Methods for Top-Down Multiplexed Mass Spectral Analysis of Mixtures of Proteins or Polypeptides

Abstract

Applications of ion-ion reaction chemistry are disclosed in which proton transfer reactions (PTR) and real-time data analysis methods are used to (1) simplify complex mixture analysis of samples introduced into a mass spectrometer, and (2) improve resolution and sensitivity for the analysis of large proteins in excess of 50 kDa by removing charge and reducing the collisional cross section.

Description

CROSS REFERENCE TO RELATED APPLICATIONS[0001]This application is a Divisional of, and claims, under 35 U.S.C. § 120, the benefit of the filing date of commonly-assigned and co-pending U.S. application Ser. No. 15 / 406,626, now U.S. Pat. No. ______, which was filed on Jan. 13, 2017 and which claims, under 35 U.S.C. § 119(e), priority to and the benefit of the filing date of commonly-assigned U.S. Provisional Application No. 62 / 278,935, filed on Jan. 14, 2016, the disclosures of which are hereby incorporated by reference in their entirety. The subject matter of this application is also related to commonly-assigned and co-pending U.S. application Ser. No. 15 / 830,439, which was filed on Dec. 4, 2017 and which is titled “Methods for Mass Spectrometry of Mixtures of Protein or Polypeptides Using Proton Transfer Reaction” and to commonly-assigned and co-pending U.S. application Ser. No. 15 / 067,727, now U.S. Pat. No. ______, which was filed on Mar. 11, 2016, the disclosures of which are here...

AI Technical Summary

Benefits of technology

The patent describes a method for analyzing complex mixtures of compounds using mass spectrometry. The method involves using ion-ion reaction chemistry to simplify the analysis of these mixtures by reducing the number of charge states and making it easier to identify specific molecules. The method also uses a simplified spectral deconvolution procedure to automatically discriminate between the signatures of different biopolymer molecules in real-time, which can help make decisions about the further analysis of the sample. The method can be used with samples from tissues, biological fluids, microorganisms, or other cells. Overall, the method improves the accuracy and efficiency of mass spectrometry analysis for complex samples.

Problems solved by technology

Although MALDI-TOF methods are rapid and cost effective, they have limitations that restrict the range of applications to pathogen characterization and identification including but not limited to virulence detection and quantitation, resistance marker determination, strain matching, and antibiotic susceptibility testing to name a few.

Because ribosomal proteins are highly conserved among prokaryotes, differentiation of closely related microorganisms by MALDI-TOF is limited.

Moreover, determination of strain and / or serovar type, antibiotic resistance, antibiotic susceptibility, virulence or other important characteristics relies upon the detection of protein markers other than ribosomal proteins which further limits the application of MALDI-TOF for microbial analysis.

In addition, the MALDI-TOF method's reliance upon matching spectral patterns requires a pure culture for high quality results and thus is not generally suitable for direct testing, mixed cultures, blood culture, or other complex samples containing different microorganisms.

However, top-down analysis has a disadvantage when compared to a bottom-up analysis in that many proteins can be difficult to isolate and purify.

A still further challenge associated with the use of mass spectral analyses of proteins and polypeptides in a clinical setting is to derive such information in the shortest time period possible, often termed as analysis in “real time”.

Obviously, the computations are much more challenging in real time during an automatic top-down data dependent analysis since this should occur very fast, especially when chromatographic separation is involved.

When applied to higher-molecular-weight biopolymer analytes (most commonly, intact proteins during the course of top-down proteomics studies) these conventional methodologies significantly under-perform due to a combination of different electrospray behavior and computational limitations.

Additional levels of complexity are introduced by oxidized species of the same analyte or adducts, overlaps of isotope clusters and inability of existing software tools correctly calculate charge state for high mass species.

This duplication of work leads to redundancy in identification of the most abundant / ionizable proteins, while the information about other species is lost and provides very little opportunity for triggering an MSn analysis.

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