implementing multi-residue methodologies for monitoring ...simplified sample extraction and...

©2015 Waters Corporation 1

Implementing multi-residue methodologies

for monitoring residues in foods using LC-MS

Dr Simon Hird Principal Scientist

[email protected]

Food & Environmental Business


Overview

Introduction

Targeted analysis

– Detection, quantification and identification

o Pesticides

– Screening (and confirmation)

o Vet drugs

Non-targeted analysis

– Screening, identification and quantification

o Pesticides

Conclusions


Current trends in residue testing

Multi-residue analyses determine as many residues as possible in the smallest number of analyses

– Reduced number of SOPs and associated costs

– Increased flexibility and optimal batch sizes

– Options to increase scope of current methodology

Combination of generic extraction with the use of high speed liquid chromatography coupled with tandem mass spectrometry

– Increase in the use of high resolution mass spectrometry (HRMS) as an alternative to MS/MS with some advantages

Achieves required LODs/LOQs even in complex matrices with simplified sample extraction and no/limited clean-up

Offers scope for rapid multi-component screening, quantification and identification

Targeted and “Non-targeted” analytical approaches


Targeted analysis

Based on establishing a method to determine a list of known

analytes using reference standards and typically methods are

validated prior to analysis of real samples

A list of selected compounds is prepared based on existing

knowledge/intelligence

The scope of a targeted approach, although extensive, will

always be limited to the chosen list

This list of compounds is continually changing and it is difficult

to ensure targeted methods cover all possible compounds of

interest

– Different regions and various laboratories have differing lists

Traditionally TQ using MRM (SRM) is the gold standard

– Often involves quantification


Results from official control of pesticide residues in the UK in 2014

In 2014, UK tested 3,615 samples for many targeted pesticides

Residues are detected

– Residues were detected in 44% of samples tested although only 2%

of samples exceeded MRLs

– Required to report MRL violations

– Residues < MRL reported for risk assessment purposes

Driver for analysis that meets performance criteria for

detection, quantification and identification in a single

analysis

No residues detected

Residue found at or below MRL

Residue found above MRL


Monitoring of pesticide residues

Increased frequency border controls – 669/2009 controls

– Specifies products/countries and frequency of testing

o Now specifies analysis of residues of at least those pesticides listed

in the EU coordinated control programme that can be analysed

with multi-residue methods based on GC-MS and LC-MS (pesticides

to be monitored in/on products of plant origin only)

o Additional pesticides specified as and when required

• e.g. Ethephon in table grapes from Peru


Multi-residue approach to pesticide residue analysis; novel in 2000

22 carbamates by extraction

with ethyl acetate, solvent

exchange and concentration,

LC-MS (SIM)


Multi-residue analysis; 400-600 compounds routine in 2015

UPLC-MS/MS APGC-MS/MS


Spike 10 mL of fruit juice with 80 pesticides @ at

0.01 mg/kg

Dilute x100 with water

Filter and inject; I-Class and Xevo

TQ-S

Multi-residue analysis without extraction: dilute and shoot of juice


Multi-residue analysis with extraction

Acetonitrile – QuEChERS (includes salting out)

Ethyl acetate – SweEt

Acetone – Mini-Luke or NL (extracted with

acetone followed of partition with dichlorometane / petroleum ether (1:1)

AOAC Official Method 2007.01 and CEN Method EN 15662

Shake

Shake and centrifuge


Multi residue analysis via QuEChERS


Selectivity of dSPE cleanup: different sorbents


Selectivity of dSPE cleanup: different sorbents

Freeze-out:

• Lipids and Waxes

• Sugars

Amino-Sorbents, Alumina:

• Acids (including fatty acids)

• Sugars

• Pigments (Anthocyanes, some Chlorophyll)

Carbon-based Sorbents:

• Carotinoids, Chlorophyll, Sterols

Reversed-Phase Sorbents:

• Lipids and Waxes

Risk: Losses of

acidic pesticides

Risk: Losses of

planar pesticides

Risk: Losses of

non-polar pesticides

Risk: Losses of

lipophilic pesticides


Overview of cleanup options (Michelangelo Anastassiades: EURL)

Weigh 10 g of Frozen Sample

Shake

Shake / Centrifuge

Add 10 mL Acetonitrile and ISTD-Solution

Add 4 g MgSO4, 1 g NaCl, Citrate Buffer Salts

Optional:

Add “Analyte Protectants”

Multiresidue Analysis

by GC-MS(/MS), LC-MS(/MS)…

Shake / Centrifuge

Acidify extract to pH ~5 to protect base-sensitive pesticides

D-SPE with MgSO4/PSA/ODS

Optional Analysis

of acidic pesticides (LC-MS/MS)

Optional Analysis :

of acid-sensitive pesticides

High content of lipids, waxes?

Freeze-out

D-SPE with MgSO4/PSA

D-SPE with MgSO4/PSA/GCB

High content ofplanar pigments?

Shake / Centrifuge

Shake / Centrifuge

Shake / Centrifuge

Decant or filter or centrifuge

Weigh 10 g of Frozen Sample

Shake

Shake / Centrifuge

Add 10 mL Acetonitrile and ISTD-Solution

Add 4 g MgSO4, 1 g NaCl, Citrate Buffer Salts

Optional:

Add “Analyte Protectants”

Multiresidue Analysis

by GC-MS(/MS), LC-MS(/MS)…

Shake / Centrifuge

Acidify extract to pH ~5 to protect base-sensitive pesticides

D-SPE with MgSO4/PSA/ODS

Optional Analysis

of acidic pesticides (LC-MS/MS)

Optional Analysis :

of acid-sensitive pesticides

High content of lipids, waxes?

Freeze-out

D-SPE with MgSO4/PSA

D-SPE with MgSO4/PSA/GCB

High content ofplanar pigments?

Shake / Centrifuge

Shake / Centrifuge

Shake / Centrifuge

Decant or filter or centrifuge

Choice also

dependant on the

selectivity and

sensitivity of the

LC-MS


Matrix effects

Matrix effects are known to occur frequently using electrospray

– Co-elution of matrix co-extractives with analytes

– Differences between commodities and even sample to sample

Matrix-matched calibration is commonly used to compensate for

matrix effects but also:

– Standard addition

– Internal standards (including isotopically labelled ones)

– Dilution of extracts


Pesticides in okra: UPLC-MS/MS Acquity H-Class and Xevo TQD

Okra: QuEChERS (AOAC), dSPE (C18,

PSA and GCB), evaporated to dryness

and reconstituted in mobile phase

Retention-time window based MRM

acquisition with autodwell

Compound name: Acetamiprid

Correlation coefficient: r = 0.998828, r̂ 2 = 0.997657

Calibration curve: 7.5159 * x + 1.16915

Response type: Internal Std ( Ref 233 ), Area * ( IS Conc. / IS Area )

Curve type: Linear, Origin: Exclude, Weighting: 1/x, Axis trans: None

ng/mL-0.0 2.5 5.0 7.5 10.0 12.5 15.0 17.5 20.0 22.5 25.0

Res

pons

e

-0

50

100

150

Quantification MRM

Qualification MRM

Calibrant @

0.001 mg/kg

RT 5.19

201 pesticides in okra @

0.01 mg/kg

Matrix-

matched

calibration

Acetamiprid


Pesticides in chilli: UPLC-MS/MS Acquity H-Class and Xevo TQ-S micro

Chilli: QuEChERS (CEN), no dSPE, direct

injection of MeCN extracts

Due to increased sensitivity

Wide retention-time window based SRM

acquisition (1 minute) for 424 pesticides

with autodwell

Due to increased scan speed

Matrix-matched calibration

Calibrant @ 0.001 mg/kg

RT 5.38

Quantification MRM

Qualification MRM

Compound name: MandipropamidCorrelation coefficient: r = 0.997983, r 2̂ = 0.995970Calibration curve: 1359.24 * x + 108.142Response type: External Std, AreaCurve type: Linear, Origin: Exclude, Weighting: 1/x, Axis trans: None

Conc-0 200 400 600 800 1000

Re

sp

on

se

-0

1000000

Conc

Re

sid

ua

l

-20.0

0.0

20.0

Selected pesticides

in chilli @ 0.01

mg/kg

Acetamiprid


Monitoring of vet drug residues

Unlike with pesticides, there are very few non-compliant samples reported in national surveillance across Europe

– In 2012, only 0.25 % of the 425,000 samples tested in Europe were non-compliant

Validated, low cost, high throughput, screening with generic, multi-residue conditions being used for operational efficiency with follow up confirmation

Validated for Decision Limit CCb

– Demonstrate minimal false detects and no false negatives

Calibrate using a positive control at Screening Target Conc.

– STC is the concentration at which a screening test categorises the sample as potentially non-compliant and triggers a confirmatory test

Separate, validated (Decision Limit CCa), confirmatory analysis, often carried out in duplicate, that meets criteria for quantification and identification


Monitoring of vet drug residues

Additional testing is carried out at border control on specific

imports of animal products entering to the European Union

Class-specific methods focusing on selected vet drugs

– e.g. currently chloramphenicol, tetracycline, oxytetracycline and

chlortetracycline and of metabolites of nitrofurans in aquaculture

products from India


67 compounds in many

(15000 p.a.) samples of

kidney and muscle

– Penicillins - e.g. amoxicillin

– Cephalosporins - e.g. Cefalexin

– Sulfonamide - e.g. sulfadiazine

– Macrolides - e.g. tylosin

– Tetracyclines - e.g. tetracycline

and epimer

– Quinolones - e.g. oxolinic acid

– Fluoroquinolones - e.g.

danofloxacin

– Aminoglycosides - e.g.

streptomycin (needs separate

analysis)

Screening for antibiotics: UPLC-MS/MS Acquity and Xevo TQ-S


Confirmation by repeat analysis by UPLC-MS/MS after the generic extraction

min1.350 1.400 1.450 1.500 1.550 1.600 1.650

%

0

100

F5:MRM of 3 channels,ES+

451.1 > 416

Run36793_a_026 Smooth(Mn,1x2)

7.532e+006Tetracycline-D6 Surrogate

1.39

min

%

0

100


445 > 98.1


1.267e+007Tetracycline

1.40

min

%

0

100


445 > 154.1


1.490e+007Tetracycline

Compound name: Tetracycline

Correlation coefficient: r = 0.998630, r^2 = 0.997262

Calibration curve: 0.392801 * x + -0.0295833

Response type: Internal Std ( Ref 8 ), Area * ( IS Conc. / IS Area )

Curve type: Linear, Origin: Exclude, Weighting: 1/x, Axis trans: None

x STC-0.00 1.00 2.00 3.00 4.00 5.00 6.00 7.00 8.00 9.00

Re

sp

on

se

-0.00

1.00

2.00

3.00

x STCR

esid

ua

l

-2.5

0.0

2.5

5.0

• Tetracycline in pig kidney

• Duplicate test portions: 4.9 and 5.1 µg/kg

• Sample ion ratios 0.86 cf. 0.88 in reference


Balance between time and robustness

Extracts of animal products contain fat and phospholipids which are not removed using dSPE using C18 in dSPE

– Soluble in solvents with high % MeCN so extracts remain clear

These are initially retained on the LC column but elute many injections later causing ion suppression

– Potential for non-detects and/or poor quantification


Vet drugs in milk

0

20

40

60

80

100

120

140

Cim

ate

rol

Cle

nbute

rol

Racto

pam

ine

Salb

uta

mol

Terb

uta

line

Tulo

bute

rol

Zilpate

rol

Clindam

ycin

Ery

thro

mycin

kitasam

ycin

Lin

com

ycin

Spiram

ycin

Tilm

icosin

Tylo

sin

Sulfachlo

rpyridazin

e

Sulfaclo

zin

e

Sulfadim

eth

oxin

e

Sulfaguanid

ine

Sulfam

era

zin

e

sulfam

ete

r

Sulfam

eth

azin

e

sulfam

eth

izole

Sulfam

eth

oxypyridazi…

sulfanilaceta

mid

e

sulfaphenazole

Sulfapyridin

e

sulfis

om

idin

e

Trim

eth

oprim

Cin

oxacin

Cip

rofloxacin

Danofloxacin

Diflo

xacin

Enoxacin

Enro

floxacin

Flu

mequin

e

Lom

efloxacin

Marb

ofloxacin

Nalidix

ic a

cid

Norf

loxacin

Ofloxacin

Orb

iflo

xacin

Oxolinic

acid

Pefloxacin

Sara

floxacin

Chlo

ram

phenic

ol

florf

enic

ol

Thia

mphenic

ol

penic

illin V

Beta

meth

asone

Cort

isone

Dexam

eth

asone

Hydro

cort

isone

Mepre

dnis

one

Meth

ylp

rednis

olo

ne

Pre

dnis

olo

ne

Triam

cin

olo

ne

Triam

cin

olo

ne

…

Cefo

taxim

e

Ceft

iofu

r

cephapirin

60 compounds in 9 drug classes in milk

Phospholipids


Identification criteria in Europe

Decision 2002/657/EC

– Animal tissues including veterinary drugs but often applied to other situations

– Weighting based upon the selectivity of the technique employed

o Identification points (IP) system

– Employs an ion ratio tolerance based upon ion intensity

– Does NOT offer an alternative of using mass accuracy from HRMS

– The minimum acceptable RT for the analyte(s) should be at least 2x the RT corresponding to the void volume of the column

– RT should correspond to that of a reference with a tolerance of ±2.5%

Relative intensity (% of

base peak)

LC-MS/MS (relative)

> 50 % 20 %

> 20 % to 50 % 25 %

> 10 % to 20 % 30 %

≤ 10 % 50 %


Identification criteria in Europe

Document No. SANCO/12571/2014

– Pesticide analysis

– No weighting based upon the selectivity of the technique

o No IP system

– No longer employs an ion ratio tolerance based upon ion intensity

o Tolerance for all LC-MS data is ±30% regardless

– Does offer an alternative of using mass accuracy from HRMS

o At least two diagnostic ions with mass accuracy of <5 ppm

– The minimum acceptable RT for the analyte(s) should be at least 2x

the RT corresponding to the void volume of the column

– RT should correspond to that of a reference with a tolerance of ±0.2

min


Limitation of targeted approach

Management of acquisition

– Need to program methods with RTs of analytes and specific transitions to monitor

– Will fail to detect other contaminants present in the sample

– Unable to go back and “mine” the data later

An alternative approach is to use LC-HRMS

– Full spectral acquisition with equivalent sensitivity to TQ

– High mass resolving power used for selectivity

– Database/library searching via mass measurements and isotope patterns of molecular species and fragment ions

o Potential to screen for more compounds compared to TQ

– If no hits, search elsewhere (e.g. Chemspider) for assignment of likely structures to the empirical formulae proposed by the software

– Use of ion mobility for added peak capacity and selectivity and CCS values to aid identification


MSE from a Xevo G2-XS

Alternate Low and

High Energy Scans

Low Energy Data

High Energy Data

Combined Data


Atrazine – QTof (HRMS)

Identification from more

sources of information


Processing MSE data using UNIFI

Raw data

Organise

Componentisation

Analyse

Report results

Peak

componentisation Only needs to be

done once

Performed in parallel

with data acquisition

Speedy

application

processing Through setting

various questions via

the application of

filters that are

combined into a

workflow


Workflow Filter

View

Report

Filter = Question imposed on data

View = What information do you need displayed to

answer the question?

Workflow Step = Filter + View, invoked by a single

click

Workflow = Series of workflow steps to review and

entire injection consistently, concisely and accurately.

Report = User reviewed result (answer)

Analysing the data in UNIFI


Workflow flexibility

Non-targeted Screening - Qualitative

Unknown Screening – Binary Compare

Non-targeted Screening Quan-Qual

Transformation products– Met ID

Same data, different questions


Review positively identified: injections and components


Score : 28/28

Some results for qualitative screening of strawberry pomace


Ion mobility for non-targeted screening on VION IMS QTof

Drift time

m/z

Drift time

m/z

Mobility

separation

Co-eluting precursor ions

Drift time aligned

precursors and products


The enhancements ion mobility offers

Provides selectivity orthogonal to UPLC and MS

– Separation based on shape, charge and mass

– Potential for separation of isomers

– Generates extra peak capacity

Generates cleaner mass spectra

– Facilitates more reliable interpretation


MSE mass spectra with no ion mobility

Fragments are Retention time aligned


HDMSE with ion mobility providing spectral clean-up all the time

Fragments are Mobility Aligned And Retention time aligned


Use of collision cross section (CCS) information reduces errors

in compound identification

Drift time is a measure of an ion’s mobility

– Related to the shape of the molecule in the gas phase

Applying a calibration gives us values for CCS

– Measurements are reproducible and don’t vary with matrix

o More robust a parameter than retention time

– Reduces false detects/positives and non-detects/false negatives

during non-targeted screening

The enhancements ion mobility offers


Results summary for EU RL proficiency sample FV-13

29 Observed Using a Screen with 1

min RT Window, and 20 ppm Mass Accuracy

8 Expected to be detected



9 Observed Using a Screen with 1 min

RT Window, 10 ppm Mass Accuracy and Fragment Presence




8 Observed Using a Screen with 1 min

RT Window, 10 ppm Mass Accuracy, Fragment Presence and 2% CCS

Tolerance


False +ve

False –ve based upon

mass accuracy alone


Conclusions

Improved performance of multi-residue methods has increased the scope of analysis with targeted analyses in routine use

Can be used to fulfil criteria for different types of analysis

There has been a significant increase in reports of the use of non-targeted screening methods (by specialist laboratories?)

– Mostly non-targeted high mass resolution mass spectrometry acquisitions supported by targeted data processing

– Mass accuracy alone is insufficient for preventing false detects

– Adding other mass spectrometric parameters helps but can lead to increase in the number of non-detects

Ion mobility increases peak capacity and provides spectral cleanup

– CCS provides an additional useful analytical measurement to aid with screening and identification

The next challenge is to continue to make this truly routine

implementing multi-residue methodologies for monitoring ...simplified sample extraction and...

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