quarterly report: may 21, 2020 - university of houston

Secure Facilitate Ensure

Quarterly Report: May 21, 2020

2

DNA Assays for Determining Honey Origins

Dr. Richard C. Willson, University of Houston (PI)Dr. Aniko Sabo, Baylor College of Medicine

Dr. Katerina Kourentzi, University of Houston

Other personnel: Dimple Chavan, University of Houston (Graduate student)Suman Nandy, University of Houston (Graduate student)


Project Overview

Project Theme — NOFO Question(s) Addressed:Theme Area 2b Legitimate Trade and Travel- TechnologiesHow can we measure, assess, and predict the impact of technologyon the facilitation of legitimate trade and travel?

Last Work Plan (Revision): January 28, 2020

Project Period:Start Date- 1 February, 2020End Date- 31 January, 2021

3


Project Overview

Goal:

Knowledge Gap Addressed:

4

The main goal of this project is to develop practical means to identify honeycountry of origin using pollen DNA, and the DNA dissolved in filtered honey

Implementation of countervailing duties on honey imported only fromspecific countries requires identification of source countries; attemptedevasion by mislabeling is common

NGS-based DNA approach facilitates exploitation of information from newsamples, both by clustering with known standards and possibly also byexploitation of trace plants limited to particular geographic origins

Novel DNA capture methods also address the problem of filtered-honeysource identification using trace DNA present in filtered honey


Project Overview

Objectives:

5

1) A DNA sequencing and sample-clustering analysis pipeline whichidentifies the origin of the great majority of honey samples based onknown standard samples and ITS2 barcode databases

2) DNA amplification-based RPA analysis methods derived from thesequencing work, capable of accurately identifying a large fraction ofhoneys originating from the People’s Republic of China, with a time-to-result below eight hours

3) Demonstration of purification, PCR amplification and sequencing ofsoluble DNA from filtered, pollen-free honey


Key Activities

6

Project Plan

Months> Feb 2020

Mar 2020

April 2020

May 2020

June 2020

July 2020

August 2020

Sep 2020

Oct 2020

Nov 2020

Dec 2020

Jan 2021

ID Task Title Start End Duration 1 2 3 4 5 6 7 8 9 10 11 12

T.1Meetings with Project

champion; kick-off, 30-days and quarterly reviews

1 12 1, Q1-Q5

T.2 Obtain honey samples 1 6 6

T.3Development of pollen

purification and DNA sample preparation

1 1 1

T.4 Honey pollen DNA sequencing 1 9 9

T.5 Honey plant DNA sequence clustering informatics analysis 1 9 9

T.6 Purification and analysis of soluble DNA from filtered honey 1 11 11

T.7 Curation and detection ofcountry-specific plant barcodes 1 9 9

T.8 RPA amplification assays 2 11 9

T.9 Testing and validation 10 12 2

T.10 Produce report 11 12 1

T.11 Phase I closing meeting 12 12 1


COVID-19 Impacts

• UH was shut down from mid-March• Now reopening at fractional capacity• Working through our inventory of honey

samples (50% of the target number)• Currently unable to obtain more honeys in-

person, limited international mail operation• Predict a delay of 2-3 months in completing

honey sample collection

7


149 samples from 27 countries (including 40 from PRC, 18 from India)

Honey Sample Library

3

1

22

1

13

1

17

2

1 7

4

1

2

1

3

5

3

18

40 3

34

25

1

1

8


Approach and Methodology

9

Objective 1: Pollen DNA sequencing and sample-clustering analysis pipeline

Centrifuge Pollen lysis

gDNA extraction

Removalof PCR inhibitors

PCR ofITS2

Purification of PCR product

Agarose gel

dsDNA quantification

DNA purity

Next-generation sequencing(Genewiz)



10

Objective 1: Pollen DNA sequencing and sample-clustering analysis pipeline

Read raw FASTQ files

Retain paired-end reads thathave 5 nt or less primermismatches

Segregate forward and reverse reads into R1_001 and R2_001 files respectively

Use NGmerge to stitchPE reads at a minimumoverlap of 20 nt with 5or less mismatches

Retain reads passing followingcriteria- a) No ambiguous basesb) Quality score of all bases ≥10c) Cumulative expected error of≤ 3 for merged reads and ≤ 4 forunmerged reads

Perform DADA2 error modeling to infer ASVs

Remove chimeric sequences

Assign Taxa via BLAST

*Bioinformatic analysis was adapted from the DADA2 ITS Pipeline Workflow and the workflow for Microbiome Data Analysis



11

Objective 2: DNA amplification-based RPA analysis methods

― Working towards developing primers for single-country plants of interest

― About to initiate RPA experiments (delayed by COVID-19)



12

Objective 3: Demonstration of purification, PCR amplification and sequencing ofsoluble DNA from filtered, pollen-free honey

Method 1:Anti-dsDNA antibodies coupled to magnetic beads

Method 2:Q Sepharose Anion exchanger (batch mode)

Method 3:Ceramic hydroxyapatite, Type I (batch mode)

Goux H J et al. Front Cell Infect Microbiol., 2018Paterson, N. G., Riboldi-Tunicliffe, A., Mitchell, T. J. and Isaacs, N. W. (2006). Acta Cryst. F62, 672-675. https://www.bio-rad.com/en-us/product/cht-ceramic-hydroxyapatite-type-ii-support?ID=a642d16e-5ca8-4981-acf2-a57271984632


Sequencing progress

13

We have obtained NGS data for pollen DNA isolated from 14honey samples (7 countries), with more in progress

We also have obtained NGS data for soluble DNA capturedfrom the same honey sample using three different methodsas mentioned below-i. Anti-dsDNA ab coupled to magnetic nanoparticlesii. CHT Type I (batch mode)iii. Q Sepharose (batch mode)

Secure Facilitate Ensure 14

Gel Electrophoresis of ITS2 PCR Products(Soluble DNA)

Four samples of same honey (Kelley’s Texas honey, USA),differently processed


An RPA Target Early Candidate

― Classified all unique taxa obtained from NGS by Endemic/Natural status reported by theproject “Flora of China”

― Millettia leptobotrya is endemic to China (found only in China, one variant in Vietnam)― “Millettia leptobotrya” was a surprising hit in a honey sample from Thailand― Possibilities: Error, ITS2 non-specificity, occurs in Thailand, mis-origined sample? Will

investigate further.

Tropicos.org. Missouri Botanical Garden. 18 May 2020<http://www.tropicos.org/Name/13060147>


Pairwise alignment of ASV with the ITS2 sequence present in the NCBI’s nucleotide database

We are working on developing primers for ITS2 of this plant


Results

17

Making progress, on schedule except for COVID-19 sample acquisition delay

Acquired 149 honey samples, working toward the target of 300 samples,likely with 2 month COVID-19 delay

Submitted SOPs for pollen DNA analysis and amplification of ITS2 frompollen for NGS

Early efforts on RPA assay for plant species endemic to China

We have successfully obtained NGS data for plant DNA isolated from filteredhoney samples using three different methods


Conference Presentations

18

We have submitted the following two abstracts which are under review atAmerican Chemical Society, Fall 2020 National Meeting & Expo

1) “Targeted next-generation sequencing using plant ITS2 for authenticatinghoney origins” to the Division of Agricultural and Food Chemistry, for oralpresentation

2) “Enrichment of trace pollen-free DNA for next-generation sequencing todetermine honey origins” to the Division of Biochemical Technology, forposter presentation


Progress towards Milestones

19

ID Description Date Means of verification

M.1 Accumulation of 300 honey samples 6 Report at 6 MAS

M.2 Sequencing of 300 honey samples 9 Report at 9 MAS

M.3 RPA assay development 9,12 Report at 9, 12 MAS

No milestone dates have yet arrived, but we are on track.

149 honey samples

NGS data for 17 honey samples (14 pollen DNA and 3 soluble DNA)

RPA assay development is in progress


Deliverables

20

Deliverables (MAS = Month after start)ID Description Type MAS Scheduled dates Current StatusD.1 Kickoff meeting minutes Report 1 Feb 21 2020 A

D.2 Accumulation of honey samples Report 3,6 April 2020, July 2020 IP

D.3 Pollen DNA purification and prep protocols Report 1 March 07 2020 A

D.4 Pollen DNA sequencing Data, Report 6, 9 July 2020, Oct 2020 IP

D.5 Pollen DNA clustering methods and data Report, Data 6, 9, 12 July 2020, Oct 2020, Jan 2021 IP

D.6 Purification and analysis of soluble DNA from filtered honey

Report, Report, Publication 3, 6, 12 April 2020, July

2020, Jan 2021 IP

D.7 Country-specific plant DNA barcode archive and informatics Report 3, 6, 9 April 2020, July

2020, Nov 2020 IP

D.8 RPA amplification assays Report, Report, Publication 6, 9, 12 July 2020, Oct

2020, Jan 2021 IP

D.9 Testing and validation to determine origins of CBP-provided or blinded honey samples Report 12 Jan 2021 Not yet started

D.10 Overall Report Report 12 Jan 2021 Not yet startedD.11 Project Debriefing Brief 12 Jan 2021 Not yet started

IP = In progressA = Accomplished as planned


Performance Metrics

21

Research and Innovation KPIs Date Means of verification

KPI-RI-1 Honey sample acquisition 6 MAS Count of samples (Target: 300)

KPI-RI-2 Honey sequencing reads per sample 3 MASRun output statistics

(Target: 30,000 reads per sample)

KPI-RI-3 Filtered honey PCR success rate 6 MASFraction amplifiable

(Target: 75%)

Dissemination KPIs (HSE, scientific community, public)

Date Means of verification

KPI-D-1 Presentation at technical conference accepted 12 MAS Acceptance letter

KPI-D-2 Paper submissions to peer-reviewed journals

9, 12 MAS

Journal acknowledges receipt

KPI-D-3 Sequencing & analysis SOPs 12 MAS Delivery to LSS


Decision Points

22

IDPerformance Target (criteria for "go"

decision)Decision

DateDrop dead

date

P.1 Initial decision to proceed 0 MAS 0 MAS

P.2Analysis and clustering of first 50

samples6 MAS 9 MAS

P.3 First honey RPA results 6 MAS 9 MAS


Transition

23

Stakeholder Engagement‒ Monthly teleconferences, supplemented by both summary and topic-focused written reporting, with

associated feedback and answers‒ A detailed report at 30 days after start‒ Provide extensive SOPs for the sample-preparation, sequencing, and informatics analysis methods to

CBP technical specialists, as well as a database of all sequence and clustering results obtained overthe course of this work

‒ Multiple in-person engagements between the Project PI and Project Champion/ CBP-LSS teamincluding at the Annual BTI meeting and at CBP HQ as requested

Notional Transition Plan‒ Upon completion of this project, we will have established a new world-class resource for

identification of the sources of honey‒ If the work is successful and CBP chooses to use DNA as a means of establishing country of origin of

honey, CBP has expressed that it likely will prefer to establish this workflow in its own facilities‒ Toward this end, UH and Baylor will document and provide SOPs, primer sequences, databases and

informatics workflows, as well as any assistance required


Risks to Deliverables

• COVID-19 shuts down UH, BCM or Genewizagain (unlikely)

• Delays in honey sample acquisition (possiblebut not likely to exceed 2-3 months). Wehave 50% of samples in hand already

24


Programmatic Risks and Mitigation Plans

25

ID Description of Risk Tasks Severity* Proposed mitigation measuresR.1 Failure to acquire sufficient samples

from PRCMedium Send/partner with people going to PRC or go to PRC to

acquire samples. We already have acquired 40 samples fromthe PRC.

R.2 Lack of specificity because plantsoccur across broad regions

Medium Accumulation of multi-plant signatures; Curation of plantsknown to occur only in PRC; deep sequencing (>30k readsper sample)

R.3 Seasonal variability of pollen content Medium Acquisition of additional samples at different times of year,use of existing botanical knowledge, deep sequencing (>30kreads per sample)

R.4 Inability to amplify DNA from filteredhoney

Low First 2 methods tested (anion-exchange and anti-DNAantibodies, applied to honey after 0.2 um filtration) bothworked on first samples tried, yielding plant ITS2 sequencesmatching those obtained from pollen from same sample.

R.5 Loss of confidentiality by use ofcommercial AWS compute resources

Low Keep data on local UH/BCM clusters

R.6 Data/sample overload (millions ofreads; hundreds of sequences;hundreds of samples)

Low Formal sample inventory and world-class bioinformatics.Automated cleanup and quality filtering of reads, read-grouping, clustering and distance calculations, auto-lookupof species, focus on clearly-present species

*Severity to completion of the project: high; medium; low


Next Steps

More fully reactivating the lab

Continuing pollen DNA NGS (4 samples in progress now)

Develop RPA assay for country-specific plant

Further develop methods for high-throughput analysis of filtered honey


Any Questions?


Backup Slides


Data

29

Sample Code Sample details Type of DNA DNA capture

H1 Wildflower Bee Pollen Granules (China)

Pollen DNADNeasy®

Plant Mini Kit (Qiagen)

H2 Lizuming Honey Comb (China)

H3 True Elements raw honey (India)

H4 Longan honey (Hong Kong)

H5 Vejpong raw honey (Thailand)

H6 Kalymnos Golden honey (Greece)

H7 Orange blossom honey (USA)

H8 Albee’s blossom honey (Philippines)


Data

30

Sample Code Sample details Type of DNA DNA capture

H9 RCW sample 1 (Texas, USA)

Pollen DNADNeasy® Plant Mini Kit

(Qiagen)





H15 Kelley’s Texas honey (USA)

25A Kelley’s Texas honey (USA)

Soluble DNA

Anti-DNA Ab

25C Kelley’s Texas honey (USA) CHT type I (batch mode)

25D Kelley’s Texas honey (USA) Q Sepharose (batch mode)

quarterly report: may 21, 2020 - university of houston

Documents