CROSS REFERENCE TO RELATED PATENT APPLICATIONS/PATENTS

U.S. Pat. Nos. 6,983,213, 7,493,225 and 7,577,538; International Patent Application PCT/US2004/013096, filed on Apr. 28, 2004; U.S. Pat. No. 7,348,553; International Patent Application PCT/US2005/039186, filed on Oct. 28, 2005; U.S. Pat. No. 8,010,306, International Patent Application PCT/US2006/013723, filed on Apr. 11, 2006; U.S. Pat. No. 7,781,729, International Patent Application PCT/US2007/069832, filed on May 28, 2007; and U.S. provisional patent application Ser. No. 60/941,656, filed on Jun. 2, 2007 and as International Patent Application PCT/US2008/065568 published as WO 2008/151153.

The entire teachings of these patent documents are hereby incorporated herein by reference, in their entireties, for all purposes.

FIELD OF THE INVENTION

The present invention generally relates to the field of Mass Spectrometry (MS) and, more particularly, to methods for acquiring, processing, and analyzing MS data.

BACKGROUND OF THE INVENTION

Mass Spectrometry (MS) is 100-year-old technology that relies on the ionization of molecules, the dispersion of the ions by their masses, and the proper detection of the ions on the appropriate detectors. There are many ways to achieve each of these three key MS processes which give rise to different types of MS instrumentations having distinct characteristics.

Many ionization techniques are available to ionize molecules entering MS system so that they can be properly charged before mass dispersion. These ionization schemes include Electrospray Ionization (ESI), Electron Impact Ionization (EI) through the impact of high-energy electrons, Chemical Ionization (CI) through the use of reactive compounds, and Matrix-Assisted Laser Desorption and Ionization (MALDI).

Once the molecules have been charged through ionization, each ion will have a corresponding mass-to-charge (m/z) ratio, which will become the basis to mass dispersion. Based on the physical principles used, there are many different ways to achieve mass dispersion and subsequent ion detection, resulting in mass spectral data similar in nature but different in details. A few of the commonly seen configurations include: magnetic/electric sector; quadrupoles; Time-Of-Flight (TOF); and Fourier Transform Ion-Cyclotron Resonance (FT ICR).

The sector MS configuration is the most straight-forward mass dispersion technique where ions with different m/z ratios would separate in an electric/magnetic field and exit this field at spatially separated locations where they will be detected with either a fixed array of detector elements or a movable set of small detectors that can be adjusted to detect different ions depending on the application. This is a simultaneous configuration where all ions from the sample are separated simultaneously in space rather than sequentially in time.

The quadrupoles configuration is perhaps the most common MS configuration where ions of different m/z values will be filtered out of a set of (usually 4) parallel rods through the manipulation of RF/DC ratios applied to these rod pairs. Only ions of a certain m/z value will survive the trip through these rods at a given RF/DC ratio, resulting in the sequential separation and detection of ions. Due to its sequential nature, only one detector element is required for detection. Another configuration that uses ion traps can be conceptually considered a special example of quadrupole MS.

The Time-Of-Flight (TOF) configuration is another sequential dispersion and detection scheme that lets ions enter through a high vacuum flight tube before detection. Ions of different m/z values would arrive at different times to the detector and the arrival time can be related to the m/z values through the use of known calibration standard(s).

In Fourier Transform Ion-Cyclotron Resonance (FT ICR), all ions can be introduced to an ion cyclotron where ions of different m/z ratios would be trapped and resonate at different frequencies. These ions can be pulsed out through the application of a Radio Frequency (RF) signal and the ion intensities measured as a function of time on a detector. Upon Fourier transformation of the time domain data measured, one gets back the frequency domain data where the frequency can be related back to m/z through the use of known calibration standard(s). Orbitrap MS systems can be conceptually considered as a special case of FT MS.

As discussed in the cross-referenced U.S. Pat. No. 6,983,213, a mass spectral data trace is typically subjected to peak analysis where peaks (ions) are identified. This peak detection routine is a highly empirical and compounded process where peak shoulders, noise in data trace, baselines due to chemical backgrounds or contamination, isotope peak interferences, etc., are considered. For the peaks identified, a process called centroiding is typically applied to report only two data values, m/z location and estimated peak area (or peak height), wherever an MS peak is detected. While highly efficient in terms of data storage, this is a process plagued by many adjustable parameters that can make an isotope appear or disappear with no objective measures of the centroiding quality, due to the many interfering factors mentioned above and the intrinsic difficulties in determining peak areas in the presence of other peaks and/or baselines. Unfortunately for many MS systems, especially quadrupole MS systems, this MS peak detection and centroiding are conventionally set up by default as part of the MS method to occur during data acquisition down at the firmware level, leading to irreparable damages to the MS data integrity, even for pure component mass spectral data in the absence of any spectral interferences from other co-existing compounds or analytes. As pointed out in U.S. Pat. No. 6,983,213, these damages or disadvantages include:a. Lack of mass accuracy on the most commonly used unit mass resolution MS systems. The centroiding process forces the reported mass value into integer m/z with ±1 Da or other m/z values with at least ±0.1 Da mass error, whereas the properly calibrated raw profile mode MS data (without centroiding) using the method disclosed in U.S. Pat. No. 6,983,213 can be accurate to ±0.005 Da, a factor of approximately 100 improvement.b. Large peak integration error. Centroiding without full mass spectral calibration including MS peak shape calibration suffers from uncertainty in mass spectral peak shape, its variability, the isotope peaks, the baseline and other background signals, the random noise, leading to both systematic and random errors for either strong or weak mass spectral peaks.c. Large isotope abundance error. Separating the contributions from various closely located isotopes (e.g., A and A+1) on conventional MS systems with unit mass resolution either ignores the contributions from neighboring isotope peaks or over-estimates them, resulting in errors for dominating isotope peaks and large biases for weak isotope peaks or even complete elimination of the weaker isotopes.d. Nonlinear operation. The centroiding typically uses a multi-stage disjointed process with many empirically adjustable parameters during each stage. Systematic errors (biases) are generated at each stage and propagated down to the later stages in an uncontrolled, unpredictable, and nonlinear manner, making it impossible for the algorithms to report meaningful statistics as measures of data processing quality and reliability.e. Dominating systematic errors. In most of MS applications, ranging from industrial process control and environmental monitoring to protein identification or biomarker discovery, instrument sensitivity or detection limit has always been a focus and great efforts have been made in many instrument systems to minimize measurement error or noise contribution in the signal. Unfortunately, the typical centroiding process currently in use create a source of systematic error even larger than the random noise in the raw data, thus becoming the limiting factor in instrument sensitivity.f. Mathematical and statistical inconsistency. The many empirical approaches currently used in centroiding make the whole processing inconsistent either mathematically or statistically. The peak processing results can change dramatically on slightly different data without any random noise or on the same synthetic data with slightly different noise. In order words, the results of the peak centroiding are not robust and can be unstable depending on a particular experiment or data acquisition.g. Instrument-to-instrument or tune-to-tune variability. It has usually been difficult to directly compare raw mass spectral data from different MS instruments due to variations in the mechanical, electromagnetic, or environmental tolerances. With the typical centroiding applied to the actual raw profile mode MS data, it not only adds to the difficulty of quantitatively comparing results from different MS instruments due to the quantized nature of the centroiding process and centroid data, but also makes it difficult, if not impossible, to track down the source or possible cause of the variability once the MS data have been reduced to centroid data.

For a well separated analyte with pure mass spectrum and without any spectral interferences, MS centroiding is quite problematic as is due to the above listed reasons. For unresolved or otherwise co-eluting analytes or compounds in complex samples (e.g., petroleum products or essential oils) even after extensive chromatographic separation (e.g., 1-hr GC separation of essential oils or LC separation of biological samples with post translational modification such as deamidation), the above centroid processing problem would only be further aggravated due to the mutual mass spectral interferences present and the quantized nature of the MS centroids, which makes mass spectral data no longer linearly additive. This necessarily makes the MS centroid spectrum of a mixture different from the sum of MS centroids obtained from each individual pure spectrum, making the nonlinear and systematic centroiding error worse and even intractable. For this reason, the conventional co-elution deconvolution approach in common use, called AMDIS (Automated Mass Spectral Deconvolution & Identification System) as reported in “Optimization and Testing of Mass Spectral Library Search Algorithms for Compound Identification” Stein, S. E.; Scott, D. R. J. Amer. Soc. Mass Spectrom. 1994, 5, 859-866, which typically operates with MS centroid data, often fails to determine the correct number of co-elution compounds, derive the correct separation time profiles (called chromatograms in the case of chromatographic separation) of individual compounds or analytes, or compute the correct pure component/analyte mass spectra for reliable library (e.g., NIST EI MS library) search and compound identification.

For complex samples without any time-based (e.g., chromatographic) separation due to the need for speedy analysis or detection, using, as an example, novel ionization techniques such as DART (Direct Analysis in Real Time), reported in R. B. Cody; J. A. Laramée; H. D. Durst (2005) “Versatile New Ion Source for the Analysis of Materials in Open Air under Ambient Conditions”. Anal. Chem. 77 (8): 2297-2302, the mass spectrum may become so complex that there may not be visually separable mass spectral peaks for either detection or centroiding, leading possibly to the outright total failure of conventional mass spectral data acquisition, processing, and analysis.

Accordingly, it would be desirable and highly advantageous to have methods to avoid MS peak detection and centroiding altogether that overcome the above-described deficiencies and disadvantages of the prior art.

SUMMARY OF THE INVENTION

The present application is directed to the following improvements:

1. An accurate approach for the determination of independent analytes contained in a chromatographic peak, through multivariate statistical analysis such as the principal component analysis (PCA) of corresponding profile mode mass spectral data acquired in a relevant separation time window. It's critical to use profile mode mass spectral data, instead of the centroid data currently in use.

2. An accurate approach to completely model the underlying chromatographic peak shape functions involved, through the use of a set of chromatographic standards. Reference is made to U.S. Pat. Nos. 6,983,213 and 7,493,225.

3. With the chromatographic peak shape fully defined, only the peak (e.g., center) positions of the involved independent analytes need to be determined to fully define and resolve the mutually overlapping components hidden inside a chromatographic peak, e.g., through Simplex optimization with initial peak positions through iterative improvements and multiple linear regression (MLR).

4. With each chromatographic peak well defined, it is feasible to compute the pure mass spectrum for each analyte for either qualitative identification (e.g., through NIST library search) or quantitative analysis through multiple linear regression. Reference is made to U.S. Pat. No. 7,577,538.

5. Application of accurate mass and spectral accuracy analysis to confirm the molecular ion or its fragment ions to increase the identification confidence of a compound already known in a library (e.g., NIST library) or to aid in the elucidation of an unknown or new compound not contained in a library.

6. Additional identification confidence may also be gained through the use of retention indexes available for compounds already contained in a compound library (e.g., NIST library).

7. An approach to combine multiple mass spectral scans acquired over a given separation time window and compare among similar or different samples for the purpose of differentiating one sample from another, for the purpose of sample or product-type analysis.

Each of these aspects will be described below along with experimental results to demonstrate their utilities.

