Glucose unit determination based on a numeric virtual EOF marker search method

Abstract

The present invention relates to a method for determining glucose unit of labeled carbohydrates, using relative effective mobility of maltodextrin ladder peaks based on a virtual EOF marker in EOF driven capillary electrophoresis. Preferably, the invention relates to glucose unit determination based on a numeric virtual eof marker search method using a double internal standard for eof driven capillary electrophoresis analysis of carbohydrates.

Description

[0001]GLUCOSE UNIT DETERMINATION BASED ON A NUMERIC VIRTUAL EOF MARKER SEARCH METHOD FIELD OF THE INVENTION The present invention relates to a method for determining glucose unit of labeled carbohydrates, using effective migration times (an inverse of relative effective mobilities) of peaks of an oligomeric ladder, preferably respective maltodextrin ladder peaks based on a virtual EOF marker in EOF driven capillary electrophoresis. Preferably, the invention relates to glucose unit determination based on a numeric virtual EOF marker search method using a double internal standard for EOF driven capillary electrophoresis analysis of carbohydrates. DESCRIPTION OF THE RELATED ART Analysis of protein glycosylation is of high importance in the biomedical and biopharmaceutical fields, as well as in the food and beverage industry [Saldova et al., 2007 #1; Shrivastava et al., 2022 #2; Sarkozy et al, 2023 #3]. Traditionally, after releasing the sugar moieties from the polypeptide backbone of a glycoprotein, chromatography, electrophoresis, mass spectrometry or NMR are used in most instances for their analysis [Mechref et al., 2002 #4; Lu et al., 2018 #5]. Capillary electrophoresis (CE) is one of the frequently used separation techniques for the analysis of complex carbohydrates. Since carbohydrates do not feature chromophore or fluorophore characteristics, their capillary electrophoresis analysis entails tagging of the free reductive end of the released sugars with a primary amine bearing fluorescent dye that is also charged to support proper electromigration [Mechref et al., 2002 #4]. In CE analysis of carbohydrates, the fluorophore tag should be charged to ensure proper electromigration of the labeled glycans [Guttman et al., 1996 #6]. The most frequently used fluorescent tags in CE are 8-aminopyrene-1,3,6-trisulfonic acid (APTS) [Guttman et al., 1996 #6] and aminonaphtalenetrisulfonate (ANTS) [Chiesa et al., 1993 #7], both carry three strong negative charges over a wide pH range. The separation of the labeled glycans in the traditionally used low pH gel-buffer systems in reversed polarity mode is based on their mass to charge ratio without any significant influence by the electroosmotic flow on the resulting differential electromigration [Liu et al., 1991 #8]. In these instances, the remaining excess labeling reagent migrates prior to the labeled carbohydrates [Váradi et al, 2014 #9], thus the tailing portion of the large fluorophore peak may cover some of the rapidly migrating sample components and N-glycans rendering them virtually undetectable. An EOF driven approach was not suggested in the past for the separation of carbohydrates, as arheic conditions, i.e. wherein EOF is reduced or eliminated was held essential for effective separation which could be achieved in negatively charged labeling agents under low pH with a bare fused silica capillary. A high pH and a significant EOF was held to be disadvantageous due to the not evenly spaced homologues at higher degree of polymerization oligosaccharides, [Chiesa et al., 1993 #7]. Contradistinctionally, the present inventors earlier has demonstrated the advantage of EOF driven 137220 / SG capillary zone electrophoresis separation with analyte molecules migrating in the opposite direction (“oppositely migrating”) in an easy-to-use purification-free workflow [Farsang et al., 2023 #]. The present inventors earlier have disclosed an online electrokinetic cleanup process with electroosmotic flow (EOF) assisted separation, wherein charged labelling agents migrate against the EOF and in a direction opposite to the analyte molecules which migrate towards the detector. The iventors used a bare fused silica capillary, alkaline pH background electrolyte and normal polarity mode. The alkaline running buffer was applied to N-glycome analysis without the need of the extra sample purification step. The same principle can be applied in any capillary having negative charged wall in an alkaline pH environment. In analogue solutions the capillary has a wall with positive charge and under reverse polarity. However, non-consistent EOF rate due to the difference in conductivity between the sample plug and the buffer may cause an uncertainty in the evaluation of the electropherogram obtained by EOF driven capillary electrophoresis (see Fig.2). Accordingly, the object of the present invention is to provide a method for determining glucose unit of carbohydrates in EOF driven capillary electrophoresis, which method eliminate the uncertainty caused by the non-consistent EOF rate. THE DISCOVERY ACCORDING TO THE PRESENT INVENTION To achieve the above-mentioned objective, the inventors of the present invention have performed significant experimental work, which has resulted in the present invention. The present invention is based on the finding that a virtual EOF marker value – equivalent to an effective EOF migration time – related to the ladder peak migration times (i.e. when no sample is present), can be calculated by using the measured ladder peaks, then effective migration times for ladder peaks can be calculated using the measured ladder peak migration times and the effective EOF marker value, from which ratios of the effective ladder peak migration times can be calculated, using the virtual EOF marker value; subsequently, for an actual sample measurement, by using the former calculated ladder peak migration time ratio values another virtual EOF marker and a virtual ladder adapted or related to the actual sample measurement can be determined, i.e. “reconstituted”; finally, for an unknown analyte (sample) in the actual sample measurement a precise glucose unit value can be determined accurately based on this mentioned virtual ladder adapted to the sample measurement. The ladder is preferably a maltodextrin ladder. BRIEF DESCRIPTION OF THE INVENTION The invention relates to technical solutions and preferred embodiments defined under the following numbered paragraphs. 1. Az igénypontok elfogadása után azokat ide beszerkesztjük. BRIEF DESCRIPTION OF THE DRAWINGS Fig. 1: Schematic representation of the electrokinetic cleanup process showing the apparent (µapp) and effective (µeff) electrophoretic mobilities in an example, wherein th apparent mobility of a dye and of labelled oligosaccharides has an opposite direction, considering the downstream EOF mobility (µEOF). Fig. 2: Illustration maltodextrin ladder electropherogram and change in current during EOF driven capillary electrophoresis. In the present examples maltodextrin standards of DP15 and DP3 (maltodextrin standards with a polymerization ratio of 15 and 3, respectively) are applied to provide a calculated ladder peak migration time ratio, from which the sample measurement related (adapted) ladder can be reconstituted. In the exemplary experiment (illustrated on Fig. 1) maltodextrin ladder peaks of higher DP have smaller migration times (i.e. higher effective mobilities). A: DP15 reaches the detector window. B: DP3 reaches the detector window. C: EOF front reaches the detector window. D: Non-consistent EOF rate due to the difference in conductivity between the sample plug and the buffer, which requires the use of a virtual EOF marker. E: EOF front reaches the end of capillary. Fig.3: The fitted straight line from DP8 to DP15. Fig.4: The fitted second-degree polynomial from DP3 to DP8. ABBREVIATIONS CE = Capillary Electrophoresis; CZE = Capillary Zone Electrophoresis EOF = Electroosmotic Flow; BFS = Bare Fused Silica; DP = Degree of Polymerization; MD = Maltodextrin; GU = Glucose Unit APTS = 8-Aminopyrene-1,3,6-trisulfonic acid; ANTS = 8-Aminonaphthalene-1,3,6-trisulfonic acid. DEFINITIONS The term “sample” is meant herein to refer to a substance prepared separation, e.g. for analysis, e.g. by capillary electrophoresis. The sample may be derived from, for example, a substance obtained from an environmental source, e.g. bodily fluid or tissue from a subject, i.e. taken from said bodily fluid or tissue of the subject and optionally processed to prepare for analysis. The sample as used herein preferably comprises carbohydrates, preferably glycans of biological or biotechnological interest, as defined, described or exemplified herein. A sample is typically a reaction mixture or a part thereof comprising said carbohydrates, preferably oligosaccharides and labeling agents. The labeling agents used herein are charged molecules, e.g positively or negatively charged, wherein preferably the labeled carbohydrates, once reacted with the labeling agent, become charged, e.g positively or negatively charged, respectively. “Carbohydrates” in a broader sense are compounds having the stoichiometric formula Cn(H2O)n, or derivatives, e.g. those having a major moiety (preferably of at least 30%, 50% or 70% or 80% or the molecular weight of the whole compound) said major moiety having the stoichiometric formula Cn(H2O)n. “Carbohydrates” preferably are aldoses or ketoses. The term carbohydrate includes monosaccharides and oligosaccharides and polysaccharides as well as substances derived from monosaccharides by reduction of the carbonyl group (alditols), by oxidation of one or more terminal groups to carboxylic acids, or by replacement of one or more hydroxy group(s) by a hydrogen atom or a substituent, in particular a substituent having a molecular weigh of at most of a monosacharide, eg. a functional group, in particular an amino group, thiol group or similar groups. It also includes derivatives of these compounds. In a sense, “glycans”, “oligosaccharides” and “polysaccharides” are used herein interchangeably and mean a carbohydrate comprising or having multiple monosaccharide units, preferably linked glycosidically. In a narrower sense “glycans”, “oligosaccharides” and “polysaccharides” are as defined by IUPAC Compendium of Chemical Terminology ^IUPAC, (2019), #16^ In a preferred embodiment “glycans” are glycans of biological or biotechnological interest. In a broader sense glycans may comprise monosaccharides. In a preferred embodiment the term “glycan” relates to the carbohydrate portion of a glycoconjugate, such as a glycoprotein, glycolipid, or a proteoglycan. Glycans can be homo- or heteropolymers of monosaccharide residues (may be composed of a single type of monosaccharide residue or from multiple type of monosaccharide residue). Glycans can be linear or branched. Glycans can be typically N-linked-glycans or O-linked-glycans or glycosaminoglycans. A “fluorescent” or a “fluorescently labeled” compound as used herein is a compound which can be detected by irradiating with an UV or VIS electromagnetic radiation and the compound absorbs the irradiating light and emits light (emitted light) at another, preferably longer wavelength than that of the irradiating light. Preferably both “fluorescently labeled” compounds of interest according to the invention as well as fluorescent labelling agents have a charge, either positive or negative charge, in a particularly preferred embodiment negative charge. In particular absolute value of the effective electrophoretic mobility of the fluorescent labelling agents used in the invention is higher than that of the “fluorescently labeled” compounds, in particular glycans, as their algebraic sign is the opposite. “Detecting” as used herein is understood broadly as obtaining an observation regarding a substance or compound of interest (preferably an analyte), as a result of the separation method on a sample. „Oligosacharide ladder” as used herein relates to an electropherogram of an series of homooligosacharides comprising different numbers of monosacharid (hexose or pentose, preferably hexose) monomers, wherein migration times or their inverse mobilities, depend on the number of monomers in the oligosacharide, i.e. its „degree of polimerization”, DP. The term „ladder” relates to the electropherogram, the set of peaks and the series of oligosaccharide compounds, as context dictates. „Maltooligosaccharides” (MOS) are homooligosaccharides that consist of 3 or more, preferably 3 to 20 or 3 to 16 glucose molecules linked by α-1,4 glycosidic bonds. A “maltooligosaccharide ladder” is an ligosaccharide ladder wherein the series of homooligosacharides consist of maltooligosaccharides. “Glucose unit” as used herein is a relative value based the comparison of the migration times of unknown analyte peaks with an oligosacharide ladder, wherein preferably it is calculated, if desired, from migration times of the analyte peaks and from the neighbouring oligosaccharide peaks before and after the respective analyte peak. Preferably, the glucose unit is a value based on the comparison of the migration times of unknown analyte peaks with a mixture of homologous oligosaccharides (usually referred to as “ladder”) to provide migration time normalization, and can be calculated based on the migration time of its adjacent oligosaccharide ladder peaks, Equation (4) where GUXis the glucose unit value of the peak of interest, e.g. an unknown analyte peak, GNis the degree of polymerization of the preceding oligosaccharide ladder peak, tXis the migration time of the peak of interest, tNand tN+ 1 are the migration times of the oligosacharide oligomers immediately preceding and following the peak of interest, respectively. The oligosacharide ladder is preferably a maltooligosaccharide ladder wherein GN is the degree of polymerization of the given (number N) maltooligosaccharide (Glc(^1 → 4)n) ladder peak. A "virtual EOF marker” is the theoretical migration time for electroosmotic flow to the detector window at constant current or a value approaching it to the extent being useful in the calculation of the effective migration time (or “resultant” migration time) from the apparent migration time of the same compound (see Equation 3). Effective migration time is the reciprocal of effective mobility. A “detector” is a device for detecting and which is located typically in connection with a specific site of the CE capillary to detect compounds of interest migrating therein. The term “internal standard” as used herein is a substance that is added in a known amount into a sample to detect and quantify together with an analyte. The term “comprises” or “comprising” or “including” are to be construed here as having a non- exhaustive meaning and allow the addition or involvement of further features or method steps or components to anything which comprises the listed features or method steps or components. “Comprising” can be substituted by “including” if the practice of a given language variant so requires or can be limited to “consisting essentially of” if other members or components are not essential to reduce the invention to practice or “consisting of” if other members or components are not present. The singular forms “a”, “an” and “the”, or at least “a”, “an”, include plural reference unless the context clearly dictates otherwise. DETAILED DESCRIPTION OF THE INVENTION While in the field of capillary electrophoresis analysis of labelled carbohydrates several high- throughput glycan separation methods are currently available, but the associated bioinformatics system to analyse the results is just beginning to emerge. The identification of glycan structures is a multifaceted challenge that integrates elements of separation science, physicochemical analysis, and bioinformatics- computational methods. Various approaches are being explored to identify glycans, including conventional glucose unit counting, the virtual ladder method, and sequencing of glycans using exoglycosidase digestion techniques (either sequential or array). Identification of glycan structures can also be performed by capillary electrophoresis coupled with mass spectrometry, but these methods are complex and expensive. The present invention relates to a capillary electrophoresis analysis method including a method for determining glucose unit of labeled carbohydrates, using effective migration times of respective maltodextrin ladder peaks based on a virtual electroosmotic flow (EOF) marker in EOF driven capillary electrophoresis. Electroosmosis plays an important role in the present invention. This phenomenon is a consequence of the surface charge on the wall of the capillary. For example, fused silica capillaries have silanol groups on their inner surface. The level of ionization of the silanol groups depends on the pH of the background electrolyte and the ionic strength of the background electrolyte, which can be controlled by the running buffer. The electroosmotic flow (EOF) can be described by the following formula (Equation 1) (Equation 1) where ∈ is the dielectric constant, E is the applied electric field, η is the viscosity of the buffer, and ζ is the zeta potential. The charged wall of the capillary attracts ions of opposite charge from the background electrolyte, whereby an electrical double layer is formed. If voltage is applied on the capillary, and the ions in the electrolyte part, i.e. in the diffuse portion of the double layer migrates in the direction of the cathode, carrying water with them. The result is a net flow of buffer solution in the direction of the negative electrode, if the wall of the capillary is negatively charged and in the direction of the positive electrode, if the wall is positively charged. The zeta potential, ξ, (electrokinetic potential) is defined at the interface of the double layer or as the potential of the diffuse layer that is at a finite distance from the capillary wall. Zeta potential depends on the thickness of the double layer, wherein a lower ionic strength in the buffer leads to a thicker double layer and / or a greater charge density on the capillary wall both result in an increased zeta-potential and increased electroosmotic flow. The electroosmotic flow is typically pH dependent. In bare fused silica (BFS) capillaries, formation of silanol groups is pH dependent. Hence, at high pH, where the surface of the capillary is more negatively charged, the electroosmotic flow is high whereas at low pH it is much lower. At pH less than 2 the groups are protonated and there is a decrease in the zeta potential and the electroosmotic flow. In the prior art this range was held ideal for glycane analysis. The opposite is true in case of positively charged wall capillaries (reversed-polarity CE or CZE). These are often capillaries coated with an adsorbed or covalent positively charged coating and exhibit reversed electroosmotic flow toward the positive electrode (the anode). Reversed-charge CZE can be used for the analysis of cationic analytes. ^Tim Wehr et al.2004 #11^ As an example a positively-charged polymer like polyethyleneimine (PEI) can be covalently attached to a capillary’s inner wall and thereby reverse the charge of the ions ont he capillary wall ^Santos, Marcia R et al. #12^. Various capillary coating methods are described e.g. in ^Hajba, L. et al., 2017 #13^ or in ^Guttman A and Hajba L.2022 #14^ as well as in ^Palaniappan KK et al.2016 #15^. Also described are labeling agents both of negative and positive charges. Considering in normal polarity separation mode in BFS column, the downstream electroosmotic flow (µEOF) and the counter-current effective mobility of the sample components including the free fluorophore (µeff), it should be possible to reason, which molecule would consequently traverse downstream towards the detector window and which would not even enter the separation capillary. It is especially in regard to the excess high mobility triple negatively charged APTS dye. In a preferred embodiment in CE analysis is carried out under alkaline background electrolyte conditions, and in normal polarity separation mode, in a CE capillary having negatively charged inner wall. In this case the negatively charged free labeling reagents, migrating upstream, i.e. counter-current relative to the electroosmotic flow, can be elektrokinetically removed, while the analyte molecules of interest migrate towards the detection zone driven by the carefully designed electroosmotic flow. The free labeling agents, by the application of the electric field, either migrate out of the capillary at the inlet side, e.g. in case of pressure injection or even do not enter capillary, e.g. in case of electrokinetic injection. The apparent mobility (µapp) of the individual sample components would be the algebraic sum of the EOF mobility (µEOF) and the counter-currently migrating effective mobility (µeff) of the analyte molecules, as delineated by Equation 2. µapp= µEOF+ µeff(Equation 2) It may be noted that Equation 2 and Equation 3 are different forms of the same relationship. The EOF mobility is a parameter that is to be carefully regulated in CE. The present inventors disclosed earlier a method according to which EOF makes possible the migration (i.e. moving) of the derivatized carbohydrates and the derivatization agents by setting the conditions so that the derivatized carbohydrates migrate by an apparent mobility towards the detector in the capillary and the free derivatization agents migrate the opposite direction, “counter-current” or upstream, their effective mobility, as to their absolute value, being higher that the electroosmotic mobility and is of opposite direction (negative), resulting in an apparent mobility directing towards the inlet (contrary to the detector). The term “migrates” (or moves) includes capable of “migrating” (or moving). For example in case of electrokinetic injection this capability of the free labeling agents result, i.e. an upstream or counter- current apparent mobility may result that they do not enter into the capillary. Thus, the electroosmotic flow is driven toward the detector and the charged, labeled carbohydrates are carried by the greater EOF mobility (i.e. migrate) towards the detector whereas the free labeling agent, having an effective mobility greater than and opposite to the EOF mobility, migrates (or at least capable of migrating) in the opposite direction. Advisably, an appropriate buffer is selected depending on the mode of separation. Typically in normal polarity separation mode a negatively charged wall capillary, e.g. a bare fused silica capillary is applied and the pH of the separation is above 7, preferably above 7.5, or preferably 7 to 10, in particular from 7.5 to 9, more preferably 7.6 to 8.6, highly particularly about 8, e.g. 8.1., depending on the pKa of the buffering component of the background electrolyte. Once the buffer is selected the ionic strength of the background electrolyte is set to obtain an appropriate EOF mobility, depending on the labeling agent and the labeled carbohydrates to ensure that the µeff of the free labeling agent may be higher, as to its absolute value, than and opposite to µEOF, i.e. having an opposite algebraic sign than µEOF, so that upon the application of the electric field during analysis the apparent mobility (µapp) of the free labeling agent and of the individual sample components point towards the opposite direction whereas the sample components are driven by the EOF towards the detector and the free labeling agent migrates to the opposite direction or does not enter the capillary. Therefore, as a first approximation the inventors contemplated that all sample components of interest with effective mobilities of less than the EOF would be carried towards the detector window as shown in Figure 1. Consequently, with the higher µeff of the charged labeling dye than that of the µEOF, its µapp will be negative, i.e., migrating out at the inlet end of the capillary. Please note that at higher buffer concentrations the µEOFvalues are lower and the µeffmay be concomitantly decreased, but not as much as the change in the µEOF, thus the concentrations and the ingredients of the buffer system were designed accordingly. Figure 1 shows the theory behind the invention in the embodiment wherein a negatively charged fused silica capillary is used in normal polarity mode. Here the charged labelling dye has to be negatively charged, an example being APTS. In case of a positively charged wall capillary a positively charged labelling agent is applied. In addition, the mobility of the co-ionic buffer component of the background electrolyte should be matched as close as possible to the mobility of the sample components to alleviate possible electromigration dispersion mediated peak efficiency losses (i.e., asymmetry based) [Mikkers et al., 1979 #10]. The present invention is in a sense is an improved method for determining glucose unit of labeled carbohydrates, using effective migration times (an inverse of relative effective mobilities) of respective maltodextrin ladder peaks. The concept of glucose unit (GU) is summarized based on the description of ^Jarvas G et al. #27^ ^Jarvas, Gabor; Szigeti, Marton; Campbell, Matthew P.; and Guttman, Andras. Chapter 19 - Database search assisted N-glycan structure identification, Editor(s): Ziad El Rassi, Carbohydrate Analysis by Modern Liquid Phase Separation Techniques (Second Edition), Elsevier, 2021, Pages 843-858^, wherein references are omitted. „The GU concept — analogously to the well-known Kovats retention index in gas chromatography — is based on the comparison of the migration times of unknown analyte peaks with a mixture of homologous oligosaccharides (usually referred to as “ladder”) to provide migration time normalization. Direct comparison of the obtained GU values of commercially available standards (e.g., well characterized carbohydrate molecules) against GUs of unknown sample components of interest is one of the essential tasks of database mediated glycan structure assignment. For a certain unknown peak in an electropherogram the GU value can be calculated based on the migration time of its adjacent sugar ladder peaks: (Equation 4) where GUX is the glucose unit value of the peak of interest, GN is the degree of polymerization of the preceding maltooligosaccharide (Glc(^1 → 4)n) ladder peak, tXis the migration time of the peak of interest, tN and tN + 1 are the migration times of the maltooligomers immediately preceding and following the peak of interest, respectively. The utilization of GU values instead of raw, unprocessed migration time data alleviates any discrepancies caused by separation parameter changes, column (capillary) history, or buffer composition alteration.” The object of the present invention is to make GU calculation even more independent of the specific experiment conditions and more stable between different measurements therefore more characteristic to a given analyte. To achieve the above-mentioned objective, at first the oligosacharide ladder, preferably the maltooligosacharide ladder migration times had to be rendered less dependent on experimental conditions. The problem here is to find a value, a "virtual EOF marker”, sufficiently approaching the theoretical migration time for electroosmotic flow to the detector window, preferably at a constant current experiment. The "virtual EOF marker” is a value sufficiently approaching the theoretical migration time for electroosmotic flow to the detector window at constant current. For example, there is a difference between the time the EOF front reaches the detector window and the time the EOF front reaches the end of the capillary providing an instability in the measurement. There is also a difference in conductivity between the sample plug and the buffer, resulting a varying EOF rate due to the difference, which also requires the use of a virtual EOF marker. Once a virtual EOF marker or “ladder-related” virtual EOF marker or “ladder-related” effective EOF migration time is obtained, it can be used to correct the migration times of the oligosaccharide ladder peaks. Such a virtual EOF marker or “ladder-related” virtual EOF marker or “ladder-related” effective EOF migration time serves as a kind of “zero” or “reference” value is obtained. The present inventors used this virtual EOF marker value – equivalent to an effective EOF migration time – to obtain “corrected” effective ladder peak migration times from an experiment when no sample is present, from the measured ladder peaks, and observered that pairwise ratios of these migration times are surprisingly stable. In a particular embodiment in case of maltooligosacharid ladder DP15 and DP3 is used to calculate this ratio. Thus, effective migration times for ladder peaks can be calculated using the measured ladder peak migration times and the effective EOF marker value using eg. Equation 3, from which such pairwise ratios of the effective ladder peak migration times can be calculated, using the virtual EOF marker value. In general, the virtual EOF marker can be used to obtain a reference value from the effective ladder peak migration times (i.e. effective migration times for ladder peaks), preferably a reference ratio from effective ladder peak migration times. In particular internal standard ladder peaks of different polymerization degree can be used for that purpose. In a further step, in an embodiment a sample measurement a sample-related virtual EOF marker or a kind of “sample-related” effective EOF migration time is obtained by running an oligosaccharide ladder, obtaining experimentally measured, i.e. sample-related ladder peaks (i.e. ladder peak migration times), using the virtual EOF marker to obtain sample-related effective ladder peaks (i.e. ladder peak migration times), and obtaining a sample-related virtual EOF marker therefrom. Alternatively this can be done by running at least a pair of internal standards from the ladder, e.g. oligosaccharide ladder and obtaining an internal standard value, e.g. a ratio, i.e. a reference ratio togetner with the sample measurement. Thereby a sample-related virtual EOF marker or a kind of “sample-related” effective EOF migration time is obtained. In an embodiment the sample-related virtual EOF marker is obtained by calculating a series of assumed reference values, preferably reference ratios of the ladder peaks, i.e. from the ladder peak migration times in the function of a series of assumed EOF migration time, i.e. an incremental set of migration times from the time-range of the migration times of the ladder peaks. The assumed reference value, e.g. ladder peak migration time ratio closest or sufficiently close to the reference value (or reference ratio) is obtained from the effective ladder peak migration times, and thereby the corresponding sample-related virtual EOF marker (or sample related EOF migration time) is identified. This value is used in further calculations as the sample-related virtual EOF marker. For example, in a further step the sample-related virtual EOF marker is used to obtain the sample- related effective ladder peaks (or ladder peak migration times). In a preferred embodiment a virtual ladder is calculated from the sample-related virtual EOF marker and the reference value (or reference ratio), e.g. the internal standard ladder peak migration time ratio. The glucose unit for a given analyte in the sample measurement is obtained by using the the sample-related effective ladder peaks (ladder peak migration times), preferably the effective ladder peak (ladder peak migration times) of the virtual ladder, in the function of the degree of polymerization, preferably by fitting a function on the sample-related effective ladder peaks in the function of the degree of polymerization; then, using the effective migration time for the analyte (calculated from the measured i.e. apparent migration time and the sample-related virtual EOF marker), and identifying the glucose unit between two sample-related effective ladder peaks. To summarize, for an actual sample measurement, by using the former calculated ladder peak migration time reference values (preferably ratio values) another virtual EOF marker and a virtual or effective ladder adapted or related to the actual sample measurement can be determined (sample-related virtual EOF marker and sample related virtual or effective ladder, i.e. the ladder is “reconstituted”; finally, for an unknown analyte (sample) in the actual sample measurement a precise glucose unit value can be determined accurately based on this mentioned virtual ladder adapted to the sample measurement. The embodiment disclosed below in detail serves to better illustrate the invention and make it easier to be understood. However, the analysis method provided herein can be applied to any CE analysis of glycanes wherein electroosmotic flow plays a part and a peak ladder as well as a reference peak ladder, e.g. a maltodextrin ladder is applied to evaluate the electropherogram migration times. Based on the above considerations, to provide an exemplary embodiment of the invention, the present inventors have disclosed earlier that alkaline pH in normal polarity mode (with anode at the injection side) the presence of electroosmotic flow can reverse the migration order of the negatively charged sample components. Using alkaline pH was thought disadvantageous in the art because of the resulting high EOF whereas reducing or eliminating EOF at lower pH, if desired together with masking (e.g. by TEA) was found to be necessary in the art for quality fluorophore labeled carbohydrate separation. However, it was possible to choose the separation conditions in a way that the charged, preferably multiply charged, in particular triply charged fluorophore labeling dye traverses the slowest or not even getting into the capillary. To exploit this concept, the present inventors disclosed earlier an electroosmotic flow assisted online electrokinetic cleanup method for negatively charged fluorophore labeled carbohydrates and negatively charged labeling dyes, (in the example APTS labeled carbohydrates, using alkaline pH background electrolyte. The resulting mobility difference between the electroosmotic flow and the counter-current differential electromigration of the sample components made possible for the analyte molecules of interest to traverse through the separation capillary towards the detector. Thus, the high electrophoretic mobility excess labeling reagent did not even enter the capillary, therefore, could not interfere with the analysis. Alternative labeling agents are well within the skills of a person skilled in the art; other examples among many are 2-aminonaphthalene trisulfonic acid (ANTS) and 2-Aminoacridone. Other variants are disclosed e.g. in ^Ruhaak LR et al. (2010) #17] and in ^Guttman A and Hajba L. (2022) #14] and references cited therein. However, non-consistent EOF rate could and can be observed at the initial period during the EOF driven capillary electrophosesis due to the difference in conductivity between the sample plug and the buffer (see Fig.2). This may cause uncertainty in the accuracy of peak analysis. In order to eliminate said uncertainty the present inventors provide a method for determining glucose unit of carbohydrates, using relative effective mobility of maltodextrin ladder peaks based on a virtual EOF marker in EOF driven capillary electrophoresis. The present invention describes a methodology for determining glucose unit of labeled carbohydrates, preferably APTS labeled carbohydrates, using the relative effective migration times, an inverse of effective mobility of maltodextrin ladder peaks in EOF driven capillary electrophoresis. The effective mobility is derived from the apparent mobility and the electroosmotic flow (EOF). In this example, a virtual EOF rate, which serves as a virtual EOF marker here, is determined using high-resolution trial substitutions for searching the best fit of the relationship between apparent migration times or mobilities and EOF migration times or mobilities and effective (or “resultant”) migration times or mobilities, e.g based on Equation 3 or Equation 2. Using migration time as shown in Equation 3 is preferred due to linearity. In an example least squares method is used in the function of virtual EOF migration times to find the best fit and virtual (or effective) EOF migration times belonging to the best fit is considered to be the virtual EOF marker and used in later experiments. Thereby the finding or identification of the virtual EOF marker provides an accurate approximation or reference (“null-point”) for the EOF. This value is then utilized to calculate the effective mobilities of ladder peaks of different DPs, allowing for the construction of a virtual ladder. The relative effective migration time ratio(s) (based on effective mobility(mobilities)) of ladder peaks is employed to find the virtual EOF for samples containing internal standards. The methodology disclosed in the present description provides a robust framework for accurate peak analysis in EOF driven capillary electrophoresis method of labeled carbohydrates. It should be noted that all mobility values in the present description are relative mobilities for simplicity, therefore, the absolute mobility values are not needed for the calculation. In an embodiment the determination of the GU value is based on the relation to the effective mobilities of the labeled, preferably APTS labeled maltodextrin (MD) ladder components in a sample- measurement (sample-related effective mobilities). To determine the effective mobility of the maltodextrin structures, we used the apparent mobility of the maltodextrin ladder components. The effective mobility is the algebraic sum of the apparent mobility and the EOF mobility (see Equation 2 above). The effective migration time (which, in the recent system without EOF and with reverse polarity, would be the detectable migration time) can be determined from the apparent migration times using the following formula (Equation 3): (Equation 3) It should be noted that a commonly applied technique to determine the EOF in CE is to measure the migration time of a neutral marker. An ideal neutral EOF marker should be uncharged throughout the whole pH range used, should be easy to detect, and it should not significantly interact with charged components in the background electrolyte. In contrast, according to the present invention a virtual EOF migration time is determined by a numeric approach as detailed below. Exemplary maltodextrin ladder electropherogram evaluation The virtual EOF migration time of maltodextrin ladder peak (MD) measurement was determined by a numeric approach (trial-and-error methodology) of using Equation 3 for finding the best linear fitting to the effective migration times of a peak assigned to a given (coordinate i) species of a given degree of polymerization (i; ), wherein coordinates i = 8 to 16, where the coefficient of determination of the best fit is always greater than 0.9999 (r2>0.9999). Thereby a virtual EOF migration time of MD measurement (virtual EOF marker) is identified. The virtual EOF migration time of MD measurement, i.e. the value is almost equal to the value obtained from a real EOF markers, except that it eliminates the error resulting from the fact that the current does not settle to a nearly constant value until the sample plug passes through the capillary via the EOF due to conductivity differences (see Fig.2). Using the virtual EOF migration time as a virtual EOF marker, we determined all the migration time ratios for j = 3 to 16 for species of each degrees of polymerization that do not change between measurements in the current system and in particular for the ratio which is particularly stable. Evaluation of an electropherogram with an unknown glycan sample containing internal standards (DP3 and DP15) peaks Because the system does not change the effective migration time rates of the ladder peaks, the virtual (effective) EOF migration time of sample measurement can be numerically determined using Equation 3, as the effective migration time ratio of the internal standards (DP3 and DP15) in this sample measurement has to be equal to the already determined ratio. With the values, effective migration time values of virtual MD ladder between DP3 - DP16 can be created for the unknown sample plus internal standard measurement. To this virtual MD ladder we fitted curves to the (n; ) coordinates: linear for n = 8 to 16 (r2> 0.9999) and second-degree polynomial for n = 3 to 8 (r2=1). We determined the effective migration time of the sample peak using the apparent migration time of the peak and sample-related virtual EOF marker value using Equation 3. The calculation of the GU value from the graphs of virtual MD ladder is carried out with the linear and polynomial fits, depending on which range of the MD ladder the sample migration time falls: applying the linear equation, , applying the second-degree polynomial equation. It must be emphasized that the method according to the present invention does not only work for DP3 and DP15, because the effective migration time ratio of any two ladder peaks can be considered asunchanged. It also works for DP4 and DP3, for example. This may be advantageous in cases where the DP15 peak is not sufficiently separated from a sample peak. Based on the forgoing, the aspect of the invention is a method for determining glucose unit of labeled carbohydrates, wherein said method comprises the following steps: a) performing a CE analysis of an MD ladder sample, b) determination of apparent migration times of MD ladder peaks DP16 to DP3 (n= 3 to 16) from the electropherogram; c) numeric determination of MD-related virtual EOF migration time related to the MD measurement within the migration time range, wherein c.1) an incremental set of values from the migration time range (into which the MD-related virtual EOF migration time must fall) is selected (preferably with small, preferably less than 0.1 s, more preferably less than 0.01 s increments) and with each selected migration time for every apparent migration times of MD ladder peaks DP16 to DP8 (n is an integer in the linear portion of the migration times of the MD ladder, preferably between 8-16) the virtual (effective) migration times of MD ladder peaks are calculated using Equation 3, preferably in the form of Equation 3.1, (Equation 3.1) c.2) a line is fitted on the data set of the polymerization degrees DP(n) and the resulting virtual (effective) migration times of MD ladder peak values (i; ), (i= 8 to 16), and then the fit of the line is examined, c.3) a sample migration time value is selected as MD related virtual EOF migration time wherein the fit is sufficiently good, preferably the coefficient of determination (R2) for a linear fit is above 0,999, preferably above 0,9999, d) using this MD related virtual EOF migration time value , d.1) calculation of every virtual (effective) MD peak migration time value for the ladder peaks between DP16-DP3 using Equation 3, preferably in the form of Equation 3.1, and d.2) calculation of every pairwise virtual (effective) MD peak migration time ratio for j = 3 to 16 and d.3) calculation of an internal standard virtual (effective) MD peak migration time ratio wherein DP(p) and DP(q) are any two internal standard MD ladder peaks, preferably p = 3 and q = 15, or p = 3 and q = 4, e) perfoming CE analysis of unknown glycan sample together with internal standards DP(p) and DP(q); f) determination of (measured) apparent migration times of DP(p), DP(q) and one or more relevant peak(s) of interest of one or more unknown analyte(s) of interest in the sample; g) numeric determination of sample-related virtual EOF migration time of sample measurement for which the effective migration time ratio of the internal standards DP(p) and DP(q) will be sufficiently close to or substantially equal to the internal standard virtual (effective) MD peak migration time ratio determined in step d); preferably by g1) a set of values from, preferably spanning the migration time range is selected (preferably with small, preferably less than 0.05 s, more preferably less than 0.01 s increments) and with each selected migration time the sample-related effective MD peak migration time ratio is calculated and g2) a value which is sufficiently close to the virtual (effective) MD peak migration time ratio determined in step d is selected and considered as the sample-related virtual (effective) EOF migration time (EOF marker value) , h) creation of virtual MD ladder from DP3 to DP16 using and ratios, by h1) calculation of the effective migration times , of the internal standard peaks DP(p) and DP(q) by substituting the sample-related virtual (effective) EOF migration time and the (measured) apparent migration times of DP(p), DP(q) into Equation 3, h2) using the effective migration times of the internal standard peaks values and the pairwise effective MD peak migration time ratios ladder peaks between DP16-DP3 a sample-related virtual ladder migration times on the sample electropherogram is calculated, i) curve fitting to the sample-related virtual ladder migration times (n; , preferably - a straight line between DP8-DP15 and - a second-degree polynomial between DP3-DP8, j) determination of the effective migration time of the one or more analyte peak of interest of the sample using the apparent migration time of the peak and virtual (effective) sample-related EOF migration time k) calculation of the GU value for the one or more analyte of interest using the virtual MD ladder migration times based on one of the following conditions: - if ≥ , applying the linear equation, or , applying the second-degree polynomial equation, effective migration time of the analyte of interest. In a preferred embodiment the numeric determination of virtual EOF migration time is carried out by a minimum-seeking method or algorithm. Preferably the method is the selection of the best fitting curve from various curve-fittings and value(s) corresponding thereto. Preferably the value is selected from an incremental set of values of a range of interest, e,g. a range into which the sought value shall fall. In an embodiment a trial-and-error methodology can be applied. In an embodiment the labeled carbohydrates are labeled by labeling agent, which in its free form is negatively or positively charged. In an embodiment the labeling agent is a dye, preferably fluorescent dye. In a preferred embodiment the labeling agent is ATPS. In an embodiment the surface of the capillary is negatively charged. In an embodiment the surface of the capillary is positively charged. The invention is further illustrated below by non-limiting example. The skilled person is aware that based on the example alternative embodiments or variants thereof may also fulfill the object of the invention. Example 1 - Demonstration of the evaluation method according to the present invention First the maltodextrin ladder is measured and then the migration times of the DP16-DP3 ladder peaks are determined from the electropherogram: Table 1 MD Peak 16 15 14 13 12 11 10 9 8 7 6 5 4 3 Migration 5.004 5.102 5.215 5.347 5.502 5.685 5.901 6.159 6.465 6.848 7.400 8.229 9.68212.707 time (min) Then, for each ladder peak between DP16 and DP8 values are substituted into Equation 3 for values from zero to twelve (a selected set of values wherein the wanted value must fall within this range) in 5-tenths of a thousandth increments: (Equation 3.1) In each case, a line is fitted between the polymerization degrees and the resulting values, and then the fit of the line is examined. The highest value of coefficient of determination (R2) must be sought and the corresponding value will be the value. As this calculation step results in thousands of data, we have listed only a few in Table 2, where the highlighted result is considered to be the best one. Table 2 0.3795 0.3800 3.4400 3.4405 3.4410 4.6675 4.6680 2 … … … … Fit (R ) 0.988459 0.98846 0.9999430.9999430.999943 0.9219830.921803 In this actual case, the best fit is R2= 0.999943, with value of = 3.4405. Using this value, we can determine the all value of the ladder peaks between DP16-DP3 using Equation 3: Table 3 MD peak 16 15 14 13 12 11 10 9 8 7 6 5 4 3 (min)11.010 10.564 10.1139.6509.1828.7138.2517.7947.3556.9146.4305.9125.3374.718 Using this values, we can determine the all ratios (effective migration time ratios) of the ladder peaks between DP16-DP3: Table 4 MD peaks 15-1614-1513-1412-1311-1210-11 9-10 8-9 7-8 6-7 5-6 4-5 3-4 Effective mig. time 0.9590.9570.9540.9520.9490.9470.9450.9440.9400.9300.9190.9030.884 ratios In addition, the effective migration time ratio of the two ladder peaks (in this case DP3 and DP15, ) used as the internal standard in the sample should also be determined. The next step is to determine the migration times of the peaks of the electropherogram under analysis, including two internal standard peaks (DP15 and DP3 in this case) and the unknown peaks: Table 5: Peak ID DP15 DP3 Peak #1 Peak #2 Migration time (min) 5.175 13.870 6.387 7.073 The ratio of the effective migration times of the two internal standards and the corresponding ladder peaks (DP15 and DP3) is the same for a given system, so it is possible to find the value for the sample electropherogram. To do this again, values are substituted into the Equation 3 in small increments, looking for the value that gives the ratio closest to the ratio already determined Table 5: 4.1998 4.1996 3.4366 3.4364 3.4362 2.4596 2.4594 Effective mig. … … ……time ratio (DP3- 0.2703 0.2703 0.4465 0.4466 0.4466 0.6378 0.6378 DP15) With this step the value has been determined, which can be used to calculate the effective migration times of the internal standard peaks based on Equation 3. Using these two values and the ratios (effective migration time ratios) of the ladder peaks between DP16-DP3 (Table 4) it can be build up the virtual ladder on the sample electropherogram: Table 6: Virtual MD peak 16 15 14 13 12 11 10 9 8 7 6 5 4 3 10.66010.2299.791 9.343 8.8908.4367.9897.546 7.1216.6946.2255.7245.167 4.568 (min) Fitting a straight line between DP8-DP15 and a second-degree polynomial between DP3-DP8 to the values of the Table 6 gives the graphs shown in Figures 3 and 4. It is then necessary to examine how the effective migration times of the unknown peaks compare to the effective migration time of DP8. If this value is greater than the value of virtual MD ladder (e.g. Peak #1), it is substituted into the linear equation, if less, it is substituted into the second-degree equation (e.g. Peak #1). The resulting GU values for the peaks are: GU(Peak #1) = 8.74; GU(Peak #2) = 6.97. INDUSTRIAL APPLICABILITY Based on the foregoing findings above, the present invention provides a method for determining glucose unit of labeled carbohydrates using relative effective mobility of maltodextrin ladder peaks calculated with a virtual EOF rate in EOF driven capillary electrophoresis. The advantage of the present invention is that the uncertainty in the evaluation of the electropherogram obtained by EOF driven capillary electrophoresis, caused by the non-consistent EOF rate, can be eliminated by the method described above. REFERENCES (1) Saldova, R.; Royle, L.; Radcliffe, C. M.; Abd Hamid, U. M.; Evans, R.; Arnold, J. N.; Banks, R. E.; Hutson, R.; Harvey, D. J.; Antrobus, R.; Petrescu, S. M.; Dwek, R. A.; Rudd, P. M. Glycobiology 2007, 17, 1344-1356. (2) Shrivastava, A.; Joshi, S.; Guttman, A.; Rathore, A. S. Analytica chimica acta 2022, 1209, 339828. (3) Sarkozy, D.; Farsang, R.; Szigeti, M.; Austin, S.; Lock, S.; Guttman, A. 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Meyers, Encyclopedia of Physical Science and Technology (Third Edition), Academic Press, 2003, Pages 355-368 (12) Santos, Marcia R; Ratnayake, Chitra K.; Fonslow, Bryan; Guttman, Andras “A covalent, cationic polymer coating method for the CESI-MS analysis of intact proteins and polypeptides” Biomarkers and Omics 2015 AB Sciex. SCIEX Separations, Brea, CA Document number: RUO-MKT-18-2325-A (13) L. Hajba, A. Guttman, Recent advances in column coatings for capillary electrophoresis of proteins, TrAC Trends in Analytical Chemistry 90 (2017) 38-44 (14) Guttman A and Hajba L. Capillary Electrophoresis, Elsevier Oxford OX51GB, United Kingdom, 2022 (15) Palaniappan KK, Bertozzi CR. Chemical Glycoproteomics. Chem Rev.2016 Dec 14;116(23):14277- 14306. doi: 10.1021 / acs.chemrev.6b00023. Epub 2016 Nov 18. PMID: 27960262; PMCID: PMC5327817. (16) IUPAC. Compendium of Chemical Terminology, 2nd ed. (the "Gold Book"). Compiled by A. D. McNaught and A. Wilkinson. Blackwell Scientific Publications, Oxford (1997). Online version (2019-) created by S. J. Chalk. ISBN 0-9678550-9-8. https: / / doi.org / 10.1351 / goldbook. (17) Ruhaak LR, Zauner G, Huhn C, Bruggink C, Deelder AM, Wuhrer M. Glycan labeling strategies and their use in identification and quantification. Anal Bioanal Chem.2010 Aug; 397(8):3457-81. (18) Farsang R., Hogyor K., Jarvas G., Guttman A., Capillary Zone Electrophoresis of 8-Aminopyrene- 1,3,6-trisulfonic Acid Labeled Carbohydrates with Online Electrokinetic Sample Cleanup. Analytical Chemistry 202395(45):16459-16464. doi:10.1021 / acs.analchem.3c03714. (19) E. Kováts, Gas-chromatographische Charakterisierung organischer Verbindungen. Teil 1: Retentionsindices aliphatischer Halogenide, Alkohole, Aldehyde und Ketone, Helv. Chim. Acta 41 (7) (1958) 1915–1932. (20) G. Jarvas, M. Szigeti, A. Guttman, Structural identification of N-linked carbohydrates using the GUcal application: a tutorial, J. Proteomics 171 (2018) 107–115. (21) K. Yamashita, T. Mizuochi, A. Kobata, Analysis of oligosaccharides by gel filtration, Methods Enzymol.83 (1982) 105–126. (22) S. Mittermayr, A. Guttman, Influence of molecular configuration and conformation on the electromigration of oligosaccharides in narrow bore capillaries, Electrophoresis 33 (6) (2012) 1000–1007. (23) A. Guttman, F.-T.A. Chen, R.A. Evangelista, Separation of 1-aminopyrene-3,6,8-trisulfonate-labeled asparagine-linked fetuin glycans by capillary gel electrophoresis, Electrophoresis 17 (2) (1996) 412–417. (24) A. Guttman, S. Herrick, Effect of the quantity and linkage position of mannose (alpha 1,2) residues in capillary gel electrophoresis of high-mannose-type oligosaccharides, Anal. Biochem. 235 (2) (1996) 236–239. (25) K. Mariño et al., A systematic approach to protein glycosylation analysis: a path through the maze, Nat. Chem. Biol.6 (10) (2010) 713–723. (26) G. Jarvas, M. Szigeti, A. Guttman, GUcal: an integrated application for capillary electrophoresis based glycan analysis, Electrophoresis 36 (24) (2015) 3094–3096. (27) Jarvas, Gabor; Szigeti, Marton; Campbell, Matthew P.; and Guttman, Andras. Chapter 19 - Database search assisted N-glycan structure identification, Editor(s): Ziad El Rassi, Carbohydrate Analysis by Modern Liquid Phase Separation Techniques (Second Edition), Elsevier, 2021, Pages 843-858

Claims

Claims 1. A method for determining glucose unit of labeled carbohydrates, wherein said method comprises the following steps: for a capillary electrophoresis analysis, providing a virtual (effective) EOF marker value, related to standard ladder peak migration times or mobilities, providing a set of effective ladder peak migration times or mobilities, using the virtual EOF marker value; providing an internal standard ladder peak value for internal standards of different degrees of polymerization; perfoming a capillary electrophoresis analysis of unknown glycan sample together with internal standards of different degrees of polymerization, for the actual sample measurement, another, sample-related virtual EOF marker is determined, sample-related effective ladder peak migration times or mobilities, using the sample-related virtual EOF marker value are calculated, sample-related effective migration times or mobilities of internal standards are calculated, and a virtual ladder is calculated (determined or “reconstituted”) from the effective ladder peak migration times or mobilities and from the migration times or mobilities of the internal standards; adjusting the adjustable variables of a related mathematical function, preferably curve fitting to the sample-related virtual ladder so calculated, determination of the effective migration time or mobility of the one or more analyte peak(s) of the sample, calculation of the GU value for the one or more analyte of interest using the virtual ladder.

2. The method for determining glucose unit of labeled carbohydrates according to claim 1, wherein said method comprises the following steps: for a capillary electrophoresis analysis, providing an effective EOF migration time useful as a virtual (effective) EOF marker value, related to standard ladder peak migration times, preferably maltooligosacharide ladder peak migration times, providing ratios of effective ladder peak migration times, using the virtual EOF marker value; providing an internal standard ladder peak migration time ratio for internal standards of different degrees of polymerization (DP(p) and DP(q), wherein p and q are the identifier of the oligosaccharide in the ladder selected as an internal standard;perfoming a capillary electrophoresis analysis of unknown glycan sample together with internal standards of different degrees of polymerization (DP(p) and DP(q)) for the actual sample measurement, another, sample-related virtual EOF marker is determined, sample-related effective ladder peak migration times, using the sample-related virtual EOF marker value are calculated, sample-related effective migration times of internal standards DP(p) and DP(q) are calculated, and a virtual ladder is calculated (determined or “reconstituted”) from the effective ladder peak migration times and migration times of the internal standards (DP(p) and DP(q)); curve fitting to the sample-related virtual ladder migration times, determination of the effective migration time of the one or more analyte peak(s) of interest of the sample, calculation of the GU value for the one or more analyte of interest using the virtual ladder migration times.

3. The method for determining glucose unit of labeled carbohydrates according to claim 1 or 2, wherein: the "virtual EOF marker” is a value sufficiently approaching the theoretical migration time for electroosmotic flow to the detector window at constant current.

4. The method for determining glucose unit of labeled carbohydrates according to any of claims 1 to 3, wherein: the virtual EOF marker value – equivalent to an effective EOF migration time – is used to effective ladder peak migration times, in an experiment when no sample is present, from the measured ladder peaks. and at least two internal standards of different degrees of polymerization are identified, wherein the ratio of the migration times of the internal standards is stable for varying measurement conditions.

5. The method for determining glucose unit of labeled carbohydrates according to any of claims 1 to 4, wherein the ladder is maltooligosacharide ladder.

6. The method for determining glucose unit of labeled carbohydrates according to any of claims 1 to 5, wherein the ladder is maltooligosacharide ladder and the internal standard pair is selected from DP15 and DP3; as well as DP4 and DP3.

7. The method for determining glucose unit of labeled carbohydrates according to any of claims 1 to 6, wherein the sample-related virtual EOF marker is obtained by calculating a series of sample-related ladder peak migration times in the function of a series of assumed EOF migration time, i.e. an incremental set of values from the migration time range, to find a sample-related virtual EOF marker (as an assumed reference value closest or sufficiently close to the reference internal standard value (or reference internal standard ratio).

8. The method for determining glucose unit of labeled carbohydrates according to any of claims 1 to 7, wherein the glucose unit for a given analyte in the sample measurement is obtained by using the sample- related virtual effective ladder peaks (ladder peak migration times) in the function of the degree of polymerization, preferably by fitting a function on the sample-related effective ladder peaks in the function of the degree of polymerization; then, using the effective migration time for the analyte (calculated from the measured i.e. apparent migration time and the sample-related virtual EOF marker), the glucose unit is identified between two sample-related effective ladder peaks.

9. A method for determining glucose unit of labeled carbohydrates according to any of claims 1 to 8 wherein said method comprises the following steps: a) performing CE analysis of MD ladder sample; b) determination of apparent migration times of MD ladder peaks DP16 to DP3(n= 3 to 16) from the electropherogram; c) numeric determination of MD-related virtual EOF migration time of MD measurementusing Equation 3 for finding a sufficiently fitting, preferably the essentially best-fitting linear curve on virtual (effective) migration times of MD ladder peak values, (i;) (i = 8 to 16) calculated with an incremental set of selected migraton time values from the migration time range into which the MD-related virtual EOF migration time must fall; d) calculation of every pairwise virtual (effective) MD peak migration time ratioan internal standard virtual (effective) MD peak migration time ratioratiousing e) perfoming CE analysis of unknown glycan sample together with internal standards DP(p) and DP(q); f) determination of apparent migration times of DP(p), DP(q) and one or more relevant peak(s) of interest of one or more unknown analyte(s) of interest in the sample; g) numeric determination of sample-related virtual EOF migration time of sample measurementfor which the effective migration time ratio of the internal standards DP(p) and DP(q) will be sufficiently close to or substantially equal to the determinedratio; as well as calculation of effective migration times of internal standards DP(p) and DP(q) with the sample-related virtual EOF migration time, h) creation of virtual MD ladder from DP3 to DP16 usingandratios; i) curve fitting to the sample-related virtual ladder migration times (n;in particular - a straight line between DP8-DP15 and - a second-degree polynomial between DP3-DP8, j) determination of the effective migration time of the one or more analyte peak of interest of the sample using the apparent migration time of the peak and virtual (effective) sample-related EOF migration timek) calculation of the GU value for the one or more analyte of interest using the virtual MD ladder migration times based on one of the following conditions: applying the linear equation, or , applying the second-degree polynomial equation,the effective migration time of the analyte of interest, wherein DP(p) and DP(q) are any two of MD ladder peaks, preferably p = 3 and q = 15, or p = 3 and q = 4.

10. The method for determining glucose unit of labeled carbohydrates according to any of claims 1 to 9 wherein said method comprises the following steps: a) performing a CE analysis of an MD ladder sample, b) determination of apparent migration times of MD ladder peaks DP16 to DP3(n= 3 to 16) from the electropherogram; c) numeric determination of MD-related virtual EOF migration time related to the MD measurementwithin the migration time range, wherein c.1) an incremental set of values from the migration time range (into which the MD-related virtual EOF migration time must fall) is selected (preferably with small, preferably less than 0.1 s, more preferably less than 0.01 s increments) and with each selected migration time for every apparent migration times of MD ladder peaks DP16 to DP8(n is an integer in the linear portion of the migration times of the MD ladder, preferably between 8-16) the virtual (effective) migration times of MD ladder peaksare calculated using Equation 3, preferably in the form of Equation 3.1,(Equation 3.1) c.2) a line is fitted on the data set of the polymerization degrees DP(n) and the resulting virtual (effective) migration times of MD ladder peak values (i;(i= 8 to 16), and then the fit of the line is examined, c.3) a sample migration time value is selected as MD related virtual EOF migration timewherein the fit is sufficiently good, preferably the coefficient of determination (R2) for a linear fit is above 0,999, preferably above 0,9999, d) using this MD related virtual EOF migration time value, d.1) calculation of every virtual (effective) MD peak migration time value for the ladder peaks between DP16-DP3 using Equation 3, preferably in the form of Equation 3.1, and d.2) calculation of every pairwise virtual (effective) MD peak migration time ratiod.3) calculation of an internal standard virtual (effective) MD peak migration time ratiowherein DP(p) and DP(q) are any two internal standard MD ladder peaks, preferably p = 3 and q = 15, or p = 3 and q = 4, e) perfoming CE analysis of unknown glycan sample together with internal standards DP(p) and DP(q); f) determination of (measured) apparent migration times of DP(p), DP(q) and one or more relevant peak(s) of interest of one or more unknown analyte(s) of interest in the sample; g) numeric determination of sample-related virtual EOF migration time of sample measurementfor which the effective migration time ratio of the internal standards DP(p) and DP(q) will be sufficiently close to or substantially equal to the internal standard virtual (effective) MD peak migration time ratiodetermined in step d); preferably by g1) a set of values from, preferably spanning the migration time range is selected (preferably with small, preferably less than 0.05 s, more preferably less than 0.01 s increments) and with each selected migration time the sample-related effective MD peak migration time ratiois calculated and g2) a value which is sufficiently close to the virtual (effective) MD peak migration time ratiodetermined in step d is selected and considered as the sample-related virtual (effective) EOF migration time (EOF marker value), h) creation of virtual MD ladder from DP3 to DP16 usingandratios, by h1) calculation of the effective migration timesof the internal standard peaks DP(p) and DP(q) by substituting the sample-related virtual (effective) EOF migration timeand the (measured) apparent migration times of DP(p), DP(q) into Equation 3,ladder peaks between DP16-DP3 a sample-related virtual ladder migration times on the sample electropherogram is calculated, i) curve fitting to the sample-related virtual ladder migration times (n;, preferably - a straight line between DP8-DP15 and - a second-degree polynomial between DP3-DP8, j) determination of the effective migration time of the one or more analyte peak of interest of the sample using the apparent migration time of the peak and virtual (effective) sample-related EOF migration timek) calculation of the GU value for the one or more analyte of interest using the virtual MD ladder migration times based on one of the following conditions: applying the linear equation, or applying the second-degree polynomial equation,effective migration time of the analyte of interest.

11. The method for determining glucose unit of labeled carbohydrates according to any of claims 1 to 10 wherein the labeled carbohydrates are labeled by labeling agent, which in its free form is negatively or positively charged.

12. The method for determining glucose unit of labeled carbohydrates according to claim 11, wherein the labeling agent is a dye, preferably fluorescent dye.

13. The method for determining glucose unit of labeled carbohydrates according to any of claims 1 to 10, wherein the surface of the capillary is negatively charged.

14. The method for determining glucose unit of labeled carbohydrates according to any of claims 1 to 10, wherein the surface of the capillary is positively charged.

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