Presentation Title

Twelve Ventura County Ocean Microbiomes Reveal Normal and Harmful Microorganisms Present During Harmful Algae Blooms

Faculty Mentor

Dr. James Harber

Start Date

23-11-2019 8:45 AM

End Date

23-11-2019 9:30 AM

Location

48

Session

poster 2

Type of Presentation

Poster

Subject Area

biological_agricultural_sciences

Abstract

A survey of bacterial and algal microbiomes was determined from a transect of twelve shoreline ocean water samples from Ventura county. Understanding the origins of Harmful Algae Blooms (HAB) involves defining the relationship between the predator species (mixotroph algae) and the bacterial microbiome in the environment that generates a competition for resources and sunlight. Toxins are released by HABs causing poisoning of fish, seizures in marine mammals and amnesic/paralytic shellfish poisoning in humans. The hypothesis of this experiment was that a standard DNA isolation from ocean samples collected ove five years and processed by Illumina nexgen sequencing could be used to generate a list of bacteria and algae of indicators of healthy or unhealthy ocean microbiomes. The data returned for bacterial microbiomes indicated that a subset of bacteria is prominent in all samples tested. A different list of bacteria was identified as most prominent species in the twelve samples (Bacillus species, exiguobacterium panipatensis, halomonas venusta, planomicrobium mcmeekinii, pseudidiomarina homiensis and multiple Vibrio species. This new analysis strengthens previous research experiments that showed the prominent Vibrio community to possess a high degree of antibiotic resistance. Additional confirmation this year in two samples was made of Coxiella burnetii (Q fever) bacteria at specific locations on the Ventura county shoreline. The algae microbiome detected points to two contrasting data sets depending on whether the analysis is generated by direct PCR followed by sequencing of the ocean samples vs. Illumina microbiome sequencing. PCR sequencing consistently defines specific algae (such as Pseudo-nitzschia and Lingulodinium polyhedra) which are very rare to detect by Illumina microbiome sequencing. Research by others shows that these mixotroph algae photosynthesize until competition blocks sunlight and scarce resources generate the release of toxins to kill other microoganisms and animals. Fish and bivalve feeding on these contaminated waters concentrates the toxins and results in brain damage in animals and humans. The conclusions of this study are that both PCR and Nextgen sequencing methods used in conjunction can more accurately define the normal microbiome flora of the ocean and document the rare pathogenic bacteria and harmful algae amongst them. Furthermore it is recommended that a third method for assessing antibiotic resistance described in this research be included in the updating of methods (past current assays that only detect acid from lactose) of the ocean microbiome of coastal Ventura County. Automating these prescribed assays for regular detection of variances of the microbiome in an ocean based environmental sample processor remains the overall goal of this project for prediction of when and where Harmful Algae Blooms will occur along the coastline.

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Nov 23rd, 8:45 AM Nov 23rd, 9:30 AM

Twelve Ventura County Ocean Microbiomes Reveal Normal and Harmful Microorganisms Present During Harmful Algae Blooms

48

A survey of bacterial and algal microbiomes was determined from a transect of twelve shoreline ocean water samples from Ventura county. Understanding the origins of Harmful Algae Blooms (HAB) involves defining the relationship between the predator species (mixotroph algae) and the bacterial microbiome in the environment that generates a competition for resources and sunlight. Toxins are released by HABs causing poisoning of fish, seizures in marine mammals and amnesic/paralytic shellfish poisoning in humans. The hypothesis of this experiment was that a standard DNA isolation from ocean samples collected ove five years and processed by Illumina nexgen sequencing could be used to generate a list of bacteria and algae of indicators of healthy or unhealthy ocean microbiomes. The data returned for bacterial microbiomes indicated that a subset of bacteria is prominent in all samples tested. A different list of bacteria was identified as most prominent species in the twelve samples (Bacillus species, exiguobacterium panipatensis, halomonas venusta, planomicrobium mcmeekinii, pseudidiomarina homiensis and multiple Vibrio species. This new analysis strengthens previous research experiments that showed the prominent Vibrio community to possess a high degree of antibiotic resistance. Additional confirmation this year in two samples was made of Coxiella burnetii (Q fever) bacteria at specific locations on the Ventura county shoreline. The algae microbiome detected points to two contrasting data sets depending on whether the analysis is generated by direct PCR followed by sequencing of the ocean samples vs. Illumina microbiome sequencing. PCR sequencing consistently defines specific algae (such as Pseudo-nitzschia and Lingulodinium polyhedra) which are very rare to detect by Illumina microbiome sequencing. Research by others shows that these mixotroph algae photosynthesize until competition blocks sunlight and scarce resources generate the release of toxins to kill other microoganisms and animals. Fish and bivalve feeding on these contaminated waters concentrates the toxins and results in brain damage in animals and humans. The conclusions of this study are that both PCR and Nextgen sequencing methods used in conjunction can more accurately define the normal microbiome flora of the ocean and document the rare pathogenic bacteria and harmful algae amongst them. Furthermore it is recommended that a third method for assessing antibiotic resistance described in this research be included in the updating of methods (past current assays that only detect acid from lactose) of the ocean microbiome of coastal Ventura County. Automating these prescribed assays for regular detection of variances of the microbiome in an ocean based environmental sample processor remains the overall goal of this project for prediction of when and where Harmful Algae Blooms will occur along the coastline.