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A Double-Barrel Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS) System to Quantify 96 Interactomes per Day.

Hosp F, Scheltema RA, Eberl HC, Kulak NA, Keilhauer EC, Mayr K, Mann M - Mol. Cell Proteomics (2015)

Bottom Line: The modified LC platform eliminates idle time between measurements, and the high sequencing speed of the Q Exactive HF reduces required measurement time.Thus, sample throughput, sensitivity and LC/MS-MS duty cycle are improved severalfold compared with established workflows.The pipeline can be extended to different types of interaction studies and to other medium complexity proteomes.

View Article: PubMed Central - PubMed

Affiliation: From the ‡Department of Proteomics and Signal Transduction, Max-Planck Institute of Biochemistry, Am Klopferspitz 18, D-82152 Martinsried, Germany.

No MeSH data available.


Related in: MedlinePlus

Chromatography optimization for very short gradients. (A) Peak-width as a function of gradient length and flow rate. Effect size is the calculation of the reduction compared with the largest change in peak-width. (B) Extrapolation of protein identifications as a function of gradient length and scan speed of various MS platforms (Q Exactive HF and plus, Orbitrap Elite, and Velos, LTQ Orbitrap XL, respectively). (C) Effect of flow rate on the signal-to-noise for a set of 750 unique isotope patterns identified in all measurements and spread out over the entire gradient. (D) Elution time shift induced by higher flow rates, normalized to the gradient length.
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Figure 1: Chromatography optimization for very short gradients. (A) Peak-width as a function of gradient length and flow rate. Effect size is the calculation of the reduction compared with the largest change in peak-width. (B) Extrapolation of protein identifications as a function of gradient length and scan speed of various MS platforms (Q Exactive HF and plus, Orbitrap Elite, and Velos, LTQ Orbitrap XL, respectively). (C) Effect of flow rate on the signal-to-noise for a set of 750 unique isotope patterns identified in all measurements and spread out over the entire gradient. (D) Elution time shift induced by higher flow rates, normalized to the gradient length.

Mentions: First, we aimed to establish optimal conditions for reducing the LC gradient length. Both the flow rate and gradient starting percentage require adaptations to ensure that the signal of each peptide does not degrade and to maximize the spread of peptides over the gradient. To achieve this, we tested the effect of flow rate (ranging from 200 to 500 nl/min) and gradient length (from 15 to 120 min) on the chromatographic peak-width with a standard HeLa digest on the Q Exactive HF (34). By far, the largest effect on peak width was shortening the gradient length as this provided a reduction of ∼75% on the width, while the flow rate reduced it only by ∼4% (Fig. 1A). With regard to overall proteome depth, we were able to identify about 740 proteins with a standard HeLa digest using the shortest gradient length of 15 min with the Q Exactive HF (Fig. 1B). Hence, the complexity of protein samples should not exceed such a number when high sample throughput is envisioned. We also determined protein identifications for lower sequencing speed (Fig. 1B). Notably, even platforms with lower sequencing speed like the Orbitrap XL identified about 1,000 proteins with a 120 min gradient, suggesting that already this machine generation had the potential to identify all proteins of a lower complexity sample given sufficiently long gradients.


A Double-Barrel Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS) System to Quantify 96 Interactomes per Day.

Hosp F, Scheltema RA, Eberl HC, Kulak NA, Keilhauer EC, Mayr K, Mann M - Mol. Cell Proteomics (2015)

Chromatography optimization for very short gradients. (A) Peak-width as a function of gradient length and flow rate. Effect size is the calculation of the reduction compared with the largest change in peak-width. (B) Extrapolation of protein identifications as a function of gradient length and scan speed of various MS platforms (Q Exactive HF and plus, Orbitrap Elite, and Velos, LTQ Orbitrap XL, respectively). (C) Effect of flow rate on the signal-to-noise for a set of 750 unique isotope patterns identified in all measurements and spread out over the entire gradient. (D) Elution time shift induced by higher flow rates, normalized to the gradient length.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4587330&req=5

Figure 1: Chromatography optimization for very short gradients. (A) Peak-width as a function of gradient length and flow rate. Effect size is the calculation of the reduction compared with the largest change in peak-width. (B) Extrapolation of protein identifications as a function of gradient length and scan speed of various MS platforms (Q Exactive HF and plus, Orbitrap Elite, and Velos, LTQ Orbitrap XL, respectively). (C) Effect of flow rate on the signal-to-noise for a set of 750 unique isotope patterns identified in all measurements and spread out over the entire gradient. (D) Elution time shift induced by higher flow rates, normalized to the gradient length.
Mentions: First, we aimed to establish optimal conditions for reducing the LC gradient length. Both the flow rate and gradient starting percentage require adaptations to ensure that the signal of each peptide does not degrade and to maximize the spread of peptides over the gradient. To achieve this, we tested the effect of flow rate (ranging from 200 to 500 nl/min) and gradient length (from 15 to 120 min) on the chromatographic peak-width with a standard HeLa digest on the Q Exactive HF (34). By far, the largest effect on peak width was shortening the gradient length as this provided a reduction of ∼75% on the width, while the flow rate reduced it only by ∼4% (Fig. 1A). With regard to overall proteome depth, we were able to identify about 740 proteins with a standard HeLa digest using the shortest gradient length of 15 min with the Q Exactive HF (Fig. 1B). Hence, the complexity of protein samples should not exceed such a number when high sample throughput is envisioned. We also determined protein identifications for lower sequencing speed (Fig. 1B). Notably, even platforms with lower sequencing speed like the Orbitrap XL identified about 1,000 proteins with a 120 min gradient, suggesting that already this machine generation had the potential to identify all proteins of a lower complexity sample given sufficiently long gradients.

Bottom Line: The modified LC platform eliminates idle time between measurements, and the high sequencing speed of the Q Exactive HF reduces required measurement time.Thus, sample throughput, sensitivity and LC/MS-MS duty cycle are improved severalfold compared with established workflows.The pipeline can be extended to different types of interaction studies and to other medium complexity proteomes.

View Article: PubMed Central - PubMed

Affiliation: From the ‡Department of Proteomics and Signal Transduction, Max-Planck Institute of Biochemistry, Am Klopferspitz 18, D-82152 Martinsried, Germany.

No MeSH data available.


Related in: MedlinePlus