Antibiotic residue determination in environmental waters by LC-MS

Trends

Trends in Analytical Chemistry, Vol. 26, No. 6, 2007

Antibiotic residue determination in environmental waters by LC-MS Fe´lix Herna´ndez, Juan V. Sancho, Marı´a Iba´n˜ez, Carlos Guerrero Pharmaceuticals, identified as emerging contaminants, are used in large quantities in human and veterinary medicine for treatment of different diseases. Among pharmaceuticals, antibiotics in the aquatic environment are of great concern as prolonged exposure to low doses may promote antibiotic resistance. The rapid development of liquid chromatography (LC) coupled to mass spectrometry (MS) and tandem MS (MS2) in the environmental field has transformed this combined technique into a valuable tool for the determination of antibiotics in water samples. To be of real value from the environmental and public health point of view, the analysis performed should meet the scientific standards established to assure data quality. These require not only accurate quantitative methods but also reliable confirmative methods, at the low concentration levels expected for antibiotics in water. We present a critical review of published methods based on LC-MS or LC-MS2 for the determination of antibiotic residues in environmental waters. We evaluate different approaches for screening, quantification and confirmation of these compounds, giving special attention to dealing with the intrinsic difficulties of confirming analytes with confidence at low-ng/L levels. ª 2007 Elsevier Ltd. All rights reserved. Keywords: Antibiotics; Liquid chromatography; Pharmaceuticals; Tandem mass spectrometry; Water analysis

1. Introduction Fe´lix Herna´ndez*, Juan V. Sancho, Marı´a Iba´n˜ez, Carlos Guerrero Research Institute for Pesticides and Water, University Jaume I, E-12071, Castello´n, Spain

*

Corresponding author. Tel.: +34 964 387366; Fax: +34 964 387368; E-mail: [email protected]

466

In recent years, there has been growing interest in the determination of emerging contaminants that are not currently covered by existing regulations on water quality or have not been previously studied, and that may be candidates for future regulation, depending on research on their toxicity and potential effects in the environment and on human health. Several groups of compounds have been considered as particularly relevant (e.g., algal and cyanobacterial toxins, hormones and other endocrine-disrupting compounds, surfactants, perfluorinated compounds, pharmaceuticals or personal-care products, and their metabolites or transformation products (TPs)). This interest justifies the relatively large number of reviews covering the

determination of emerging contaminants in environmental samples, especially in aquatic compartments, as listed in the bibliography. Analytical methods are usually based on mass spectrometry (MS) coupled to liquid chromatography (LC) [1–9] or gas chromatography (GC) [1,5,9]. Because of the widespread use of pharmaceuticals, approximately 3000 different active substances are used in human and veterinary medicine [9], so their detection in environmental waters is of significant interest. This was demonstrated recently in articles and correspondence in specialized journals, one of the most critical organizations in this field being the Pharmaceutical Research Manufacturers of America (PhRMA) [10,11]. The need to employ quality criteria before reporting data on pharmaceuticals is emphasized and some critical comments have been made to some studies performed in this field [12,13]. Among pharmaceuticals, antibiotics are of particular concern, as they can induce bacterial resistance, even at low concentrations, through continuous exposure. The increasing use of these compounds for prevention and treatment of diseases and as a supplement to promote growth in animal-feeding operations has resulted in genetic selection of more harmful bacteria in recent years [6]. Increased bacterial resistance has been observed in waste effluents from pharmaceutical plants and hospitals. The term ‘‘antibiotic’’ nowadays comprises a wide spectrum of substances, including synthetic compounds (e.g., sulphonamides and quinolones) and natural compounds (e.g., penicillins, tetracyclines and macrolides). Until now, the most studied antibiotic in the environment was macrolide erythromycin, followed by

0165-9936/$ - see front matter ª 2007 Elsevier Ltd. All rights reserved. doi:10.1016/j.trac.2007.01.012

Trends in Analytical Chemistry, Vol. 26, No. 6, 2007

Trends

their direct determination using GC, so a previous derivatization step is necessary. As a consequence, LC has become the technique of choice, as it can allow determination of antibiotics with notable simplification in sample manipulation. Although some papers have reported dealing with the determination of antibiotics by LC with different detection techniques, such as fluorescence, ultraviolet (UV) or radioimmunoassay (RIA), the use of LC coupled to MS (LC-MS), and especially to tandem MS (LC-MS2) has made impressive progress within this field. Fig. 1 shows the evolution of scientific papers dealing with the determination of antibiotics in water by LC-MS and LC-MS2. Atmospheric pressure interfaces (APIs) have been by far the most widely used for this purpose. LC-MS2 is a suitable technique for the determination of antibiotics (and their metabolites or TPs) in the environment, because of its improved selectivity and high sensitivity. However, despite this high sensitivity, a preconcentration step is normally necessary to reach the low limits of detection (LODs) required in the analysis of environmental waters. A previous paper [6] reviewed the state-of-the-art in environmental analysis of pharmaceutically active substances, including antibiotics, focusing on sample preparation, analyte stability and degradation, and matrix effects. Another recent review [7] described a considerable number of analytical methods based on LC-MS2 for antibiotics in surface waters, groundwaters and wastewaters. It presented the advances achieved in MS detection and recently reported data on the analysis of

quinolones ofloxacin and ciprofloxacin, sulphonamide sulfamethoxazole, chloramphenicol and trimethoprim. Penicillin and the tetracycline group have also been widely investigated. The large amounts of antibiotics used in both human and veterinary medicine have led to their occurrence in the environment. After their application and excretion, residual human antimicrobials frequently end up entering into municipal sewage-treatment plants (STPs). In general, studies have addressed final effluents [14–29] whereas raw wastewater influents have been investigated less frequently [16,18,19,21–24,26,28,29]. Some data indicate that these compounds are not efficiently eliminated during water treatment [7,27], so, depending on the mobility and the persistence of antimicrobials and metabolites in the soil-water environment, they may threaten surface waters and groundwaters. Numerous articles have reported the levels of antibiotics in water samples, although reporting the concentration levels found in the environment is not within the scope of this article. The low analyte concentrations normally present (low ng/L), the complexity of enviromental matrices and the diverse physico-chemical properties that antibiotics may present make their determination difficult, and highly sensitive, selective methods are necessary for monitoring antibiotics in the aquatic environment. The simultaneous determination of different analytes therefore requires chromatographic techniques. Although GC has a high resolving power, antibiotics are polar compounds, insufficiently volatile or too thermally unstable to allow

12 12 11

10

10

9

9 8

7

7 6 5

4

4 3 2

1

1

1

1

0

0

1998

1999

2000

2001

2002

2003

2004

2005

2006

Figure 1. Evolution of articles dealing with the determination of antibiotics in water by LC-MS and LC-MS2 published in the last few years.

http://www.elsevier.com/locate/trac

467

Trends

468 http://www.elsevier.com/locate/trac

Table 1. Summary of LC-MS and LC-MS2 methods for the determination of antibiotics and metabolites or transformation products (TPs) in water samples Analytes

Matrix

Treatment/SPE

MS

Validation level (lg/L)

Calibration/ matrix effect

Quantification/ confirmation criteria

[14]

Method 1: 7 MLs Method 2: 4 TCs Method 3: 7 PENs

STP effluent SW

(1) Lyophilization: EDTA + phosphate buffer (pH 6.0) Sample volume = 100 mL (preconc. · 100) (2) Off-line SPE (except TCs): Sample pH = 3.0 (H2SO4) Lichrolute EN + Lichrolute C18 Sample volume = 1000 mL (preconc. · 1000)

(ESI) QqQ

1

Matrix-matched standards (mountain spring water)

To quantify, either TIC (1–3 transitions) or strongest mass signal was used

[26]

13 SAs

WWTP effluent SW

Sample pH = 2.5 Off-line SPE LiChrolut EN Sample volume = 200–1000 mL (preconc. · 130–670)

(ESI) QqQ

1

–

Quantification: 1 transition Confirmation: Daughter ion scan vs standard. At lower concentration: 2 transitions + ion ratioB

[42]

6 SAs 5 TCs

GW SW

H2SO4 + EDTA + HCl Off-line SPE HLB OASIS Sample volume = 123 mL (preconc. · 1000)

(ESI) Q

0.2 1 0.2

SAs: IS or surrogate-IS TCs: Standard addition

2 SIMs

[55]

9 PENs

DW GW River water STP (influent, effluent)

‘‘in situ’’ derivatization Off-line SPE Carbograph 4 Sample volume = 4000 mL (tap); 2000 mL (GW); 1000 mL (river); 200 mL (effluent); 100 mL (effluent) (preconc · 13000, 6500, 3200, 1600 and 800, respectively)

(ESI) Q

DW: 0.025 GW: 0.05 River: 0.1 Effluent: 0.5 Influent: 1

IS

Quantification: Sum of the ion-current profiles for both parent and fragment ions (1–3 ions) Confirmation: 1–3 SIMs + tr (±2%) + relative abundance (20%)

[40]

3 TCs

GW WW Lagoon

Phosphate buffer + EDTA + citric acid Sample pH = 2.5 (H3PO4) Off-line SPE Sep-Pak tC18 (eluted with oxalic acid) vs OASIS HLB (eluted with TFA) Sample volume = 100 mL (preconc. · 500)

(ESI) IT

40 200

Surrogate-IS

Daughter full scan (1 product ion used for quantification)

Line missing

100

Trends in Analytical Chemistry, Vol. 26, No. 6, 2007

Ref.

3 TCs 1 ML

Soil water GW

Glassware heated + EDTA Sample pH = 2.5 (acetic acid) + citric acid buffer (pH 4.7) Off-line SPE Baker SDB-1 Sample volume = 25–50 mL (preconc. · 125–250)

(ESI) IT

0.2 1

Data corrected for recovery

Quantification: Daughter full scan Confirmation: MS3

[67]

Method 1: 6 TCs Method 2: 6 MLs + lincomycin + tiamulin

WW

Off-line SPE Method 1 (TCs): C18: NaH2PO4 + EDTA + citric acid HLB: sample pH = 2.5 (H3PO4) + citric acid Method 2 (others): Sample pH = 7 + OASIS HLB Sample volume = 20 mL (preconc.: NR)

(ESI) IT

–

IS

Daughter full scan (1 product ion used for quantification)

[37]

Gentamycin (aminoglycoside) (C1,C2)

Hospital WW influent

Neutral pH Off-line SPE (eluted with HFBA) Widepore CBX Sample volume = 20–50 mL (preconc. · 50–100)

(ESI) QqQ

10

Matrix-matched standards (GW) + surrogate IS

1 transition

[58]

(26 pharmaceuticals + 1 pesticide) 1 ML 1 SA trimethoprim

SW

Sample pH = 2 (H2SO4) Off-line SPE OASIS HLB Sample volume = 1000 mL (preconc. · 1000)

(ESI/APCIC) QqQ

0.05

Matrix effect observed in ESI

1 transition

[59]

(23 pharmaceuticals) 1 PE 1 TC 1Q 1 CE 7 MLs

River water

Off-line SPE (3 methods) Method 1: OASIS MCX: EDTA + Sample pH = 2 (HCl) Method 2: LiChrolutEN: Sample pH = 7 (NH4Ac) Method 3: Bakerbond C18 + sample pH = 8 (NH4Ac) Sample volume = 500 mL (preconc. · 2500)

(ESI) QqQ

0.01

2 surrogate ISs

2 transitions

Trends in Analytical Chemistry, Vol. 26, No. 6, 2007

http://www.elsevier.com/locate/trac

[30]

(continued on next page)

Trends

469

http://www.elsevier.com/locate/trac

Analytes

Matrix

Treatment/SPE

MS

Validation level (lg/L)

Calibration/ matrix effect

Quantification/ confirmation criteria

[19]

4 TCs 2 Qs

River Well STP (influent, effluent)

Sample pH = 2.8 (HCl) Off-line SPE OASIS HLB Sample volume = 100 mL (influent); 250 mL (effluent); 1000 mL (river and well) (preconc. · 100, 250, 1000, respectively)

(ESI) Q

0.05

Matrix effect observed. Reduced sample volume for STP

2 SIM

[20]

13 pharmaceuticals (4 methods ) Method 1: 2 SAs + 1 ML + trimethoprim

Sewage effluent SW

Silanisation material Sample pH = 3 (HCl) Off-line SPE Strata X Sample volume = 1000 mL (preconc. · 1000)

(ESI) IT

10

Surrogate IS

Daughter full scan (1 product ion used for quantification)

[39]

12 PENs 8 MLs 2 SAs 2 Qs 4 TCs trimethoprim

SW

Sample pH = 4 (H2SO4) + EDTA Off-line SPE SDB-2 + OASIS HLB EDTA Sample volume = 500 mL (preconc. · 1000)

(ESI) QqQ

0.001 0.1

–

1 transition

[27]

5 MLs

WWTP effluent

Sample pH = 7 (H2SO4 or NaOH) LiChrolute EN + LiChrolute RP18 Sample vol = 1000 mL (preconc. · 1000)

(ESI) Q

0.025–0.2

Surrogate IS

2 ions + ion ratio (10– 20% deviation)A

[24]

Polar organic contaminants (including antibiotics)

WWTP (influent, effluent)

OASIS HLB Sample volume effluent = 500 mL (preconc. · 500)

Q QqQ TOF

–

–

Q: 1 SIM QqQ: 1 transition TOF: 1 ion (accurate mass)

[13]

(22 pharmaceuticals) 1 PEN trimethoprim

SW

Off-line SPE OASIS HLB Sample vol = 1000 mL (preconc. · 1000)

(ESI) Q

1 0.5

IS

Quantification: 1 SIM Confirmation: 2–3 SIMs + tr (±0.1 min) + relative abundanceB

[41]

3 MLs

Natural water WW

EDTA + sample pH = 5.0 (H2SO4) Off-line SPE OASIS HLB Sample volume = 120 mL (preconc. · 1000)

(ESI) IT

0.1 1 2.5

Matrix-matched standards + IS

Daughter full scan (1 product ion used for quantification)

Line missing

Trends in Analytical Chemistry, Vol. 26, No. 6, 2007

Ref.

Trends

470

Table 1 (continued)

6 SAs 7 TCs

SW

EDTA Sample pH < 3.0 (H2SO4) Off-line SPE OASIS HLB Sample volume = 120 mL (preconc. · 1000)

(ESI) IT

0.05 0.1 0.5 1 2 5

Significant matrix effects for TCs but not SAs. Matrix-matched standards + IS

Daughter full scan (1 product ion used for quantification)

[16]

4 MLs 6 SA + 1 TP

WWTP (influent, effluent)

NaCl + sample pH = 4.0 (H2SO4) Off-line SPE OASIS HLB Sample volume = 250 mL (2nd and 3rd effluent); 50 mL (1st influent) (preconc. · 500 and 25 respectively)

(ESI) QqQ

1st effluent: 2 3rd effluent: 5

5 Surrogate ISs + recovery rates factor

Retention time + 2 transitions + concentration ratio (<10%)A

[31]

(12 pharmaceuticals) 1 SA 1 ML cloramphenicol

SW GW DW

Sample pH = 3 (HCl) Off-line SPE OASIS-MCX Sample volume = 100 mL (preconc. · 200)

(ESI) QqQ QTOF

0.1

–

(1) QqQ: Screening: 1 transition Confirmation: 2 transitions + ion ratio + tolerance (EU criteria) (2) QTOF: accurate mass of 2 product ions + ion ratio + tolerance (EU criteria)

[17]

2 SAs 4 Qs trimethoprim

WWTP effluent

NaCl + Sample pH = 2.5 (H3PO4) Off-line SPE Anion-exchange Isolute + OASIS HLB EDTA Sample volume = 1000 mL (preconc. · 1000)

(ESI) Q

1

6 compounds quantified based on 2 ISs 1 compound based on standard addition.

2 or 3 SIMs at 2 fragmentation cones Confirmation: tr+ relative abundance (<25%)A

[44]

1 SA 1 Qs trimethoprim florphenicol

SW

Sample pH = 5 (H3PO4) Off-line SPE OASIS HLB Sample volume = 40 mL (preconc. · 80)

(APCI) QqQ

0.01 10

Study of matrix effect. Residual matrix components enhance signal, which decreases with increasing pH sample

2 transitions following EU criteriaA

Trends in Analytical Chemistry, Vol. 26, No. 6, 2007

http://www.elsevier.com/locate/trac

[21]

(continued on next page)

Trends

471

http://www.elsevier.com/locate/trac

Ref.

Analytes

[15]

Method 1: Method 2: dioxides Method 3: Method 4:

3 MLs 6 Qs + 2Q-

Matrix

Treatment/SPE

MS

Validation level (lg/L)

Calibration/ matrix effect

Quantification/ confirmation criteria

STP effluent

Off-line SPE OASIS HLB Method 1 (MLs): sample pH = 6.0 (H2SO4) Method 2 (rest): EDTA Sample volume = 1000 mL (preconc. · 1000)

(ESI) QqQ

0.2 1

Matrix-matched standards

1 transition

16 SAs 4 TCs

Method 1: 4 FQs + 2 SAs + trimethoprim Method 2: 2 CEs + 1 PEN + 2 TCs + 2 NIs

Hospital sewage water

Sample pH = 3 (H2SO4) Off-line SPE C2/ENV+ Sample volume = 200–500 mL (preconc. · 200–500)

(ESI) IT

2.5

6 surrogate ISs

Daughter full scan (1 production used for quantification)

[46]

Method 1: 5 SAs + 5 TPs Method 2: neutral pesticides Method 3: acidic pesticides

SW

Sample pH = 4.0 (acetate buffer) On line-SPE OASIS HLB Sample volume =18 mL

(ESI) QqQ

0.1 0.25 0.5 1 2.5 5

Matrix effect observed. 7 surrogate ISs

2 transitions

[23]

6 TCs 5 SAs

Domestic WW (influent, effluent)

Off-line SPE EDTA + citric acid Sample pH < 3 (H2SO4) OASIS HLB Sample volume = 120 mL (preconc. · 1000)

(ESI) IT

0.1 0.5 1 3 5

Matrix effect observed. Matrix-matched standards +IS

Daughter full scan (1 product ion used for quantification)

[32]

2 3 3 3

SW GW WWTP effluent

Sample pH < 3.0 + EDTA Off-line SPE OASIS HLB Sample volume = 500 mL (preconc. · 500)

(ESI) IT

0.25 2.5

IS

Quantification + confirmation: full scan + daughter full scan (data-dependent scanning)

[25]

Method 1: 1 PEN + 2 Qs +1 TC+ 1 SA + 1 ML + lyncomycin Method 2: 4 MLs

STP effluent

Off-line SPE Method 1: sample pH = 2.0 (HCl) + EDTA + OASIS MCX Method 2: sample pH = 7.0 (NH4OH) + Lichrolut EN Sample volume = 500 mL (preconc. · 5000)

(ESI) QqQ

0.02 0.2 2

3 IS

2 transitions + tr

[38]

4 IPs

SW

Glassware heated + EDTA + NaCl Sample pH = 7.5 (NaOH) Off-line SPE OASIS HLB Sample volume = 120 mL (preconc. · 1000)

(ESI) IT

0.07 1.5

Matrix-matched standards + IS

Daughter full scan (1 product ion used for quantification)

Qs TCs MCs SAs

Line missing

Trends in Analytical Chemistry, Vol. 26, No. 6, 2007

[56]

Trends

472

Table 1 (continued)

Azythromycin (ML)

Municipal WW (influent, effluent)

LLE (K2CO3 + MTBE) Sample volume = 10 mL (preconc. · 100)

(ESI) IT

0.0125 0.04 0.125

Surrogate-IS

Daughter full scan (1 product ion used for quantification)

[22]

5 b-LCs

SW urban WW (influent, effluent)

Glassware heated + EDTA Sample pH = 7.5 (NH4OH) Off-line SPE OASIS HLB Sample volume = 200 mL (preconc. · 1500)

(ESI) IT

0.1 0.5 2

Minimal matrix effects observed. Matrix-matched standards + IS

Daughter full scan (1 product ion used for quantification)

[45]

10 Qs 6 PENs

GW SW

Sample pH = 2.5 (HCOOH) (1) on line SPE (QqQ) C18 Sample volume = 9.8mL (2) Off-line SPE (QTOF)

(ESI) QqQ QTOF

0.01 0.1

No remarkable matrix effects observed

Screening: 1 transition Confirmation: highest number of transitions + ion ratio + tolerance (EU criteria) False positives described

[34]

(16 pharmaceuticals) 1 ML trimethoprim metronidazole

Hospital effluent WW

Sample pH = 7.0 (H2SO4) Off-line SPE OASIS HLB Sample volume = 100 mL (preconc. · 100)

(ESI) QqQ

1

Matrix suppression observed. Dilution + matrixmatched standards

2 transitions + tr (± 2%) + ion ratio + tolerance (<10%)A

[35]

11 SAs

SW DW

Off-line SPE OASIS HLB Sample volume = 1000 mL (mineral); 250 mL (SW) (preconc. · 4000 and 1000 respectively)

(ESI) QqQ

0.03 0.1 0.2

No matrix effects observed

2 transitions

[18]

2 MLs

WW (influent, effluent)

Sample pH = 5.0 (H2SO4) + EDTA + citric acid Off-line SPE OASIS HLB Sample volume = 100 mL (influent); 200 mL (effluent) (preconc. · 350 and 1500 respectively)

(ESI) IT

0.1 0.5 1.0

Dilution of influent samples (1:2) Matrix-matched standards + IS

Quantification: Daughter full scan (1 product ion used) Confirmation: Daughter full scan (2 product ions used) + ion ratio + tolerance (EU criteria, US FDA criteria)

[33]

5 MLs

River water

Sample pH = 6 (NaOH) Off-line SPE OASIS HLB Sample volume = 250 mL (preconc. · 250)

(ESI) QqQ

0.025 0.125

No matrix effects observed.

Quantification: 1 transition Confirmation: 2 transitions

Trends in Analytical Chemistry, Vol. 26, No. 6, 2007

http://www.elsevier.com/locate/trac

[28]

(continued on next page)

Trends

473

http://www.elsevier.com/locate/trac

Analytes

Matrix

Treatment/SPE

MS

Validation level (lg/L)

Calibration/ matrix effect

Quantification/ confirmation criteria

[43]

(27 pharmaceuticals) 5 SAs 5 TCs 7 MLs trimethoprim chloramphenicol carbadox

Environmental waters

EDTA + sample pH = 8.2 (H2SO4 or NaOH) Off-line SPE OASIS HLB Sample volume = 400 mL (preconc. · 4000)

(ESI) QqQ

1.25

Not clearly reported

1 transition + tr (<5%)

[47]

5 Qs

SW WWTP

In-tube SPME Sample volume = 800 lL

(ESI) QqQ

0.1 2

–

1 transition

[36]

Method Method Method Method

River water

Off-line SPE OASIS HLB Sample volume = 120 mL (preconc. · 1000)

(ESI) IT

0.1 1 5

Matrix-matched standards

Daughter full scan (1 product ion used for quantification)

[29]

10 SAs

WW (influent, effluent)

(1) immersion SPME sample pH = 4.5 (HCOOH) CW-TPR coated SPME fibre Sample volume = 25 mL (preconc. · 100) (2) Off-line SPE: Sample pH = 3 (H2SO4) MCX Sample volume = 500 mL (preconc. · 2000)

(ESI) QqQ

IS

1 transition

[60]

(29 pharmaceuticals) 2 MLs 1 SA 1 FQ trimethoprim

SW WWTP (influent, effluent)

Off-line SPE OASIS HLB vs Isolute ENV+ vs C18 vs OASIS MCX OASIS HLB No sample pH adjustment Sample volume = 500 mL (SW); 200 mL (effluent); 100 mL (influent) (preconc. · 500,200 and 100, respectively)

(ESI) QqQ

SW: 0.050, 1 Effluent: 0.1, 1 Influent: 1, 10

Study of different approaches to reduce matrix effect. Dilution of sample extracts

2 transitions + tr + ion ratio + tolerance (EU criteria)

[57]

(8 pharmaceuticals) 3 FQs

STP Recipient rivers SW GW

Sample pH = 10 (NaOH) Off-line SPE OASIS HLB Sample volume = 100 mL (influent); 250 mL (effluent); 500 mL (SW); 1000 mL (GW) (preconc. · 200, 500, 1000 and 2000, respectively)

(ESI) QqQ

GW, SW: 0.1 Influent: 2 Effluent: 1

Ofloxacin: IS used only in STP influents Ciprofloxacin and norfloxacin poorly recovered, therefore only a rough estimation was allowed

1 transition + tr

1: 2: 3: 4:

Line missing

7 6 3 3

TCs SAs MLs IPs

Trends in Analytical Chemistry, Vol. 26, No. 6, 2007

Ref.

Trends

474

Table 1 (continued)

tr = retention time. CE, Cephalosporine; DW, Drinking water; FQ, Fluoroquinolone; GW, Groundwater; IP, Ionophore; ML, Macrolide; NI, Nitrofurane; PEN, Penicillin; Q, Quinolone; SA, Sulphonamide; STP, Sewage-treatment plant; SW, Surface water; TC, Tetracycline ; TP, Transformation product; WW, Wastewater; WWTP, Wastewater-treatment plant. A No experimental ion ratio given. B Neither experimental ion ratio or accepted tolerance deviations given. C Not used for antibiotic determination.

[68]

Organic contaminants (include antibiotics)

SW GW

(ESI) QqQ QTOF

Detailed study on confirmation. False positives and false negatives described

Trends in Analytical Chemistry, Vol. 26, No. 6, 2007

Trends

metabolites, with interesting information regarding the removal of antimicrobials in wastewater-treatment procedures. The aim of this article is to review critically the determination of antibiotic residues in water samples by LC-MS and LC-MS2. We focus mainly on quantification and confirmation of the analytes detected in samples, as this subject has not had much coverage in the literature. We also include information about several recent papers that have not been previously reported in published reviews. The most relevant data on papers reviewed are shown in Table 1.

2. General considerations 2.1. Extraction or preconcentration of analytes Commonly used methods for determining antibiotics typically include extraction for both clean-up and enrichment of aqueous samples, due to the predicted low concentration levels present in the aquatic environment. A recent survey of literature by Barcelo`Õs group [6–8] reveals that, although different techniques are employed to extract antibiotics, such as lyophilization [14] or liquid-liquid extraction [28], the most frequently used is solid-phase extraction (SPE) [15–27,30–44] using polymeric cartridges. Among these, OASIS hydrophiliclipophilic balanced (HLB) cartridges are the most widely used [13,15,21–24,26,36,38,41–44]. C18 silica sorbents [14,40,45] have also been used, although to a lesser extent. For specific applications, cation-exchange sorbents have also been applied [25,29,31,37]. In some cases, two cartridges have been used in tandem (e.g., anion-exchange [17] or polymeric SDB-2 [39], followed by an HLB cartridge). Polar solvents (e.g., acetone, methanol or acetonitrile) are employed for elution. Due to the low LODs required, high enrichment factors are required, typically a 1000-fold preconcentration. Sample volumes have usually been in the range 100–1000 mL. Most recently, several authors have started to use online preconcentration or extraction due to its inherent advantages respect to off-line mode (e.g., little manipulation of sample or easy automation of the process). Rapid, fully automated methods have been developed (e.g., SPE [45,46], in tube-solid-phase microextraction (SPME) [47] or immersion-SPME [29] coupled on-line to LC-MS2) and process considerably lower volumes of water (less than 30 mL). One important parameter to take into account when determining antibiotics is sample pH. This parameter is critical because, in many cases, it determines the chemical form of the analytes in the solution, hence the extraction efficiency. For example, the high breakthrough of quinolones during the SPE process was minimised after acidifying the sample to pH 2.5. However, this low pH favoured penicillin G degradation. This undesirable effect was http://www.elsevier.com/locate/trac

475

Trends

Trends in Analytical Chemistry, Vol. 26, No. 6, 2007

avoided by adding the acid immediately before extraction [45]. In another example, recoveries for tetracyclines were higher than expected at low-extraction pH, surely due to the enhancement of ionization by co-extracted organic matter. However, under basic extraction conditions, recoveries were within acceptable ranges for the three tetracyclines studied [43]. Pichon et al. [48] showed that SPE co-extraction of humic and fulvic acid from water was influenced by the pH of the sample, co-extraction being lower at neutral rather than acidic pH. Sørensen and Elbaek [44] showed that recoveries for sulfadiazine and oxolinic acid were clearly influenced by the pH used during SPE.

mass ion was interpreted as a loss of water during LC-MS ionization, some experiments proved that this loss occurred in acidic aqueous solution (pH < 7.0) [51]. Contrary to this, despite performing SPE extraction at acidic pH, some authors have detected the intact parent [20]. Regarding penicillins, a methanolysis process has been observed when standards were prepared in methanol [45]. Thus, acetonitrile was considered a more appropriate solvent for preparing penicillin standards. Some compounds, such as fluoroquinolones and tetracyclines, may be affected by photodegradation, which makes it necessary to store samples at low temperatures (around 4C) in amber-glass containers.

2.2. Analyte considerations Typical problems found in multi-residue multi-class antibiotic methods come from the different physico-chemical behaviours of the analytes, which create difficulties (e.g., with simultaneous extraction). Since silanol groups of the SPE-cartridge material can bind to metal ions and tetracyclines can potentially be sorbed onto residual metals in the sample matrix [49], it may result in lower recovery by irreversible binding. Although different approaches have been reported to prevent this problem (e.g., silanization of glass material [20] or the use of other container materials (e.g., PTFE)), the most frequently used has been the addition of chelating agents (e.g., Na2EDTA [14,15,18,21 –23,40–43] or citric acid [18,23,40]) to samples to decrease the tendency for tetracyclines and macrolides to form complexes with metal ions. It has also been reported that recoveries of quinolone antimicrobials are improved with the addition of Na2EDTA [15]. An advantage of HLB cartridges used in SPE is the absence of silanol groups to which metal ions may bind. Determination of ionophore antibiotics also presents substantial problems, as these compounds exhibit limited solubility in water due to the formation of lipid-soluble cyclic complexes with alkali metal cations [38]. It has also been found that various metals catalyze the rate of inactivation or hydrolytic opening of b-lactams [50]. In these cases, all glassware used in the laboratory was heated for 1 hour at 450C, cooled and rinsed with an ethylenediaminetetraacetic acid (EDTA) solution [22,38]. Contact with glass has been avoided as much as possible in the determination of aminoglycosides, because of the high sorption affinity of these compounds to polar surfaces. Additionally, laboratory equipment made of PTFE and polypropylene was used during sample preparation [37]. It is interesting to mention that some analytes can suffer transformation processes in the water sample or in the analytical process, so one of the most widely studied antibiotics, erythromycin, is not usually detected in its original form but as a degradation product corresponding to the dehydration process [14–16,18,21,31–33,36,51]. Although the apparent difference of 18 Da in the precursor

2.3. Antibiotic metabolites or transformation products (TPs) Several studies have shown that some antimicrobial compounds, especially polar ones, are not completely removed during wastewater-treatment processes, making it interesting to determine their breakdown pathways as well as to evaluate the fate of their TPs in the environment. However, until now, most efforts have focused on detecting parent compounds, while degradation of antibiotics has scarcely been studied. This might be due to the lack of commercially available degradate standards, and also to the minor problems expected for these compounds from environmental and toxicological points of view. Recently, some authors have studied the degradation pathway of antibiotics. As an example, Halling-Sorensen et al. [52] investigated oxytetracycline degradation and evaluated the occurrence of this analyte and eight degradation products in soil-interstitial water. The parent compound and four degradation products were detected in the soil-water environment at significant concentrations.

476

http://www.elsevier.com/locate/trac

2.4. LC-MS considerations The most common stationary phase in LC-MS methods for antibiotics is the C18 reversed phase, with only a few exceptions for specific applications. Typical mobile phases comprise water/acetonitrile or water/methanol mixtures, where modifiers (e.g., formic acid [21,34,38,40], ammonium acetate [20,31] or oxalic acid [14]) are added to improve ionization efficiencies and to control pH. In some works the use of ion-pair reagents is needed, as the analytes were present as ionic forms. In these cases, perfluorinated (e.g., heptafluorobutyric anhydride (HFBA)) have been used [37,43]. Regarding interfaces, electrospray-ionization (ESI) sources has been by far the most frequently applied in antimicrobial residue determination, since it is particularly suitable for polar and moderately non-polar analytes and for thermally labile substances, although it is well known to be more prone to signal suppression than atmospheric pressure chemical ionization (APCI) [44].

Trends in Analytical Chemistry, Vol. 26, No. 6, 2007

LC-MS2 is typically required to quantify the low concentration levels of antibiotics in real-world samples. Analyzers used most in the detection or quantification of antimicrobials are ion trap (IT), especially triple quadrupole (QqQ), due to the high sensitivity and selectivity afforded through selected reaction monitoring (SRM) acquisitions, as well as to their wide linear dynamic range. Recently, the quadrupole time-of-flight (QTOF) hybrid analyzer has been explored for identification purposes, as it offers higher resolution than QqQ and elevated mass accuracy working in both MS and MS2 modes.

3. Screening and quantitative methods Different strategies can be applied for monitoring organic contaminants in environmental waters, depending on the objectives of the analysis and on the instrumentation available [53,54]. Analytical methods can be classified into different categories: 1. screening – to detect (rapidly) the presence of one analyte or a class of analytes; 2. quantitative – to quantify the amount of an analyte that may be present in the sample; 3. confirmatory – to confirm unequivocally the presence of a detected target analyte; or, 4. elucidation – to discover the identity of a non-target compound detected in the sample. 3.1. Screening Screening methods are very useful when investigating environmental samples because they allow (rapid) discrimination of samples with no detectable pollutants (negative samples) from those suspected of being positive. In some cases, they can also be used for quantitative purposes or to give a semi-quantitative estimation of the concentration level. However, a second analysis is generally required to provide an accurate quantification of the analytes and/or a reliable confirmation of their identity. Alternatives might be considered for LC-MS screening methods in the environmental field: (i) ‘‘pre-target’’ – where the analytes are selected before injection into the LC-MS system, and other compounds present in samples cannot be detected. These methods are typically limited to fewer than 20 compounds. This means that many pollutants that might be contained in the sample would not be detected even if they were present at high concentrations; and, (ii) ‘‘post-target’’ – where all the compounds eluting from the chromatographic column are measured by MS and the selection of the compound to be investigated can be made after MS data acquisition.

Trends

These methods might potentially detect an unlimited number of compounds, with the obvious limitations derived from the chromatographic and ionization behaviour of the analytes in the LC-MS system employed. Selecting one or the other alternative depends on the objective of the screening, and also, especially, on the instrument available. When dealing with antibiotics, different approaches have been used for ‘‘pre-target’’ screening. Some authors acquire two or three ions for each analyte in LC-MS methods using selected ion monitoring (SIM) mode [13,17,19,27,42,55], although MS2 seems more interesting due to its improved analytical characteristics. In MS2, when using IT, the product ion giving the highest relative abundance was typically used for quantification [18,20–23,28,38,41,56]. Full-scan and full-scan-MS2 data have also been collected simultaneously using data-dependent scanning [32]. In this case, the data-dependent criteria included a minimum MS signal for 14 specified precursor masses. Full-scan data were used for quantification, while full-scan-MS2 data were used for structural confirmation of target antibiotics. A drawback of IT instruments comes from the difficulties of measuring product ions with m/z lower than 30% of that of precursor ion, which may limit their applicability in some particular cases. Regarding LC-MS2 with QqQ analyzers, the acquisition of only one transition per analyte in SRM mode seems sufficient for screening purposes, although it is clearly insufficient for reliable confirmation. Using one transition would allow discrimination between negative samples and (possible) positives [15,24,29,37,39,43,47, 57,58] that should be subsequently confirmed. As an example, Fig. 2 shows the time-scheduled SRM chromatograms of several antibiotics belonging to different families. In those cases where more than one transition is acquired, the most sensitive is normally used for quantification, while the rest are used for confirmation [25,32–34,44–46,59,60]. The situation is different using TOF-MS, as this instrument does not filter out any ions prior to detection, making it ideal for a ‘‘post-target’’ screening. Although very little used, this analyzer has extraordinary potential for screening purposes, and interesting applications are expected in the near future. Benotti et al. [24] used LC-TOF-MS for screening antibiotics and other organic contaminants in wastewater-treatment-plant (WWTP) effluent at low analyte concentrations (20–450 ng/L). 3.2. Matrix effects and quantification One of the main problems in quantitative LC-MS analysis is the susceptibility of API interfaces to co-extracted matrix components. Matrix effects typically result in an important loss of sensitivity as a consequence of suppressing ionization from the co-extracted components of the matrix, thus hampering the analyte quantification.

http://www.elsevier.com/locate/trac

477

Trends

Trends in Analytical Chemistry, Vol. 26, No. 6, 2007

MU382 Sm (Mn, 2x1) %

100

Clarithromycin

8: MRM of 9 Channels ES+ 590.5 > 158.1 3.56e4

0 20.00

100

8: MRM of 9 Channels ES+ 590.5 > 158.1 4.73e4

100

30.00 40.00 6: MRM of 8 Channels ES+ 425.1 > 126 2.26e5

Clindamycin

10.00 MU407 Sm (Mn, 2x1)

20.00

30.00 40.00 6: MRM of 8 Channels ES+ 425.1 > 126 3.03e4

20.00

30.00 40.00 6: MRM of 8 Channels ES+ 375.5 > 83.1 2.14e4

20.00

30.00 40.00 4: MRM of 7 Channels ES+ 332.2 > 231 2.39e3

20.00

30.00 40.00 3: MRM of 3 Channels ES+ 291.1 > 230.1 1.45e4

20.00

30.00 40.00 2: MRM of 6 Channels ES+ 304 > 217 4.50e3

20.00

30.00 40.00 1: MRM of 4 Channels ES+ 407.3 > 126.1 4.61e3

100 %

%

MU407 Sm (Mn, 2x1)

0

10.00 MU382 Sm (Mn, 2x1)

0

0

10.00 MU382 Sm (Mn, 2x1)

20.00

100

30.00 40.00 6: MRM of 8 Channels ES+ 375.5 > 83.1 3.60e3

0 10.00 MU382 Sm (Mn, 2x1)

20.00

100

30.00 40.00 4: MRM of 7 Channels ES+ 332.2 > 231 4.95e3

20.00

100

30.00 40.00 3: MRM of 3 Channels ES+ 291.1 > 230.1 5.51e4

20.00

%

100

30.00 40.00 2: MRM of 6 Channels ES+ 304 > 217 2.81e4

Pipedimic acid

0 10.00 MU382 Sm (Mn, 2x1)

20.00

100

30.00 40.00 1: MRM of 4 Channels ES+ 407.3 > 126.1 9.84e4

0

Time 20.00

0 10.00 MU407 Sm (Mn, 2x3) 100

0 10.00 MU407 Sm (Mn, 2x3) 100

0 10.00 MU407 Sm (Mn, 2x3) 100 %

%

Lincomycin 10.00

100

%

%

Trimethoprim

0 10.00 MU382 Sm (Mn, 2x1)

0 10.00 MU407 Sm (Mn, 2x3) %

%

Ciprofloxacine

0 10.00 MU382 Sm (Mn, 2x1)

100 %

Azithromycin

10.00 MU407 Sm (Mn, 2x1)

%

%

B

%

A

30.00

40.00

0

Time 10.00

20.00

30.00

40.00

Figure 2. SPE-LC-MS2 chromatograms (QqQ analyser) for selected antibiotics: (A) 50 ng/L standard solution; and, (B) real surface-water sample.

Although less frequent, enhancement of the analyte signal can also occur. Matrix effects depend on the analyte-sample combination, so the strategy adopted to correct them should take into account the variability of the matrix within the set of samples to be analyzed (e.g., river water, and STP influent and effluent). Different approaches have been used to minimize or to correct matrix effects in the determination of antibiotics (e.g., increasing sample pretreatment, performing matrix-matched calibration, quantifying by the standardaddition method, using an isotope-labeled internal standard (IS) or simply diluting the sample). Solutions associated with reducing matrix components prior to analysis by applying selective extraction and/or improved sample clean-up have the drawback of increasing sample manipulation, which increases the possibility of associated analytical errors. This approach may not be the most convenient for monitoring programs where rapid methods are preferred. Diluting the sample is a simple alternative to minimize matrix effects, but it would compromise method sensitivity, an important parameter due to the low limits of quantification (LOQs) required in antibiotic analysis. Thus, Go´mez et al. [34] avoided matrix effects 478

http://www.elsevier.com/locate/trac

for compounds determined in both negative and positive ESI by diluting the SPE extracts three-fold. However, this dilution was insufficient for four analytes (erythromycin, atenolol, paroxetine and fluoxetine) that showed severe ion suppression and still experienced a matrix effect of around 40%. For these four compounds, ion suppression was completely eliminated with a dilution of 1:10, but the decrease in sensitivity was noticeable. The same group [60], after evaluating different approaches to solve matrix effects, avoided signal suppression observed in effluent wastewaters by diluting sample extracts three-fold. When analyzing influent wastewaters, a five-fold dilution was required to solve this problem. As before, a considerable decrease in sensitivity was observed. Similarly, Yang et al. [18] observed that dilution of the raw-influent samples with deionized water increased the signal intensity of the analytes to a certain extent. A possible explanation of this effect might be suppression of the matrix ion by compounds co-extracted with the analyte. These interferences would be minimized by sample dilution, improving the analyte ionization and therefore obtaining a response higher than expected in relation to the dilution factor.

Trends in Analytical Chemistry, Vol. 26, No. 6, 2007

Although matrix effects are usually corrected in other analytical fields using matrix-matched standards calibration (e.g., food analysis), this approach is unfortunately difficult to apply in environmental aqueous samples, due to their different origin and matrix composition, the latter varying significantly in time on some occasions. In such cases, the selection of a representative blank sample with a matrix content similar to the samples is almost impossible. Despite these limitations, this approach is quite widely used in water analysis [14,15,18,21–23,34,36–38,41]. For example, Kim and Carlson [36] prepared matrix-matched calibration curves, comprising several river-water samples spiked at different concentration levels. Average recoveries for all compounds studied were in the range 77–127% with RSD below 13% for the three measured concentrations, except for minocycline, where recoveries <30% were obtained. Miao et al, [15] applied this approach for the determination of 27 macrolides, quinolones and sulphonamide antibiotics in WWTP effluents, obtaining quantitative recoveries in all cases. Similarly, Go´mez et al. [34] prepared calibration curves from the SPE diluted extract in spiked hospital wastewater to reduce inaccuracies due to matrix components. Surprisingly, Hirsch et al. [14] prepared calibration standards by adding the standard solution to mountain spring water for the determination of 18 antibiotics in STP-effluent and surface-water samples, for which the matrix compositions were surely quite different from those of the blank samples used for calibration. The use of an IS is an ideal, simple approach, but it may be troublesome in multi-residue LC-MS analysis due to the large number of ISs required (ideally, the isotopically-labeled analyte) for the correction of the effects of all individual matrices on the analytes. Other drawbacks of using isotopically-labeled compounds are the high cost and the low commercial availability of reference standards, although more facilities have become available to obtain labeled ISs in recent years. Most methods reported so far have used only one or two ISs or surrogates (either analyte-analogue or labeled) for all compounds investigated. However, this approach may not compensate for signal suppression or enhancement for the wide range of chemical classes that can exist in a sample, as it would imply that the matrix effect was uniform throughout the chromatographic run, and that may not be the case. Thus, although sulfamerazine (used as IS) closely resembles sulfamethazine and sulfamethoxazole, the chromatographic retention times of these three sulphonamides span a wide range (9.5 min, 12.6 min and 18 min, respectively), leading to different matrix effects caused by co-eluting constituents. Despite using ISs, recoveries in wastewater matrices were in the ranges 37–64%

Trends

for sulfamethazine and 56–65% for sulfamethoxazole [17]. Another example was shown by Hilton and Thomas [20], who quantified several antibiotics using only one IS, obtaining recoveries in the range 56–123%. Several illustrative examples can be found in the literature of a variety of analytes determined by LC-MS2, where there were difficulties in obtaining an adequate IS [61,62]. When using an IS different from the labeled analyte, a similar retention time between the analyte and the IS does not always ensure adequate quantification, so, although trimethropym and the IS (sulfamethazinephenyl-13C6) presented similar retention times (difference of about 0.5 min), recoveries for this compound were unsatisfactory [16], possibly due to differences in their structure resulting in the ionization of each compound being differently affected by matrix components. The best way to ensure proper correction of matrix effects would be to use a different labeled IS for each analyte. This was done in the method developed by Go¨bel et al. [16], who used five different commercial labeled ISs for the reliable quantification of five sulphonamides. In the same method, recoveries for another six antibiotics were generally above 80% in all matrices studied (primary, secondary and tertiary effluents) with the exception of one analyte (trimethoprim). The lower recoveries obtained for this compound (30–47%) were caused by the use of a less than ideal IS. Unexpectedly, despite the use of the analyte-labeled IS, recoveries of about 130% with an RSD of 17% were obtained for sulfamethazine [42]. The last option for dealing with matrix effects is timeconsuming, laborious quantification by standard additions for each sample and analyte investigated. This approach results in more analyses per sample instead of one multiple analysis, as each sample has to be calibrated and quantified separately. Besides, although standard addition can correct for matrix effects, it cannot avoid a loss of sensitivity. Renew and Huang [17] assessed quantification of trimethoprim by the standardaddition method, due to the non-availability of an appropriate IS. Average recoveries for the two wastewater matrices tested were in the range 98–109% for a spike with a concentration of 1 lg/L. 3.3. Validation of the analytical methodology Validation of the analytical method usually includes estimating the following parameters: sensitivity; LOD; LOQ; linearity; recovery; and, precision. Validation is typically carried out at two or more levels in an attempt to cover the concentration ranges expected in samples. Ideally, the lowest level validated should be the LOQ. However, it is quite common to report concentration levels much lower than those validated when analyzing real-world samples. In some cases, there is no evidence http://www.elsevier.com/locate/trac

479

Trends

Trends in Analytical Chemistry, Vol. 26, No. 6, 2007

that accurate quantification is performed at the levels found in samples. The great interest and concern associated with the presence of antibiotics in the aqueous environment make it very important to use adequate quality criteria that substantiate the findings presented before reporting measurements below the analytical reporting levels [10,11]. LODs and LOQs for antibiotic analysis have been estimated using several criteria, including:  signal/noise ratio (S/N) [15,25,30,34,35,37,45,46];  selection of the second lowest point of the calibration curve [14]; and,  statistical methods [13,18,22,26,38,40,44]. Even using a particular approach (e.g., S/N ratio), different criteria are sometimes considered. Also, while some authors calculate the S/N ratio from a lowconcentration reference standard, others use a sample spiked at a low level. Although typical values (S/N = 3 and S/N = 10) are applied for LOD and LOQ, respectively, other values have been found (in the range 3–10), depending on the author. It is therefore difficult to perform realistic comparison of the LODs reported in the literature, because the criteria and the methodology used for their estimation are very variable. In addition, LODs are continually decreasing with each new generation of mass spectrometers. It seems more realistic to define an LOQ objective considering the concentration levels expected in samples (e.g., below 0.1 lg/L) and fully validate the method using blank samples spiked at this level [45]. In this way, accurate quantification at the low concentrations of analyte would be more supported, as occurs in pesticide-residue analysis [63]. For all these reasons, we do not give LOD values in Table 1, but instead show the validation levels. For quantification purposes, the latter give more realistic information on the concentration levels for which the method can be used accurately. The lack of chromatograms, even for reference standards, in most papers published so far is surprising. Real chromatograms of samples at the levels of antibiotics found would support the applicability of the methods used and would be highly recommendable. Moreover, a full validation should include confirmation criteria for the identity of the analyte at the same levels at which it is quantified, obviously including the LOQ. This interesting aspect is not commonly treated in the scientific literature, and we will discuss it in the next section.

4. Confirmatory methods Confirmation of positive pollutant findings in the environmental field has become a matter of concern due to the negative effects associated with erroneous 480

http://www.elsevier.com/locate/trac

identifications. Reliable analytical methods that lead to accurate quantification of analytes have to be developed, but also, and even more importantly, the analyte needs to be unequivocally identified at the concentration levels of interest. The latter is of outstanding importance, especially when maximum permitted levels are exceeded in the samples analyzed. However, despite the increasing interest in obtaining reliable data. There is no detailed regulation for confirmation of analyte identity in the environmental field. This lack of guidelines has encouraged some authors to use those elaborated by the World Anti-Doping Agency (WADA) [64], the US Food and Drug Administration (FDA) [65] or the European Union (EU) [66] in other applied fields. For example, the criteria established by European Commission (EC) Decision 2002/657/EC for the confirmation of contaminants in samples of animal origin has become one of the most widely applied in recent years [18,31,44,45,60]. In summary, this EC Decision proposes a system of Identification Points (IPs), where at least three IPs are required (four in the case of banned compounds) to confirm a positive finding. The number of IPs earned by a specific analysis depends on the technique used, differentiating between MS and MSn, and between low-resolution and high-resolution instruments. Additionally, the deviation of the relative intensity of the recorded ions must not exceed a certain percentage of the reference standard, and the retention time must not deviate more than 2.5%. This leads to the needs to acquire at least three ions in single MS instruments (i.e. 3 IPs), or to select one precursor ion and record two product ions in low-resolution MS2 instruments (i.e. 4 IPs). The main advantage of using IPs is that identity can be verified in a well-described, uniform way. However, the number of assigned IPs depends on the mass analyzer used, not on the quality of the information acquired. In our opinion, the specificity of the ions or transitions selected should also be considered in the near future, as it plays an important role in the confirmation process. Another problem arises from the EC definition of ‘‘high-resolution MS instruments’’ independent of the mass accuracy that they obtain. This definition does not sufficiently take into account the relevant parameter of accurate mass, which is relevant in the identification of a pollutant. Despite some limitations, the Guidelines in EC Decision 2002/657/EC provide a useful starting point for the confirmation of organic micropollutants. Most published papers based on LC-MS or LC-MS2 scarcely deal with the confirmation of antibiotics detected in water samples, possibly due to difficulties resulting from the extremely high sensitivity needed (typically at low-ng/L levels), the lack of analytical information on the sample matrix composition and the absence of accepted universal criteria to perform a reliable identification with this technique. Several published

Trends in Analytical Chemistry, Vol. 26, No. 6, 2007

methods only acquired one ion (LC-MS) or one transition (LC-MS2) for each analyte, so they should be considered screening or determinative methods (normally quantification is possible) [15,20–23,28,36–41,43,47,56,67], but not confirmatory methods. Several authors have monitored two ions (using SIM) [19,27,42], but the deviation in the ion-abundance ratio [27] was taken into account in only a few cases. In other works [13,17], the lack of selectivity of single MS was dealt with by performing two analyses: one using an ion for quantitation, usually the molecular ion; and, a second under conditions that induce fragmentation in the source to detect one or two, more or less specific, fragments for confirmation purposes. The deviations in both retention time and relative abundance were also considered. Regarding LC-MS2 (both QqQ and IT), some authors only use one product ion and consider the analytes to be positively identified if the selected ‘‘transition’’ shows any signal [20–23,36–41,43,47,56,67]. The deviation in the retention time [43] has also been used as an additional criterion. It is noteworthy that the transition acquired in several LC-MS2 methods corresponded to low specific losses, such as water [20,21,36,38], ammonium [23] or carbon dioxide [47]. Unfortunately, present guidelines do not make reference to the ‘‘quality’’ of the MS information provided. This omission is relevant as the selection of the ions or transitions may be quite arbitrary and may lead to poor-quality data, insufficient for a safe confirmation, because the possibilities for interferences would increase. In our experience, the selection of transitions of low specificity notably increases the possibility of finding false positives [68]. We have reported several examples of antibiotic ‘‘false positives’’ (e.g., for oxolinic acid, where the most sensitive SRM transition (loss of water, 262 fi 244), was selected for quantification). The low specificity of this loss led to finding several ‘‘positives’’, which were revealed as false when all the remaining available transitions were acquired (Fig. 3). As a result, confirmation of the identity of organic micropollutant findings based on the acquisition of only one MS2 transition seems not to be sufficiently reliable. This approach might be used for a rapid screening of organic pollutants in water, but more confidence is needed in the confirmation criteria applied. Recently, a few authors have applied confirmation rules in the environmental field, normally by extrapolating existing guidelines from other fields. The most usual approach has been the acquisition of two transitions in LC-MS2 using QqQ instruments [16,25,34,35,44,46]. Additionally, when confirming a positive, some authors also consider the deviation of the calculated concentrations [16] or the relative abundance from the two product ions [34] to be lower than 10%. The deviation in the retention time with

Trends

respect to a reference standard has also been included as an additional criterion for confirmation [25,34]. Another option is to develop a rapid screening method by acquiring only one SRM transition for each analyte. Positive samples are then re-injected for a second independent analysis, when another transition is recorded for each compound [26,31,33]. Normally, the ion-ratio deviation is also calculated and the EC criteria followed [26,31]. The occurrence of a false positive under these circumstances seems quite difficult, as it would imply the presence of an interferent sharing analyte-retention time and two transitions with similar relative abundance to those of the analyte. However, a false positive was found in the determination of the quinolone flumequine in surface water [68]. The two most sensitive transitions selected for flumequine were observed in a sample, with both retention-time deviation (0.75%) and ion-intensity-ratio deviation (10%) within the limits previously established, so this detection would have been reported as positive. Fortunately, the confirmation analysis applied in this case for antibiotics included the acquisition of the highest number of available transitions for each analyte [45]. The acquisition of four additional transitions then revealed that the compound detected did not correspond to flumeq;uine because none of the additional transitions acquired were observed in the sample. The occurrence of this false positive was possibly related to the ion selection carried out when working with QqQ in SRM mode, as the transitions selected had poor selectivity: (262 fi 244) that corresponded to the neutral loss of water, and (262 fi 202) that corresponded to the neutral loss of acetic acid. However, it must be emphasized that this false positive was the only one found among all samples investigated for antibiotics, so the occurrence of false positives when acquiring two MS2 transitions, considering also ion-ratio deviations, seems exceptional. When acquiring all available transitions, the main limitation came from the differing sensitivities attained for each transition. At low analyte concentrations, this makes it difficult to obtain an adequate response for the less sensitive transitions. Despite this drawback, many analytes present several transitions with enough sensitivity to allow a reliable identification at low concentrations [68]. In acquiring two transitions, it is important to take into account that they must be as specific as possible, trying to avoid the use of common losses (e.g., H2O, CO2, and HCl) in order to prevent false positives [68]. In some cases, a compromise between sensitivity and selectivity has to be reached. Recently, the number and the concept of ‘‘earned IPs’’ have been revised, and our group has pointed out the importance of the inherent specificity of the product ion selected [68,69]. http://www.elsevier.com/locate/trac

481

Trends

Trends in Analytical Chemistry, Vol. 26, No. 6, 2007

NF 067 A CO 100

MRM of 7 Channels ES+ 304 > 70. 3 3. 76e3 Ar ea

13.63; 195

% 0 CO NF 067 100

MRM of 7 Channels ES+ 304 > 162 3. 59e3 Ar ea

13. 65 708

% 0 CO NF 067 100

MRM of 7 Channels ES+ 304 > 2 86. 1 1. 19e4 Ar ea

13. 65 2673

% 0 CO NF 067 100

MRM of 7 Channels ES+ 304 > 148 6. 06e3 Ar ea

13. 65 1407

%

MRM of 7 Channels ES+ 304 > 189 1. 11e4 Ar ea

13. 65 2639

%

11.00 12.62 14.70

MRM of 7 Channels ES+ 304 > 70.3 1.46e4 15.19

% 0 CO NF064

MRM of 7 Channels ES+ 304 > 162 7.49e3 Ar ea

13.49 960

100 % 0 CO NF064 100

13.52 2525

MRM of 7 Channels ES+ 304 > 2 86.1 1.46e4 Ar ea

13.54 1299

MRM of 7 Channels ES+ 304 > 148 6.59e3 Ar ea

13.54 2812

MRM of 7 Channels ES+ 304 > 189 1.13e4 Ar ea

13.54 5946

MRM of 7 Channels ES+ 304 > 217 2.33e4 Ar ea

% 0 CO NF064 100

0 CO NF064 100 %

0 CO NF 067 100

100

%

0 CO NF 067 100

B CO NF064

MRM of 7 Channels ES+ 304 > 217 2. 44e4 Ar ea

13. 65 6122

%

0 CONF064 100 %

0 10.00

12. 50

15.00

NF 09 3 C CO 10 0 0 CO NF 09 3

MRM of 7 Channels ES+ 26 2 > 215. 9 2. 73 e3 Ar ea

17. 39 12 59

% 0 CO NF 09 3 17. 42 10 22

10 0 % 0 CO NF 09 3 10 0

17. 42 39 8

% 0 CO NF 09 3 10 0

17. 39 13 22

% 0 CO NF 09 3 10 0

17. 39 22 06

% 0 CO NF 09 3 10 0

Ti me 20.00

MRM of 7 Channels ES+ 26 2 > 221. 2 1. 00 e3 Ar ea

%

10 0

17. 50

17. 42 95 42

%

MRM of 7 Channels ES+ 26 2 > 172. 1 2. 59 e3 Ar ea MRM of 7 Channels ES+ 26 2 > 118. 1 1. 93 e3 Ar ea MRM of 7 Channels ES+ 26 2 > 129. 9 4. 03 e3 Ar ea MRM of 7 Channels ES+ 26 2 > 16 0 4. 41 e3 Ar ea MRM of 7 Channels ES+ 26 2 > 244. 1 1. 82 e4 Ar ea

0

Ti me 15 .00

20. 00

25 .00

0 10.00

12.50

15.00

D CONF095 10 0

17.50

Time 20.00

MR M of 7 C han nels ES + 26 2 > 221. 2 1.08e3 Ar ea

% 5 CO NF 09 5

MR M of 7 C han ne ls ES + 26 2 > 215. 9 2. 72 e3 Ar ea

10 0 % 0 CO NF 09 5 15. 69

10 0

MR M of 7 C han ne ls ES + 26 2 > 172. 1 2. 47 e3

% 0 CONF095 19. 52

10 0

MR M of 7 C han ne ls ES + 26 2 > 118. 1 2. 92 e3

% 0 CONF095

MR M of 7 C han ne ls ES + 26 2 > 129. 9 3. 96 e3

10 0 % 0 CONF 09 5

MR M of 7 C han ne ls ES + 26 2 > 16 0 3. 47 e3

10 0 % 0 CONF095 10 0

17. 15 166 84

%

MR M of 7 C han ne ls ES + 26 2 > 244. 1 5. 35 e4 Ar ea

0

Ti me 15 .00

20. 00

25 .00

Figure 3. Confirmation of findings by LC-MS2 (QqQ). (A) standard of 10 ng/L pipedimic acid; (B) Surface-water sample collected from the Spanish area of the Mediterranean containing 9.7 ng/L of pipedimic acid; (C) standard of oxolinic acid 10 ng/L; (D) surface-water sample suspected to contain oxolinic acid, but confirmed to be a false positive if only the most sensitive transition (262 > 244) is acquired (Reproduced from [45] with permission).

Another problematic matter is the possibility of reporting false negatives, which can occur when one of the two transitions is interfered (shared) by an unknown 482

http://www.elsevier.com/locate/trac

compound present in the sample matrix. When this happens, the ion-abundance ratio would be modified, and high deviations, compared to a reference standard,

Trends in Analytical Chemistry, Vol. 26, No. 6, 2007

might be obtained. Under these circumstances, although the analyte was present in the sample, it would be reported as negative because of the non-compliance in the ion-intensity ratio, leading to a false negative [68]. IT analyzers have also been used for the confirmation of positive samples [18,30,32] although less frequently that QqQ. Batt and Aga [32] simultaneously collected full-scan and full-scan-MS2 spectra by using datadependent scanning. In other cases, two analysis were performed [18,30], one for screening and one for confirmation. Samples were then confirmed by measuring two product ions together with their ion ratio [18] or by MS3 [30]. However, although the LC-MS3 procedure is highly selective, it was approximately seven-fold less sensitive than MS2, so it is only recommended for higher concentrations [30]. Despite the inherent confirmation potential of IT-MS2, where a complete daughter full scan is acquired, there has not been much evidence of the confirmation process in real-world samples. MS instruments with elevated resolution and massaccuracy capabilities, such as TOF-MS, have recently been used for confirmation in the environmental field. The accurate mass obtained by TOF mass analyzers in full-scan mode is as a valuable parameter for confirmation of positive samples [54]. On some occasions, its potential can be limited when using API sources due to the difficulty of achieving more than one significant ion. Identification based on the mass error obtained on just one ion has been applied for antibiotics. However, this approach might be inadequate, as the number of compounds sharing the same empirical formula, and therefore the exact mass, can be surprisingly high, making information on fragments necessary [24]. The number of IPs earned by measuring one ion in a TOF instrument could be up to 2 depending on the mass error [69], which would be below the minimum required for a safe confirmation [66]. Hybrid QTOF-MS can solve some of these limitations because it allows the measurement of all product ions with accurate mass (so product-ion selection is unnecessary). This leads to a notable increase in the confirmation capabilities and in reliability due to the greater amount and better quality of information gathered, compared with QqQ instruments. Confirmation performed by QTOF can be considered as an ultimate, unequivocal confirmation, as the risk of reporting false positives is extremely low. Besides, a single LC run suffices for both screening and confirmation, which saves a lot of time. Stolker et al. [31] used QTOF-MS for screening and confirmation of low concentrations of antimicrobials from different classes. In their study, confirmation of ‘‘positive’’ samples was based on the ion ratios of two MS2 transition ions and their accurate masses. The main drawback of QTOF instruments is their lower sensitivity compared with QqQ working in SRM

Trends

mode. An attempt to improve sensitivity in QTOF detection of penicillins and quinolones in surface water and groundwater was carried out by Pozo et al. [45], who increased the sample volume extracted in off-line SPE. However, the method sensitivity was lower than that obtained by on-line SPE-LC and QqQ using lower sample volumes. New-generation QTOF instruments will surely solve this limitation and we expect that enhanced technique will dramatically increase its application in the environmental field in the very near future.

5. Conclusions The occurrence of antibiotics in the environment, especially in aquatic compartments, has become a matter of concern in recent years. The improved sensitivity and selectivity of MS2 make LC-MS2 an ideal technique for the trace-level determination of these compounds in water. The application of advanced LC-MS2 technologies to environmental analysis has allowed the determination of a broader range of compounds and therefore permitted more comprehensive assessment of environment. Although some authors have used LC-MS in SIM mode with a single quadrupole analyzer, the majority of articles reviewed have applied LC-MS2 with QqQ or IT to determine antibiotic residues in water. The high sensitivity achieved in SRM mode makes QqQ instruments ideal for screening target analytes, due to the excellent characteristics of the LC-MS2 methods (improved sensitivity and selectivity, little sample manipulation and rapid analysis). However, correct quantification can be hampered by matrix effects, which typically result in an important loss of sensitivity as a consequence of ionization suppression by the co-extracted components of the matrix. Different approaches have been applied to solve or to minimize this problem, one of the simplest, most effective solutions being the use of labeled (or analogue) ISs. Nevertheless, this approach may be troublesome in multi-residue LC-MS2 analysis due to the high number of ISs required. Confirmation of positive findings of organic pollutants in the environment is of outstanding importance due to the undesirable effects associated with erroneous identifications, so appropriate criteria are required for confirmation of antibiotics detected in water. Using one MS2 transition and retention-time deviation is insufficient for a safe confirmation, so at least two transitions are required, although the specificity and the ion-intensity ratio of the transitions selected are of crucial importance for reliable identification of antibiotics at the low concentration levels usually present in water. More critical is the use of LC-MS in SIM mode, where the measurement of only one or two ions is insufficient for a safe identification of antibiotics in water. http://www.elsevier.com/locate/trac

483

Trends

Trends in Analytical Chemistry, Vol. 26, No. 6, 2007

In spite of the importance of the confirmation process, it has scarcely been treated in the papers cited as using LC-MS methods. Most papers deal with quantitative methods and report the antibiotic levels found in samples, but only a few deal with the confirmation of the analytes. Normally, when analyzing real-world samples, no evidence is given to support the work performed, so there are rarely reports of data on experimental ionabundance ratios, deviations accepted to report a sample positive, or chromatograms of real samples, although this information is valuable to help the reader to understand the analytical problems found when determining antibiotics in the aqueous environment. The reliable identification of antibiotics in water is problematic due to the low concentration levels found in environmental samples (typically below 0.1 lg/L). Under these circumstances, the number of potential interferences can increase dramatically. As the most sensitive transition is typically used in LC-MS2 methods for quantification, the confirmation can be hampered due to the lower sensitivity commonly associated with the second or other additional confirmatory transitions. Although higher antibiotic levels (above 1 lg/L) can be found in urban wastewater, the number and the concentration of matrix interferences also dramatically increase in these samples, again making reliable confirmation difficult. The inherent characteristics of TOF and hybrid QTOF make these analyzers more than adequate for qualitative purposes. Their high resolution (FWHM > 5000) and high mass accuracy (<5 ppm) improve their suitability for screening purposes. Moreover, hybrid QTOF has the capability to perform product-ion full scan with accurate mass. Despite all these advantages, these two instruments have scarcely been used in antibiotics analysis, mainly due to their high cost. Besides, their lower sensitivity, when compared to a QqQ working in SRM mode, and limited linear dynamic range can make identification and correct quantification troublesome at low analyte concentrations. New generations of QTOF instruments, with improved capabilities such as faster spectra acquisition, will surely increase their applicability in environmental samples in the near future. Given the high public and health concern associated with this field, it is highly desirable, from both analytical and regulatory perspectives, that confirmation of antibiotics detected in environmental samples by LC-MS techniques receives due attention in the near future.

Acknowledgement The authors thank the Generalitat Valenciana (GV04A/ 710) and Fundacio´ Bancaixa (Project P1 1B2004-31) for financial support to investigate the presence of 484

http://www.elsevier.com/locate/trac

antibiotics in water. M. Iba´n˜ez is very grateful to the Generalitat Valenciana for her pre-doctoral grant. The authors are very grateful to the Serveis Centrals dÕInstrumentacio´ Cientı´fica (SCIC) of University Jaume I for using the Quattro LC triple quadruple and QTOF I mass spectrometers.

References [1] T.A. Ternes, Trends Anal. Chem. 20 (2001) 419. [2] M.J. Lo´pez de Alda, S. Dı´az-Cruz, M. Petrovic, D. Barcelo´, J. Chromatogr., A 1000 (2003) 503. [3] I. Ferrer, E.M. Thurman (Editors), Liquid Chromatography/Mass Spectrometry, MS/MS and Time-of-Flight MS Analysis of Emerging Contaminants, ACS Symposium series, vol. 850, American Chemical Society, Washington, DC, USA, 2003. [4] C. Zwiener, F.H. Frimmel, Anal. Bioanal. Chem. 378 (2004) 862. [5] S. Richardson, T.A. Ternes, Anal. Chem. 77 (2005) 3807. [6] M. Petrovic, M.D. Hernando, M. Silvia Dı´az-Cruz, D. Barcelo´, J. Chromatogr., A 1067 (2005) 1. [7] M. Silvia Dı´az-Cruz, D. Barcelo´, Anal. Bioanal. Chem. 386 (2006) 973. [8] M. Gros, M. Petrovic, D. Barcelo´, Anal. Bioanal. Chem. 386 (2006) 941. [9] S.D. Richardson, Anal. Chem. 78 (2006) 4021. [10] A.E. Till, Environ. Sci. Technol. 37 (2003) 1052. [11] A.E. Till, Sci. Total Environ. 350 (2005) 273. [12] P.E. Stackelberg, E.T. Furlong, M.T. Meyer, S.D. Zaugg, Sci. Total Environ. 329 (2004) 99. [13] J.D. Cahill, E.T. Furlong, M.R. Burhardt, D.W. Kolpin, L.G. Anderson, J. Chromatogr., A 1041 (2004) 171. [14] R. Hirsch, T.A. Ternes, K. Haberer, A. Mehlich, F. Ballwanz, K.L. Kratz, J. Chromatogr., A 815 (1998) 213. [15] X. Miao, F. Bishay, M. Chen, C.D. Metcalfe, Environ. Sci. Technol 38 (2004) 3533. [16] A. Go¨bel, C.S. McArdell, M.J.-F. Suter, W. Giger, Anal. Chem. 76 (2004) 4756. [17] J.E. Renew, C.H. Huang, J. Chromatogr., A 1042 (2004) 113. [18] S. Yang, J. Cha, K.H. Carlson, Anal. Bioanal. Chem. 385 (2006) 623. [19] S. Reverte´, F. Borrull, P. Pocurull, R.M. Marce´, J. Chromatogr., A 1010 (2003) 225. [20] M. Hilton, K.V. Thomas, J. Chromatogr., A 1015 (2003) 129. [21] S. Yang, K.H. Carlson, J. Chromatogr., A 1038 (2004) 114. [22] J.M. Cha, S. Yang, K.H. Carlson, J. Chromatogr., A 1115 (2006) 46. [23] S. Yang, J. Cha, K.H. Carlson, J. Chromatogr., A 1097 (2005) 40. [24] M.J. Benotti, P. Lee Ferguson, R.A. Rieger, C.R. Iden. C.E. Heine, B.J. Brownawell, in: [3], pp. 109–127. [25] S. Castiglioni, R. Bagnati, D. Calamari, R. Fanelli, E. Zuccato, J. Chromatogr., A 1092 (2005) 206. [26] C. Hartig, T. Storm, M. Jekel, J. Chromatogr., A 854 (1999) 163. [27] C.S. McArdell, E. Molnar, M.J.-F. Suter, W. Giger, Environ. Sci. Technol. 37 (2003) 5479. [28] D.E. Koch, A. Bhandari, L. Close, R.P. Hunter, J. Chromatogr., A 1074 (2005) 17. [29] V.K. Balakrishnan, K.A. Terry, J. Toito, J. Chromatogr., A 1131 (2006) 1. [30] G. Hamscher, S. Sczesny, H. Hoˇper, H. Nau, Anal. Chem. 74 (2002) 1509. [31] A.A.M. Stolker, W. Nielsing, E.A. Hogendoorn, J.F.M. Versteegh, R. Fuchs, U.A.T. Brinkman, Anal. Bioanal. Chem. 378 (2004) 955.

Trends in Analytical Chemistry, Vol. 26, No. 6, 2007 [32] A.L. Batt, D.S. Aga, Anal. Chem. 77 (2005) 2940. [33] S. Abuin, R. Codony, R. Compan˜o´, M. Granados, M.D. Prat, J. Chromatogr., A 1114 (2006) 73. [34] M.J. Go´mez, M. Petrovic, A.R. Ferna´ndez-Alba, D. Barcelo`, J. Chromatogr., A 1114 (2006) 224. [35] D. Perret, A. Gentili, S. Marchese, A. Greco, R. Curini, Chromatographia 63 (2006) 225. [36] S.C. Kim, K.H. Carlson, Anal. Bioanal. Chem. (doi:10.1007/ s00216-006-0613-0). [37] D. Lo¨ffler, T.A. Ternes, J. Chromatogr., A 1000 (2003) 583. [38] J.M. Cha, S. Yang, K.H. Carlson, J. Chromatogr., A 1065 (2005) 187. [39] T. Christian, R.J. Schneider, H.A. Farber, D. Stutlarek, M.T. Meyer, H.E. Goldbach, Acta Hydrochim. Hydrobiol. 31 (2003) 36. [40] J. Zhu, D.D. Snow, D.A. Cassada, S.J. Monson, R.F. Spalding, J. Chromatogr., A 928 (2001) 177. [41] S. Yang, J. Cha, K.H. Carlson, Rapid Commun. Mass Spectrom. 18 (2004) 2131. [42] M. Lindsey, M. Meyer, E.M. Thurman, Anal. Chem. 73 (2001) 4640. [43] C. Hao, L. Lissemore, B. Nguyen, S. Kleywegt, P. Yang, K. Solomon, Anal. Bioanal. Chem. 384 (2006) 505. [44] L.K. Sørensen, T.H. Elbaek, Chromatographia 60 (2004) 287. [45] O.J. Pozo, C. Guerrero, J.V. Sancho, M. Iba´n˜ez, E. Pitarch, E. Hogendoorn, F. Herna´ndez, J. Chromatogr., A 1103 (2006) 83. [46] K. Stoob, H.P. Singer, C.W. Goetz, M. Ruff, S.R. Mueller, J. Chromatogr., A 1097 (2005) 138. [47] K. Mitani, H. Kataoka, Anal. Chim, Acta 562 (2006) 16. [48] V. Pichon, C. Cau Dit Coumes, L. Chen, S. Guenu, M.C. Hennion, J. Chromatogr., A 737 (1996) 25. [49] F.J. Schenk, P.S.J. Callery, J. Chromatogr., A 812 (1998) 99. [50] A.D. Desphande, K.G. Baheti, N.R. Chatterjee, Curr. Sci. 87 (2004) 1684. [51] R. Hirsch, Sci. Total Environ. 225 (1999) 109. [52] B. Halling-Sørensen, A. Lykkeberg, F. Ingerslev, P. Blackwell, J. Tjørnelund, Chemosphere 50 (2003) 1331. [53] F. Herna´ndez, O.J. Pozo, J.V. Sancho, F.J. Lo´pez, J.M. Marı´n, M. Iba´n˜ez, Trends Anal. Chem. 24 (2005) 596.

Trends [54] J.V. Sancho, O.J. Pozo, M. Iba´n˜ez, F. Herna´ndez, Anal. Bioanal. Chem. 386 (2006) 987. [55] F. Bruno, R. Curini, A. Di Corcia, M. Nazzari, R. Samperi, Rapid Commun. Mass Spectrom. 15 (2001) 1391. [56] R. Lindberg, P.-A. Jarnheimer, B. Olsen, M. Johansson, M. Tysklind, Chemosphere 57 (2004) 1479. [57] N.M. Vieno, T. Tuhkanen, L. Kronberg, J. Chromatogr., A 1134 (2006) 101. [58] B.J. Vanderford, R.A. Pearson, D.J. Rexing, S.A. Snyder, Anal. Chem. 75 (2003) 6265. [59] D. Calamari, E. Zuccato, S. Castiglioni, R. Bagnati, R. Fanelli, Environ. Sci. Technol. 37 (2003) 1241. [60] M. Gros, M. Petrovic, D. Barcelo´, Talanta 70 (2006) 678. [61] F. Herna´ndez, J.V. Sancho, O.J. Pozo, Anal. Bioanal. Chem. 382 (2005) 934. [62] O.A. Olsson, S.E. Baker, J.V. Nguyen, L.C. Romanoff, S.O. Udunka, R.D. Walker, K.T. Flemmen, D.A. Barr, Anal. Chem. 76 (2004) 2453. [63] European Commission (EC), Directorate General Health and Consumer Protection, SANCO/825/00 rev 7 17/03/2004 Guidance documents on residue analytical methods, EC, Brussels, Belgium, 2004. [64] World Anti Doping Agency (WADA), Identification criteria for qualitative analysis, WADA Technical Document TD2003IDCR 1.2, WADA, Montreal, Canada, 2004. [65] US Food and Drug Administration (FDA) Guidance for industry: Mass spectrometry for confirmation of the identity of animal drugs residues, Draft Guidance 118, FDA, Washington, DC, USA, 2001. [66] European Commission, European Union Decision 2002/657/ EC, 12 August 2002, implementing Council Directive 96/23/ EC concerning the performance of analytical methods and the interpretation of results, Off. J. Eur. Commun. 221 (2002) 8. [67] D. Snow, D.A. Cassada, S.J. Monson, J. Zhu, R.F. Spalding, A. Rieger, C.R. Iden, C.E. Heine, B.J. Brownawell, in: [3], pp. 161– 174. [68] O.J. Pozo, J.V. Sancho, M. Iba´n˜ez, F. Herna´ndez, W.M.A. Niessen, Trends Anal. Chem. 25 (2006) 1030. [69] F. Herna´ndez, M. Iba´n˜ez, J.V. Sancho, O.J. Pozo, Anal. Chem. 76 (2004) 4349.

http://www.elsevier.com/locate/trac

485