Rapid, compound-specific δ13C and δ15N analysis of amino acids ...
Transcript of Rapid, compound-specific δ13C and δ15N analysis of amino acids ...
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