T . . A ...... A.C 73 67 67 St2DecG09 . . T . . A ...... A.C 73 67 67 St2DecD01 . . T . . A ...... A.C 73 67 67 St2DecE01 . . T . . A ...... A.C 73 67 67 St2DecE05 . . T . . A ...... A.C 73 67 67 St2DecG10 . . T . . A ...... A.C 73 67 67 St2DecD11 . . T . . A ...... A.C 73 67 67 St2DecA04 . . T . . G ...... A.C 73 67 67 St2DecG03 . . T . . G ...... A.C 73 67 67 St2DecE04 . . T . . G ...... A.C 73 67 67 St2DecC09 . . T . . G ...... A.C 73 67 67 St2DecF12 . . T . . G ...... A.C 73 67 67 St2DecD02 . . T . . G ...... A.C 73 67 67 St2DecD06 . . T . . G ...... A.C 73 67 67 St2DecD09 . . T . . G ...... A.C 73 67 67 St2DecF08 . . T . . G ...... A.C 73 67 67 St2DecE12 . . T . . G ...... A.C 73 67 67 St2DecB11 . . T . . G ...... A.C 73 67 67 St2DecB10 . . T . . G ...... A.C 73 67 67 St2DecE11 . . T . . G ...... A.C 73 67 67 St2DecF05 . . T . . G ...... A.C 73 67 67 St2DecC12 . . T . . G ...... A.C 73 67 67 Sar01400725 . . A . . T . . T ...... 80 67 67 Sar01400725 . . A . . T . . T ...... 80 67 67 eBACred25D05 . . A .....T...C.. 80 83 67 red12242701 . . A .....T...C.. 80 83 67 red12222201 . . A .....T...C.. 80 83 67 redE100P3 . . A .....T...C.. 80 83 67 cDNA-3D12 . . T ...... A.C 80 83 67 cDNA-1D5 . . T ...... A.C 80 83 67 cDNA-3A10 . . T ...... A.C 80 83 67 DB_2E09 . . G . . . A . A . . A . . A 67 83 67 SarY01093008 . . G . . . A . A . . A . . A 67 83 67 SarY01093008 . . G . . . A . A . . A . . A 67 83 67 Sar01194873 . . T . . T . . T . . A . . A 67 67 67 Sar01194873 . . T . . T . . T . . A . . A 67 67 67 red13211051 . . T . . T . . T . . A C . . 67 67 67 St2DecC02 . . G . . A .....AA.C 67 67 67 St2DecE07 . . T . . A .....AA.T 67 67 67

Diversity and distribution of three distinct ecotypes of the aerobic anoxygenic phototroph gene, pufM Supplemental Table S2 Waidner and Kirchman

3' 5' Percent match to WHOLE 6 BASES AT 3 BASES AT RbaR1 primer (rev. compl.) GGCGACCGCGAGTTG PRIMER 3' END 3' END translation GDREL St2DecF06 . . T . . A .....AA.T 67 67 67 DelRiverFos06H03 . . T . . A .....AA.T 67 67 67 St2DecE08 . . T . . A .....AA.T 67 67 67 St2DecF07 . . T . . A .....AA.T 67 67 67 cDNA-1D3 . . T . . A . . T . . . A . T 67 67 67 cDNA-3E8 . . T . . A . . T . . . A . T 67 67 67 cDNA-1H2 . . T . . A . . T . . . A . T 67 67 67 cDNA-3E11 . . T . . A . . T . . . A . T 67 67 67 cDNA-1F4 . . T . . A . . T . . . A . T 67 67 67 cDNA-1G11 . . T . . A . . T . . . A . T 67 67 67 cDNA-1A8 . . T . . A . . T . . . A . T 67 67 67 cDNA-1G3 . . T . . A . . T . . . A . T 67 67 67 cDNA-1E10 . . T . . G .....AC.C 67 67 67 cDNA-3D10 . . T . . G .....AC.C 67 67 67 cDNA-1B12 . . T . . G .....AC.C 67 67 67 cDNA-3B10 . . T . . G .....AC.C 67 67 67 cDNA-3C3 . . T . . G .....AC.C 67 67 67 cDNA-1G4 . . T . . G .....AC.C 67 67 67 cDNA-1C4 . . T . . G .....AC.C 67 67 67 cDNA-3C11 . . T . . G .....AC.C 67 67 67 cDNA-3B3 . . T . . G .....AC.C 67 67 67 cDNA-3D11 . . T . . G . . T . . . A . A 67 67 67 cDNA-3E4 . . T . . G . . T . . . A . A 67 67 67 cDNA-3B11 . . T . . G . . T . . . A . A 67 67 67 cDNA-3C7 . . T . . G . . T . . . A . A 67 67 67 cDNA-1F11 . . T . . G . . T . . . A . A 67 67 67 cDNA-1A10 . . T . . G . . T . . . A . A 67 67 67 cDNA-3D8 . . T . . G . . T . . . A . A 67 67 67 cDNA-3A6 . . T . . G . . T . . . A . A 67 67 67 cDNA-1G1 . . T . . G . . T . . . A . A 67 67 67 cDNA-1E12 . . T . . G . . T . . . A . A 67 67 67 cDNA-3A11 . . T . . G . . T . . . A . A 67 67 67 cDNA-3C10 . . T . . G . . T . . . A . A 67 67 67 cDNA-1B3 . . T . . G . . T . . . A . A 67 67 67 cDNA-1D9 . . T . . A . . G . . . A . C 67 67 67 cDNA-1F12 . . T . . A . . G . . . A . C 67 67 67 cDNA-1B11 . . T . . A . . G . . . A . C 67 67 67 St2DecC08 . . T . . G .....AA.T 67 67 67 ST2AUG39 . . T . . G .....AA.T 67 67 67 St2DecH07 . . T . . G .....AA.T 67 67 67 St2DecG02 . . T . . G .....AA.T 67 67 67 St2DecB04 . . T . . G .....AA.T 67 67 67 St2DecB08 . . T . . G .....AA.T 67 67 67 St2DecC03 . . T . . G .....AA.T 67 67 67 ST2AUG100 . . T . . G . . T . . . A . T 67 67 67 ST2AUG49 . . T . . G . . T . . . A . T 67 67 67 ST2AUG29 . . T . . G . . T . . . A . T 67 67 67 ST2AUG103 . . T . . G . . T . . . A . T 67 67 67

Diversity and distribution of three distinct ecotypes of the aerobic anoxygenic phototroph gene, pufM Supplemental Table S2 Waidner and Kirchman

3' 5' Percent match to WHOLE 6 BASES AT 3 BASES AT RbaR1 primer (rev. compl.) GGCGACCGCGAGTTG PRIMER 3' END 3' END translation GDREL ST2AUG104 . . T . . G . . T . . . A . T 67 67 67 ST2AUG14 . . T . . G . . T . . . A . T 67 67 67 ST2AUG87 . . T . . G . . T . . . A . T 67 67 67 ST2AUG75 . . T . . G . . T . . . A . T 67 67 67 ST2AUG40 . . T . . G . . T . . . A . T 67 67 67 ST2AUG25 . . T . . G . . T . . . A . T 67 67 67 ST2AUG56 . . T . . G . . T . . . A . T 67 67 67 ST2AUG85 . . T . . G . . T . . . A . T 67 67 67 St2DecG05 . . T . . G . . A . . . A . C 67 67 67 St2DecD03 . . T . . A .....AA.C 67 67 67 ST2AUG19 . . T . . A .....AA.C 67 67 67 ST2AUG88 . . T . . A .....AA.C 67 67 67 St2DecA11 . . T . . A .....AA.C 67 67 67 ST2AUG65 . . T . . A .....AA.C 67 67 67 ST2AUG10 . . T . . A .....AA.C 67 67 67 St2DecF10 . . T . . A .....AA.C 67 67 67 ST2AUG43 . . T . . A .....AA.C 67 67 67 ST2AUG52 . . T . . A .....AA.C 67 67 67 ST2AUG72 . . T . . G . . T . . . A . C 67 67 67 ST2AUG48 . . T . . G . . T . . . A . C 67 67 67 ST2AUG26 . . T . . T . . T . . . A . C 67 67 67 ST2AUG78 . . T . . T . . T . . . A . C 67 67 67 DB_2A02 . . A . . G . . T . . . A . C 67 67 67 SarY01078100 . . A . . . A . G . . A C . C 60 83 67 SarY01078100 . . A . . . A . G . . A C . C 60 83 67 ST2AUG16 . . T . . A . . T . . A G . T 60 67 67 ST2AUG08 . . T . . A . . T . . A G . T 60 67 67 ST2AUG91 . . T . . A . . T . . A G . T 60 67 67 St2DecB09 . . T . . G .....AAAT 60 67 67 ST2AUG01 . . T . . G . . G . . A A . C 60 67 67 cDNA-3E12 . . T . . A . . T . . A A . T 60 67 67 cDNA-1F3 . . T . . A . . T . . A A . T 60 67 67 ST2AUG33 . . T . . A . . T . . A A . C 60 67 67 ST2AUG94 . . T . . A . . T . . A A . C 60 67 67 ST2AUG45 . . T . . A . . T . . A A . C 60 67 67 cDNA-3A7 . . T . . A . . T . . A A . T 60 67 67 cDNA-1B9 . . T . . A . . T . . A A . T 60 67 67 medS06P3 . C ...... A.C 80 83 67 medS01P12 . C ...... A.C 80 83 67 DB_2B11 . C . . . T ...... A.T 73 67 67 DB_2E11 . C . . . T ...... A.T 73 67 67 DB_2B04 . C . . . T ...... A.T 73 67 67 DB_2G03 . C . . . T ...... A.T 73 67 67 DB_2B12 . C . . . T ...... A.T 73 67 67 DB_2C01 . C . . . T ...... A.T 73 67 67 DB_2G01 . C . . . T ...... A.T 73 67 67 DB_2D12 . C . . . T ...... A.T 73 67 67 DB_2C08 . C . . . T ...... A.T 73 67 67

Diversity and distribution of three distinct ecotypes of the aerobic anoxygenic phototroph gene, pufM Supplemental Table S2 Waidner and Kirchman

3' 5' Percent match to WHOLE 6 BASES AT 3 BASES AT RbaR1 primer (rev. compl.) GGCGACCGCGAGTTG PRIMER 3' END 3' END translation GDREL MBBAC29C02 . C T ...... A.C 73 67 33 MBBAC39B11 . C T ...... A.C 73 67 33 DB_2A08 . C G .....G...A.C 67 67 33 DB_2G06 . C T .....G..AA.C 60 67 33 DB_2B07 . C T .....G..AA.C 60 67 33 DB_2F01 . C T .....G..AA.C 60 67 33 DB_1B12 . C T .....G..AA.C 60 67 33 DB_1E02 . C T .....G..AA.C 60 67 33 DB_2A05 . C T .....G..AA.C 60 67 33 DB_2E05 . C T .....G..AA.C 60 67 33 DB_1B01 . C T .....G..AA.C 60 67 33 DB_2B09 . C T .....G..AA.C 60 67 33 DB_2D07 . C T .....G..AA.C 60 67 33 DB_2G09 . C T .....G..AA.C 60 67 33 DB_2E07 . C T .....G..AA.C 60 67 33 DB_1D03 . C T . . T .....AA.C 60 50 33 DB_2G10 . C T . . T .....AA.C 60 50 33 DB_2F08 . C T . . T .....AA.C 60 50 33 DB_1C01 . C T . . T .....AA.C 60 50 33 DB_2F03 . C T . . T .....AA.C 60 50 33 DB_2G05 . C T . . T .....AA.C 60 50 33 DB_2B05 . C T . . T .....AA.C 60 50 33 DB_2C04 . C T . . T . . T . . . A . C 60 50 33 cDNA-3A5 . C T . . G .....AA.C 60 50 33 cDNA-1C7 . C T . . G .....AA.C 60 50 33 DB_2D04 . C A .....T..AA.C 60 67 33 DB_1C03 . C A .....T..AA.C 60 67 33 DB_2D03 . C A .....T..AA.C 60 67 33 cDNA-1B4 . C T . . G .....AA.C 60 50 33 cDNA-3C4 . C T . . G .....AA.C 60 50 33 cDNA-1C9 . C T . . G .....AA.C 60 50 33 DB_2C03 . C G . . T . . G . . . A . C 60 50 33 cDNA-1G5 . C T . . G .....AA.C 60 50 33 DB_2H05 . C G . . T . . G . . . A . C 60 50 33 cDNA-1A9 . C T . . G .....AA.C 60 50 33 DB_2E12 . C G .....T..AA.A 60 67 33 DB_1H02 . C T . . T . . A . . A A . C 53 50 33 DB_1F02 . C A . . T . . A . . A A . C 53 50 33 DB_2D08 . C A . . T . . A . . A A . C 53 50 33 DB_1G03 . C A . . T . . A . . A A . C 53 50 33 DB_2B01 . C A . . T . . A . . A A C C 47 50 33

Diversity and distribution of three distinct ecotypes of the aerobic anoxygenic phototroph gene, pufM Supplemental Table S2 Waidner and Kirchman

5' 3' Percent match to WHOLE 6 BASES AT 3' 3 BASES AT 3' RbaF1 primer TGGACGAACCTGTTCAGC PRIMER END END bacterium_MBIC3951 .....C.CGGC....TCG 56 50 0 bacterium_R2A163 .....C...... 94 100 100 Roseobacter_OCH114 ...... CAGC...TTCG 56 33 0 Rhodobacter_blasticus .....C...AAC...... 78 100 100 Rhodovulum_sulfidophilum .....C.C.GCC...TCG 56 50 0 Roseobacter_BS90 .....C.CGGCT...TCG 50 50 0 Roseobacter_denitrificans ...... CAGC...TTCG 56 33 0 Roseobacter_litoralis ...... CAGC...TTCG 56 33 0 Roseobacter_S03 .....C..T...... TC. 78 67 33

64 57 26

Diversity and distribution of three distinct ecotypes of the aerobic anoxygenic phototroph gene, pufM Supplemental Table S2 Waidner and Kirchman

3' 5' Percent match to WHOLE 6 BASES 3 BASES RbaR1 primer (rev. compl.) GGCGACCGCGAGT TG PRIMER AT 3' END AT 3' END bacterium_MBIC3951 ...... T...C.A 80 100 100 bacterium_R2A163 ...... G...C.. 87 100 100 bacterium_R2A84 . . T . . A ...... A.C 73 67 67 Rhodobacter_azotoformans ....TG...... C.. 80 67 100 Rhodobacter_blasticus ...... C.. 93 100 100 Rhodobacter_capsulatus .....A...... C.. 87 83 100 Rhodobacter_sphaeroides .....G...... C.. 87 83 100 Rhodobacter_veldkampii .....G.....AC.. 80 83 100 Rhodovulum_sulfidophilum ...... C.. 93 100 100 Roseobacter_BS110 .....G..T...A.C 73 83 100 Roseobacter_BS90 ...... C.C 87 100 100 Roseobacter_denitrificans ...... 100 100 100 Roseobacter_litoralis ...... C.. 93 100 100 Roseobacter_OCH114 ...... 100 100 100 Roseobacter_S03 .....A...... A.T 80 83 100

86 90 98

Diversity and distribution of three distinct ecotypes of the aerobic anoxygenic phototroph gene, pufM UWF-Escambia County Vibrio Winter Report

04/01/20

Technical report summarizing results from winter 2020 sampling: Escambia County 2020 Aquatic Bacteria Survey, Vibrio Assessment

Research Questions to be addressed: What is the likelihood of encountering dangerous species of Vibrio in the major basins of the PBS? Is there a difference between substrates: water column/hard (oyster)/sediment?

University’s Tasks: UWF CEDB personnel will perform a survey of local waters to assess Vibrio abundance near shorelines two (2) times - once in the winter (in February/March 2020) and once in summer (August/September 2020).

ESCO Technical Point of Contact: J. Taylor “Chips” Kirschenfeld [email protected] UWF Technical Point of Contact: Lisa Waidner [email protected] UWF Co-PI’s: Jane Caffrey [email protected] Wade Jeffrey [email protected]

Summary. To determine baseline abundances of potentially dangerous species of bacteria, UWF CEDB researchers surveyed 44 locations in 7 major basins for the abundances of Vibrio vulnificus (V. vulnificus) and Vibrio parahaemolyticus (V. parahaemolyticus). We collected samples from 44 stations on 7 dates between 02/03/20 and 03/02/20. The average surface water temperature of all stations was 15.4oC; and temperatures ranged from 12.3 – 22.2oC. Surface water salinities ranged from 0.9 to 18.2 PSU. Surface water (n=44), sediment (n=43) and biofilm (n=14) samples were processed to assess abundances of Vibrio vulnificus and V. parahaemolyticus, employing a chromogenic agar assay. In surface waters, V. vulnificus was detected in 37 out of 44 samples, with maximum levels of 3,556 cells/mL. V. parahaemolyticus was only detected in 15 surface water samples, with a maximum concentration of 8,919 cells/mL. Sediments contained V. vulnificus in all but one sediment sample. V. vulnificus sediment concentrations ranged from 121 to 607,222 cells/mL. In contrast, V. parahaemolyticus were only detected in 33 of the 43 sediment samples, where concentrations ranged from 28 to 77,333 cells/mL. Biofilms, collected from oyster or barnacle shells or from invertebrate worms found in sediment samples, contained on average 7,735 and 1,490 cells/mL, of V. vulnificus and V. parahaemolyticus, respectively. In comparing biofilm abundances on different types of shells, there was not a statistical difference between oysters (n=5) and barnacles (n=7) for V. vulnificus (p=0.675) or V. parahaemolyticus (p=0.628).

A partial analysis of these species’ distribution with respect to water quality data was performed. Of note in our preliminary analyses is the statistically significant correlation between V. vulnificus abundances in sediments and the salinity observed in the water column at depth. Due to the University's response to COVID-19, sample laboratory processing, including total suspended solids (TSS), chlorophyll a, dissolved and total nutrient concentrations, was halted prematurely. Approximately 2/3 to ¾ of the laboratory-based water quality analyses are complete as of this date. However, all laboratory-based winter data and analyses of winter and summer data will be provided in the final report submitted on Nov 1, 2020.

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Overview of Sampling Sites. A total of 44 stations were sampled on 7 dates between 02/03/20 and 03/02/20 (Fig. 1). All sampling and in situ measurements, with the exception of QuietWater Beach (QWB) in Santa Rosa Sound, were performed from UWF small vessels.

Fig. 1. Locations of sampling sites. Colors of map pins indicate dates on which samples and in situ measurements were obtained.

Methods. At each location (station), UWF CEDB personnel measured in situ water quality data with a YSI Multimeter, including dissolved oxygen (mg/L and %), temperature (oC), and salinity (Practical Salinity Units, PSU). Light attenuation was calculated from Secchi disk visibility depth (in meters) and from the slope of attenuation at 0.5-meter intervals measured with a LiCor spherical underwater quantum sensor (PPFFR, photosynthetic photon flux fluence rate). Total water column depth was measured with the line on the Secchi disk and with the vessel’s on- board instrumentation. Surface water samples were collected via bucket cast; and sediment samples were collected with a Ponar grab sampler. Water was filtered on-site through GF/F filters to collect biomass and filtrate, which were immediately preserved in coolers on ice and later stored at the laboratory at -20oC, for subsequent chlorophyll a and nutrient analyses. Whole water samples (1 L) were preserved in coolers at in situ temperature for subsequent plating on chromogenic medium agar plates. Sediment samples (0.5 to 2.0 mL of surface sediment) were collected with sterile plastic spatulas and resuspended in 0.5 mL of phosphate-buffered saline (PBS) and held at in situ temperature. Subsequent to dilutions and plating, exact volumes of each sediment sample were determined. Each abundance calculation took into account the inevitable variabilities in volumes of sediments collected in the field. For consistency of reported abundances, total Vibrio abundances normalized to milliliters (mL) are reported below, since abundances per square cm (cm3) are equivalent to abundances per volume (mL). In addition, approximately 50 mL of sediment was collected for analysis of water content, loss on ignition and sediment chlorophyll and phaeopigment concentrations. Sediment samples were stored on ice and either processed on return to the lab or frozen for later processing.

Biofilm samples, approximately 1 cm2 surface area per sample, were collected and preserved on board in PBS, in the same manner as sediments. As with sediments, for consistent reporting, numbers of Vibrio cells per mL were calculated and recorded. At all locations, we sought invertebrates on marker poles or shells/bodies of invertebrates in sediment grabs. In 5 major basins, we collected biofilms from invertebrates. Biofilms were collected with sterile cotton

EsCoVibrio Winter Report_law033120.docx Page 2 of 12 UWF-Escambia County Vibrio Winter Report swabs, resuspended in 0.1 mL of transport media (PBS), and held at in situ temperature until they were plated on chromogenic agar in the same manner as sediment and whole water samples.

At the laboratory, all samples (water, sediment suspension, and biofilm suspension) were processed to determine the abundance of V. vulnificus and V. parahaemolyticus was determined using a chromogenic substrate method. Three aliquots of each sample, 0.15 mL in triplicate, were plated on CHROMagar-Vibrio agar in petri plates and processed as previously described (Huq et al., 2012; Oliver, 2003; Thomas et al., 2014; Yeung and Thorsen, 2016). Plating was followed by incubation in the dark at 24oC for 24, 48, and 72 hours. After each 24-hour time period, the number of colored colonies (pink, parahaemolyticus; blue, vulnificus) were recorded. The abundances of each type of Vibrio were calculated in the same manner for all sample types. That is, the number of Vibrio cells per mL of suspension (sediment and biofilm samples) or per mL of whole surface water were calculated; these values (cells/mL) are reported below.

Additionally, water and sediment samples were collected and preserved for subsequent laboratory analyses of water quality and sediment characteristics. Dissolved and total nutrients, and chlorophyll a processing is as previously described (Babcock et al., 2020), and total suspended solids (TSS) in surface water samples is determined with the EPA method (METHOD#160.2). Sediment characteristics (percent water, ash-free dry weight, and percent organic content) are determined by the method previously described (Babcock et al., 2020). For DNA analysis, only if needed, water samples were also filtered onto 0.22 mm Durapore filters and preserved as previously described (Waidner and Kirchman, 2007). Due to the success of evaluation of abundances using the chromogenic agar method, DNA extractions and molecular analyses were not necessary; but water and sediment samples have been preserved for DNA and are stored in a -20oC freezer for future analyses, if necessary.

Due to the University's response to COVID-19, sample laboratory processing was halted prematurely, preventing full data analyses to determine Vibrio abundance correlations with all environmental parameters. All data acquisition and analyses of winter and summer sample data will be provided in the final report submitted on Nov 1, 2020.

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Overview of bodies of water sampled. In all stations of all basins surveyed, the minimum depth was approximately 0.5 meters, with a maximum depth at any station of 4.3 meters (Table 1). All surface water temperatures ranged from 12.3 to 22.2oC, while bottom water temperatures were 13.0 to 22.0oC. In most basins, the average surface water temperature was 13-17oC, except Bayou Chico (Table 1). Surface water salinities in all locations were from 0.9 to 18.2 PSU; and bottom water salinities were from 1.9 to 28 PSU. The lowest dissolved oxygen concentration at any location or depth was 59% (5.09 mg/L).

Table 1. Overview of sampling stations (sites). Range of depths, all Surface water Bottom water Number stations in each basin Date Basin of Average Average Average Average sampled Minimum Maximum stations temperature salinity temperature salinity (meters) (meters) (oC) (PSU) (oC) (PSU) Escambia Bay / Pensacola Bay 12 02/03/20 0.9 3.5 13 12 13 14 Bayou Texar 6 02/07/20 1.0 2.7 15 8 16 12 Bayou Chico 5 02/12/20 0.4 4.3 21 4 20 12 Bayou Grande 7 02/21/20 0.9 2.9 17 9 17 10 Big Lagoon 8 02/28/20 1.1 6.1 14 17 15 22 Perdido Bay (FL) 5 03/02/20 1.1 3.0 16 10 16 11 Santa Rosa Sound, QuietWater 1 02/10/20 0.5 n/a n.d. n.d. n.d. n.d. Beach (QWB)

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Overview of Vibrio in surface waters. Overall, in surface waters, V. vulnificus was more ubiquitous than V. parahaemolyticus. However, in certain bodies of water, V. parahaemolyticus concentrations were much higher than V. vulnificus (Fig. 2). In 7 of 44 surface water samples, V. vulnificus was below detection limits of the chromogenic agar assay. In the remaining 37 locations, the concentrations ranged from 15 to 3,556 cells/mL, with a median concentration of 44 cells/mL. In contrast, V. parahaemolyticus was below the limit of detection at 29 of the 44 stations. In the 15 surface water samples where it was detectable, V. parahaemolyticus was at concentrations ranging from 15 to 8,919 cells/mL, with a median concentration of 104 cells/mL.

Fig. 2. Abundances of V. vulnificus and V. parahaemolyticus in surface waters. Abundances (in cells per milliliter, cells/mL) were determined using the chromogenic substrate agar assay. The ranges of abundances are indicated by color-coded map pins.

Overview of Vibrio in sediment samples. At the 44 locations sampled, 43 sediment samples were obtained. Sediment types ranged from sand to sand/mud mix to mud; to date, we have analyzed water and organic content of 24 of the sediment samples. Dry weight proportions (%) in the analyzed samples range from 23-81%, and organic material ranged from 0.2-26%. In 42 out of 43 sediment samples, V. vulnificus was detected (Fig. 3), where concentrations were from 121 to 607,222 cells/mL, with a median concentration of 18,160 cells/mL. In contrast, V. parahaemolyticus was generally less concentrated in the sediments and was below detection limits in 10 of the sediment samples. In the remaining 33 stations, V. parahaemolyticus were found at concentrations of 28 to 77,333 cells/mL, with a median concentration of 652 cells/mL.

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Given that the average concentration of total active aerobic bacterial cells present per mL of estuarine, riverine, or coastal marine sediments is 1 to 500 x106 (Glavin et al., 2004; Kirchman, 2018; Luna et al., 2002; Proctor and Souza, 2001), the data suggest V. vulnificus make up from 0.2% to 60% of total sedimentary bacteria; whereas V. parahaemolyticus could comprise 0.003% to 0.2% of all bacteria in sediments. On average, V. vulnificus outnumbered V. parahaemolyticus by approximately 18-fold in all sediments.

Fig. 3. Abundances of V. vulnificus and V. parahaemolyticus in sediments. Abundances (in cells per milliliter, cells/mL) were determined using the chromogenic substrate agar plating assay. The ranges of abundances are indicated by color-coded map pins.

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Vibrio in biofilm samples. For biofilm samples on invertebrates, when present, the numbers of V. vulnificus and V. parahaemolyticus were obtained using the same chromogenic agar assay employed for water and sediment analyses (Table 2). The median concentrations of V. vulnificus and V. parahaemolyticus in the preserved biofilms were 5,052 and 326, respectively. Only two invertebrate biofilm samples resulted in undetectable Vibrio, from a polychaete worm in Pensacola Bay station #2, and an oyster located at Bayou Grande station #3. In the remaining samples, mostly from swabbed oyster or barnacle shells, V. vulnificus were in abundances ranging from 81 to 28,844 cells/mL, and V. parahaemolyticus abundances 81 to 14,422 cells/mL. In comparing biofilm abundances on different types of shells, there was not a statistical difference between oysters (n=5) and barnacles (n=7) for V. vulnificus (p=0.675) or V. parahaemolyticus (p=0.628).

Table 2. Numbers of V. vulnificus and V. parahaemolyticus present in biofilms on invertebrates. V. V. Station vulnificus parahaemolyticus Ratio Date Time name Organism type, collection method, notes cells/mL cells/mL V:P 02/03/20 08:27 PensBay-4 barnacle, cotton swab 7,822 489 16 02/03/20 08:53 PensBay-3 barnacle, cotton swab, pole marker #7 2,281 326 7 02/03/20 09:22 PensBay-1 oyster, cotton swab, east pole marker 28,844 0 n/a 02/03/20 09:50 PensBay-2 white polychaete worm in Ponar grab, whole worm 0 0 n/a 02/03/20 10:15 EscBay-7 small worm w/ mud, in Ponar grab, whole worm 27,215 0 n/a 02/07/20 09:28 Texar-6 Oyster, cotton swab, marker 14A pole 1,630 4,726 0.34 02/07/20 10:49 Texar-2 oyster shell in Ponar Grab, cotton swab 1,548 163 9.5 02/10/20 06:45 QW Beach barnacle, cotton swab 1,548 0 n/a 02/12/20 12:09 Chico-4 barnacle, cotton swab 17,519 14,422 1.2 02/12/20 12:35 Chico-5 barnacle, cotton swab 244 163 1.5 02/12/20 12:59 Chico-2 oyster shell in Ponar Grab, cotton swab 9,289 81 114 02/21/20 11:32 Grande-2 barnacle, cotton swab 10,267 163 63 02/21/20 11:54 Grande-3 oyster, cotton swab 0 0 n/a 02/21/20 13:15 Grande-7 barnacle, cotton swab 81 326 0.25 All dates Median biofilm Vibrio abundance 5,052 326

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Vibrio concentrations in surface waters and sediments in the 7 major basins surveyed. The lowest abundances of V. vulnificus in surface waters were observed in the Pensacola Bay basin (Pensacola Bay and Escambia Bay) and in Perdido Bay (Table 3). In the remaining basins (Big Lagoon and Bayous Texar, Chico and Grande), there was not a basin-wide high concentration of V. vulnificus in surface waters. For example, in Bayou Chico, with a basin-wide average abundance of 1,046 cells/mL, there were 3 stations with low (15 cells/mL) or undetectable V. vulnificus. In Chico, Grande, Big Lagoon, and at the QuietWater Beach location in Santa Rosa Sound, the maximum number of V. vulnificus in surface waters was 222 cells/mL. Similarly, high numbers of V. parahaemolyticus were not restricted to any one basin, except Bayou Texar.

In Bayou Texar, there were unusually high abundances of V. parahaemolyticus at most stations, reaching 8,919 cells/mL in one location (Table 4), where V. parahaemolyticus outnumbered surface V. vulnificus by 43-fold. In this basin, the lowest number of V. parahaemolyticus exceeded 1,000 cells/mL; whereas the V. vulnificus in all 5 Bayou Texar stations were in the range of 89-207 cells/mL. However, with the exception of Bayous Texar and Chico, V. vulnificus outnumbered V. parahaemolyticus by about 5-fold in all remaining bodies of water.

As observed in surface waters, overall, sediment V. vulnificus was the more abundant of the two species (Tables 3 and 4). In sediments, V. vulnificus outnumbered V. parahaemolyticus by 50- fold, and were highly concentrated, with numbers reaching as high as 607,000 cells/mL. In contrast, the maximum V. parahaemolyticus concentration in any sample from any basin was only approximately 77,000, at a location in Bayou Chico where V. vulnificus was measured at >125,000 cells/mL.

Basin-wide analyses indicate there is no body of water with low sedimentary Vibrio concentrations, but sediments in three of the 7 major basins had exceptionally high V. vulnificus (Table 3). In Bayous Chico and Texar, V. vulnificus was found in some locations at concentrations >300,000 cells/mL, and in one location of Big Lagoon at >600,000 cells/mL. The only other basin in which this species was higher than 100,000 cells/mL was Perdido Bay, but this was only in 1 of the 5 stations sampled. All other locations in Perdido Bay had sedimentary V. vulnificus concentrations at 25,000 or lower. The only basin in which V. vulnificus was found at >30,000 cells/mL in all stations sampled was Big Lagoon (Table 3).

In contrast to V. vulnificus, sedimentary V. parahaemolyticus was generally at lower concentrations, and there were 40 locations in which this species was undetectable or at concentrations below 10,000 (Table 4). Very high numbers of V. parahaemolyticus were observed in sediments only in Big Lagoon (2 locations, 19,000 and 11,000 cells/mL) and Bayou Chico (1 location, 77,000 cells/mL). There were three major basins with overall low numbers of this species. In 4 of the 5 Perdido Bay sites, V. parahaemolyticus was undetectable, with the 5th site having only 130 cells/mL. In Bayou Grande (7 stations), V. parahaemolyticus was undetectable in 2 locations and in the remaining 5 samples was at <400 cells/mL. In the Pensacola Bay basin (Pensacola Bay and Escambia Bay), we collected 11 sediment samples. Of those, two contained undetectable levels of this species, one site had 1,649 cells/mL, and the remaining 8 sites contained <655 cells per mL of sediment.

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Table 3. Overview of V. vulnificus abundances in each basin. Sediment Surface water Samples Min >0 Max Basin Samples Min >0 Max Basin Basin n1 undetect.2 cells/mL3 cells/mL Avg. n4 undetect.2 cells/mL3 cells/mL Avg. Pensacola Bay 4 0 762 21,055 9,249 5 2 15 89 30 Escambia Bay 7 0 1,653 42,218 17,138 7 2 15 44 21 Bayou Texar 6 0 169 388,338 93,535 6 0 89 207 138 Bayou Chico 5 0 188 314,667 107,669 5 1 15 3,556 1,046 Bayou Grande 7 0 475 17,333 7,966 7 1 15 222 72 Big Lagoon 8 0 36,681 607,222 203,195 8 0 15 148 69 Perdido Bay 5 1 4,665 164,273 43,042 5 1 15 59 27 QuietWater Beach 1 0 121 121 121 1 0 59 59 59 Min >0, Max, Avg, >0, Median, Min >0, Max, Avg, >0, Median, 3 5 3 5 cells/mL cells/mL cells/mL cells/mL cells/mL cells/mL cells/mL cells/mL All All sediments 121 607,222 75,076 18,160 water 15 3,556 205 44 1 Number of sediment samples obtained in each basin 2 Number of samples in which this Vibrio species was below detection limit 3 Minimum cells/mL in which this Vibrio species was above detection limit 4 Number of surface water samples obtained from each basin 5 Average of all samples, excluding those in which the species was below detection limit

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Table 4. Overview of V. parahaemolyticus abundances in each basin. Sediment Surface water Samples Min >0 Max Basin Samples Min >0 Max Basin Basin n1 undetect.2 cells/mL3 cells/mL Avg. n4 undetect.2 cells/mL3 cells/mL Avg. Pensacola Bay 4 2 73 655 182 5 5 0 0 0 Escambia Bay 7 1 92 1,649 367 7 6 193 193 28 Bayou Texar 6 0 132 3,124 1,422 6 0 1,096 8,919 3,136 Bayou Chico 5 0 586 77,333 17,156 5 3 15 89 21 Bayou Grande 7 2 28 392 143 7 3 15 104 25 Big Lagoon 8 0 227 19,185 4,712 8 6 15 30 6 Perdido Bay 5 4 130 130 26 5 5 0 0 0 QuietWater Beach 1 1 n/a n/a 0 1 1 n/a n/a 0 Min >0, Max, Avg, >0, Median, Min >0, Max, Avg, >0, Median, 3 5 3 5 cells/mL cells/mL cells/mL cells/mL cells/mL cells/mL cells/mL cells/mL All All sediments 28 77,333 4,135 652 water 15 8,919 1,289 104 1 Number of sediment samples obtained in each basin 2 Number of samples in which this Vibrio species was below detection limit 3 Minimum cells/mL in which this Vibrio species was above detection limit 4 Number of surface water samples obtained from each basin 5 Average of all samples, excluding those in which the species was below detection limit

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Correlation of abundances with abiotic environmental parameters. A partial analysis of these species’ distribution with respect to water quality data was performed. Incomplete analyses include concentrations of total suspended solids (TSS), chlorophyll a, dissolved and total nutrient concentrations. However, some new observations include those relationships of Vibrio abundance with respect to physical parameters measured in situ, including salinity, temperature, and dissolved oxygen. Most strikingly, sediment vulnificus abundances were positively correlated with salinity observed at depth (R=0.3887, p<0.05), where salinities ranged from 2 to 28 PSU (Fig. 4). This is in contrast to previously published observations in which V. vulnificus abundances in the water column are negatively correlated with water salinities (Chase et al., 2015; Kelly, 1982; Lipp et al., 2001; Randa et al., 2004).

Fig. 4. Relationship of sediment V. vulnificus abundance (cells per milliliter) to salinity in bottom waters.

Additional analyses, including the influence of other factors, including total suspended solids (TSS), chlorophyll a, dissolved and total nutrient concentrations, are underway. These data and additional analyses will be provided in the final report (November 2020).

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References cited

Babcock, K.K., Cesbron, F., Patterson, W.F., Garner, S.B., Waidner, L.A., and Caffrey, J.M. (2020). Changing biogeochemistry and invertebrate community composition at newly deployed artificial reefs in the Northeast Gulf of Mexico. Estuaries Coasts.

Chase, E., Young, S., and Harwood, V.J. (2015). Sediment and vegetation as reservoirs of Vibrio vulnificus in the Tampa Bay Estuary and Gulf of Mexico. Appl. Environ. Microbiol. 81, 2489–2494.

Glavin, D.P., Cleaves, H.J., Schubert, M., Aubrey, A., and Bada, J.L. (2004). New method for estimating bacterial cell abundances in natural samples by use of sublimation. Appl. Environ. Microbiol. 70, 5923– 5928.

Huq, A., Haley, B.J., Taviani, E., Chen, A., Hasan, N.A., and Colwell, R.R. (2012). Detection, isolation, and identification of Vibrio cholerae from the environment. Curr. Protoc. Microbiol. CHAPTER, Unit6A.5.

Kelly, M.T. (1982). Effect of temperature and salinity on Vibrio (Beneckea) vulnificus occurrence in a Gulf Coast environment. Appl. Environ. Microbiol. 44, 820–824.

Kirchman, D.L. (2018). Processes in Microbial Ecology (New York: Oxford University Press).

Lipp, E.K., Rodriguez-Palacios, C., and Rose, J.B. (2001). Occurrence and distribution of the human pathogen Vibrio vulnificus in a subtropical Gulf of Mexico estuary. In The Ecology and Etiology of Newly Emerging Marine Diseases, J.W. Porter, ed. (Dordrecht: Springer Netherlands), pp. 165–173.

Luna, G.M., Manini, E., and Danovaro, R. (2002). Large fraction of dead and inactive bacteria in coastal marine sediments: comparison of protocols for determination and ecological significance. Appl. Environ. Microbiol. 68, 3509–3513.

Oliver, J.D. (2003). Chapter 17 Culture media for the isolation and enumeration of pathogenic Vibrio species in foods and environmental samples. In Progress in Industrial Microbiology, J.E.L. Corry, G.D.W. Curtis, and R.M. Baird, eds. (Elsevier), pp. 249–269.

Proctor, L.M., and Souza, A.C. (2001). Method for enumeration of 5-cyano-2,3-ditoyl tetrazolium chloride (CTC)-active cells and cell-specific CTC activity of benthic bacteria in riverine, estuarine and coastal sediments. J. Microbiol. Methods 43, 213–222.

Randa, M.A., Polz, M.F., and Lim, E. (2004). Effects of temperature and salinity on Vibrio vulnificus population dynamics as assessed by quantitative PCR. Appl. Environ. Microbiol. 70, 5469–5476.

Thomas, P., Mujawar, M.M., Sekhar, A.C., and Upreti, R. (2014). Physical impaction injury effects on bacterial cells during spread plating influenced by cell characteristics of the organisms. J. Appl. Microbiol. 116, 911–922.

Waidner, L.A., and Kirchman, D.L. (2007). Aerobic anoxygenic phototrophic bacteria attached to particles in turbid waters of the Delaware and Chesapeake estuaries. Appl. Environ. Microbiol. 73, 3936– 3944.

Yeung, M., and Thorsen, T. (2016). Development of a more sensitive and specific chromogenic agar medium for the detection of Vibrio parahaemolyticus and other Vibrio species. J. Vis. Exp. JoVE.

EsCoVibrio Winter Report_law033020.docx Page 12 of 12 Changing Biogeochemistry and Invertebrate Community Composition at Newly Deployed Artificial Reefs in the Northeast Gulf of Mexico

Kendra K. Babcock, Florian Cesbron, William F. Patterson, Steven B. Garner, Lisa A. Waidner & Jane M. Caffrey

Estuaries and Coasts Journal of the Coastal and Estuarine Research Federation

ISSN 1559-2723

Estuaries and Coasts DOI 10.1007/s12237-020-00713-4

1 23 Your article is protected by copyright and all rights are held exclusively by Coastal and Estuarine Research Federation. This e-offprint is for personal use only and shall not be self- archived in electronic repositories. If you wish to self-archive your article, please use the accepted manuscript version for posting on your own website. You may further deposit the accepted manuscript version in any repository, provided it is only made publicly available 12 months after official publication or later and provided acknowledgement is given to the original source of publication and a link is inserted to the published article on Springer's website. The link must be accompanied by the following text: "The final publication is available at link.springer.com”.

1 23 Author's personal copy

Estuaries and Coasts https://doi.org/10.1007/s12237-020-00713-4

Changing Biogeochemistry and Invertebrate Community Composition at Newly Deployed Artificial Reefs in the Northeast Gulf of Mexico

Kendra K. Babcock1 & Florian Cesbron1,2,3 & William F. Patterson III4 & Steven B. Garner4 & Lisa A. Waidner1 & Jane M. Caffrey1

Received: 23 August 2019 /Revised: 5 January 2020 /Accepted: 30 January 2020 # Coastal and Estuarine Research Federation 2020

Abstract Artificial reefs have been deployed throughout US coastal waters since the late 1970s, primarily to enhance fisheries. Although numerous studies have examined their effects on fish communities, few have examined interactions between artificial reefs and primary producers or their effects on biogeochemistry of the surrounding water column. Understanding how reefs may alter biogeochemistry and primary producers is key to understanding overall reef productivity. In this study, we examined the relationships among epifauna, algae, and biogeochemical processes on artificial reefs located on the shallow Florida shelf in the Northeast Gulf of Mexico over a year following their deployment. We measured oxygen and nutrient fluxes, attached chlorophyll a, and invertebrate macrofauna. Temporal differences in biomass and chlorophyll a production occurred due to changes in in situ conditions including fluctuations in bottom-water temperature over the year as well as decreasing bottom- water oxygen and increasing chlorophyll a fluorescence during the summer. Invertebrate biomass was greater than micro- or macroalgal biomass. Biomass of the invertebrate epifaunal community increased exponentially during the first 5 months of this study. The reef was net heterotrophic with few differences between oxygen or nutrient fluxes in the light and dark. Positive nitrate and nitrite fluxes and abundances of amoA genes in the microbiomes of benthic invertebrates indicate significant nitrification associated with the epifaunal community. Reef biogeochemistry was directly related to the composition and biomass of the epifaunal community at the reef sites.

Keywords Artificial reefs . Nutrients . Benthic invertebrates . Shallow Florida shelf

Introduction

Artificial reefs have been deployed around the world for cen- Communicated by Mark J. Brush turies to enhance fishing opportunities, but their effects on Electronic supplementary material The online version of this article marine ecosystems still are not well understood. Structured (https://doi.org/10.1007/s12237-020-00713-4) contains supplementary habitats can increase productivity by increasing resource material, which is available to authorized users. (i.e., food and refuge) abundance and diversity, thereby enhancing growth rates and increasing survival (Bohnsack and * Jane M. Caffrey Sutherland 1985;PickeringandWhitmarsh1997). A central [email protected] question in reef fisheries management is whether artificial structures serve to enhance production or simply aggregate 1 Center for Environmental Diagnostics and Bioremediation, University of West Florida, 11000 University Parkway, existing biomass (Bohnsack and Sutherland 1985,Lindberg Pensacola, FL 32514, USA 1997; Pickering and Whitmarsh 1997). For example, approx- 2 Conservatoire National des Arts et Métiers INTECHMER, imately 10% of red snapper biomass in the northern Gulf of 50100 Cherbourg, France Mexico (nGOM) occurs at artificial reefs yet catch rates on 3 Laboratoire des Sciences Appliquées de Cherbourg, Normandie artificial reefs can exceed those at natural reefs by nearly 20- University, UNICAEN, EA 4253, 50100 Cherbourg, France fold (Karnauskas et al. 2017). The disparity between catch 4 Fisheries and Aquatic Sciences, University of Florida, 7922 NW 71st rates and biomass may reflect differential catchability between Street, Gainesville, FL 32653, USA habitats, but fisheries data alone are insufficient to evaluate the Author's personal copy

Estuaries and Coasts contribution from bottom-up processes to productivity at arti- Methods ficial reefs. One mechanism by which artificial reefs may enhance bi- Sampling was conducted at three newly deployed artificial ological production is by increasing the availability of nutri- reef sites in the nGOM approximately 7 km southwest of the ents to primary producers in a relatively nutrient-deficient en- mouth of Pensacola Bay, Florida (Fig. 1). On September 29, vironment, potentially creating a biogeochemical hotspot 2016, six artificial reefs constructed of concrete and limestone (McClain et al. 2003; Falcão et al. 2007;Laymanetal. were deployed for the BACI project. The three reefs used for 2013). Nitrogen and phosphorus, essential nutrients for phy- this study (AR4, AR5, and AR6) consisted of a single module toplankton growth and production, regulate marine primary that was approximately 1.8 m tall with a volume of approxi- productivity and drive benthic metabolism (Berner et al. mately 5 m3. This location also has three control sites without 1993; Layman et al. 2013). Fish aggregations around reef artificial reefs which are not part of this study. To examine structures produce waste products that increase ambient nitro- algal and invertebrate colonization at reef sites, 32 limestone gen and phosphorous (McIntyre et al. 2008; Layman et al. rocks were cut such that each had a surface area between 400 2013). Prokaryotes enhance nitrogen and phosphorous cy- and 500 cm2. Twenty-four rocks were deployed at reef AR5 cling by mineralizing organic matter while eukaryotic hetero- for the temporal component of this study, while four rocks trophs such as benthic invertebrates release dissolved-reduced each were placed at reefs AR4 and AR6 to evaluate spatial forms such as ammonium or urea (Dame et al. 1986). Both variability at the end of the study. Settlement rocks were benthic microalgal and phytoplankton production may be placed in plastic crates, attached to reefs by divers and re- higher near the reefs due to increased nutrient loads (Mazzei trieved (n = 4) haphazardly every other month from October and Biber 2015). Increased primary production is then trans- 2016 to August 2017 from AR5. Rocks from AR4 and AR6 ferred through food webs as phytoplankton and benthic were retrieved in August 2017. microalgae are taken up by primary and secondary consumers, During each collection trip, water column profiles of salin- which are ultimately consumed by top predators and re- ity, temperature (°C), oxygen (% and μmol L−1), chlorophyll mineralized by bacteria through decomposition (McIntyre fluorescence (mg m−3), and dissolved organic matter fluores- et al. 2008). cence (mg m−3) were measured with a Seabird 19plus V2 Artificial reefs can enhance productivity and increase me- SeaCAT Profiler CTD. A LiCor 4Π light meter was also used tabolism of relatively unstructured habitats by providing set- to measure light attenuation. At least 40 L of bottom water tlement sites for sessile invertebrates. Sessile invertebrates was collected via a pump or Niskin bottle for laboratory settling on newly deployed reef surfaces increase three- experiments. dimensional complexity through successional processes. Rocks and bottom water were placed in a temperature- High complexity reduces flow velocity at the reef surface controlled chamber set to the average temperature and light causing plankton and other organic particulates to collect in levels found in situ (roughly 25–32 μEinsteins m−2 s−1). Each interstitial spaces, thereby altering nutrient recycling rates, rock was placed in a 1.7-L plastic container, filled with ambi- affecting algal primary productivity, and enhancing secondary ent bottom water, and sealed with a plastic lid. A fifth, water- production (Bracken 2004). Sessile invertebrates and algae only container was used as a control. Rocks were acclimated directly provide essential food resources (Johnson et al. overnight in aerated water, and then containers were filled 1994), and successive settlers continue to increase refugia by completely to remove any remaining air bubbles. Electronic altering reef topography (Wege and Anderson 1979). stir plates with stir bars provided slight agitation, and a four-

Secondary productivity on artificial reefs can even exceed channel O2 probe (Firesting, Ohio Lumex Company, Inc) was than that found on natural reefs (Pickering and Whitmarsh used to continuously measure dissolved oxygen (DO, μmol 1997;RedmanandSzedlmayer2009). L−1) concentrations during the incubation. The potential for The purpose of this study was to examine primary produc- exchange or diffusion of DO into chambers was evaluated tion and nutrient cycling in relation to algal and invertebrate prior to sampling. A manifold was used to replace the water community succession at newly deployed artificial reefs. This removed during sampling and to avoid any addition of air. is part of a larger before-after-control-impact (BACI) study in Nutrient samples were collected and filtered through GF/F the northeastern Gulf of Mexico examining biogeochemistry, filters for later analysis. For the first four sampling events primary production, and fish production at artificial reefs (October, December, February, April), flux measurements (Cesbron et al. 2019). Specifically, we conducted an in situ were collected every 1.5 h (n = 4) in light and every 1.5 h in colonization experiment in which limestone rocks of standard- dark (n = 4) during an 11-h period, including when the labo- ized size were collected bimonthly from newly deployed arti- ratory lights were turned off during a 2-h acclimation period ficial reef sites. Rocks were then incubated with ambient bot- for transitioning from light to dark incubations. Due to higher tom water in a controlled laboratory experiment to estimate respiration rates, during the final two sampling events (June nutrient fluxes. and August), samples were taken four times in the light and Author's personal copy

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Fig. 1 Location of before-after- control-impact study sites in the shallow Northwest Florida shelf oftheGulfofMexiconear Pensacola, Florida. Reefs deployed at sites 4 (AR4), 5 (AR5), and 6 (AR6) were used for this study

four times in the dark every 0.5 h, with no additional time in- Ash-free dry weight (AFDW) combustion was at 500 °C. between light and dark periods, for a total of 3.5 h. All fluxes were calculated as At the end of each sampling event, each rock was removed, Δy*V photographed, and encrusting biota were visually identified to ð Þ Δ 1 lowest possible taxa. Epifauna and encrusting macrofauna (re- t*A ferred to hereafter as epifauna) were removed and wet, dry, where y represents the changes in concentration (nutrient or and ash-free dry weights were measured. Epifauna biomass oxygen in μmol L−1) with change in time t in hour, adjusting was the ash-free dry weight, while inorganic mass was the for volume (V) of benthic chamber in liter, and rock surface ashed weight. Remaining microalgae or organic material (re- area (A)incm2. All rates were expressed in μmol cm−2 h−1 ferred to hereafter as biofilm) were removed with filtered bot- and calculated separately for light and dark periods. tom water and a brush. Representative aliquots from each rock Twelve representative invertebrate samples from the were filtered for chlorophyll a and dry weight. For the control February experiments were preserved in ethanol. DNA was container, samples were taken directly from the container and extracted from invertebrates using the MOBIO Powermax filtered for chlorophyll a analysis. The surface area of each Soil DNA isolation kit (Leray and Knowlton 2015). rock was calculated using ImageJ computer software. Quantitative PCR was conducted on these DNA extracts to All nutrient samples were analyzed using the following enumerate prokaryote amoA and 16S genes using previously + − methods: NH4 as in Holmes et al. (1999), NO2 as in published primers (Suzuki et al. 2000; Caffrey et al. 2007,and − − Parsons et al. (1984), NO3 +NO2 as in Schnetger and Hollibaugh et al. 2011), using archaeal and bacterial plasmid Lehners (2014), dissolved inorganic phosphate (DIP) as in clones for amoA standards and E. coli genomic DNA for 16S Parsons et al. (1984). Samples for chlorophyll a were extract- standards (Waidner and Kirchman 2008; Christman et al. ed in 90% acetone and analyzed as in Welshmeyer (1994). 2011). Author's personal copy

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All statistical analyses were performed with R. One-factor www.ndbc.noaa.gov). Bottom salinity was greatest in ANOVAs were computed to test for differences in light and February and lowest in June, with a range of 4.6 (Table 1). dark treatments for oxygen and nutrient fluxes. If ANOVAs Highest DO occurred during spring, and the greatest differ- revealed no significant difference between light and dark ence between surface and bottom DO occurred in February fluxes, values were averaged and used for further calculations. (Fig. 2c). Bottom-water DO at AR5 was lower on average All P values are reported. Generalized additive mixed models than at the surface, with the mean being about 156 μmol L−1 (GAMMs) were computed to test the effects of duration and was markedly lower in August (93.8 μmol L−1) when (months), epifauna biomass (AFDW), inorganic mass, bio- stratification was strongest (Table 1). Bottom-water DO was film, and chlorophyll a content on fluxes of dissolved oxygen also low at AR4 and AR6 in August (Table 1). + − − (DO), ammonium (NH4 ), nitrate (NO3 +NO2 ), and dis- Chlorophyll a fluorescence was relatively consistent through- solved inorganic phosphate (DIP) with the model: out the course of the year, with higher levels near the bottom and lower levels near the surface. This was most pronounced in ¼ α þ ðÞþβ þ þ Fim fDurationim 1X 1im B2X 2im B3X 3im March and again in August; near-bottom values were 4–5times greater than surface values (Fig. 2d). Water clarity at AR5 varied þ B4X 4im þ εim ð2Þ considerably from month to month, primarily due to freshwater ε ¼ ρε þ η ð Þ im i;m−1 im 3 exiting the estuary following storm events. Mean irradiance at + 1ifm ¼ t AR5 was 1.9% of surface irradiance (Table 1). NH4 concentra- corðÞε ; ε ¼ j − j ð4Þ im it ρ t m else tions in bottom water were highest in December. At AR5, − − bottom-water NO3 +NO2 and DIP concentrations were where Fi is the nutrient flux of each response variable for ob- highest in February, while bottom-water chlorophyll a concen- servation i in each month m.TheXis indicate the four explana- tration was highest in April (Table 1). AR4 and AR6, which tory variables and f() indicates that a cubic-spline smoother was were sampled in August, had similar salinity, temperature, and + − − used to model the effect of duration (i.e., the number of months NH4 and DIP concentrations to AR5. However, NO3 +NO2 since the start of the experiment) on the explanatory variables. and chlorophyll a were higher at these locations while irradiance Residual variances, εim, were assigned an auto-regressive cor- on the reefs was lower (Table 1). relation structure ρ with time lag = 1 and noise ηim due to temporal correlation between successive samples. Samples were Temporal Changes in Biomass and Fluxes assigned a constant variance function structure grouped by the factor Duration to account for heteroscedasticity over time Epifauna biomass on AR5 increased rapidly during the first (Pinheiro and Bates 2000). Thus, m-1 coefficients were estimat- 5 months post deployment, then remained unchanged for sev- ed with the value of each representing the ratio of the group- eral months, followed by a slight decrease in August (Fig. 3a). level variance to the initial group-level variance (i.e., reference Inorganic mass from barnacles, tube worms, etc. increased variance). Random variation among experimental units (i.e., over the duration of the study (Fig. 3b). Biofilm biomass rocks) was accounted for by nesting the factor Replicate within was low throughout the study period except in February the autocorrelation structure of the factor Duration. Model pa- (Fig. 3c). Attached chlorophyll a increased between rameters were estimated with restricted maximum likelihoods December and April, then decreased for the remainder of the (REML) in the “mgcv” package (Wood 2004;Zuuretal.2009; study (Fig. 3d). Colonization by the fouling community on the Wood 2017) in R (version 3.5.1, R Core Team 2018). reef shifted over the study (SI Fig. 1,SIphotos1–6). Hard-bodied organisms (e.g., barnacles, crabs, and tube- dwelling worms) were dominant from October to February Results and again in August, while soft-bodied organisms (e.g., tunicates, anemones, and bryozoans) were dominant in April and Environmental Conditions June (SI Fig. 1). In October, just a month after the reefs were deployed, only a few small barnacles and polychaetae worms Temperature declined following reef deployment to a winter were present while algal growth was minimal (SI Photo 1). minimum in February (Fig. 2a) and increased through spring The community composition during this period was different and summer to a maximum in August. Bottom temperatures than the remaining months (SI Fig. 1). However, by February, were consistently cooler than surface temperatures with a chlorophyll a increased and rocks visually appeared to be range of 7.6 °C. Similarly, degree of stratification and mean equally dominated by benthic algae and small invertebrates salinity were consistent until April 2017 when an influx of (Fig. 3d, SI Photo 3). In April and June, new invertebrate taxa freshwater occurred leading to stratification in the water col- had recruited, including soft-bodied organisms like tunicates, umn (Fig. 2b). By August, the site was strongly stratified anemones, and bryozoans (SI Fig. 1 , SI Photo 4, SI Photo 5). following a record 139 cm of rain in May and June (http:// By August, soft-bodied invertebrates were less common, and Author's personal copy

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Fig. 2 Changes in temperature (a), salinity (b), dissolved oxygen (c), and chlorophyll fluorescence (d) with depth over time since deployment (October 2016– August 2017) at the AR5 artificial reef site in the Northeast Gulf of Mexico. Dates of CTD profiles indicated by dashed vertical lines

rocks were again dominated by barnacles, crabs, and bivalves. increased in June and August (Fig. 3). Applying smoothing A red encrusting alga was observed only during this last sam- functions only to the effect of duration and treating the other pling event (SI Photo 6). four factors as fixed resulted in relatively good fits to the ob- DO flux decreased (increasing respiration) over the duration served data (SI Figs. 2–5). Smoothing functions in GAMMs of the study (p <0.001,Fig. 3d; Table 2), while all nutrient estimated a non-linear partial effect of duration on flux values − − fluxes increased (p < 0.005, Fig. 3e–h;Table2). Light and dark for NO3 +NO2 or DIP fluxes; linear partial effects were es- − − + treatments were different from one another for NO3 +NO2 timated for the effect of duration on DO and NH4 (SI Fig. 6– + fluxes (p = 0.01), but not for DO (p = 0.12), NH4 (p = 0.88), or 9). Partial effects from GAMMs indicated that DO had a neg- − − DIP (p = 0.06) fluxes. Fluxes of NO3 +NO2 and DIP were ative relationship with epifauna biomass (p < 0.001) with more near zero for the first 5 months following deployment, and then negative fluxes (higher respiration) when epifauna biomass Author's personal copy

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Table 1 Environmental parameters in bottom water from October 2016 to August 2017 at AR5 and AR4 and AR 6 in August 2017

− − + Month Site Salinity Temp DO Light on reef NO2 +NO3 NH4 DIP Chlorophyll a (PSU) (°C) (μmol L−1) (% SI) (μM) (μM) (μM) (μgL−1)

Oct AR5 34.2 25.0 200.0 3.9 0.22 1.10 0.01 0.1 Dec AR5 34.9 20.7 206.3 1.7 0.07 2.28 0.02 0.6 Feb AR5 35.3 19.6 193.8 0.2 3.06 0.21 0.36 0.1 Apr AR5 34.3 22.7 237.5 0.0 0.61 0.79 0.03 0.8 Jun AR5 30.7 26.2 190.6 0.2 0.08 0.20 0.10 0.5 Aug AR5 34.3 27.2 93.8 1.7 0.10 0.74 0.23 0.5 Aug AR4 34.2 27.2 106.3 0.0 1.44 0.38 0.18 4.2 Aug AR6 34.8 26.8 115.0 0.0 6.04 0.63 0.21 1.2

Fig. 3 Boxplot of epifaunal biomass (a), epifaunal inorganic mass (b), Mexico from October 2016–August 2017 versus month (duration). Box biofilm (c), Chlorophyll (Chl a) (d), dissolved oxygen (DO) (e), ammo- tops and bottoms indicate the 25th and 75th percentiles, dashed lines + − − nium (NH4 )(f), nitrate (NO3 +NO2 )(g) and dissolved inorganic phos- indicate mean values, whiskers indicate 1.5*IQR, and symbols indicate phate (DIP) (h) fluxes at the AR5 artificial reef site in northeast Gulf of extreme values Author's personal copy

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Table 2 Summary of generalized additive model output for the Dependent variable Model terms Est Std. Error t-value p value effect of fixed factors duration, epifauna biomass, inorganic DO Intercept − 0.412 0.017 − 24.48 <0.001 mass, biofilm fraction, and Epifauna Biomass − 45.900 2.382 − 19.26 <0.001 chlorophyll a on flux variables Inorganic.mass 5.250 0.325 16.16 <0.001 dissolved oxygen (DO), + Chl a < − 0.001 < 0.001 − 10.54 <0.001 ammonium (NH4 ), nitrate − (NO3 ), or dissolved inorganic edf Ref.df F-value p value phosphate (DIP). The factor s(Duration) 1.0 1.0 485.60 <0.001 duration was smoothed with a adj. R2 0.950 cubic-spline (k =6),andedf max + indicates the number of knots (k) NH4 Intercept 0.022 0.002 12.70 <0.001 that minimizes the negative log Epifauna Biomass − 2.309 0.289 − 8.00 <0.001 likelihood. p values greater than Inorganic.mass 0.109 0.024 4.50 0.001 0.05 are shown in italics. Dependent variable = s(dura- edf Ref.df F-value p value tion) + epifauna biomass + s(Duration) 1.0 1.0 81.75 <0.001 inorganic.mass + biofilm frac- adj. R2 0.289 tion + Chl a − NO3 Intercept 0.004 < 0.001 5.11 <0.001 Epifauna Biomass 0.600 0.123 4.89 <0.001 edf Ref.df F-value p value s(Duration) 2.0 2.0 78.69 <0.001 adj. R2 0.127 DIP Inorganic.mass 0.084 0.027 3.16 0.006 edf Ref.df F-value p value s(Duration) 2.8 2.8 6.24 0.006 adj. R2 0.887

was high. Chlorophyll a content and DO flux were also nega- Spatial Variability tively related (< 0.001), while DO flux and inorganic mass + −2 were positively related (p < 0.001) (SI Fig. 2). NH4 flux was Epifauna biomass was greatest on AR5 at 0.009 g cm and negatively related to epifauna biomass (p < 0.001), but posi- lower at AR4 and AR6 (Fig. 4). Attached chlorophyll a was − − tively related to inorganic mass (p = 0.001). NO3 +NO2 flux highest on AR4, lower on AR5, and lowest at the deepest site, was related to epifauna biomass (p < 0.001). DIP was positive- AR6 (Fig. 4). Epifauna species composition also varied ly related only to inorganic mass (p = 0.006). among the three reefs (SI Fig. 1). Barnacles were the most 0.18 300

0.15 250 -2 -2 m

c 0.12 200 g t h

g 0.09 150 i e w y

r 0.06 100 D

0.03 50 Chlorophyllcm µg a

0 0 AR4 AR5 AR6 Biofilm Inorganic mass Epifauna biomass AFDW Chl a Fig. 4 Chlorophyll a, biofilm biomass, inorganic mass and epifauna biomass of AR4, AR5, and AR6 artificial reef sites in the Northeast Gulf of Mexico in August 2016 where AR4 = 13.2 m, AR5 = 14.1 m, and AR6 = 14.5 m. Mean ± S.E. of chlorophyll a Author's personal copy

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Fig. 5 Oxygen (a) and nutrient a b − − − 0 0.05 fluxes (b NO2 , c NO3 +NO2 , + -0.1 d NH4 and e DIP) at an 1 -1 - 0.04 h increasing depth gradient from h -0.2 2 2 - AR4, AR5, and AR6 artificial - -0.3 0.03 reef sites in the Northeast Gulf of -0.4 Mexico in August 2016 where -0.5 0.02 AR4 = 13.2 m, AR5 = 14.1 m, µmolcm flux + 4

and AR6 = 14.5 m. Mean ±S.E. cm DO flux µmol -0.6

NH 0.01 of DO and nutrient fluxes -0.7 -0.8 0 AR4 AR5 AR6 AR4 AR5 AR6 c d 0.016 0.016 -1 -1 h h 0.012 -2 -2 0.012

0.008 0.008 flux µmolcm flux - 3 0.004 0.004 flux µmol cm DIP NO

0 0 AR4 AR5 AR6 AR4 AR5 AR6

abundant organisms among all three sites, and other crusta- 0.001) and between light and the dark treatments (p =0.01, ceans were also abundant at AR4 and AR5. Except for barna- Fig. 5). However, DO fluxes did not change from negative to cles, no other epifauna were abundant on AR6. There were positive during dark and light treatments. Regardless of the also differences in DO fluxes across all three reef sites (p = light level, all sites showed net respiration. All nutrient fluxes

Table 3 Ammonia monooxygenase (amoA)-containing microbiomes was extracted from animal and associated microbiome. The abundance of of early artificial reef settlers. Quantitative PCR (qPCR) was used to archaeal amoA (AOA) and bacterial amoA (AOB) genes were normalized enumerate prokaryote amoA and 16S rRNA genes. Animals were collect- to total prokaryotes (Proks: bacteria, archaea, crenarchaea) ed from the reef in February 2017, preserved in ethanol, and total DNA

Phylum of organism based on morphological Material DNA yield (mg) per Total Prokaryotes, 16S Ratio AOA/ Ratio AOB/ taxonomic identification extracted mm3 tissuea rDNA copies/ngb Tot Proks Tot Proks

Bryozoan T + E 4.4 1.8E+06 2.2E−02 2.6E−01 Arthropoda (barnacle) T + E 2.2 1.3E+07 9.7E−03 2.6E−03 Arthropoda (crab) T + E 1.5 1.0E+07 1.0E−02 n.d. Arthropoda (amphipod) T + E 0.83 3.7E+05 n.d. n.d. Arthropoda (amphipod) T + E 0.85 1.9E+07 7.5E−03 1.8E−03 Arthropoda (skeleton shrimp) T + E 0.7 2.3E+06 n.d. n.d. Gastropod (bivalve) T 50 1.8E+05 n.d. n.d. Gastropod (nudibranch) T 6.7 1.1E+06 n.d. n.d. Cnidarian (hydrozoan) T + E 3.4 4.8E+06 n.d. n.d. Chordata (tunicate) T + E 33 2.9E+06 n.d. 3.4E−02 Chordata (tunicate) T + E 15 1.8E+06 n.d. n.d. Chordata (tunicate) T + E 3.4 8.2E+05 5.0E−02 n.d. Bottom-water samplec n/a 9.0E+07 1.0E+00 1.5E−03

T+Etissue plus exoskeleton T tissue only, n.d. amoA not detected a Total animal and prokaryote DNA yield (mg) per 3 mm3 of tissue extracted b Total prokaryotes, bacteria + archaea + crenarchaea, 16S copies per ng DNA c For comparison, AOA and AOB abundance in prokaryote DNA from water sample collected at artificial reef site AR5, March 2016 Author's personal copy

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+ across the reef sites were different from one another (p <0.03) NH4 can increase benthic productivity in tide pools up to 8- + except for NH4 (p =0.60,Fig.5). Despite these differences, fold (Bracken 2004; Pfister 2007). In our study, invertebrate- + all reef sites had net respiration and net nutrient release. Light excreted NH4 and organic N likely stimulated attachment and and dark nutrient fluxes were not different from one another productivity of micro- and macroalgal communities similar to (p >0.10). enhanced phytoplankton and benthic microalgal biomass at an artificial reef compared to a nearby control site, which was AOO Associated with Epifauna attributed to increased benthic remineralization (Falcão et al. 2007). Nine taxa in five phyla (Bryozoa, Arthropoda, Mollusca, In addition to bottom-up effects of invertebrates on primary Chordata, and Cnidaria) collected in February were used to producers, they are also linked by top-down effects through examine abundance of ammonium oxidizing archaea (AOA) grazing. Oysters and other reef building invertebrates con- and bacteria (AOB). Single individuals of each taxa were an- sume phytoplankton and particulate organic carbon through alyzed except for duplicate amphipods and triplicate tunicates. filter-feeding (Newell et al. 2005;MazzeiandBiber2015). Ammonia oxidizing organisms were associated with four Quantifying interactions between sessile invertebrates and taxa: barnacles, crabs, amphipods, and tunicates. AOA were phytoplankton communities are complicated by large-scale present on five of the 12 samples: three crustaceans, a bryo- along-shore transport and estuarine export in these open coast- zoans, and one of the three tunicate samples (Table 3). Three al systems. Local nitrogen recycling may be overwhelmed of these samples (bryozoan and two crustaceans) also had during periods of heavy rainfall and subsequent estuarine out- AOB present. When detected, the number of AOA or AOB flow or coastal upwelling, but recycling may be significant copies per 16S gene copy was similar to those observed in during summer months when upwelling or freshwater outflow sediment samples (Caffrey et al. 2007). However, there was is minimal. In addition to the fluxes measured directly on the not agreement among replicates of animals within a taxa. Of reef, some reef-associated organic matter will sink into the the two amphipod samples, one had both AOA and AOB sediments where additional oxygen uptake and nutrient re- while the other had neither. Of the three tunicates, AOA were lease will occur. This will result in greater rates of nutrient found on one sample, AOB on the other, and neither on the cycling in the area than simply what is occurring on reef ma- third. terial itself.

Control by Invertebrate Biomass Discussion One of the surprising results of this study was the similarity Studies of biogeochemical cycling on artificial reefs are few, between light and dark fluxes. Systems dominated by benthic with none from the nGOM, so we use systems such as natural micro- or macroalgae commonly have differences in oxygen hard bottoms, oyster reefs, other reef builders, and tide pools and nutrient fluxes during light versus dark periods while to provide insights into the role of benthic fauna and primary systems dominated by microbes, invertebrates and other fauna producers on nutrient cycling. Macrofauna on artificial reefs typically exhibit consistently high rates of respiration and + as in these natural systems affect the nitrogen supply by di- NH4 flux (Joye and Anderson 2008). We did not observe + rectly increasing NH4 concentrations via waste products and oxygen production and nutrient uptake during light incuba- increasing nutrient retention by altering flow dynamics (Stief tions, and consistently observed oxygen consumption and nu- 2013). Hopkinson Jr. et al. (1991) attributed higher respiration trient release during dark incubations. Thus, epifaunal bio- + rates and NH4 fluxes to increased invertebrate biomass at mass appears to be the dominant factor over micro- and Gray’s Reef, a natural hard-bottom. This hard-bottom habitat macroalgae controlling oxygen and nutrient fluxes at these in the Georgia Bight was net heterotrophic with a consump- artificial reef sites. tion rate nearly 2-fold higher than the rate of organic matter The first and dominant invertebrates colonizing the artifi- production (Hopkinson Jr. et al. 1991). Primary productivity cial reefs over the 11-month period were barnacles, followed in the water column was high; however, greater than one third by small crabs, jingle shells, and other small bivalves. Soft- of the biomass and respiration was attributed to sessile inver- bodied invertebrates were primarily stalked tunicates, bryo- tebrates. Nutrient fluxes observed in our study were similar to zoans, and various marine worms. These taxa along with Gray’s Reef (Hopkinson Jr. et al. 1991). Artificial reefs are anemones and nudibranchs began to colonize during spring also open systems which function similarly to hard-bottom, and summer. Biomass growth was low during the first oyster, and invertebrate reefs. While artificial reefs have less in 3 months of deployment and the species composition was + common with tide pools, NH4 excretion by sessile inverte- likely affected by both recruitment timing and settlement sur- brates in tide pools may alleviate nutrient limitation of face availability (Cummings 1994; Pickering and Whitmarsh macroalgae (Pfister 2007). This release of organic N and 1997; Steimle et al. 2002). Changes in site-specific chemical Author's personal copy

Estuaries and Coasts cues in the environment may promote or deter larval inverte- Mayzaud and Conover 1988; Mukai et al. 1989; Rosas et al. brate settlement on the reef material (Pawlik 1992;Whalan 1999). The carbon-specific component is inferred from the and Webster 2014). These same chemical cues can elicit rate of oxygen consumption by benthic organisms, while the + changes in life history functions such as reproduction and nitrogen-specific component is inferred from the rate of NH4 feeding, causing them to carry out different processes at dif- excretion (Mukai et al. 1989). While the main product of + ferent times (Pawlik 1992). This may further explain the var- excretion is NH4 , a significant fraction may also be organic iation we observed in community composition across time nitrogen (Mayzaud 1973). Dall and Smith (1986)demonstrat- and season, as well as between reef modules only several ed the importance of carbon consumption to metabolism in kilometers apart (SI Table 1). Future studies continuing be- controlled tank experiments with fed versus starved inverte- yond 1 year to see if how epifauna biomass and community brate populations. For fed individuals, O:N ratios were around composition changes would be valuable. 15:1, whereas O:N ratios decreased to approximately 7:1 for starved individuals. Abiotic parameter such as temperature or Microbial Processes salinity, food availability, and feeding habits alter O:N ratios (Mukai et al. 1989;Mayzaud1973; Brockington and Clarke Spatial heterogeneity of the sessile invertebrate community 2001; Langenbuch and Pörtner 2002). An unstated assump- alters nutrients, space, and other resources which then affect tion of many of these studies is that these rates are solely a microorganisms and microbial processes (Dang and Lovell function of the metabolism of the invertebrates. The role 2015). Complex interactions among microbial communities, played by microbial microbiomes associated with inverte- primary producers, and invertebrates alter the biogeochemical brates in altering O:N ratios is not well understood. processes that manifest as changes in oxygen and nutrient The O:N:P ratios measured in this study reflect both the fluxes. We use relationships between nutrient and oxygen invertebrate metabolism and microbial processes, so attribut- fluxes to assess the contribution from invertebrate versus mi- ing these net fluxes to specific biogeochemical pathways as crobial processes to biogeochemical cycling. Many studies has been done in sediments is a challenge. In sediments where + have examined the ratios of oxygen consumption to ammoni- phytoplankton are the main source of organic matter, O:NH4 um excretion (O:N) of benthic organisms to provide informa- flux ratios that are greater than 6:1 have often been attributed tion about metabolism (Regnault 1979;DallandSmith1986; to nitrification while N:P flux ratios less than 16:1 have been

Fig. 6 Ammonium flux versus a -1 y = -9.49x - 0.124 respiration rates on rock material R² = 0.651 from AR5 artificial reef site in the -1 h -0.8

Northeast Gulf of Mexico from -2 7:1 Oct October 2016–August 2017 Dec where 7:1 ratio represents -0.6 Redfield C:N ratio (a). DIP fluxes Feb vs DIN fluxes on rock material -0.4 April from AR5 artificial reef site in the June Northeast Gulf of Mexico from -0.2 August October 2016–August 2017 Respiration µmol cm where 16:1 ratio represents 0 Redfield N: P ratio (b) 0 0.02 0.04 0.06 0.08 0.1 + -2 -1 NH4 flux µmol cm h b 0.16 16:1 -1 h

-2 0.12 y = 6.11x Oct R² = 0.05 Dec 0.08 Feb April 0.04 June DIN flux µmol cm µmol DIN flux August 0 0 0.005 0.01 0.015 0.02 DIP flux µmol cm-2 h-1 Author's personal copy

Estuaries and Coasts attributed to denitrification (Groffman et al. 2006). The ratio Nutrient concentrations are generally low in this area of the + of O:NH4 fluxes in this study was 9.5:1 (Fig. 6a). This is shallow northeastern GOM shelf, with DIP generally at or −1 + −1 − similar to ratios reported for invertebrates, but other factors below 0.2 μmol L ,NH4 near 3.0 μmol L ,andNO3 + − −1 affecting this ratio include the loss of ammonium either by NO2 concentrations below 2.0 μmol L (Cesbron et al. uptake by microalgae or oxidation to nitrite and then to nitrate 2019). High nutrient concentrations in February may have − by nitrifying organisms (Stief 2013). Additionally, nitrate and resulted from upwelling of NO3 -rich waters onto the shallow ammonium may be taken up, stored intracellularly, and assim- shelf. Seasonal upwelling of deeper, nitrate-rich colder waters ilated by heterotrophic bacteria, archaea, and benthic has been previously observed in this region (Collard et al. microalgae at the reef surface (Stief 2013). Positive nitrate 2000; Cesbron et al. 2019). Increased water temperatures fluxes in April, June, and August provide evidence not only and nutrient availability in the spring may have promoted of nitrification in this artificial reef system, but of increased increased growth of attached microalgae in April (Table 1). microbial communities with time from deployment (Fig. 3). In addition to nutrients, light availability controls primary This evidence of nitrification is consistent with some of our production by phytoplankton, benthic microalgae, and at- invertebrate samples which had abundant ammonia oxidizing tached algal communities. As water depth increases, light organisms (AOO). Although these results are limited since availability decreases exponentially affecting rates of photo- they represent a single time point at a single reef with limited synthesis on the reefs and at the sediment-water interface. replication within species, they suggest that colonization of Although water depths were similar among sites from 13.2 epifauna by AOO does occur even before we observed posi- to 14.5 m, chlorophyll a concentrations on the reef were tive nitrate fluxes. Similarly, we use the ratio of dissolved highest at the shallowest reef site and lowest on the deepest − − + inorganic nitrogen (DIN = NO3 +NO2 +NH4 ) to dissolved site. inorganic phosphorous (DIP) ratio to examine the potential impact of microbial activities. The DIN:DIP flux ratio from these experiments was about 6:1 (Fig. 6b), indicating a loss of Methodological Challenges nitrogen in the system. This is most likely due to denitrifica- − − tion, the reduction of NO3 to N2 gas. The negative NO3 As previously discussed, dissolved oxygen and other nutrient fluxes in the dark in February may have been due to denitri- fluxes were statistically similar during light and dark and in fication. This is consistent with ratios measured on hard- most cases, the magnitude of dark fluxes was less than that in bottom (Hopkinson Jr. et al. 1991)orrockybiofilm the light. This was most likely due to experimental design, as (Magalhāes et al. 2005) and direct measurement of nitrifica- the light portion of the experiment was consistently run before tion and denitrification (Magalhāes et al. 2005). Future studies the dark portion, and more oxygen was available during the should examine the rates of microbial processes by inverte- light portion. Initial oxygen concentrations were lower at the brates found on the Gulf of Mexico artificial reefs to better beginning of dark incubations, particularly in February and understand their effect. April (SI Fig. 10). In addition, February and April had DO fluxes which were lower in the dark than in the light, most Environmental Conditions likely due to high invertebrate biomass compared to previous months. Thus, the methods were adjusted after April to sample Thermal stratification is common during the summer every 0.5 h instead of 1.5 h. As a result, initial oxygen con- (Dzwonkowski et al. 2011; Dzwonkowski et al. 2015). centrations were similar for both the light and dark periods of However, August 2017 was a period of unusually intense salin- the experiment in June and August (SI Fig. 10). Because of the ity stratification. Record rainfall levels in May and June 2017 high animal biomass and their respiration, it was possible that were nearly double levels from the previous 2 years (http:// hypoxic or anoxic conditions existed at the rock surface. www.ndbc.noaa.gov). At AR5, bottom-water DO was lower Below about 125 μmol L−1 of DO, organisms become on average during the sampling year than at the surface due to stressed and either stop or slow their respiration. This was microbial respiration in bottom waters and sediments along with likely an issue in February and April when initial DO concen- intense stratification which reduced mixing between surface and trations for dark fluxes were below 125 μmol L−1. It may − − bottom waters. Bottom DO was markedly lower in August than explain the switch from NO2 and NO3 production in the any other month with concentrations at about 94 μmol L−1 light to consumption during the dark. In the future, it might (Table 1), which may have stressed benthic invertebrate com- be wise to have more experimental units and to test each unit munities on the reef. DO concentrations this low, while rare, completely in the light or completely in the dark for the dura- have been associated with areas of high chlorophyll a at other tion of the experiment. Similarly, it is recommended that if locations within the GOM (Schroeder and Wood 1999, Collard these methods are replicated, sampling should occur every et al. 2000, Rabalais et al. 2001, Murrell et al. 2013). 0.5 h instead of 1.5 h when animal biomass is high. Author's personal copy

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Conclusions Bracken, M.E.S. 2004. Invertebrate-mediated nutrient loading increases growth of an intertidal macroalga. Journal of Phycology 40: 1032– 1041. Biomass of epibenthic and sessile invertebrates was greater Brockington, S., and A. Clarke. 2001. The relative influence of temper- than that of epiphytic micro- or macroalgae at newly intro- ature and food on the metabolism of a marine invertebrate. Journal duced artificial reef material in the Northeast Gulf of Mexico. of Experimental Marine Biology and Ecology 258 (1): 87–99. In addition, rapid growth by fouling invertebrates occurred Caffrey, J.M., N. Bano, K. Kalanetra, and J.T. Hollibaugh. 2007. Ammonia-oxidation and ammonia oxidizing Bacteria and Archaea during the first 5 months of deployment, and after that time, from estuaries with differing histories of hypoxia. ISME Journal 1 biomass increased, but at a slower rate. This study focused on (7): 660–662. the early response to artificial reef deployments. Longer-term Cesbron, F., M.C. Murrell, M.E. Hagy, W.H. Jeffrey, W.F. Patterson III, studies are needed since previous research by Bohnsack and and J.M. Caffrey. 2019. Patterns in phytoplankton and benthic production on the shallow continental shelf in the Northeastern Gulf of Sutherland (1985) suggests that artificial reefs typically reach a Mexico. Continental Shelf Research 179: 105–114. https://doi.org/ mature, equilibrium community within 1–5 years. Seasonal 10.1016/j.csr.2019.04.003. variability in the fouling communities is most likely influenced Christman, G.D., M.T. Cottrell, B.N. Popp, E. Gier, and D.L. Kirchman. by environmental parameters such as temperature, salinity, and 2011. Abundance, diversity, and activity of ammonia-oxidizing prokaryotes in the coastal Arctic ocean in summer and winter. Applied dissolved oxygen changes, as well as light availability, top- and Environmental Microbiology 77: 2026–2034. down predator control, hydrographic parameters, and recruit- Collard, S.B., A. Lugo-Fernandez, G. Fitzhugh, J.J. Brusher, and R. ment (Dance et al. 2011). This variability may be beneficial to Shaffer. 2000. A mass mortality event in coastal waters of the central the reef ecosystem as the development of complex fouling Florida Panhandle during spring and summer 1998. Gulf of Mexico Science 18: 7. communities as the reef site ages likely provide greater struc- Cummings, S.L. 1994. Colonization of a nearshore artificial reef at Boca tural complexity and an increased forage base known to con- Raton (Palm Beach County), Florida. Bulletin of Marine Science 55: tribute to greater macrofaunal species diversity (Gratwicke and 2–3. Speight 2005; Redman and Szedlmayer 2009). This study pro- Dall, W., and D.M. Smith. 1986. Oxygen consumption and ammonia-N excretion in fed and starved tiger prawns Penaeus esculentus vides key information on how deployment of artificial reefs Haswell. Aquaculture 55: 23–33. affects biogeochemical cycling in a region, the nGOM, with Dame, R., T. Chrzanowski, K. Bildstein, B. Kjerfve, H. McKellar, D. every increasing deployment of reefs but few studies. Nelson, J. Spurrier, S. Stancyk, H. Stevenson, J. Vernberg, and R. Zingmark. 1986. The outwelling hypothesis and North Inlet, South Carolina. Marine Ecology Progress Series 33: 217–229. Acknowledgements We thank David Walter and Walter Marine for do- nating the reef modules utilized in this study and Robert Turpin of Dance, M.A., W.F. Patterson III, and D.T. Addis. 2011. Fish community and trophic structure at artificial reef sites in the Northeast Gulf of Escambia County Florida Marine Resources Division for providing a – permitted artificial reef zone for deployment. We thank Fritz Scharer, Mexico. Bulletin of Marine Science 87: 301 324. Joe Moss, Rachel Presley, Amy Brower, Gary Baine, Matt Davis, Dang, H., and C.R. Lovell. 2015. Microbial surface colonization and biofilm development in marine environments. Microbiology and Stewart Hood, Ryan Lavoie, Christina Toms, Jeff Eble, Nine – Henriksen, Sarah Friedl, Miaya Glaback, Steve Garner, Joe Tarnecki, Molecular Biology Reviews 80: 91 138. Sean Kelly, and the crew of the Total Package, and Douglas Hammock Dzwonkowski, B., K. Park, Ha H. Kyung, W.M. Graham, F.J. and the crew of the H2O Below for their assistance in the field. We thank Hernandez, and S.P. Powers. 2011. Research papers: Hydrographic Alexis Janosik for assisting with invertebrate identifications. Jeremy variability on a coastal shelf directly influenced by estuarine out- – Bosso, Katherine Haynes, Chelsea Barfield, Whitney Brentana, and flow. Continental Shelf Research 31: 939 950. Porsha Hernandez assisted in the laboratory. Dzwonkowski, B., K. Park, and R. 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Program: Interstate Shellfish Sanitation Conference Web Address (URL) of RFP http://www.issc.org/Data/Sites/1/media/2020/issc-rfp-techniques-and-practices-for-vibrio- reduction-2020-4-27.pdf Proposed project director (PI): Lisa Waidner, The University of West Florida Proposed co-PI’s: Jane Caffrey and Wade Jeffrey Proposed Project Title: Using Bioinformatics and Quantitative PCR to Track Pathogenic Vibrio vulnificus and Vibrio parahaemolyticus

EXECUTIVE SUMMARY Vibrio vulnificus and Vibrio parahaemolyticus are naturally-occurring gram-negative bacteria that generally thrive in warm, marine or brackish natural bodies of water. They are often associated with sediments or bodies of water in which oysters occur naturally or in aquaculture. Their success in the environment is largely driven by temperature and salinity; however our recent enumeration of these two species in local waterways indicates a myriad of other environmental factors driving the abundance and distribution (Waidner et al., 2020). In our coastal Gulf of Mexico community, public perception about Vibrio threats is heightened.

In response to increasing public health concerns, we have been working with Escambia County, Florida to assess the prevalence of Vibrios, including Vibrio parahaemolyticus (V.p.) and V. vulnificus (V.v.). As sought in ISSC RFP items [RFP I.A.(1-2)], we have demonstrated our ability to track Vibrio species with respect to a wide variety of environmental parameters. In 44 locations of the greater Pensacola Bay System and Perdido Bay, we have enumerated Vibrio in water columns, sediments and biofilms on oysters.

To address the RFP item [RFP I.A.(3)], we propose to use bioinformatics tools unique to our facility in the Center for Environmental Diagnostics and Bioremediation at UWF to improve and increase the sensitivity of pathogen detection. To date, we have amassed a database of >80 gene sequences encoding the cytolytic toxic hemolysin, vvhA, of V.v. Similarly, databases for toxic hemolysin genes from V.p. have been constructed and include: thermostable direct hemolysin, tdh (>120 sequences), thermostable direct hemolysin-related gene, trh (>200 sequences), and thermolabile hemolysin, tlh (>150 sequences). Additional sequences will be added, and our databases will inform quantitative PCR primer and probe design, for detection of pathogenic Vibrio species. To address [RFP I.A.(4)], we will continue our partnership with a regional citizen science organization. We will collect oysters from their oyster gardening locations and wild oysters from a selection of our previously surveyed locations. These animals and associated environments will be surveyed to determine levels of pathogenic V.v. and V.p. This will provide pathogen level data for oyster biofilms and liquors, and will allow for comparison of wild-caught and aquaculture-raised oysters.

Finally, to address RFP items [RFP I.A.(4-5)], we propose to additionally screen oyster microbiome biofilms and gut microbes for pilus- and flagella-related genes. These genes, when expressed, affect retention time of Vibrio in oyster and clam tissues. To better determine controls on colonization and retention, the abundance of these genes may also be assessed simultaneously with direct pathogenicity-related genes.

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SCOPE, APPROACH, AND METHODOLOGY Objectives  As sought in RFP items [RFP I.A.(1-2)], we will track Vibrio species with respect to a wide variety of environmental parameters. This will be done twice in the one-year study time, first in early-mid Fall (Sept 2020), and again in early Spring 2021. (For details, see below, DETAILED AND ITEMIZED BUDGET). Fall 2020 samplings will be done at 12 locations previously surveyed for Vibrio (Fig. 1) and at an additional 12 sites where homeowners are performing oyster gardening combined with citizen science. DNA samples collected in Fall will comprise the majority of new sequences used to inform new primer design. All DNA samples from Fall will also be screened with existing and new primer sets. Spring 2021 DNA samples will be screened with new primer sets. All DNA samples will be accompanied by all water quality parameters as previously done (see Appendix, EsCoVibrio Winter Report_law033120.pdf).

 To address [RFP I.A.(4)], we will continue our partnership with a regional citizen science organization, Bream Fishermen Association, who performs oyster gardening with homeowners at 23 locations in local waterways. We will collect oysters from a selection of their existing locations and wild oysters from a selection of our previously surveyed locations (see Appendix, EsCoVibrio Winter Report_law033120.pdf, and Fig. 1). These animals and associated environments will be surveyed to determine levels of pathogenic V.v. and V.p. This will provide pathogen level data for oyster biofilms and liquors, and will allow for comparison of wild-caught and aquaculture-raised oysters.

 To address [RFP I.A.(3)], we will use bioinformatics tools to improve and increase the sensitivity of pathogen detection. Databases of gene sequences encoding the cytolytic toxic hemolysin, vvhA, from V.v. (>80 sequences), toxic hemolysin from V.p.: thermostable direct hemolysin, tdh (>120 sequences), thermostable direct hemolysin-related gene, trh (>200 sequences), and thermolabile hemolysin, tlh (>150 sequences). Additional databases may include toxR and vcg. Additional sequences will be obtained from databases, which will inform quantitative PCR primer and probe designs.

 Finally, to address RFP items [RFP I.A.(4-5)], we propose to additionally screen oyster microbiome biofilms and gut microbes for pilus formation and related genes. These genes, including tcp and transcription factors SmcR and OpaR, possibly affecting Vibrio shellfish retention time, will also be evaluated in developing screening tools.

Figure. 1. Locations of sampling sites previously surveyed for V.v. and V.p. Colors of map pins indicate dates on which samples and in situ measurements were obtained. For more information, please see Appendix, EsCoVibrio Winter Report_law033120.pdf.

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Preliminary data To determine baseline abundances of potentially dangerous species of Vibrio, UWF M.S. graduate student Mark Prousalis, under the mentorship of Waidner, surveyed surface waters at 4 locations in the Indian Bayou, Santa Rosa County, FL. In 17 sampling dates from January 2018 – March 2019, Prousalis conducted in situ measurements of water quality and collected samples for later lab processing for total suspended solids (TSS), DNA, dissolved nutrients, chlorophyll a (Chl a), and bacterial abundances and production. Dr. Wade Jeffrey and his students performed bacterial production analyses.

Total bacterioplankton DNA was isolated from whole water, the particle-attached fraction (>0.8 micron) and free-living fraction (>0.2 micron, <0.8 micron). Using quantitative polymerase chain reaction (qPCR), Prousalis enumerated total bacteria using previously-published primers and conditions (Waidner and Kirchman, 2007, 2008). Prousalis also screened all DNA samples (n=172) for the hemolysin gene, vvhA, from Vibrio vulnificus (V.v.) using qPCR and conditions as previously published (Panicker et al., 2004). Dr. Darrell Grimes kindly provided 6 strains to us from his collection of environmental isolates of V.v. Of those 6, only one (#12-8) contained the vvhA gene, as determined by screening with the (Panicker et al., 2004) primer set in end- point PCR (Table 1). This served as the positive control for all qPCR analyses.

Table 1. Previously-published primer sets for enumerating V.v. List of oligonucleotide primers, target genes, amplicon sizes, annealing temperatures and sources of gene sequences used for PCR amplification detection of total and/or hemolysin-producing Vibrio species. Target Primer Primer Sequence (5’ NN Melting Amplicon Reference Gene Name to 3’) Temperature Size (bp) (°C)b vvhA a Vvh-785F CCGCGGTACAGG 61 538 (Staley et al., 2013) TTGGCGCA Vvh- CGCCACCCACTTT 58 1303R CGGGCC vvhA a L-vvh TTCCAACTTCAAA 54 205 (Panicker et al., 2004) CCGAACTATGA R-vvh ATTCCAGTCGATG 58 CGAATACGTTG vvhA a Clinical- AGCTGCCGATAG 55 277 (Rosche et al., 2005) type P1-F CGATCT Clinical CGCTTAGGATGAT 51 type P3-F CGGTG Env. type CTCAATTGACAAT 42 277 (Rosche et al., 2005) P2 (with GATCT P3) a vvhA, V.v. hemolysin b Nearest neighbor calculation, (Kibbe, 2007)

Of all 172 Indian Bayou samples, only 8 (whole water and particle-attached fraction samples only) resulted in amplicons of vvhA above our limit of detection (10 copies per reaction, with cycle threshold, CT, values >35). Prousalis and undergraduate research assistants proceeded to screen the 172 DNA samples for V. parahaemolyticus (V.p.) hemolysin or toxin genes, using end-point PCR and a variety of primer sets from previously published works (Caburlotto et al., 2009; Honda and Iida, 1993; Iida et al., 1998; Johnson et al., 2010, 2012; McCarthy et al., 1999; Nishibuchi et al., 1990; Taniguchi et al., 1985). A low number of samples (n=2) contained

Page 3 of 31 UWF ISSC Vibrio proposal: Waidner-Caffrey-Jeffrey May 2020 detectable toxR, tdh, trh, or tlh genes using previously published primer sets, so Prousalis designed new primers for the tlh and trh hemolysin genes (see Table 2, below). His data analyses are still underway. Notably, Prousalis’s focus of DNA screening was only in surface waters, and did not include bottom water or sediments. Subsequent to that project, the proposed PI and co-PI’s performed surveys of a larger area, in conjunction with Escambia County, FL. For that project, we surveyed sediments, water columns, and invertebrates.

Survey of 7 major basins for Vibrio vulnificus (V.v.) and Vibrio parahaemolyticus (V. p.) In response to concerns of local citizens, we have been working with Escambia County, Florida to assess the prevalence of V.p. and V.v (Waidner et al., 2020). Using the chromogenic agar assay (CHROMagar-Vibrio agar in petri plates) and processing as previously described (Huq et al., 2012; Oliver, 2003; Thomas et al., 2014; Yeung and Thorsen, 2016), we enumerated V.v. and V.p. at 44 locations in 7 major basins adjacent to the Gulf of Mexico. New observations included those relationships of Vibrio abundance with respect to physical parameters measured in situ, including salinity, temperature, and dissolved oxygen. Of note in our preliminary analyses was the statistically significant correlation between V. vulnificus abundances in sediments and the salinity observed in the water column at depth (PSU range 2-28), in contrast to previously published observations in which V.v. abundances in the water column are negatively correlated with salinity, in coastal and estuarine waters with salinities ranging 1-35 (Chase et al., 2015; Kelly, 1982; Lipp et al., 2001; Randa et al., 2004). Most strikingly in our study, sediment V.v. abundances were positively correlated with salinity observed at depth (R=0.3887, p<0.05), where salinities ranged from 2 to 28 PSU. Additional analyses, including the influence of other factors such as meteorological effects (rainfall and wind), as well as water quality data including TSS, Chl a, dissolved and total nutrient concentrations, among others, are underway. Findings from our existing study will inform our proposed ISSC project sampling efforts and further support the findings of this proposed project and [RFP I.A.(1-2)].

Hemolysin and other genes specific to pathogenic Vibrio vulnificus (V.v.) and Vibrio parahaemolyticus (V. p.)

It is well-established that the tdh and trh genes play environmental roles in distribution of V.p, but existing primer sets are limited (Table 2). To date, the best-designed primer sets for trh and tdh (Gutierrez West et al., 2013) have appropriate nearest-neighbor (NN) melting temperatures for low-cost SYBR Green assays (Table 2, red flags). However, PCR with these sets are likely to result in amplicons which are either too large (410 bp, trh), or more often contain tdh sequences specific to environmental-only isolates, and not pathogen-specific sequences. Therefore, our unique bioinformatics approach, via mining of existing, but not yet published, genomic data (Rigney et al., 2019), will serve to improve primer and probe specificity (see below, New primers and databases).

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Table 2. Previously-published primer sets and in-house primers for enumerating V.p. List of oligonucleotide primers, target genes, amplicon sizes, annealing temperatures and sources of gene sequences used for PCR amplification detection of total and/or hemolysin-producing Vibrio species. Melting temperatures in red font are indicative of non-specific amplification red flags. Target Primer Primer Sequence (5’ NN Melting Amplicon Reference Gene Name to 3’) Temperature Size (bp) (°C)d tlha L-tlh AAAGCGGATTAT 59 450 (Taniguchi et al., 1985) GCAGAAGCACTG R-tlh GCTACTTTCTAGC 56 ATTTTCTCTGC tdhb L-tdh GTAAAGGTCTCTG 52 269 (Nishibuchi et al., 1990) ACTTTTGGAC R-tdh TGGAATAGAACC 53 T TCATCTTCACC trhd L-trh TTGGCTTCGATAT 53 500 (Honda and Iida, 1993) TTTCAGTATCT R-trh CATAACAAACAT 55 ATGCCCATTTCCG toxR L-toxR GTCTTCTGACGCA 53 368 (Caburlotto et al., 2009) ATCGTTG R-toxR ATACGAGTGGTT 53 GCTGTCATG tlha L-lth- GCGGATTATGCA 56 This study ALT GAAGCACTG tlha L-tlh- GCGGATTATGCA 56 ALT GAAGCACTG tlha R-tlh GCTACTTTCTAGC 56 ATTTTCTCTGC R-trh- ATAACAAACATA 56 ALT2 TGCCCATTCCCGG tdhb tdh86F CTGTCCCTTTTCC 58 245 (Gutierrez West et al., 2013) TGCCCCCG trhc tdh331R AGCCAGACACCG 60 CTGCCATTG trhc trh90F ACCTTTTCCTTCT 53-56 410 (Gutierrez West et al., 2013) CCWGGKTCSG trh500R CCGCTCTCATATG 57-59 CYTCGACAKT tdhb Tdh-F TCCCTTTTCCTGC 50 Not stated (Nordstrom et al., 2007)e CCCC Tdh probe TGACATCCTACAT 49 GACTGTG Tdh-F CGCTGCCCATTGT 57 ATAGTCTTTATC a tlh, thermolabile hemolysin b tdh, thermostable direct hemolysin c trh, thermostable-related direct hemolysin d Nearest neighbor calculation, (Kibbe, 2007) e requires TaqMan probe, patent pending at time of publication, but no evident U.S. patent in current system.

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New primers and databases of hemolysin and other genes specific to V.v. and V. p. In Waidner’s current Bioinformatics cohort, students are building databases of sequences encoding the various hemolysins, toxR, and other pathogenicity-related genes, by curating genomes of pathogenic Vibrio. Additional genes to be curated and added to in-house multiple sequence alignment databases will include genes involved in pilus formation and quorum sensing (see below). Improvements to existing primers or development of new primers will include several factors for accurate quantitation of uncultured bacteria. For example, precise and sensitive enumeration of specific groups of bacteria is only possible with qPCR primers that: (a) Accurately hybridize to the target gene of interest with annealing temperatures of at least 55oC (Waidner and Kirchman, 2008). (Also see Waidner and Kirchman 2008 supplement). (b) Hybridize with high specificity to the majority of the known target sequences (Waidner and Kirchman, 2007, 2008). (c) Are well-matched, in that forward and reverse primers have similar nearest-neighbor (NN) sequence annealing properties (Kibbe, 2007). (d) Do not require addition of a third “probe” (e.g. TaqMan probe, molecular beacon, or other type of Fluorophore-Quencher system , since these additional probes add considerable cost for each assay (Buh Gašparič et al., 2010). Only under very specific applications are fluorophore-quencher combination probes necessary (Andersen et al., 2006). (e) Result in an amplicon no less than 175 bp and no greater than 275 bp, to maximize efficiency of amplification and minimize amplification of non-specific amplicons. (f) All qPCR pairs evaluated further in Waidner lab, in that amplicons generated with new primer pairs are initially screened by performing sequencing of a selection of products to ensure specificity of amplification.

The current primers to amplify sequences from pathogenic V.v. and V.p. in water or oyster samples are limited and do not meet all the criteria listed above. For example, using molecular tools for determining whether particular strains of V. v. are capable of causing human disease is still largely unanswered. There is no evidence that the region of vvhA in previously published studies (Rosche et al., 2005) is directly involved in virulence. However, this region appears to be a potential predictor of strain virulence. More in-depth analysis is required to see if there is a subtype of the E-genotype with greater virulence, and we propose to answer this question using bioinformatics tools to mine genome sequence data for previously unannotated gene regions in known pathogenic strains (such as the genomes uploaded to the NCBI database, (CDC, 2019)).

Approach: V.v. and V.p. molecular tool development The overview of our existing workflow and pipeline is as follows: a. Literature review and search of established protocols for use of molecular tools to enumerate specific group of bacteria (example, Tables 1 and 2).

b. Initial evaluation of published primer pairs using SYBR Green chemistry, with annealing temperatures based on nearest neighbor calculation of melting temperatures.

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c. Mining of genomes and annotated sequences (if present) to form multiple sequence alignments (MSA) for each gene, grouping sequences by clinical strains, environmental strains, and unknown/uncharacterized groups (example, Fig. 2). 1) All protein-encoded genes aligned by codons, to delineate variability at the wobble position and from variable regions conferring amino acid changes.

Figure 2. Example MSA in which sequences of grouped species or strains are differentiated from the other group of bacteria, in regions of variability. Primers are designed to match well to strains in lines #1 and 2, while simultaneously not hybridizing well to the remainder of sequences in the alignment, assuming established qPCR conditions. Multiple sequence alignments are performed with CLUSTAL-W algorithm in MEGA X (Kumar et al., 2018). d. Location of regions of conservation among clinical only, environmental only, with and without inclusion of sequences from uncharacterized groups of strains.

e. Insertion of primer sequences into MSA and development of new primers, either 1) overlapping directly with previously published primer sequences, or 2) inside or outside of previously published primers, depending on the size of the amplicon. 3) In all cases, whether the new amplicon size is adjusted or not, primer specificity is directed only to hybridize well (again, NN minimum of 55oC) to the intended target and exclude non-pathogenic strains’ sequences.

f. To address specific considerations of assay development (FDA, 2019), section 3.2, new primer design will be evaluated for specificity for the intended targets, and inclusivity and exclusivity will be evaluated where possible. 1) Secondary evaluation of newly developed primer pairs using SYBR chemistry as above, while also determining lower detection limit. Maximum number of acceptable CT values are in the range of 37-38, as typically after 38 cycles, nonspecific amplification is likely (Ruiz-Villalba et al., 2017).

g. Determination of amplification efficiency, based on the slope of the regression of logfold DNA dilution with CT values, as previously described (Waidner and Kirchman, 2008).

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h. For a selection of samples and new primer pairs, to address specific considerations of assay development (FDA, 2019), section 3.0, testing in qPCR may be repeated in an alternative platform. In Waidner’s lab, we use the QuantStudio3 machine, using QuantStudioTM Design & Analysis software v1.5, but also have access to an alternative real-time machine: StepOneTM Real-Time PCR System, with StepOne Software v2.3. Repetition on the alternative machine will ensure translation across multiple platforms.

i. To address general considerations of assay development (FDA, 2019), section 2.4.1, matrix aging to assess the robustness of the method will be again tested on a selection of samples. Currently, there are extracted DNA samples in the CEDB freezers, originally extracted from seawater in 2017, which are still in use today for qPCR analyses. The numbers of gene copies determined by qPCR in these samples determined in 2017 have recently been retested (late 2019) and again result in the same copy number from the same DNA preparations.

j. Initial testing will be performed on DNA extracted from Dr. Jay Grimes’ cultures and new isolates obtained from CHROMagar plates in the Sept. 2020 sampling. Additionally, Vibrio numbers obtained from CHROMagar plates (culturable cells) will be compared to calculated cell numbers obtained by qPCR from DNA of the same sample.

Use of this already-established workflow will directly address prioritized activities [RFP I.A.(3)], in particular by improving existing primer sets, developing new primer sets, while maintaining low cost assay format which will be translatable across multiple platforms.

Quorum sensing and pilus formation In addition to the genes directly associated with virulence (toxR and hemolysin genes), additional factors may be considered when screening oyster biofilms or gut associated bacteria and their surrounding waters and sediments. In particular, it is known there are specific bacterial genes responsible for increased uptake and retention of pathogenic Vibrio, directly affecting depuration (Froelich and Noble, 2014). Pilus and flagellum formation directly affects the retention time of Vibrio in oyster tissues (Aagesen et al., 2013). As pilus formation is essential for inhabiting and colonizing oyster and clam tissues, it is also essential for pathogenicity in humans (Paranjpye et al., 2007), in particular their tendency to subsist in human intestinal epithelia. The lack of understanding of these genes, particularly with respect to Vibrio assessments based on counts of cultured colonies as the only abundance data, further confounds food safety experts’ understanding of Vibrio-oyster ecological relationships (Chae et al., 2009; Froelich and Noble, 2014; Shen et al., 2019). Therefore it is imperative, when planning food safety protocols [RFP I.A.(4-5)] that pilus-, flagella- and other related genes are assessed simultaneously with direct pathogenicity-related genes.

The original lux family genes was initially known only for quorum sensing to direct bioluminescence in V. fischeri (Visick et al., 2000), but recently we have mined genomic data in the NCBI database in search of quorum sensing genes present in pathogenic Vibrio. Those lux genes are now known to exist in genomes of pathogenic V. cholerae (Genbank record , CP046742.1 (CDC, 2019). Similarly, we are mining V.v. and V.p. genomic data for SmcR and OpaR transcription factor genes. These transcription factors control expression of quorum

Page 8 of 31 UWF ISSC Vibrio proposal: Waidner-Caffrey-Jeffrey May 2020 sensing, a mechanism by which groups of bacteria, often within the same genera or species, communicate (Ball et al., 2017). Pathogens are often highly dependent on quorum sensing mechanisms and/or expression of pili-associated genes for colonization of surfaces, biotic and abiotic. To determine if aquaculture-grown oysters are more likely to have higher numbers of V.v. and V.p. in their guts or microbiomes, we will also screen aquaculture- and wild-caught oysters for these genes. We hypothesize higher numbers of both types of genes in the microbiomes of aquaculture oysters, due to the high density of oysters, as compared to wild- caught.

Initial screening for pilus related genes will be performed on already-extracted bacterioplankton DNA from both types of oysters. Initial screening will use previously-published primer sets (Hughes et al., 2013), but as above, the bioinformatics pipeline steps above will also be used to develop more inclusive primer sets for these groups of gene. For instance, the toxin co-regulated pilus gene region (tcp: 385 bp) is detectable by end-point PCR, but the primers used in this previous study for enumerating Vibrio seal pathogens was too large for optimal qPCR assays using SYBR Green chemistry. As described in the workflow and pipeline above, we will identify pilin-related genes that are co-regulated with toxins, and design new primer pairs for optimal low-cost assays.

PROJECT MANAGEMENT APPROACH The UWF PI and co-PI’s have expertise in microbial molecular ecology, aquatic sciences, water quality, microbiology, aquatic optics, art, and science pedagogy. The team also has a close working relationship with Ms. Barbara Albrecht (see below, APPENDIX PROJECT TEAM STAFFING), a Community Engagement scientist responsible for coordinating Project Oyster Pensacola science and an Educational Coordinator for closely working with UWF and K-12 teachers. The Program Management timeline is shown below (Table 3), showing approximate time ranges of activities (A) and/or milestones (M) for field sampling, bioinformatics data mining, laboratory activities, and data analyses. Table 3. Project Timeline: Ranges of dates for all activities (A) and milestones (M) in project work plan. (A) Activity or Sept. Oct.–Dec. Jan.-Mar. Apr. May-July Aug. (M) Milestone 2020 2020 2021 2021 2021 2021 (A) 3 boat trips, 12 Escambia X X County stations (Fig. 1) (A) 3-4 days of collection at 12 POPa sites. X X (A) DNA extractions, amplification of X target genes, submission for sequencing (A) Data mining of CDC pathogen genomes X X X (and other NCBI genomic data) (A) Water quality sample processing X X (A) New primer design, ordering X X (A) New primer set testing X X (M) Evaluation of qPCR results, data X X X analyses, and multivariate analyses (A) Screening of Fall and Spring DNA X X samples with new primers (M) National Dissemination X X X (M) Internal Reports evaluated by Waidnerb X X X X (M) Final Report to ISSC X a POP = Project Oyster Pensacola b Research assistants will submit monthly data reports to Waidner.

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Principal Investigator: Lisa Waidner, Ph.D., Assistant Professor, will serve as the PI on the project, will have fiscal responsibility for the project, and will generate the annual progress reports and the final project report. Waidner’s inexpensive but powerful molecular techniques to enumerate uncultured or unculturable marine and estuarine bacteria (Campbell et al., 2008; Waidner and Kirchman, 2005, 2007, 2008) (Campbell et al., 2008; Waidner and Kirchman, 2005, 2007, 2008), are also essential to the success of this project. Waidner will be responsible for directly supervising graduate student molecular biology laboratory work, as well as coordination of field personnel, UWF Marine Services Center, and undergraduate research assistants. Co-Principal Investigator: Jane Caffrey, Ph.D., Professor, will serve as a Co-PI on the project. Caffrey’s expertise in estuarine ecology and interest in local water quality (Babcock et al., 2020; Caffrey and Murrell, 2016; Hester et al., 2016; Murrell et al., 2018) will be essential for proper data analyses, including water quality and multivariate statistical analyses of environmental parameters. Dr. Caffrey will supervise the graduate student performing water quality sampling and processing. Additionally, Caffrey, working closely with Barbara Albrecht and Donnie McMahon (Founder, Pensacola Bay Oyster Company), will assist with informing efficacies of new assays in commercial oyster operations, both wild caught and aquaculture facilities. The development of the Oyster Ecosystem-Based Fishery Management Plan for the Greater Pensacola Bay System represents an ideal opportunity for collaboration between industry and UWF. Dr. Caffrey’s current work with both Albrecht and McMahon poise our research group to have access to oysters in aquaculture settings, both from for-profit and citizen-science led operations. Co-Principal Investigator: Wade Jeffrey, Ph.D., UWF Distinguished Professor, Director of UWF Center for Environmental Diagnostics and Bioremediation, and Director of the Reubin O’D. Askew Institute for Multidisciplinary Studies (AIMS), will serve as a Co-PI on the project. Jeffrey is an expert in microbial ecology and Northwest Florida Gulf of Mexico ecosystems (Aas et al., 1996; Bullock and Jeffrey, 2010; Jeffrey, 2017; Vaughan et al., 2016). His expertise and current roles as Director of CEDB and AIMS will be essential for the success of overall project management, infrastructure maintenance, and hiring of properly vetted research assistants.

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LITERATURE CITED Aagesen, A.M., Phuvasate, S., Su, Y.-C., and Häse, C.C. (2013). Persistence of Vibrio parahaemolyticus in the Pacific oyster, Crassostrea gigas, is a multifactorial process involving pili and flagella but not type III secretion systems or phase variation. Appl. Environ. Microbiol. 79, 3303–3305.

Aas, P., Lyons, M.M., Pledger, R., Mitchell, D.L., and Jeffrey, W.H. (1996). Inhibition of bacterial activities by solar radiation in nearshore waters and the Gulf of Mexico. Aquat. Microb. Ecol. 11, 229– 238.

Andersen, C.B., Holst-Jensen, A., Berdal, K.G., Thorstensen, T., and Tengs, T. (2006). Equal Performance of TaqMan, MGB, Molecular Beacon, and SYBR Green-Based Detection Assays in Detection and Quantification of Roundup Ready Soybean. J. Agric. Food Chem. 54, 9658–9663.

Babcock, K.K., Cesbron, F., Patterson, W.F., Garner, S.B., Waidner, L.A., and Caffrey, J.M. (2020). Changing Biogeochemistry and Invertebrate Community Composition at Newly Deployed Artificial Reefs in the Northeast Gulf of Mexico. Estuaries Coasts 43, 680–692.

Ball, A.S., Chaparian, R.R., and Kessel, J.C. van (2017). Quorum Sensing Gene Regulation by LuxR/HapR Master Regulators in Vibrios. J. Bacteriol. 199.

Buh Gašparič, M., Tengs, T., La Paz, J.L., Holst-Jensen, A., Pla, M., Esteve, T., Žel, J., and Gruden, K. (2010). Comparison of nine different real-time PCR chemistries for qualitative and quantitative applications in GMO detection. Anal. Bioanal. Chem. 396, 2023–2029.

Bullock, A.K., and Jeffrey, W.H. (2010). Temperature and solar radiation interactions on 3H-leucine incorporation by bacterioplankton in a subtropical estuary. Photochem. Photobiol. 86, 593–599.

Caburlotto, G., Gennari, M., Ghidini, V., Tafi, M., and Lleo, M.M. (2009). Presence of T3SS2 and other virulence-related genes in tdh-negative Vibrio parahaemolyticus environmental strains isolated from marine samples in the area of the Venetian Lagoon, Italy. FEMS Microbiol. Ecol. 70, 506–514.

Caffrey, J.M., and Murrell, M.C. (2016). A Historical Perspective on Eutrophication in the Pensacola Bay Estuary, FL, USA. In Aquatic Microbial Ecology and Biogeochemistry: A Dual Perspective, (Springer, Cham), pp. 199–213.

Campbell, B.J., Waidner, L.A., Cottrell, M.T., and Kirchman, D.L. (2008). Abundant proteorhodopsin genes in the North Atlantic Ocean. Environ. Microbiol. 10, 99–109.

CDC (2019). Pathogen: clinical or host-associated sample from NCBI’s BioSample submissions. https://www.ncbi.nlm.nih.gov/biosample/SAMN12648318.

Chae, M.J., Cheney, D., and Su, Y.-C. (2009). Temperature effects on the depuration of Vibrio parahaemolyticus and Vibrio vulnificus from the American oyster (Crassostrea virginica). J. Food Sci. 74, M62-66.

Chase, E., Young, S., and Harwood, V.J. (2015). Sediment and vegetation as reservoirs of Vibrio vulnificus in the Tampa Bay Estuary and Gulf of Mexico. Appl. Environ. Microbiol. 81, 2489–2494.

FDA (2019). Guidelines for the Validation of Analytical Methods for the Detection of Microbial Pathogens in Foods and Feeds, Edition 3.0 https://www.fda.gov/media/83812/download.

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Froelich, B.A., and Noble, R.T. (2014). Factors Affecting the Uptake and Retention of Vibrio vulnificus in Oysters. Appl. Environ. Microbiol. 80, 7454–7459.

Gutierrez West, C.K., Klein, S.L., and Lovell, C.R. (2013). High Frequency of Virulence Factor Genes tdh, trh, and tlh in Vibrio parahaemolyticus Strains Isolated from a Pristine Estuary. Appl. Environ. Microbiol. 79, 2247–2252.

Hester, C.M., Smith, H.M., Head, M.E., Langsten, H., Linder, S., Manor, E., Norman, J., Sartory, L., and Caffrey, J.M. (2016). Comparing productivity and biogeochemistry of native and transplanted thalassia testudinum and halodule beaudettei in big Lagoon, Florida, USA. Gulf Mex. Sci. 1, 14–25.

Honda, T., and Iida, T. (1993). The pathogenicity of Vibrio parahaemolyticus and the role of the thermostable direct haemolysin and related haemolysins. Rev. Med. Microbiol. 4, 106–113.

Hughes, S.N., Greig, D.J., Miller, W.A., Byrne, B.A., Gulland, F.M.D., and Harvey, J.T. (2013). Dynamics of Vibrio with Virulence Genes Detected in Pacific Harbor Seals (Phoca vitulina richardii) Off California: Implications for Marine Mammal Health. Microb. Ecol. 65, 982–994.

Huq, A., Haley, B.J., Taviani, E., Chen, A., Hasan, N.A., and Colwell, R.R. (2012). Detection, Isolation, and Identification of Vibrio cholerae from the Environment. Curr. Protoc. Microbiol. CHAPTER, Unit6A.5.

Iida, T., Park, K.S., Suthienkul, O., Kozawa, J., Yamaichi, Y., Yamamoto, K., and Honda, T. (1998). Close proximity of the tdh, trh and ure genes on the chromosome of Vibrio parahaemolyticus. Microbiol. Read. Engl. 144 ( Pt 9), 2517–2523.

Jeffrey, W.H. (2017). CEDB Wetlands: http://uwf.edu/cse/departments/cedb/resources/wetlands-research- laboratory/.

Johnson, C.N., Flowers, A.R., Noriea, N.F., Zimmerman, A.M., Bowers, J.C., DePaola, A., and Grimes, D.J. (2010). Relationships between environmental factors and pathogenic Vibrios in the Northern Gulf of Mexico. Appl. Environ. Microbiol. 76, 7076–7084.

Johnson, C.N., Bowers, J.C., Griffitt, K.J., Molina, V., Clostio, R.W., Pei, S., Laws, E., Paranjpye, R.N., Strom, M.S., Chen, A., et al. (2012). Ecology of Vibrio parahaemolyticus and Vibrio vulnificus in the Coastal and Estuarine Waters of Louisiana, Maryland, Mississippi, and Washington (United States). Appl. Environ. Microbiol. 78, 7249–7257.

Kelly, M.T. (1982). Effect of temperature and salinity on Vibrio (Beneckea) vulnificus occurrence in a Gulf Coast environment. Appl. Environ. Microbiol. 44, 820–824.

Kibbe, W.A. (2007). OligoCalc: an online oligonucleotide properties calculator. Nucleic Acids Res. 35, W43-46.

Kumar, S., Stecher, G., Li, M., Knyaz, C., and Tamura, K. (2018). MEGA X: Molecular Evolutionary Genetics Analysis across Computing Platforms. Mol. Biol. Evol. 35, 1547–1549.

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McCarthy, S.A., DePaola, A., Cook, D.W., Kaysner, C.A., and Hill, W.E. (1999). Evaluation of alkaline phosphatase- and digoxigenin-labelled probes for detection of the thermolabile hemolysin (tlh) gene of Vibrio parahaemolyticus. Lett. Appl. Microbiol. 28, 66–70.

Murrell, M.C., Caffrey, J.M., Marcovich, D.T., Beck, M.W., Jarvis, B.M., and Hagy, J.D. (2018). Seasonal Oxygen Dynamics in a Warm Temperate Estuary: Effects of Hydrologic Variability on Measurements of Primary Production, Respiration, and Net Metabolism | SpringerLink. Estuaries Coasts 41, 690–707.

Nishibuchi, M., Khaemonee‐iam, V., Honda, T., Kaper, J.B., and Miwatani, T. (1990). Comparative analysis of the hemolysin genes of Vibrio cholerae non-01, V. mimicus, and V. hollisae that are similar to the tdh gene of V. parahaemolyticus. FEMS Microbiol. Lett. 67, 251–256.

Nordstrom, J.L., Vickery, M.C.L., Blackstone, G.M., Murray, S.L., and DePaola, A. (2007). Development of a Multiplex Real-Time PCR Assay with an Internal Amplification Control for the Detection of Total and Pathogenic Vibrio parahaemolyticus Bacteria in Oysters. Appl. Environ. Microbiol. 73, 5840–5847.

Panicker, G., Myers, M.L., and Bej, A.K. (2004). Rapid detection of Vibrio vulnificus in shellfish and Gulf of Mexico water by real-time PCR. Appl. Environ. Microbiol. 70, 498–507.

Paranjpye, R.N., Johnson, A.B., Baxter, A.E., and Strom, M.S. (2007). Role of Type IV Pilins in Persistence of Vibrio vulnificus in Crassostrea virginica Oysters. Appl. Environ. Microbiol. 73, 5041– 5044.

Randa, M.A., Polz, M.F., and Lim, E. (2004). Effects of Temperature and Salinity on Vibrio vulnificus Population Dynamics as Assessed by Quantitative PCR. Appl. Environ. Microbiol. 70, 5469–5476.

Rigney, Z., Santovenia, M., Griswold, T., and Batra, D. (2019). CDC Pathogenic Clinical Isolates Genomes: Bioproject PRJNA266293 https://www.ncbi.nlm.nih.gov/bioproject/PRJNA266293.

Rosche, T.M., Yano, Y., and Oliver, J.D. (2005). A rapid and simple PCR analysis indicates there are two subgroups of Vibrio vulnificus which correlate with clinical or environmental isolation. Microbiol. Immunol. 49, 381–389.

Ruiz-Villalba, A., van Pelt-Verkuil, E., Gunst, Q.D., Ruijter, J.M., and van den Hoff, M.J. (2017). Amplification of nonspecific products in quantitative polymerase chain reactions (qPCR). Biomol. Detect. Quantif. 14, 7–18.

Shen, X., Hou, Y., Su, Y.-C., Liu, C., Oscar, T., and DePaola, A. (2019). Efficacy of Vibrio parahaemolyticus depuration in oysters (Crassostrea gigas). Food Microbiol. 79, 35–40.

Staley, C., Chase, E., and Harwood, V.J. (2013). Detection and differentiation of Vibrio vulnificus and V. sinaloensis in water and oysters of a Gulf of Mexico estuary. Environ. Microbiol. 15, 623–633.

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Taniguchi, H., Ohta, H., Ogawa, M., and Mizuguchi, Y. (1985). Cloning and expression in Escherichia coli of Vibrio parahaemolyticus thermostable direct hemolysin and thermolabile hemolysin genes. J. Bacteriol. 162, 510–515.

Vaughan, P.P., Wilson, T., Kamerman, R., Hagy, M.E., McKenna, A., Chen, H., and Jeffrey, W.H. (2016). Photochemical changes in water accommodated fractions of MC252 and surrogate oil created during solar exposure as determined by FT-ICR MS. Mar. Pollut. Bull. 104, 262–268.

Visick, K.L., Foster, J., Doino, J., McFall-Ngai, M., and Ruby, E.G. (2000). Vibrio fischeri lux Genes Play an Important Role in Colonization and Development of the Host Light Organ. J. Bacteriol. 182, 4578–4586.

Waidner, L.A., and Kirchman, D.L. (2005). Aerobic anoxygenic photosynthesis genes and operons in uncultured bacteria in the Delaware River. Environ. Microbiol. 7, 1896–1908.

Waidner, L.A., and Kirchman, D.L. (2008). Diversity and Distribution of Ecotypes of the Aerobic Anoxygenic Phototrophy Gene pufM in the Delaware Estuary. Appl. Environ. Microbiol. 74, 4012–4021.

Waidner, L.A., Jeffrey, W.H., and Caffrey, J.M. (2020). Technical report summarizing results from winter 2020 sampling: Escambia County 2020 Aquatic Bacteria Survey, Vibrio Assessment (Pensacola, FL.: University of West Florida).

Yeung, M., and Thorsen, T. (2016). Development of a More Sensitive and Specific Chromogenic Agar Medium for the Detection of Vibrio parahaemolyticus and Other Vibrio Species. J. Vis. Exp. JoVE.

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DETAILED AND ITEMIZED BUDGET

Supplies The itemized supplies, boat fuel, and other charges, with current UWF contract pricing and quantities requested, is in Table 4. In Fall 2020 and early Spring 2021, we will collect samples from 12 of our previously surveyed locations (accessible by boat only) and from 12 of the Bream Fisherman’s Association “Project Oyster Pensacola” locations (all accessible from land). In the field, we collect and process water for water quality analyses (Chl a, TSS, dissolved and total nutrients). Determining nutrients and chlorophyll a concentrations requires the use of standards in spectrophotometric or fluorometric analyses ($9.50/sample). Total Kjeldahl Nitrogen and Total Phosphorous are processed at the UWF Wetlands Research Laboratory, a FL-state-certified lab ($25.00/sample for TKN+TP; $12.50/sample for TKN). At selected sites, water is also processed for DNA and culturable Vibrio abundances. Culturable Vibrio will be determined for only selected samples from water, sediments, oyster liquors and biofilms. Selected colonies will be subjected to end-point PCR and subsequent Sanger sequencing to determine gene sequences and improved qPCR primer design. Sediments are collected and preserved for DNA, water content, grain size, and in selected sites, Vibrio counts. DNA will be preserved from all liquors and biofilms from animals collected from water sites (n=12 each season) and POP sites (n=12 each season). In the field, water is fixed with 4% glutaraldehyde to determine total bacteria, via direct counts. At the lab, we filter this fixed whole water onto black etched polycarbonate filters (0.22-micron, 25 mm) for epifluorescence microscopy to enumerate total prokaryotes and to determine average bacterial cell sizes (Kirchman et al., 1985). For DNA analyses from water samples, total bacterioplankton are captured on 0.22-micron 25 mm Durapore filters. For DNA analyses of sediments, oyster liquors, and oyster biofilms, samples are preserved in the field in phosphate-buffered saline. DNA analyses are performed by extraction of total nucleic acids using bead beating, enzyme digestion with Lysozyme, Proteinase K, RNAse A, and columns and other reagents (ThermoFisher GeneJet). All DNA extractions are quantified via spectrophotometry. Prior to quantitative PCR (qPCR), we assess selected samples’ DNA quality using end-point PCR, which will also be subjected to gene cloning (TOPO™ TA Cloning) and subsequent Sanger sequencing for gene diversity analyses and new qPCR primer design. End-point PCR analysis requires the use of Taq DNA polymerase. Quantitative PCR (qPCR) is used to enumerate pathogenic V.v. (vvhA and/or other genes) and V.p. (trh, tdh, tlh, and/or other genes). Quantitative PCR primers for colonization and/or retention of Vibrio in oyster tissues or biofilms will also be evaluated. All DNA extraction, end-point PCR, and qPCR methods require the use of disposable plastic materials, including barrier pipette tips, microcentrifuge tubes, and screw-cap microcentrifuge tubes.

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Table 4. Detailed budget for supplies, reagents, and other consumable items. Year 1 (Sept 2020 to Category and Details Aug 2021) Other Details and Comments Consumables (plasticware, standards, reagents) Consumables other than DNA extraction & qPCR cost per # item requested Invitrogen™ TOPO™ TA Cloning™, with One Shot™ TOP10 cells, 25 reactions $558.90 2 $1,117.80 Taq DNA Polymerase, 1 U/µL, 500 units $109.86 2 $ 219.72 Whatman™ Binder-Free Glass Microfiber Filters GF/F Circles (for TSS). Pack of 100 $129.74 1 $ 129.74 EMD Millipore™ Durapore™ PVDF Membrane Filters: 0.22µ Pore Size $95.87 2 $ 191.74 Barrier pipette tips, 1.0 mL $44.72 3 $ 134.16 Barrier pipette tips, 20-200 uL $39.02 3 $ 117.06 Barrier pipette tips, 2-20 uL $87.15 3 $ 261.45 Barrier pipette tips, 0.1-10 uL $44.92 3 $ 134.76 1.5 mL microcentrifuge tubes $43.33 3 $ 129.99 2.0 mL screw-cap tubes for bead beater $62.11 3 $ 186.33 subtotal $2,622.75 CHROMagar plate media, 5-L size bottle $ 250 Total volume needed = 4,325 mL for 173 plates Total anticipated 720 runs needed. Cost per plate of 96 reactions is Sequencing costs $400.00 7.5 $3,000.00 $400 (GeneWiz). Total number anticipated is 7.5 plates. DNA extraction and qPCR costs (ThermoFisher GeneJet extraction and associated enzymes, Forward and Reverse Primers, Non- Cost per reaction $7.06 per sample, including all associated NTC skirted 96-well PCR plates, and PowerUp SYBR and standard curve wells run on each plate. Includes cost per DNA MM, #A25742) $7.06 sample extraction, new oligonucleotide orders, and qPCR reagent per rxn 753 rxns $ 5,317.38 mixes and consumable plasticware. Total 753 reactions anticipated. Subtotal, all consumables $ 11,190.13

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Y1 (Sept 2020 Table 4., ctd. Category and Details - Aug 2021) Other Details and Comments Travel Mileage Miles $ 0.45 Travel to local sites (putting in small vessel, or to POP land sites Local travel 500 $ 223 where homeowners maintain and monitor oyster farms) Travel to meetings -- N/A $ - subtotal, travel $ 223 Travel category is simply for University Van fuel and mileage.

Equipment -- N/A $ - No equipment will be purchased.

cost per Other Costs trip # trips *Three boat trips total for each of 2 sampling seasons in 1 year. Will not be charged to this budget, as boat costs are paid by UWF (match) Not Biology Department for graduate student thesis work. These charged charges are included in the MATCH portion Boat rental charges* $250 6 $1,500 (see below, and Table 5).

Boat fuel $ 50 6 $ 300 cost per # sample samples WQ Analytical charges: Nutrients, WRL ($25 per sample for TKN+TP) + in-house $ 34.50 TSS and nutrient analyses ($9.50/sample) 48 $ 1,656 24 water samples total: 12 in fall; 12 in early spring. Subtotal, Other Costs $ 1,956

Total Supplies and Other Costs Budget $ 13,369.63

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BUDGET OVERVIEW. The overall budget is shown below, Table 5. Total requested funds $73,206 includes salaries (+fringe) for faculty, staff, graduate and undergraduate students. This total also includes all supplies listed above (Table 4) and other direct costs listed below. The total match funds, $53,038, is 72.4% of the total requested funds. Table 5. Total budget, including requested funds $73,207 and match funds $53,038. GRANT FUNDS UNIVERSITY MATCHING FUNDS Senior Personnel Salary Fringe Total Senior Personnel Salary Fringe Total PI L. Waidner (1 month summer) $7,788 $1,558 $9,346 PI L. Waidner (1 month) $7,788 $1,558 $9,346 Co-PI W. Jeffrey (0.25 month) $3,599 $1,008 $4,607 Co-PI W. Jeffrey (0.75 month) $10,797 $3,023.16 $13,820 Co-PI J. Caffrey (1 month summer) $9,243 $1,849 $11,092 Sub-Total $20,630 $4,415 $25,045 Sub-Total $23,166 Other Personnel Graduate student (0.5 FTE) $18,324 $852 $19,176 Graduate Student (0.167 FTE) $6,123 $285 $6,408 Undergraduate Student $1,700 $79 $1,779 Nine Henriksson $1,360 $63 $1,423 Sub-Total $27,507 $1,279 $28,786 Total Personnel $53,831

Materials & Supplies $13,369 University Boat Usage $1,500

Publication Costs $2,000 Total Direct Costs $73,207 MTDC Exempt Costs $4,007 Graduate Student Tuition & Fees $4,007 TMTDC Base $69,199 TOTAL DIRECT COSTS $73,207 HHS Approved F&A Rate 41% $28,372 Indirect costs Charged $0 Unrecovered F&A $28,372 TOTAL GRANT BUDGET $73,207 TOTAL UNIVERSITY MATCH $53,038 Salaries and In-kind (match) salaries The Principal Investigator/Project Director for UWF, Dr. Lisa Waidner, is budgeted for 1.0 person months. Time for project activities (1.0 match person month) during academic year will be part of University work assignment at no cost, but is included in the MATCH portion of the budget. The Co-project director, Dr. Wade Jeffrey, is budgeted for 0.25 person months annually, 4.20% FTE on a 12- month contract period. An additional 0.75 month of Dr. Jeffrey’s time is applied to the MATCH portion of the budget. The Co-project director, Dr. Jane Caffrey, is budgeted for 1.0 month. Caffrey’s additional activities in the academic year will be part of the University work assignment at no cost.

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Graduate Student Research Assistants: A total of 2 Graduate Student Research Assistants are requested. Graduate student #1 (Waidner’s student) will commit 100% of her University job assignment time (20 hr/wk) to this project. The second graduate student (Caffrey’s student) will commit 1/3 time (6.67 hr/wk) on nutrient and TSS sample processing and analyses. All graduate students are paid at an hourly rate of $17/hr. The graduate research assistants will be responsible for completion of specific projects as portions of the overall research plan, leading to a publication, in addition to fulfillment of the M.S. degree requirements in the Department of Biology.

Undergraduate Student Research Assistants: A total of 1 undergraduate student assistant is requested. An hourly rate of $ 10/hr x 10 hours/wk x 17 weeks (Fall 2020 semester).

Boat staff, Ms. Nine Henriksson, will serve as field coordinator and boat captain, compensated for 2 weeks each sampling season, total 4 weeks, 20 hr/week, at $17/hr.

FRINGE BENEFITS Fringe benefits and payroll taxes such as Workman's Compensation and FICA are calculated based on the University's fringe benefit analysis percentage applicable to salary rate as referenced in HHS Approved Cost-Rate Agreement are included for all salaried positions in each year. Hourly rate employees are calculated at 4.65% including costs for a FICA Alternative Plan and Unemployment and Worker’s Compensation insurance. A copy of this rate analysis is available upon request. Graduate Student Tuition: $4,007 is requested to support two graduate student research assistants (full support for graduate student #1 and 1/3 support for graduate student #2). Table 5. Total budget, including requested funds $73,206 and match funds $53,038. Other Direct Costs 1. Materials and Supplies: Materials and supplies are detailed above in Table 4. 2. Publication Costs: $2,000 is requested in year1 for publication charges to non-open-access journals, such as Aquatic Microbial Ecology, Limnology and Oceanography, Applied and Environmental Microbiology, and Environmental Microbiology. 3. Other: Boat time and fuel. 6 total days boat time is requested using University of West Florida vessels at $250 per day (exclusive of fuel) per trip. Boat fuel per trip is approximately $50. Boat rental charges will not be applied to this budget as these are provided by the Biology Department in support of Waidner’s graduate student thesis work (See Table 4) and are included in the University Match portion of the budget (Table 5).

Equipment (over $5,000): Not Applicable. General Office Supplies: Not Applicable. ADP/Computer Services: Not Applicable.

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Consultant Services: Not Applicable. Subcontracts: Not Applicable. Consultant Services: Not Applicable.

MATCH (IN-KIND) One (1) month of PI salary and 0.75 month co-PI Jeffrey salary will serve as match. Additional match funds will come from uncharged boat rental fees ($1500). Finally, as this funding mechanism does not support overhead costs, the unrecovered F&A (41% as per HHS current rate) will also be applied to the match funds total (pers. comm., Keith Skiles). The total match funds, $53,038, is 72.4% of the total requested funds.

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APPENDIX REFERENCES Three references demonstrating similar work for others: Drs. Caffrey, Jeffrey, and Waidner have successfully completed the winter sampling and early data analyses for the Vibrio survey of Escambia County waterways. The Escambia County Contract, Winter 2020 Report is in the following Appendix: EsCoVibrio Winter Report_law033120.pdf Drs. Caffrey’s graduate student, Kendra Babcock, has recently published a transformative paper on the use of the well-established water quality analyses regularly performed in the Caffrey lab, and how these analyses support a new understanding of early settlers of artificial reefs. Ms. Babcock’s paper is in the following Appendix: Babcock et al 2020 (AR invert biogeochemistry).pdf Dr. Waidner established the workflow described above while developing new primers to enumerate previously-uncharacterized groups of bacteria. The original paper and supplemental material are in the following Appendices: Waidner-Kirchman2008.pdf And Waidner2008_Supplement.pdf

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APPENDIX PROJECT TEAM STAFFING Include biographies and relevant experience of key staff and management personnel. Describe the qualifications and relevant experience of the types of staff that would be assigned to this project by providing biographies for those staff members. Describe bonding process and coverage levels of employees. Affirm that no employees working on the engagement have ever been convicted of a felony.

For Management Personnel, please see below Biosketch-format CV’s of Dr. Jane Caffrey, Dr. Wade Jeffrey, and Dr. Lisa Waidner. Additionally, management will work with Bream Fisherman Association President, Ms. Barbara Albrecht, whose role will be to continue to coordinate between UWF personnel and management and the regional homeowners participating in Project Oyster Pensacola: https://nwdistrict.ifas.ufl.edu/nat/2019/04/18/exploring-with-oyster-cultivation/ Biography: Ms. Barbara Albrecht has 30 years of experience with local watershed and environmental issues. She is actively engaged with citizen science programs and has served as an advocate for many communities as they address local environmental concerns. She has a long history of working with University faculty and students and is currently the Coastal Communities Coordinator for the Reubin O’D. Askew Institute for Multidisciplinary Studies (AIMS) at UWF. Her knowledge of the local environment is extensive and she sees issues from a multidisciplinary perspective (e.g., science, archeology, engineering, the arts), meeting the objectives of AIMS. Since 2011, Barbara has led the Bream Fishermen Association, a citizen water quality monitoring and watchdog group established in the late 1960s during a time when fish kills were common and measured in square miles. She is also the director of the Panhandle Watershed Alliance, which collaborates between six contiguous interstate watersheds (NW-FL and S-AL) that flow into four northwest FL bays. Through the activities of citizens and groups such as Audubon and the Native Plant Society and this organization, she hopes to bring appreciation, awareness, conservation, low impact restoration, and appropriate management to local area waters and all the user groups. Barbara earned a B.S. in Marine Biology from the University of West Florida in 1987.

Key staff will also include: OPS staff member (UWF CEDB) Ms. Nine Henriksson: Biography: Ms. Nine Henriksson earned an M.S. in Biology at UWF under the direction of Dr. Wade Jeffrey. She is a certified dive master, regularly performs marine field technical support for UWF CEDB faculty, and has recently obtained her Florida Boat Captain’s license. She will be responsible for preparing boat and field equipment and for the safety of all faculty and students in the field during boat sampling events.

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Two graduate students (M.S. level): Under the direction of Dr. Jane Caffrey and Dr. Lisa Waidner: Mackenzie Rothfus and Trupti Potdukhe. Their responsibilities will include field sampling, preparation of materials for lab analyses, and laboratory sample processing. Both Rothfus and Potdukhe have been trained in the Caffrey and Waidner lab techniques, in particular in all water quality analyses (Caffrey lab), DNA extractions, DNA concentration determination, and PCR (Waidner lab). Two undergraduate students (B.S. level): Will be supervised directly by Drs. Wade Jeffrey, Jane Caffrey, and/or Lisa Waidner. Responsibilities will be limited to reagent and microbiological media aliquoting, tube labelling, and preparation/cleaning of field equipment.

UWF Hiring and Training Practices (applicable to all faculty, staff, and students listed above): All faculty, staff, and students hired by the University are pre-screened and subjected to background screening, verification of U.S. citizenship, and various immediate training, including but not limited to Information Security. Examples of required training that are relevant to this proposal: Employees are required to complete the following training modules upon being hired by UWF: Checkpoint: Data Security & Privacy (EDU) Knowledge Worker Skills Assessment Statement of Understanding Regarding Confidentiality Certified Knowledge Workers (VGRP) These trainings must be repeated on a regular basis to ensure sustained employment.

Faculty and staff hiring procedures: https://uwf.edu/offices/human-resources/i-am-a/supervisor/employment/staff-employment/ Student hiring procedures: https://uwf.edu/offices/human-resources/i-am-a/supervisor/employment/student-employment/

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Jane M. Caffrey Professor University of West Florida 11000 University Parkway Pensacola, FL 32514 850-857-6089, 850-474-3130, [email protected]

A. Professional Preparation: Cornell University, Ithaca, NY Biology. A.B. 1981. Louisiana State University, Baton Rouge, LA Marine Science. M.S. 1983. University of Maryland, College Park, MD Marine Environmental and Estuarine Studies Program. Ph.D. 1989. Horn Point Environmental Laboratories, University of Maryland. Estuarine Ecology Post- Doctoral Research Associate. 1990. Dept. of Ecology & Genetics. Univ. of Aarhus. Denmark. Estuarine Ecology. Fulbright scholar. 1990-1991. Water Resources Division. U.S. Geological Survey. Menlo Park, CA. Estuarine Ecology Post- Doctoral Research Associate. 1991-1993.

B. Appointments: Professor. Center for Environmental Diagnostics and Bioremediation. University of West Florida. Since August 2014 Associate Professor. Center for Environmental Diagnostics and Bioremediation. University of West Florida. May 2008 – August 2014 Research Assistant Professor. Center for Environmental Diagnostics and Bioremediation. University of West Florida. 1999 – May 2008 Research Oceanographer. Institute of Marine Science. University of California, Santa Cruz. June 1995-June 2003. Research Coordinator. Elkhorn Slough National Estuarine Research Reserve. December 1995- December 1998. Oceanographer. Water Resources Division. U.S. Geological Survey. June 1993 - June 1995. Adjunct Faculty. Department of Oceanography. Florida State University. Summer 1994.

C. Publications

Related: 1. Babcock, K.K., F. Cesbron, W.F. Patterson III, S. B Garner, L.A. Waidner, and J.M. Caffrey. 2020. Changing biogeochemistry and invertebrate community composition at newly deployed artificial reefs in the Northeast Gulf of Mexico. Estuaries and Coasts. DOI: 10.1007/s12237-020-00713-4 2. Cesbron, F., M.C. Murrell, M.E. Hagy, W.H. Jeffrey, W.F. Patterson III and J.M. Caffrey. 2019. Patterns in phytoplankton and benthic production on the shallow continental shelf in the Northeastern Gulf of Mexico. doi.org/10.1016/j.csr.2019.04.003. Continental Shelf Research 179:105-114

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3. Murrell, M.C., J.M. Caffrey, D.T. Marcovich, M.W. Beck, B.M. Jarvis, J.D. Hagy III. 2018. Seasonal oxygen dynamics in a warm temperate estuary: effects of hydrologic variability on measurements of primary production, respiration, and net metabolism. Estuaries and Coasts 41:690-707. DOI 10.1007/s12237-0328-9. 4. Caffrey, J.M., J.T. Hollibaugh, B. Mortazavi. 2016. Living oysters and their shells as sites of nitrification and denitrification. Marine Pollution Bulletin. 112:86-90. http://dx.doi.org/10.1016/j.marpolbul.2016.08.038 5. Caffrey, J.M. and M.C. Murrell. 2016. A historical perspective on eutrophication in the Pensacola Bay estuary, FL, USA. pp. 199-213 In P. Glibert and T. Kana (eds). Aquatic Microbial Ecology and Biogeochemistry: A Dual Perspective. Invited book chapter.

Other Significant: 1. Caffrey, J.M., M.C. Murrell, K.R.S Amacker, J. Harper, S. Phipps, and M. Woodrey. 2014 Sustained observations of estuarine metabolism in 3 estuaries in the northeast Gulf of Mexico. Estuaries and Coasts invited Special Issue, “Drivers of Change in Shallow Coastal Photic Systems" 37: 222-241. http://dx.doi.org/10.1007/s12237-013-9701-5 2. Yvon-Durocher, G., J. M. Caffrey, A. Cescatti, M. Dossena, P. del Giorgio, J.M. Gasol, J.M. Montoya, J. Pumpanen, P.A. Staehr, M. Trimmer, G. Woodward & A.P. Allen. 2012. Reconciling differences in the temperature-dependence of ecosystem respiration across time scales and ecosystem types. Nature 487: 472-476. 3. Murrell, M.C., J.G. Campbell, J.D Hagy III, and J.M. Caffrey. 2009. Effects of irradiance on benthic and water column processes in a Gulf of Mexico estuary: Pensacola Bay, Florida, USA. Estuarine Coastal and Shelf Science.81:501-512. 4. Caffrey, J.M. and W.M. Kemp. 1990. Nitrogen cycling in sediments with submerged macrophytes: Microbial transformations and inorganic pools associated with estuarine populations of Potamogeton perfoliatus L. and Zostera marina. Marine Ecology - Progress Series. 66:147-160. 5. Kemp, W.M., P. Sampou, J. Caffrey, M. Mayer, K. Henriksen and W.R. Boynton. 1990. Ammonium recycling versus denitrification in Chesapeake Bay sediments. Limnology and Oceanography 35:1545-1563.

D. Synergistic Activities: 1. Review Panel for the NOAA Science Collaborative RFP. April 2018 2. Member National Water Quality Monitoring Council since 2004. NWQMC is a subgroup of the Advisory Committee on Water Information and improves methods, assessment and collaboration on water quality issues. 3. Development of Citizen Science activities with County Sea Grant extension and the Bream Fisherman Association, a local volunteer monitoring organization (2017-2019) 4. Oral session co-chair for Coastal and Estuarine Research Federation 2019 conference in Mobile AL 5. Member of San Francisco Estuary Institute Biogeochemistry Expert Working Group (2019)

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WADE H. JEFFREY Distinguished University Professor

Director; Center for Environmental Diagnostics & Bioremediation (850) 474-2472 University of West Florida (850) 474-3130 (FAX) Bldg 58, 11000 University Parkway Email: [email protected] Pensacola, FL 32514 http://uwf.edu/wjeffrey

(a) Professional Preparation Virginia Polytechnic Institute & State University B.S. Biology 1981 University of South Florida M.S. Marine Science 1985 University of South Florida Ph.D. Marine Science 1989 U.S.EPA, Gulf Breeze, FL. NRC-Post Doc Bacterial Genetics 1989-91

(b) Academic Appointments 2017-present. Distinguished University Professor, Director Askew Institute for Multidisciplinary Studies, University of West Florida, Pensacola, FL 2015-present. Director, Center for Environmental Diagnostics and Bioremediation, University of West Florida, Pensacola, FL 2006-present. Professor, Center for Environmental Diagnostics and Bioremediation, Department of Biology. University of West Florida, Pensacola, FL 2000-2006. Associate Professor, Center for Environmental Diagnostics and Bioremediation, Department of Biology, University of West Florida, Pensacola, FL 1997–2000. Assistant Professor, Center for Environmental Diagnostics and Bioremediation, Department of Biology, University of West Florida, Pensacola, FL 1991-1997. Research Assistant Professor, Center for Environmental Diagnostics and Bioremediation. University of West Florida, Pensacola, FL

(c) Products ii. MOST CLOSELY RELATED PRODUCTS (1) Cesbron, F., M. Ederington-Hagy, W.H. Jeffrey, M. Murrell, W.F. Patterson III, J.M. Caffrey. Pelagic and benthic coupling in the shallow Northeastern Gulf of Mexico shelf. Continental Shelf Research 179: 105-114.

(2) Moss, J.A., N. Henriksson, J.D. Pakulski, R.A. Snyder, and W.H. Jeffrey. 2019. Oceanic microplankton do not adhere to the latitudinal diversity gradient. Microbial Ecology doi.org/10.1007/s00248-019-01413-8

(3) Moss, J.A., C. McCurry, P. Schwing, W.H. Jeffrey, I.C. Romero, D.J. Hollander, and R.A. Snyder. 2016. Molecular characterization of benthic foraminifera communities from the Northeastern Gulf of Mexico shelf and slope following the Deepwater Horizon Event. Deep Sea Research I 115: 1-9.

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(4) Cherrier, J., S. Valentine, B, Hamill, W.H. Jeffrey, and J.F. Marra. 2015. Light-mediated release of dissolved organic carbon by phytoplankton: implications for carbon cycling. Journal of Marine Systems 147: 45-51. DOI: 10.1016/j.jmarsys.2014.02.008.

(5) Nienow, J.A., R.A. Snyder, W.H. Jeffrey, and S. Wise, Jr. 2016. Fine Structure and ecology of Nanoneis longta in the northeastern Gulf of Mexico with a revised definition of the species. Diatom Research 32:43-58. doi.org/10.1080/0269249X.2016.1268978. ii. OTHER SIGNIFICANT PRODUCTS 1. Aas, P., M. M. Lyons, R. J. Pledger , D.L. Mitchell, and W.H. Jeffrey. 1996. Inhibition of Bacterial Activities by Solar Radiation in Nearshore Waters and the Gulf of Mexico. Aquat. Microb. Ecol. 11: 229-238.

2. Jeffrey, W.H., R.J. Pledger, P. Aas, S. Hager, R.B. Coffin, R. Von Haven, and D.L. Mitchell. 1996. Diel and depth profiles of DNA photodamage in bacterioplankton exposed to ambient solar ultraviolet radiation. Mar. Ecol. Progr. Ser. 137: 293-304.

3. Baldwin, A.J., J.A. Moss, J.D. Pakulski, P. Catala. F. Joux, W.H. Jeffrey. 2005. Microbial diversity in a Pacific Ocean transect from the Arctic to Antarctic circles. Aquat. Microb. Ecol. 41: 91-102.

4. Horak, R.E.A., W. Qin, A. Bertagnolli, A. Nelson, K. Heal, H. Han, M. Heller, A. Schauer, W.H. Jeffrey, E.V. Armbrust, J.W. Moffett, A.E. Ingalls, D.A. Stahl, and A.H. Devol. 2017. Influence of light and temperature upon ammonia oxidation activity in marine Thaumarchaeota in the North Pacific Ocean. Limnology and Oceanography doi:10.1002/lno.10665

5. Pérez, V., M. Hengst, L. Kurte, C. Dorador, W.H. Jeffrey, R. Wattiez, S. Matallana-Surget. 2017. Adaptation to Extreme UV Radiation: A comparative proteomics study of Rhodobacter sp, isolated from high altitude wetlands in Chile. Frontiers in Microbiology. 8:1173 doi: 10.3389/fmicb.2017.01173.

(d) Synergistic Activities

1. Director of the Ruebin O’D. Askew Institute for Multidisciplinary Studies at the University of West Florida, a newly created Center with an emphasis on STEAM driven research, problem solving, and education

2. Design and production of Extremophiles, a Photographic exhibition of extreme environments and their sensitivity to human activities

3. Participation in BIOSCOPES/ Florida Center for Research in Science, Technology, Engineering & Mathematics (FCR-STEM) Earth Science Institute to work with 6-12 science teachers to provide professional development in Life, Earth and Space, and Physical Sciences

4. Email correspondence with K-12 schools from Antarctica, maintain a blog with local newspaper while deployed, guest lectures and discussions with local grade and high schools. Mentor Science Fair and/or Internationale Baccalaureate Programme Projects every year

5. Associate Editor, Limnology and Oceanography (2004 – 2016).

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Lisa Anne Waidner Assistant Professor 11000 University Parkway, Building 58, Room 62i, Pensacola FL 32514 Office phone: 850.474.3386 Mobile phone: 301.509.8966 [email protected]

(a) Professional Preparation University of Maryland Baltimore, MD Biological Sciences B.S., 1991 Baltimore County University of Maryland Baltimore, MD Applied Molecular Biology M.S., 1993 University of Delaware Lewes, DE Marine Biosciences Ph.D., 2007 Delaware Newark, DE Postdoctoral in microbial physiology: 2007-2008 Biotechnology Institute Chlorobium (Chlorobaculum) genetics (post-doc) University of Delaware Newark, DE USDA Postdoctoral Fellow: 2008-2010 MicroRNAs of Herpesviruses (post-doc)

(b) Appointments 2018 –Assistant Professor, Center for Environmental Diagnostics and Bioremediation, and Biology Department, University of West Florida. Pensacola, FL. 2016 – Research Assistant Professor, Center for Environmental Diagnostics and Bioremediation, and Biology Department, University of West Florida. Pensacola, FL. 2014- Research Associate / Molecular Biologist, BHO Technology, LLC. Baton Rouge, LA 2012-Consultant and Postdoctoral Researcher, University of Delaware and H2OPE Biofuels, LLC. Lewes, DE and Greenwood Village, CO. 2010-Principal Research Associate, Elcriton, Inc. Newark, DE and New Castle, DE. 2001-Research Assistant, Ph.D. student, University of Delaware. Lewes, DE. 1995-2000-Staff Associate and Supervisor, Technical Services, Life Technologies, Inc. Rockville, MD. 1992-1995-Research Assistant, University of Maryland, Biochemistry. Baltimore, MD.

(c) Products Five publications/products most closely related to the proposed project Babcock, K.K., Cesbron, F., Patterson, W.F., Garner, S.B., Waidner, L.A., and Caffrey, J.M. (2020). Changing Biogeochemistry and Invertebrate Community Composition at Newly Deployed Artificial Reefs in the Northeast Gulf of Mexico. Estuaries Coasts 43, 680–692. Madeira, C.L., Jog, K.V., Vanover, E.T., Brooks, M.D., Taylor, D.K., Sierra-Alvarez, R., Waidner, L.A., Spain, J.C., Krzmarzick, M.J., and Field, J.A. (2019). Microbial Enrichment Culture Responsible for the Complete Oxidative Biodegradation of 3-Amino-1,2,4-triazol-5-one (ATO), the Reduced Daughter Product of the Insensitive Munitions Compound 3-Nitro-1,2,4-triazol-5-one (NTO). Environ. Sci. Technol. 53, 12648–12656.

Palatucci, M.L., Waidner, L.A., Mack, E.E., and Spain, J.C. (2019). Aerobic biodegradation of 2,3- and 3,4-dichloronitrobenzene. Journal of Hazardous Materials. 378, 120717.

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Plummer, M., Plummer, S.M., Merkel, P.A., Hagen, M., Biddle, J.F., and L.A. Waidner. (2016) Using directed evolution to improve hydrogen production in chimeric hydrogenases from Clostridia species. Enzyme and Microbial Technology. 93, 132–141. Jamindar, S., Polson, S.W., Srinivasiah, S., Waidner, L.A., and Wommack, K.E. (2012). Evaluation of two approaches for assessing the genetic similarity of virioplankton populations as defined by genome size. Applied and Environmental Microbiology. 78,8773-8783. Five other significant publications/products: Schab, C.M., Park, S., Waidner, L.A., and Epifanio, C.E. (2013). Return of the Native: Historical Comparison of Invasive and Indigenous Crab Populations near the Mouth of Delaware Bay. Journal of Shellfish Research. 32, 751–758. Waidner, L.A., Burnside, J., Anderson, A.S., Bernberg, E.L., German, M.A., Meyers, B.C., Green, P.J., and Morgan, R.W. (2011). A microRNA of infectious laryngotracheitis virus can downregulate and direct cleavage of ICP4 mRNA. Virology. 411, 25–31. Waidner, L.A., and Kirchman, D.L. 2008. Diversity and distribution of ecotypes of the aerobic anoxygenic phototrophy gene, pufM, in the Delaware estuary. Applied and Environmental Microbiology. 74, 4012-4021. Waidner, L.A., and Kirchman, D.L. (2007). Aerobic anoxygenic phototrophic bacteria attached to particles in turbid waters of the Delaware and Chesapeake estuaries. Applied and Environmental Microbiology. 73, 3936–3944. Waidner, L.A., and Kirchman, D.L. (2005). Aerobic anoxygenic photosynthesis genes and operons in uncultured bacteria in the Delaware River. Environmental Microbiology. 7, 1896–1908.

(d) Synergistic Activities

 Served as ad hoc reviewer, 2 proposals, for NSF Biological Oceanography (2019)  Serve as a core faculty member, NSF CURE integration into Genetics Laboratory and Cell Biology Laboratory (PI’s, Chung and Cavnar). Developing new curriculum, improving methods, and training of graduate student TAs in current molecular techniques (Genetics, Molecular Biology Lab courses). Summer 2019, participated in first UWF CURE Bio-CORE workshop.  Served as event coordinator: Wrote exams, coordinated the regional ECOLOGY event for Northwest Florida Science Olympiad. Coordinated and graded exams from 5 teams of Middle School students and 16 teams of High School students (2018)  Served as scientific consultant: As part of an NSF-funded project, “Editing our Evolution,” leading conversations with religious, medical, and science education leaders at a local science museum, Pensacola MESS Hall, with Megan Pratt. (2018)  Served as lead PI on internal UWF Innovative Interdisciplinary Research project, for combining informal STEM learning with Art. Project title: STEAMing the River to the Gulf: Water Quality Assessments and Communication. (2016-2017) Project Website: http://www.waidnerresearchlab.com/steam-2017.html

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APPENDIX: COMPANY OVERVIEW

 Official registered name: University of West Florida 11000 University Parkway Pensacola, FL 32514 DUNS #:053000709 EIN#: 59-2976783 SIC Code: 8221- Colleges, Universities, and Profession Schools NAICS: 611310

 Key Contact Name: The grant administrator contact is: Elan Travis, CRA Senior Grants Specialist 850-474-2825 [email protected] The prosed technical point of contact (PI) is: Lisa Waidner, Ph.D. Assistant Professor Center for Environmental Diagnostics & Bioremediation University of West Florida Bldg 58; 11000 University Parkway Pensacola, FL 32514 [email protected] Proposed co-PI’s (same address and building as PI): Jane Caffrey, Ph.D., Professor [email protected] Wade Jeffrey, Ph.D., Professor [email protected]

 Person Authorized to contractually bind the organization for any proposal against the RFP Matthew C. Schwartz, Ph.D. Assistant Vice President for Research Administration [email protected]

 Brief history, including year established and number of years your company has been offering Information Security Testing Full (13 pages) document included as an attachment in this email: IT-04.02-11.18 UWF Info Security and Privacy Policy.pdf

 Describe system for identifying conflict of interest. UWF’s website for conflict of interest: https://uwf.edu/offices/human-resources/i-am- a/employee/conflict-of-interest/ (Please let us know if more information is needed.)

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LIST of ADDITIONAL APPENDICES:

IT-04.02-11.18 UWF Info Security and Privacy Policy.pdf EsCoVibrio Winter Report_law033120.pdf Babcock et al 2020 (AR invert biogeochemistry).pdf Waidner-Kirchman2008.pdf Waidner2008_Supplement.pdf

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