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Transcript of Algae For Conversion of Manure Nutrients to Animal Feed: Evaluation Of Advanced Nutritional Value,...
Algae for Conversion of Manure Nutrients to Animal Feed:
Evaluation of advanced nutritional value, toxicity, and zoonotic pathogens
1Shelton Murinda, 2Marcia Murry, 3Gregory Schwartz, 4Trygve Lundquist, 5A. Mark Ibekwe
1Animal and Veterinary Sciences Department, California State Polytechnic University, Pomona, CA.2Biological Sciences Department, California State Polytechnic University, Pomona, CA.
3BioResource and Agricultural Engineering Department, California Polytechnic State University, San Luis Obispo, CA.4Civil & Environmental Engineering Department, California Polytechnic State University, San Luis Obispo, CA.
5USDA Agricultural Research Service, U. S. Salinity Laboratory, Riverside, CA.
INTRODUCTION
Manure disposal is a major concern in concentrated feeding operations (CAFOs), e.g., dairy industry
Microalgae offer great potential for sustainable bioremediation of manure nutrients and wastewaters for production of biofuel, feedstock and bio-products (e.g., nutritional supplements).
GOALS OF PROJECT Collect field data to calibrate growth models for the culture of algae
Maximize the nutritional value of produced algae for animal feed
Optimize pathogen inactivation methods, and
Quantify and control any cyanobacterial (“blue-green algae”) toxins
OVERALL GOAL: Benefit agriculture and the environment by introducing microalgae, as a fast-growing safe, livestock feed crop.
LAGOON LAGOON
Shade Shade
Algae ponds/bio-reactors
(in red rectangle)
BIOREACTORS then
WEEKLY DAILYSecchi disk visibilityAfternoon oxygen and pHWater temperatureSolar radiation Pond colorDLE additionExchange
Dairy Lagoon Effluent (DLE)Total suspended solids (TSS) Volatile suspended solids (VSS) Nitrogen (N): soluble and particulate
Total N, Total Insoluble N Phosphorus (P)Chemical oxygen demand (COD)Algal species identification
Ponds are operated as a semi-continuous culture. Data will be used to develop a predictive model.
DAIRY LAGOON EFFLUENT (DLE) NUTRIENT CHARACTERISTICS
MONITORING NUTRIENT UPTAKE (N & P)
Seasonal Nitrogen Uptake Rates
SOLAR RADIATION DATA
DAILY TEMPERATURE DATA
WEEKLY PRODUCTIVITY
Photobioreactors Used to Simulate Seasonal Light and Temperature Regimes in the lab
SYMBIOTIC NUTRIENT RECOVERY (BACTERIA & ALGAE)
COMPOSITION OF HARVESTED BIOMASS: Feb vs. Sep 2016
% C
hlor
ophy
ll/Bi
omas
s
BIO-REACTOR UNIT OPERATION
• Units were exchanged daily and fed nutrients from DLE
• Controls have no DLE: synthetic fertilizer
• Units with nutrients supplied 100% by DLE, brown in color, have lower overall oxygen concentrations, and lower pH
Identification of Algal Strains: Microscopy and Sequencing
>100 strains isolated from seasonal samples (2014-2016)
Sequenced ITS 4-5 intergenic region of several isolates.
Identified seasonally dominant spp.: Scenedesmus Desmodesmus Chlorella variety of small, unspeciated Chlorophyta
Eustigmatos sp.
Microactinium NannochloropsisMarine Isolate
TetraselminisMarine Isolate Scenedesmus sp.
Sequence Comparisons of ITS 4-5 region of
Ribosomal Genes to identify Pond Isolates
ADVANCED NUTRITION ANALYSIS
Pond isolates cultured to optimize growth rate while also attempting to have the highest value algae composition for feed (i.e.):
DigestibilityCarbohydrates, Lipids, Proteins Fatty acid & amino acid profiles
Sampled in exponential phase and stored (-80ᵒC) for proximate analysis
Fatty Acid Profiles of 9 Algae StrainsFAME Composition FAME Standard PBR1 CP71 PBR2 CP71
PBRa
CP24 PBRb PBR1&2 PBRR PBR1 PBR2a PBR3
C6:0 - - - - - - - - - -
C7:0 - - - - - - - - - -
C8:0 + - - - - - - - - -
C9:0 + - - - - - - - - -
C10:0 + + - + - - + + - -
C11:0 + - - - - - - - - -
C12:0 + + + + + + + + + +
C13:0 + + + + + + + + + +
C14:0 + + + + + + + + + +
C14:1 + - - - - - - - - -
C15:0 + + + + + + + + + +
C16:0 + + + + + + + + + +
C16:1 + - - + - - - - - -
C17:0 + + + + + + + + + +
C17:1 + + + + - - - - - -
C18:0 + + + + + + + + + +
C18:1(Z) + + - + + + + + + -
C18:1 € + + - + - - - - - -
C18:2 + + + - + - + + + -
C18:3 + - - - - + - - - -
C19:0 - - - - - - - - - -
C20:0 + + - - - - + - - +
C20:1 + - - - - - - - - -
C20:2 + - - - - - - - - -
C20:3 + - - - - - - - - -
C20:3 + - - - - - - - - -
C21:0 + - - - - - - - - -
C22:0 + - - - - - - - - -
C22:1 + - - - - - - - - -
C22:2 + - - - - - - - - -
C22:6 + - - - - - - - - -
C23:0 + - - - - - - - - -
C24:0 + - - - - - - - - -
C24:1 + - - - - - - - - -
FAMEs analysis: GC-MS; C6-C24
Quantitation
CYANOBACTERIA DETECTION
Important in monitoring of algae ponds and safety of algae-based feeds
CYANOBACTERIA DETECTION PROTOCOLS
Universal detection of cyanobacteria targeting 16s RNA and rpoC1 gene sequences
Universal detection of cyanobacteria targeting the rpoC1 gene sequence
Gels stained with Midori green
16s RNArpoC1
CELL TOXICITY AND CYANOTOXIN TESTS
• Cell Counters (Abaxis & TC 20 cell counter)
TC 20 >>> Total, Live vs. dead cell countsAbaxis >>> blood cell counts (WBCs/RBCs/Platelets)
• ELISA toxin detection (Abraxis & Beacon kits)
Evaluation of Different DNA Extraction Kits On Bio-reactor Bacterial Community Structures
Mo Bio Power water extraction kitZymo fungi/bacterial extraction kitMP Biomedicals FastDNA spin kit DNA
DNA was extracted from samples for analysis of total bacteria, cyanobacteria and other microalgae (targeting V4 16s rDNA)
Used Illumina MiSeq’s next generating sequencing (NGS) platform [Second Genome - The Microbiome Co., San Francisco, CA].
.
OTU; operational taxonomic unit
Phylum Extraction Kit (%) MP MoBio Zymo
Cyanobacteria 3.78 2.5 2.5 Proteobacteria 38.2 40.9 28.7 ---Beta 6.4 9.5 4.6 ---Alpha 12.6 16.3 11.7 ---Gamma 7.6 9.3 5.8 ---Epsilon 1.01 2.7 1.5 ---Delta 8.4 2.5 4.4 Actinobacteria 3.7 4.9 4.9 Bacteroidetes 15.83 20.1 18.9 Verrucomicrobia 7.8 8.8 8.3 Chloroflexi 1.32 1.6 2.5 Firmicutes 7.76 4.5 9.3 Tenericutes 0.3 0.6 1.1 SR1 0.6 0 0 Acidobacteria 1.7 0.2 0 Chlorobi 0.7 0.6 0.4 Planctomycetes 5.82 1.8 3.7 OD1 2.65 2.2 5.2 Fibrobacteres 0.03 0 0 Gemmatimonadetes 0.1 0.2 0.4 Chlamydiae 0.1 0.2 0.1 Spirochaetes 0.8 0.4 1.1 TM7 0.7 0.2 0.2 GN02 0.1 0.6 0.7 Caldithrix 0.1 0.2 0.1 Thermi 0.1 0 0 NKB19 0.3 0 0.2 Armatimonadetes 0.1 0 0 TM6 0.1 0 0.1 Fusobacteria 0.4 6 0.5 BRC1 1.2 0 0 OP3 0.3 2 1.6 WPS-2 0.3 0 0 LD1 0.1 0.2 0.1 Elusimicrobia 0.1 0.2 0 WWE1 0 1.1 0.8 Lentisphaerae 0 0.6 1.5 Spirochaetes 0 0.4 1.1
Detection of significantly different *OTUs from each DNA extraction kit
*OUT; operational taxonomic unit
CONCLUSIONS
• Good nutrient (N&P) uptake rates were measured. Removal of 75-85% N; greater removal efficiency of P.
• Recommended seasonal HRT‘s: Summer/Fall 2.5-3 days; Spring 4 days, and Winter 6 days
• Confidence to narrow the scope of model parameters that optimize nutrient uptake and productivity to: Temperature, HRT, and DLE addition.
• Isolated, characterized and identified seasonally dominant algae strains for final productivity model development.
FUTURE STUDIES
• Well characterized seasonally dominant algae strains will be cultured in ponds, optimized for biomass productivity, and monitored for safety
• Refine technics for toxin detection to improve reliability of ELISA tests.
• Pathogens will be identified and quantified using PCR (real-time or digital droplet), employing optimized DNA extraction technics.
• Computer software and bioinformatics analyses will facilitate identification of pathogens and non-pathogens (Quantitation and relative abundance).
DISSEMINATION
• Presented at least 20 local, regional and national conferences
• Presented at 3 international conferences (ASM, ABO, ABBB)
• Published 2 book chapters
• Authored 2 book manuscripts (in review)
• Authored 1 journal manuscript (in review)
ACKNOWLEDGEMENTS
• This project was supported by USDA Award # 2013-67019-21374
• Thanks to all the student research assistants, volunteers and interns