Algorithms and tools for analysis and management of mass spectrometry data

Mass spectrometry (MS) is a technique that is used for biological studies. It consists in associating a spectrum to a biological sample. A spectrum consists of couples of values (intensity, m/z), where intensity measures the abundance of biomolecules (as proteins) with a mass-to-charge ratio (m/z) present in the originating sample. In proteomics experiments, MS spectra are used to identify pattern expressions in clinical samples that may be responsible of diseases. Recently, to improve the identification of peptides/proteins related to patterns, MS/MS process is used, consisting in performing cascade of mass spectrometric analysis on selected peaks. Latter technique has been demonstrated to improve the identification and quantification of proteins/peptide in samples. Nevertheless, MS analysis deals with a huge amount of data, often affected by noises, thus requiring automatic data management systems. Tools have been developed and most of the time furnished with the instruments allowing: (i) spectra analysis and visualization, (ii) pattern recognition, (iii) protein databases querying, (iv) peptides/proteins quantification and identification. Currently most of the tools supporting such phases need to be optimized to improve the protein (and their functionalities) identification processes. In this article we survey on applications supporting spectrometrists and biologists in obtaining information from biological samples, analyzing available software for different phases. We consider different mass spectrometry techniques, and thus different requirements. We focus on tools for (i) data preprocessing, allowing to prepare results obtained from spectrometers to be analyzed; (ii) spectra analysis, representation and mining, aimed to identify common and/or hidden patterns in spectra sets or in classifying data; (iii) databases querying to identify peptides; and (iv) improving and boosting the identification and quantification of selected peaks. We trace some open problems and report on requirements that represent new challenges for bioinformatics.     

Sample preparation of Gram-positive bacteria for identification by matrix assisted laser desorption/ionization time-of-flight.

A new sample preparation method was developed for fresh, whole-cell Gram-positive bacteria to be analyzed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI ToF MS). With fresh, whole-cell Gram-negative bacteria of the Enterobacteriaceae family, we had previously achieved spectra consisting of >50 peaks and mass ranges of 2-25 kDa. Because similar spectral quantity could not be achieved for Gram-positive bacteria, using this same protocol, we investigated an alternative approach that focuses on the thick peptidoglycan layer of the cell wall. Gram-positive bacteria were incubated with 0.05-0.5 mg/ml lysozyme for 30 min prior to being analyzed by MALDI ToF MS. Lysozyme is an enzymatically stable, 14-kDa protein that specifically cleaves between peptidoglycan disaccharide subunits. A significant increase in overall number of peaks (>50) in the 2-14 kDa range was observed without interference from the presence of lysozyme. We show that for four different species (Staphylococcus aureus, S. haemolyticus, Streptococcus pyogenes, and S. agalactiae) reproducible subset of peaks were found within spectra from a reference strain and two unrelated clinical isolates. The data suggests that this sample preparation may be useful for increasing the overall number of peaks within spectra for subsequent development of bacterial identification strategies.     

利用基因组学和MALDI-TOF MS技术鉴定放线菌纲细菌的核糖体蛋白质标志物

【目的】基质辅助激光解吸电离飞行时间质谱(MALDI-TOF MS)法基于微生物的特征蛋白指纹图谱鉴定菌种,本研究利用基因组学和MALDI-TOFMS技术鉴定放线菌纲细菌的核糖体蛋白质标志物。【方法】从MALDI-TOF MS图谱数据库选取放线菌纲代表菌种,在基因组数据库检索目标菌种,获取目标菌株或其参比菌株的核糖体蛋白质序列,计算获得分子质量理论值,用于注释目标菌株MALDI-TOFMS指纹图谱中的核糖体蛋白质信号。【结果】从8目,24科,53属,114种,142株放线菌的MALDI-TOFMS图谱中总共注释出31种核糖体蛋白质。各菌株的指纹图谱中核糖体蛋白质信号数量差异显著。各种核糖体蛋白质信号的注释次数差异显著。总共15种核糖体蛋白质在超过半数图谱中得到注释,注释次数最高的是核糖体大亚基蛋白质L36。【结论】本研究找到了放线菌纲细菌MALDI-TOF MS图谱中常见的15种核糖体蛋白质信号,可为通过识别核糖体蛋白质的质谱特征峰鉴定放线菌的方法建立提供依据。     

A new algorithm for the evaluation of shotgun peptide sequencing in proteomics: support vector machine classification of peptide MS/MS spectra and SEQUEST scores

Shotgun tandem mass spectrometry-based peptide sequencing using programs such as SEQUEST allows high-throughput identification of peptides, which in turn allows the identification of corresponding proteins. We have applied a machine learning algorithm, called the support vector machine, to discriminate between correctly and incorrectly identified peptides using SEQUEST output. Each peptide was characterized by SEQUEST-calculated features such as delta Cn and Xcorr, measurements such as precursor ion current and mass, and additional calculated parameters such as the fraction of matched MS/MS peaks. The trained SVM classifier performed significantly better than previous cutoff-based methods at separating positive from negative peptides. Positive and negative peptides were more readily distinguished in training set data acquired on a QTOF, compared to an ion trap mass spectrometer. The use of 13 features, including four new parameters, significantly improved the separation between positive and negative peptides. Use of the support vector machine and these additional parameters resulted in a more accurate interpretation of peptide MS/MS spectra and is an important step toward automated interpretation of peptide tandem mass spectrometry data in proteomics.     

Improving feature detection and analysis of surface-enhanced laser desorption/ionization-time of flight mass spectra

Discovering valid biological information from surface-enhanced laser desorption/ionization-time of flight mass spectrometry (SELDI-TOF MS) depends on clear experimental design, meticulous sample handling, and sophisticated data processing. Most published literature deals with the biological aspects of these experiments, or with computer-learning algorithms to locate sets of classifying biomarkers. The process of locating and measuring proteins across spectra has received less attention. This process should be tunable between sensitivity and false-discovery, and should guarantee that features are biologically meaningful in that they represent chemical species that can be identified and investigated. Existing feature detection in SELDI-TOF MS is not optimal for acquiring biologically relevant data. Most methods have so many user-defined settings that reproducibility and comparability among studies suffer considerably. To address these issues, we have developed an approach, called simultaneous spectrum analysis (SSA), which (i) locates proteins across spectra, (ii) measures their abundance, (iii) subtracts baseline, (iv) excludes irreproducible measurements, and (v) computes normalization factors for comparing spectra. SSA uses only two key parameters for feature detection and one parameter each for quality thresholds on spectra and peaks. The effectiveness of SSA is demonstrated by identifying proteins differentially expressed in SELDI-TOF spectra from plasma of wild-type and knockout mice for plasma glutathione peroxidase. Comparing analyses by SSA and CiphergenExpress Data Manager 2.1 finds similar results for large signal peaks, but SSA improves the number and quality of differences betweens groups among lower signal peaks. SSA is also less likely to introduce systematic bias when normalizing spectra.     

Clustering of MS spectra for improved protein identification rate and screening for protein variants and modifications by MALDI-MS/MS

It is an established fact that allelic variation and post-translational modifications create different variants of proteins, which are observed as isoelectric and size subspecies in two-dimensional gel based proteomics. Here we explore the stromal proteome of spinach and Arabidopsis chloroplast and show that clustering of mass spectra is a useful tool for investigating such variants and detecting modified peptides with amino acid substitutions or post-translational modifications. This study employs data mining by hierarchical clustering of MALDI-MS spectra, using the web version of the SPECLUST program (http://bioinfo.thep.lu.se/speclust.html). The tool can also be used to remove peaks of contaminating proteins and to improve protein identification, especially for species without a fully sequenced genome. Mutually exclusive peptide peaks within a cluster provide a good starting point for MS/MS investigation of modified peptides, here exemplified by the identification of an A to E substitution that accounts for the isoelectric heterogeneity in protein isoforms.     

Analysis of human serum proteins by liquid phase isoelectric focusing and matrix-assisted laser desorption/ionization-mass spectrometry

Direct matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) analysis of human serum yielded ion signals from only a fraction of the total number of peptides and proteins expected to be in the sample. We increased the number of peptide and protein ion signals observed in the MALDI-TOF mass spectra analysis of human serum by using a prefractionation protocol based on liquid phase isoelectric focusing electrophoresis. This pre-fractionation technique facilitated the MALDI-TOF MS detection of as many as 262 different peptide and protein ion signals from human serum. The results obtained from three replicate fractionation experiments on the same serum sample indicated that 148 different peptide and protein ion signals were reproducibly detected using our isoelectric focusing and MALDI-TOF MS protocol.     

基于谱图库的蛋白质鉴定策略研究进展

基于质谱的蛋白质组学快速发展,蛋白质质谱数据也呈指数式增长。寻找速度快、准确度高以及重复性好的鉴定方法是该领域的一项重要任务。谱图库搜索策略直接比较实验谱图与谱图库中的真实谱图,充分利用了谱图中的丰度、非常规碎裂模式和其他的一些特征,使得搜索更加快速和准确,成为蛋白质组学的主流鉴定方法之一。文中介绍基于谱图库的蛋白质组质谱数据鉴定策略,并针对其中两个关键步骤——谱图库构建方法和谱图库搜索方法进行深入介绍,探讨了谱图库策略的进展和挑战。     

A signature-based method to distinguish time-of-flight secondary-ion mass spectra from biological samples

Time-Of-Flight Mass Spectrometry (TOF-SIMS) was used to determine elemental and biomolecular ions from isolated protein samples. We identified a set of 23 mass-to-charge ratio (m/z) peaks that represent signatures for distinguishing biological samples. The 23 peaks were identified by Singular Value Decomposition (SVD) and Canonical Analysis (CA) to find the underlying structure in the complex mass-spectra data sets. From this modified data, SVD was used to identify sets of m/z peaks, and we used these patterns from the TOF-SIMS data to predict the biological source from which individual mass spectra were generated. The signatures were validated using an additional data set different from the initial training set used to identify the signatures. We present a simple method to identify multiple variables required for sample classification based on mass spectra that avoids overfit. This is important in a variety of studies using mass spectrometry, including the ability to identify proteins in complex mixtures and for the identification of new biomarkers.     

Matrix-assisted laser desorption/ionization-tandem mass spectrometry with high resolution and sensitivity for identification and characterization of proteins

Although peptide mass fingerprinting is currently the method of choice to identify proteins, the number of proteins available in databases is increasing constantly, and hence, the advantage of having sequence data on a selected peptide, in order to increase the effectiveness of database searching, is more crucial. Until recently, the ability to identify proteins based on the peptide sequence was essentially limited to the use of electrospray ionization tandem mass spectrometry (MS) methods. The recent development of new instruments with matrix-assisted laser desorption/ionization (MALDI) sources and true tandem mass spectrometry (MS/MS) capabilities creates the capacity to obtain high quality tandem mass spectra of peptides. In this work, using the new high resolution tandem time of flight MALDI-(TOF/TOF) mass spectrometer from Applied Biosystems, examples of successful identification and characterization of bovine heart proteins (SWISS-PROT entries: P02192, Q9XSC6, P13620) separated by two-dimensional electrophoresis and blotted onto polyvinylidene difluoride membrane are described. Tryptic protein digests were analyzed by MALDI-TOF to identify peptide masses afterward used for MS/MS. Subsequent high energy MALDI-TOF/TOF collision-induced dissociation spectra were recorded on selected ions. All data, both MS and MS/MS, were recorded on the same instrument. Tandem mass spectra were submitted to database searching using MS-Tag or were manually de novo sequenced. An interesting modification of a tryptophan residue, a "double oxidation", came to light during these analyses.     

Effect of 2MEGA labeling on membrane proteome analysis using LC-ESI QTOF MS

One of the challenges associated with large-scale proteome analysis using tandem mass spectrometry (MS/MS) and automated database searching is to reduce the number of false positive identifications without sacrificing the number of true positives found. In this work, a systematic investigation of the effect of 2MEGA labeling (N-terminal dimethylation after lysine guanidination) on the proteome analysis of a membrane fraction of an Escherichia coli cell extract by 2-dimensional liquid chromatography MS/MS is presented. By a large-scale comparison of MS/MS spectra of native peptides with those from the 2MEGA-labeled peptides, the labeled peptides were found to undergo facile fragmentation with enhanced a1 or a1-related (a(1)-17 and a(1)-45) ions derived from all N-terminal amino acids in the MS/MS spectra; these ions are usually difficult to detect in the MS/MS spectra of nonderivatized peptides. The 2MEGA labeling alleviated the biased detection of arginine-terminated peptides that is often observed in MALDI and ESI MS experiments. 2MEGA labeling was found not only to increase the number of peptides and proteins identified but also to generate enhanced a1 or a1-related ions as a constraint to reduce the number of false positive identifications. In total, 640 proteins were identified from the E. coli membrane fraction, with each protein identified based on peptide mass and sequence match of one or more peptides using MASCOT database search algorithm from the MS/MS spectra generated by a quadrupole time-of-flight mass spectrometer. Among them, the subcellular locations of 336 proteins are presently known, including 258 membrane and membrane-associated proteins (76.8%). Among the classified proteins, there was a dramatic increase in the total number of integral membrane proteins identified in the 2MEGA-labeled sample (153 proteins) versus the unlabeled sample (77 proteins).     

An improved in‐gel digestion method for efficient identification of protein and glycosylation analysis of glycoproteins using guanidine hydrochloride

In‐gel digestion followed by LC/MS/MS is widely used for the identification of trace amounts of proteins and for the site‐specific glycosylation analysis of glycoproteins in cells and tissues. A major limitation of this technique is the difficulty in acquiring reliable mass spectra for peptides present in minute quantities and glycopeptides with high heterogeneity and poor hydrophobicity. It is considered that the SDS used in electrophoresis can interact with proteins noncovalently and impede the ionization of peptides/glycopeptides. In this study, we report an improved in‐gel digestion method to acquire reliable mass spectra of a trace amount of peptides/glycopeptides. A key innovation of our improved method is the use of guanidine hydrochloride, which forms complexes with the residual SDS molecules in the sample. The precipitation and removal of SDS by addition of the guanidine hydrochloride was successful in improving the S/N of peptides/glycopeptides in mass spectra and acquiring a more comprehensive MS/MS data set for the various glycoforms of each glycopeptide.     

Rapid Characterization of Microalgae and Microalgae Mixtures Using Matrix-Assisted Laser Desorption Ionization Time-Of-Flight Mass Spectrometry (MALDI-TOF MS)

Current molecular methods to characterize microalgae are time-intensive and expensive. Matrix Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (MALDI-TOF MS) may represent a rapid and economical alternative approach. The objectives of this study were to determine whether MALDI-TOF MS can be used to: 1) differentiate microalgae at the species and strain levels and 2) characterize simple microalgal mixtures. A common protein extraction sample preparation method was used to facilitate rapid mass spectrometry-based analysis of 31 microalgae. Each yielded spectra containing between 6 and 56 peaks in the m/z 2,000 to 20,000 range. The taxonomic resolution of this approach appeared higher than that of 18S rDNA sequence analysis. For example, two strains of Scenedesmus acutus differed only by two 18S rDNA nucleotides, but yielded distinct MALDI-TOF mass spectra. Mixtures of two and three microalgae yielded relatively complex spectra that contained peaks associated with members of each mixture. Interestingly, though, mixture-specific peaks were observed at m/z 11,048 and 11,230. Our results suggest that MALDI-TOF MS affords rapid characterization of individual microalgae and simple microalgal mixtures.     

MS2‐Deisotoper: A Tool for Deisotoping High‐Resolution MS/MS Spectra in Normal and Heavy Isotope‐Labelled Samples

High‐resolution MS/MS spectra of peptides can be deisotoped to identify monoisotopic masses of peptide fragments. The use of such masses should improve protein identification rates. However, deisotoping is not universally used and its benefits have not been fully explored. Here, MS2‐Deisotoper, a tool for use prior to database search, is used to identify monoisotopic peaks in centroided MS/MS spectra. MS2‐Deisotoper works by comparing the mass and relative intensity of each peptide fragment peak to every other peak of greater mass, and by applying a set of rules concerning mass and intensity differences. After comprehensive parameter optimization, it is shown that MS2‐Deisotoper can improve the number of peptide spectrum matches (PSMs) identified by up to 8.2% and proteins by up to 2.8%. It is effective with SILAC and non‐SILAC MS/MS data. The identification of unique peptide sequences is also improved, increasing the number of human proteoforms by 3.7%. Detailed investigation of results shows that deisotoping increases Mascot ion scores, improves FDR estimation for PSMs, and leads to greater protein sequence coverage. At a peptide level, it is found that the efficacy of deisotoping is affected by peptide mass and charge. MS2‐Deisotoper can be used via a user interface or as a command‐line tool.     

Quantitative proteome analysis using differential stable isotopic labeling and microbore LC-MALDI MS and MS/MS

We demonstrate an approach for global quantitative analysis of protein mixtures using differential stable isotopic labeling of the enzyme-digested peptides combined with microbore liquid chromatography (LC) matrix-assisted laser desorption ionization (MALDI) mass spectrometry (MS). Microbore LC provides higher sample loading, compared to capillary LC, which facilitates the quantification of low abundance proteins in protein mixtures. In this work, microbore LC is combined with MALDI MS via a heated droplet interface. The compatibilities of two global peptide labeling methods (i.e., esterification to carboxylic groups and dimethylation to amine groups of peptides) with this LC-MALDI technique are evaluated. Using a quadrupole-time-of-flight mass spectrometer, MALDI spectra of the peptides in individual sample spots are obtained to determine the abundance ratio among pairs of differential isotopically labeled peptides. MS/MS spectra are subsequently obtained from the peptide pairs showing significant abundance differences to determine the sequences of selected peptides for protein identification. The peptide sequences determined from MS/MS database search are confirmed by using the overlaid fragment ion spectra generated from a pair of differentially labeled peptides. The effectiveness of this microbore LC-MALDI approach is demonstrated in the quantification and identification of peptides from a mixture of standard proteins as well as E. coli whole cell extract of known relative concentrations. It is shown that this approach provides a facile and economical means of comparing relative protein abundances from two proteome samples.     

Specific peptide patterns of follicular fluids at different growth stages analyzed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry

Human follicular fluid (HFF) has been suggested to influence oocyte development potential, and some of HFF proteins may be potential markers for oocyte maturation during follicular development. Using matrix-assisted laser desorption /ionization-time of flight mass spectrometry (MALDI-TOF MS), the presence of specific peptide peaks in HFF which could represent the follicle development potential was evaluated. HFF from different developmental stages were first digested and the resultant peptide mixtures were directly analyzed by MALDI-TOF MS. It was shown that the frequencies of specific peaks demonstrated higher reproducibility than peak intensities after multiple measurements (>or=6 times) per sample. Using this approach, a reliable peak list for each different sample could be generated by combining the information from multiple measurements. By comparing the peak lists from different samples at different growth stages, we found that 5 specific peaks appeared in the 100% frequency category of 6 replicates in all the HFF samples containing mature oocyte. Similarly, such 25 peptide peaks were also identified for HFF containing immature oocyte. These specific peaks could be used to distinguish HFF from different stages as biomarkers related to follicle development and maturation. After searching the protein database, some proteins that are known to be involved in the development and maturation of oocyte were identified, such as apolipoprotein A-I, collagen type IV, integrin, et al. Identification of such proteins in our experiment further proved that the direct analysis of tryptic digests could be of practical value.     

A new method to improve sensitivity and resolution in matrix-assisted laser desorption/ionization time of flight mass spectrometry

High detection sensitivity and resolution are two critical parameters for recording good peptide mass fingerprints (PMF) of low abundance proteins. This paper reports a mass spectrometry (MS) sample preparation technique that could improve sensitivity and resolution. By coating the MS steel target with a thin layer of pentadecafluorooctamido propyltrimethoxysilane, which was both polar and nonpolar solvent repellent, the transferred sample droplets on its surface were significantly smaller. As a result, the analyte of the peptide mixture became more concentrated and homogeneous, which helped to improve the sensitivity. The advantages of a modified MS target were documented by mass spectra improvement of attomole level standard peptides and silver-stained proteins from polyacrylamide gels. The mass signal of angiotensin II at 100 attomole was difficult to record on the conventional support, whereas it was easily detected on the modified one. The PMF of cytochrome C was also better recorded on the modified support, in terms of both signal-to-noise ratio and the number of detected peptides. When silver-stained proteins from two-dimensional electrophoresis gels were analyzed, in most cases more satisfactory peptide mass spectra were obtained from the modified support. Searching protein databases with more mass data from the improved PMFs, several unknown proteins were successfully identified.     

Human urine proteome analysis by three separation approaches

The urinary proteome is known to be a valuable field of study related to organ functions. There have been several extensive urine proteome studies. However, the overlapping rate among different studies is relatively low. Whether the low overlapping rate was caused by different sample sources, preparation, separation and identification methods is unknown. Moreover, low molecular mass (<10 kDa) proteins have not been studied extensively. In this report, male and female pooled urine samples were collected from healthy volunteers. The urinary proteins were acetone precipitated, separated and identified by three approaches, 1-DE plus 1-D LC/MS/MS, direct 1-D LC/MS/MS and 2-D LC/MS/MS. 1-D tricine gels were used to separate low molecular mass proteins. The tandem mass spectra of positive identifications were quality controlled both by manual validation and using advanced mass spectrum scanner software. A total of 226 urinary proteins were identified; 171 proteins were identified by proteomics approach for the first time, including 4 male-specific proteins. Twelve low molecular mass proteins were identified. Most urinary proteins had a molecular mass between 30 and 60 kDa and a pI between 4 and 10. The apparent molecular masses of many proteins were different from theoretical ones, which indicated their post-translational modification and degradation. The effects of sample preparation, separation and identification methods on the overlapping rate of different experiments are discussed.     

Protein labeling by iTRAQ: a new tool for quantitative mass spectrometry in proteome research

A novel, MS-based approach for the relative quantification of proteins, relying on the derivatization of primary amino groups in intact proteins using isobaric tag for relative and absolute quantitation (iTRAQ) is presented. Due to the isobaric mass design of the iTRAQ reagents, differentially labeled proteins do not differ in mass; accordingly, their corresponding proteolytic peptides appear as single peaks in MS scans. Because quantitative information is provided by isotope-encoded reporter ions that can only be observed in MS/MS spectra, we analyzed the fragmentation behavior of ESI and MALDI ions of peptides generated from iTRAQ-labeled proteins using a TOF/TOF and/or a QTOF instrument. We observed efficient liberation of reporter ions for singly protonated peptides at low-energy collision conditions. In contrast, increased collision energies were required to liberate the iTRAQ label from lysine side chains of doubly charged peptides and, thus, to observe reporter ions suitable for relative quantification of proteins with high accuracy. We then developed a quantitative strategy that comprises labeling of intact proteins by iTRAQ followed by gel electrophoresis and peptide MS/MS analyses. As proof of principle, mixtures of five different proteins in various concentration ratios were quantified, demonstrating the general applicability of the approach presented here to quantitative MS-based proteomics.     

Proteomic profiling of erythrocyte proteins by proteolytic digestion chip and identification using two-dimensional electrospray ionization tandem mass spectrometry

Self-assembled monolayers (SAMs) on coinage metal provide versatile modeling systems for studies of interfacial electron transfer, biological interactions, molecular recognition, and other interfacial phenomena. The bonding of enzyme to SAMs of alkanethiols onto gold surfaces is exploited to produce an enzyme chip. In this work, the attachment of trypsin to a SAMs surface of 11-mercaptoundecanoic acid was achieved using water soluble N-ethyl-N'-(3-dimethylaminopropyl) carbodiimide hydrochloride and N-hydroxysuccinimide as coupling agent. A two-dimensional liquid-phase separation scheme coupled with mass spectrometry is presented for proteomic analysis of erythrocyte proteins. The application of proteomics, particularly with reference to analysis of proteins, will be described. Surface analyses have revealed that the X-ray Photoelectron Spectroscopy (XPS) C1s and N1s core levels illustrate the immobilization of trypsin. These data are also in good agreement with Fourier Transformed Infrared Reflection-Attenuated Total Reflection (FTIR-ATR) spectra for the peaks at Amide I and Amide II. Using two-dimensional nano-high performance liquid chromatography electrospray ionization tandem mass spectrometry (2D nano-HPLC-ESI-MS/MS) system observations, analytical results have demonstrated the erythrocyte proteins digestion of the immobilized trypsin on the functionalized SAMs surface. For such surfaces, it also shows the enzyme digestion ability of the immobilized trypsin. The experiment results revealed the identification of 272 proteins from erythrocyte protein sample. The terminal groups of the SAMs structure can be further functionalized with biomolecules or antibodies to develop surface-base diagnostics, biosensors, or biomaterials.