Rapid, compound-specific δ13C and δ15N analysis of amino acids: A chloroformate-based method for biological studies

Robert G. Walsh, Shaoneng He, Christopher T. Yarnes

CSIA of Amino Acids: Why bother? • Conventional bulk analysis obscures meaningful

isotopic variation at the molecular level

• Data from a Tree Swallow (Tachycineta bicolor) feather: δ13(C‰) δ15N(‰)

Bulk -22.54 9.76Alanine -24.74 11.56Aspartic Acid + Asparagine -23.78 10.67Glutamic Acid + Glutamine -22.93 10.34Glycine -15.99 12.08Isoleucine -26.83 16.17Leucine -33.22 14.03Lysine -9.83 4.07Phenylalanine -31.31 4.13Proline -23.05 16.42Threonine -22.23 -10.17Tyrosine -31.17 2.34Valine -29.40 16.27

CSIA of Amino Acids: Why bother?

CSIA of Amino Acids: Status quo • All methods involve tradeoffs between precision,

scope, and time

• General approaches • Offline HPLC to separate AAs EA/IRMS • LC/IRMS with/without derivatization • GC/C/IRMS with derivatization

• Prevailing method to prepare amino acids for GC/C/IRMS is esterification/trifluoroacetylation

• 2-step, 70-minute derivatization reaction • Multiple drying steps, solvents • Strictly anhydrous conditions required

Objective • Improve ease and efficiency of CSIA of amino acids

without compromising accuracy, precision

• Ideal method should: • Generate a sample suitable for both C and N

analysis • Be compatible with a wide range of biological

materials • Require minimal preparation time and

instrument time

The Method, Briefly

Hydrolysis: 150̊C, 70 min

Conventional: 110̊C, 1440 min

methyl chloroformate

pyridine

methanol

Derivatization: 1 step, 1 min

Conventional: 2 steps, 70 min

GC/C/IRMS 30m, 40 min

Conventional: 60m, 60 min

“Like a big bang, a paper on Amino Acid Derivatization and Analysis in Five Minutes appeared in 1991…A trick? By no means! It was pyridine only, a common base in the reaction medium, that caused the miracle…The reagents constituted an era—to such a degree that it was also said: BC – Before Chloroformates, AD – Advanced Derivatization using chloroformates.”

Petr Husek (2006) modestly describes his derivatization method:

oxycarbonylation/ esterification

acetylation/ esterification

valine

Valine, derivatized 5 ways

Benefits of this approach • Hydrolysis

• High-temperature, short duration acid hydrolysis minimizes racemization, preserves some amino acids degraded by long-term hydrolysis (Csapó et al. 1997)

• Derivatization • Microscale (Chen et al. 2010) • One-step aqueous solution derivatization takes minutes

rather than hours, can be used on biological solutions with free amino acids (e.g., blood, cellular lysates)

• GC/C/IRMS • Small, polar derivatives elute quickly, minimizing

instrument time

• From left to right: Alanine, Valine, Glycine, Isoleucine, Leucine, Norleucine (“X”), Proline, Aspartic Acid, Threonine, Methionine, Phenylalanine, Glutamic Acid, Lysine, Histidine, Tyrosine

Inte

nsity

(mV

)

C

N

X

X

Typical chromatograms, reference mixture

Nitrogen chromatograms, biological materials

Mahi Mahi muscle Phytoplankton, whole organism

Nori, thallus Right Whale baleen

• Northern Rough-winged Swallow feather; labels indicate mole percent abundance of the amino acids

Alan

ine (5

%)

Glyc

ine (1

2%)

Valin

e (8%

)

Isoleu

cine (

4%)

Leuc

ine (7

%)

Proli

ne (1

2%)

Aspa

rtic A

cid (7

%)

Thre

onine

(5%

) Se

rine (

12%

) Me

thion

ine (0

.4%)

Phen

ylalan

ine (2

%)

Glut

amic

Acid

(8%)

Lysin

e (1%

) [H

istidi

ne (0

.4%)]

Tyro

sine (

1%)

Inte

nsity

(mV

) Typical chromatogram, biological sample

Precision • Average precision for standard (n = 10 preps)

• σ (C/N): ±1.41/ ± 0.98 • This value is total propagated error for carbon;

measurement error is ±0.63

• Average precision for biological samples of chicken egg, whale baleen, seaweed, with n = 4 preparations per material: • σ (C/N): ±1.67/ ± 0.88

• Good correlation between GC/C/IRMS values and EA/IRMS values; amino acids with aliphatic side-chains shown

Accuracy with Reference Mixture

C N

• Accurate determinations; no significant difference between EA (dark bars) and GC (light bars) values

Accuracy with Ala, Glu Standards

Caveats & Limitations • Low recovery of some amino acids with polar side-

chains (e.g., histidine, serine)

• Challenges of running samples of unknown AA abundance “blind”

• MCF toxicity

• Some additional purification may be necessary on some samples, especially high-cellulose, high-lipid

Case Study: Riparian Food Webs

Case Study: Riparian Food Webs • Do songbirds rely more on emergent aquatic insects

or terrestrial insect production? Are they part of the algae- or tracheophyte-based food webs?

• Performed discriminant analysis using animals with known aquatic diet (n=20 e.g., fish, crustaceans, bivalves) and known terrestrial diet (n=20, e.g., ungulates, canids, insects) from other studies for training; values of Phe (C & N), Glu (C & N) used

• How will birds with empirically known aquatic/terrestrial diets be classified?

Birds with Empirically Known Aquatic/Terrestrial Diets

Eared Grebe Nuttall’s Woodpecker Aquatic invertebrates, fish Wood-boring insects Belted Kingfisher Bushtit Fish Aphids Marsh Wren California Thrasher Emergent aquatic insects Spiders, insects American Dipper Bullock’s Oriole Aquatic invertebrates Grasshoppers, fruit

Probability of Assignment to Correct Diet Group: Habitat Specialists

Eared Grebe Nuttall’s Woodpecker 98.1% Aquatic 88.7% Terrestrial Belted Kingfisher Bushtit 97.9% Aquatic 97.4% Terrestrial Marsh Wren California Thrasher 85.4% Aquatic 96.9% Terrestrial American Dipper Bullock’s Oriole 75.5% Aquatic 97.0% Terrestrial

Case Study: Riparian Food Webs • CSIA-AA data have the potential to resolve aquatic

versus terrestrial prey sources, a challenge for bulk C/N analysis

• Applied to generalist insectivores (Tree Swallows) to look at resource use of aquatic and terrestrial resources during particular life history stages, in drought years, etc.

• Findings match up with ecological expectations, other studies

Tree Swallow with Callibaetis mayflies

Conclusions & Future Potential • Analysis of biological solutions with free AAs (blood,

cell lysates, urine, etc.) to study glutamine, cysteine, and others typically lost in hydrolysis would be novel

• Additional time savings possible (microwave hydrolysis, neutralizing samples with NaOH instead of drying, automating derivatization)

• Scaling up sampling—capitalizing on short preparation and run times to analyze more samples with similar effort

methyl chloroformate

• UC Davis Stable Isotope Facility graduate fellowship support

• Biological samples donated from many individuals and institutions

Acknowledgments