Single Isotopologue for In-Sample Calibration and Absolute Quantitation by LC-MS/MS.

Targeted mass spectrometry (MS)-based absolute quantitative analysis has been increasingly used in biomarker discovery. The ability to accurately measure the masses by MS enabled the use of isotope-incorporated surrogates having virtually identical physiochemical properties with the target analytes as calibrators. Such a unique capacity allowed for accurate in-sample calibration. Current in-sample calibration uses multiple isotopologues or structural analogues for both the surrogate and the internal standard. Here, we simplified this common practice by using endogenous light peptides as the internal standards and used a mathematical deduction of "heavy matching light, HML" to directly quantify an endogenous analyte. This method provides all necessary assay performance parameters in the authentic matrix, including the lower limit of quantitation (LLOQ) and intercept of the calibration curve, by using only a single isotopologue of the analyte. This method can be applied to the quantitation of proteins, peptides, and small molecules. Using this method, we quantified the efficiency of heart tissue digestion and recovery using sodium deoxycholate as a detergent and two spiked exogenous proteins as mimics of heart proteins. The results demonstrated the robustness of the assay.

Discovery and Visualization of the Hidden Relationships among N-Glycosylation, Disulfide Bonds, and Membrane Topology.

Membrane proteins (MPs) are functionally important but structurally complex. In particular, MPs often carry three structural features, i.e., transmembrane domains (TMs), disulfide bonds (SSs), and N-glycosylation (N-GLYCO). All three features have been intensively studied; however, how the three features potentially correlate has been less addressed in the literature. With the growing accuracy from computational prediction, we used publicly available information on SSs and N-GLYCO and analyzed the potential relationships among post-translational modifications (PTMs) and the predicted membrane topology in the human proteome. Our results suggested a very close relationship between SSs and N-GLYCO that behaved similarly, whereas a complementary relation between the TMs and the two PTMs was also revealed, in which the high SS and/or N-GLYCO presence is often accompanied by a low TM occurrence in a protein. Furthermore, the occurrence of SSs and N-GLYCO in a protein heavily relies on the protein length; however, TMs seem not to possess such length dependence. Finally, SSs exhibits larger potential dynamics than N-GLYCO, which is confined by the presence of sequons. The special classes of proteins possessing extreme or unique patterns of the three structural features are comprehensively identified, and their structural features and potential dynamics help to identify their susceptibility to different physiological and pathophysiological insults, which could help drug development and protein engineering.

Protein Adsorption Loss─The Bottleneck of Single-Cell Proteomics.

Single-cell proteomics is a promising field to provide direct yet comprehensive molecular insights into cellular functions without averaging effects. Here, we address a grand technical challenge impeding the maturation of single-cell proteomics─protein adsorption loss (PAL). Even though widely known, there is currently no quantitation on how profoundly and selectively PAL has affected single-cell proteomics. Therefore, the mitigations to this challenge have been generic, and their efficacy was only evaluated by the size of the resolved proteome with no specificity on individual proteins. We use the existing knowledge of PAL, protein expression, and the typical surface area used in single-cell proteomics to discuss the severity of protein loss. We also summarize the current solutions to this challenge and briefly review the available methods to characterize the physical and chemical properties of protein surface adsorption. By citing successful strategies in single-cell genomics for measurement errors in individual transcripts, we pinpoint the urgency to benchmark PAL at the proteome scale with individual protein resolution. Finally, orthogonal single-cell proteomic techniques that have the potential to cross validate PAL are proposed. We hope these efforts can promote the fruition of single-cell proteomics in the near future.

Hidden Relationships between N-Glycosylation and Disulfide Bonds in Individual Proteins.

N-Glycosylation (NG) and disulfide bonds (DBs) are two prevalent co/post-translational modifications (PTMs) that are often conserved and coexist in membrane and secreted proteins involved in a large number of diseases. Both in the past and in recent times, the enzymes and chaperones regulating these PTMs have been constantly discovered to directly interact with each other or colocalize in the ER. However, beyond a few model proteins, how such cooperation affects N-glycan modification and disulfide bonding at selective sites in individual proteins is largely unknown. Here, we reviewed the literature to discover the current status in understanding the relationships between NG and DBs in individual proteins. Our results showed that more than 2700 human proteins carry both PTMs, and fewer than 2% of them have been investigated in the associations between NG and DBs. We summarized both these proteins with the reported relationships in the two PTMs and the tools used to discover the relationships. We hope that, by exposing this largely understudied field, more investigations can be encouraged to unveil the hidden relationships of NG and DBs in the majority of membranes and secreted proteins for pathophysiological understanding and biotherapeutic development.

Absolute Quantification of Nav1.5 Expression by Targeted Mass Spectrometry.

Nav1.5 is the pore forming α-subunit of the cardiac voltage-gated sodium channel that initiates cardiac action potential and regulates the human heartbeat. A normal level of Nav1.5 is crucial to cardiac function and health. Over- or under-expression of Nav1.5 can cause various cardiac diseases ranging from short PR intervals to Brugada syndromes. An assay that can directly quantify the protein amount in biological samples would be a priori to accurately diagnose and treat Nav1.5-associated cardiac diseases. Due to its large size (>200 KD), multipass transmembrane domains (24 transmembrane passes), and heavy modifications, Nav1.5 poses special quantitation challenges. To date, only the relative quantities of this protein have been measured in biological samples. Here, we describe the first targeted and mass spectrometry (MS)-based quantitative assay that can provide the copy numbers of Nav1.5 in cells with a well-defined lower limit of quantification (LLOQ) and precision. Applying the developed assay, we successfully quantified transiently expressed Nav1.5 in as few as 1.5 million Chinese hamster ovary (CHO) cells. The obtained quantity was 3 ± 2 fmol on the column and 3 ± 2 × 104 copies/cell. To our knowledge, this is the first absolute quantity of Nav1.5 measured in a biological sample.

Characterization of Sample Loss Caused by Competitive Adsorption of Proteins in Vials Using Sodium Dodecyl Sulfate-Polyacrylamide Gel Electrophoresis.

Sample loss caused by competitive protein adsorption on solid surfaces from complex samples remains to be a major hurdle in sensitive analyses of proteins. No label-free techniques can easily quantify individual proteins adsorbed on irregular surfaces of Eppendorf vials or Falcon tubes, which are commonly used to contain complex biological samples. Multiplexed characterization of such adsorption by different proteins is technically challenging. Herein, we developed a direct protein analysis based on sodium dodecyl sulfate-polyacrylamide gel electrophoresis for the characterization of sample loss occurred on the curved surface with limited area. Using this simple and easily accessible method, we discovered the effect of ethylenediaminetetraacetic acid on surface adsorption of different milk proteins, specifically an augmented loss of milk proteins in low-binding sample vials. In this study, we also identified severe biases of silver staining and established proteomics-based mapping of protein distribution in biological samples for absolute quantification of competitive protein adsorption on irregular surfaces.

Optimization and Modeling of Quadrupole Orbitrap Parameters for Sensitive Analysis toward Single-Cell Proteomics.

Single-cell proteomics represents a field of extremely sensitive proteomic analysis, owing to the minute amount of yet complex proteins in a single cell. Without amplification potential as of nucleic acids, single-cell mass spectrometry (MS) analysis demands special instrumentation running with optimized parameters to maximize the sensitivity and throughput for comprehensive proteomic discovery. To facilitate such analysis, we here investigated two factors critical to peptide sequencing and protein detection in shotgun proteomics, i.e. precursor ion isolation window (IW) and maximum precursor ion injection time (ITmax), on an ultrahigh-field quadrupole Orbitrap (Q-Exactive HF). Counterintuitive to the frequently used proteomic parameters for bulk samples (>100 ng), our experimental data and subsequent modeling suggested a universally optimal IW of 4.0 Th for sample quantity ranging from 100 ng to 1 ng, and a sample-quantity dependent ITmax of more than 250 ms for 1-ng samples. Compared with the benchmark condition of IW = 2.0 Th and ITmax = 50 ms, our optimization generated up to 300% increase to the detected protein groups for 1-ng samples. The additionally identified proteins allowed deeper penetration of proteome for better revealing crucial cellular functions such as signaling and cell adhesion. We hope this effort can prompt single-cell and trace proteomic analysis and enable a rational selection of MS parameters.

Method comparison for analyzing wound healing rates.

Wound healing scratch assay is a frequently used method to characterize cell migration, which is an important biological process in the course of development, tissue repair, and immune response for example. The measurement of wound healing rate, however, varies among different studies. Here we summarized these measurements into three types: (I) direct rate average; (II) regression rate average; and (III) average distance regression rate. Using Chinese hamster ovary (CHO) cells as a model, we compared the three types of analyses on quantifying the wound closing rate, and discovered that type I & III measurements are more resistant to outliers, and type II analysis is more sensitive to outliers. We hope this study can help researchers to better use this simple yet effective assay.

Proteomics and glycoproteomics of pluripotent stem-cell surface proteins.

Pluripotent stem cells are a unique cell type with promising potential in regenerative and personalized medicine. Yet the difficulty to understand and coax their seemingly stochastic differentiation and spontaneous self-renewal have largely limited their clinical applications. A call has been made by numerous researchers for a better characterization of surface proteins on these cells, in search of biomarkers that can dictate developmental stages and lineage specifications, and can help formulate mechanistic insight of stem-cell fate choices. In the past two decades, proteomics has gained significant recognition in profiling surface proteins at high throughput. This review will summarize the impact of these studies on stem-cell biology, and discuss the used proteomic techniques. A systematic comparison of all the techniques and their results is also attempted here to help reveal pros, cons, and the complementarity of the existing methods. This awareness should assist in selecting suitable strategies for stem-cell related research, and shed light on technical improvements that can be explored in the future.

Protein-centric N-glycoproteomics analysis of membrane and plasma membrane proteins.

The advent of proteomics technology has transformed our understanding of biological membranes. The challenges for studying membrane proteins have inspired the development of many analytical and bioanalytical tools, and the techniques of glycoproteomics have emerged as an effective means to enrich and characterize membrane and plasma-membrane proteomes. This Review summarizes the development of various glycoproteomics techniques to overcome the hurdles formed by the unique structures and behaviors of membrane proteins with a focus on N-glycoproteomics. Example contributions of N-glycoproteomics to the understanding of membrane biology are provided, and the areas that require future technical breakthroughs are discussed.

Sodium dodecyl sulfate polyacrylamide gel electrophoresis for direct quantitation of protein adsorption.

A simple method, sodium dodecyl sulfate polyacrylamide gel electrophoresis coupled with direct protein adsorption analysis (SDS-PAGE/DPA), is presented here for the quantitation of adsorption-caused protein loss. No complicated steps and expensive equipment are involved, and this method is capable of measuring proteins adsorbed on sample vials at extremely low concentrations (in pg/µl). We used this method to characterize the effects of concentration, time, and volume on adsorption. We also applied this method to discover differential sample loss in protein mixtures and its utility in developing preventive strategies of adsorption.

A quest for cytosolic sequons and their functions.

Evolution shapes protein sequences for their functions. Here, we studied the moonlighting functions of the N-linked sequon NXS/T, where X is not P, in human nucleocytosolic proteins. By comparing membrane and secreted proteins in which sequons are well known for N-glycosylation, we discovered that cyto-sequons can participate in nucleic acid binding, particularly in zinc finger proteins. Our global studies further discovered that sequon occurrence is largely proportional to protein length. The contribution of sequons to protein functions, including both N-glycosylation and nucleic acid binding, can be regulated through their density as well as the biased usage between NXS and NXT. In proteins where other PTMs or structural features are rich, such as phosphorylation, transmembrane ɑ-helices, and disulfide bridges, sequon occurrence is scarce. The information acquired here should help understand the relationship between protein sequence and function and assist future protein design and engineering.

Glycocapture-assisted global quantitative proteomics (gagQP) reveals multiorgan responses in serum toxicoproteome.

Blood is an ideal window for viewing our health and disease status. Because blood circulates throughout the entire body and carries secreted, shed, and excreted signature proteins from every organ and tissue type, it is thus possible to use the blood proteome to achieve a comprehensive assessment of multiple-organ physiology and pathology. To date, the blood proteome has been frequently examined for diseases of individual organs; studies on compound insults impacting multiple organs are, however, elusive. We believe that a characterization of peripheral blood for organ-specific proteins affords a powerful strategy to allow early detection, staging, and monitoring of diseases and their treatments at a whole-body level. In this paper we test this hypothesis by examining a mouse model of acetaminophen (APAP)-induced hepatic and extra-hepatic toxicity. We used a glycocapture-assisted global quantitative proteomics (gagQP) approach to study serum proteins and validated our results using Western blot. We discovered in mouse sera both hepatic and extra-hepatic organ-specific proteins. From our validation, it was determined that selected organ-specific proteins had changed their blood concentration during the course of toxicity development and recovery. Interestingly, the peak responding time of proteins specific to different organs varied in a time-course study. The collected molecular information shed light on a complex, dynamic, yet interweaving, multiorgan-enrolled APAP toxicity. The developed technique as well as the identified protein markers is translational to human studies. We hope our work can broaden the utility of blood proteomics in diagnosis and research of the whole-body response to pathogenic cues.

Mouse Organ-Specific Proteins and Functions.

Organ-specific proteins (OSPs) possess great medical potential both in clinics and in biomedical research. Applications of them-such as alanine transaminase, aspartate transaminase, and troponins-in clinics have raised certain concerns of their organ specificity. The dynamics and diversity of protein expression in heterogeneous human populations are well known, yet their effects on OSPs are less addressed. Here, we used mice as a model and implemented a breadth study to examine the panorgan proteome for potential variations in organ specificity in different genetic backgrounds. Using reasonable resources, we generated panorgan proteomes of four in-bred mouse strains. The results revealed a large diversity that was more profound among OSPs than among proteomes overall. We defined a robustness score to quantify such variation and derived three sets of OSPs with different stringencies. In the meantime, we found that the enriched biological functions of OSPs are also organ-specific and are sensitive and useful to assess the quality of OSPs. We hope our breadth study can open doors to explore the molecular diversity and dynamics of organ specificity at the protein level.

Molecular profiling of stem cells.

Stem cells, with their profound implication in development and enormous potential in regenerative medicine, have been the subject of extensive molecular profiling studies in search of better markers and regulatory schema governing self-renewal versus differentiation. In this review article, we will discuss current advancement in high throughput technologies dedicated to the transcriptome, proteome and genome-wide localization analyses, and how they have been adopted in molecular profiling of stem cells with an emphasis on embryonic stem cell (ESC), hematopoietic stem cell (HSC) and neural stem cell (NSC).

Membrane gene ontology bias in sequencing and microarray obtained by housekeeping-gene analysis.

Microarray (MA) and high-throughput sequencing are two commonly used detection systems for global gene expression profiling. Although these two systems are frequently used in parallel, the differences in their final results have not been examined thoroughly. Transcriptomic analysis of housekeeping (HK) genes provides a unique opportunity to reliably examine the technical difference between these two systems. We investigated here the structure, genome location, expression quantity, microarray probe coverage, as well as biological functions of differentially identified human HK genes by 9 MA and 6 sequencing studies. These in-depth analyses allowed us to discover, for the first time, a subset of transcripts encoding membrane, cell surface and nuclear proteins that were prone to differential identification by the two platforms. We hope that the discovery can aid the future development of these technologies for comprehensive transcriptomic studies.

Detection bias in microarray and sequencing transcriptomic analysis identified by housekeeping genes.

This work includes the original data used to discover the gene ontology bias in transcriptomic analysis conducted by microarray and high throughput sequencing (Zhang et al., 2015) [1]. In the analysis, housekeeping genes were used to examine the differential detection ability by microarray and sequencing because these genes are probably the most reliably detected. The genes included here were compiled from 15 human housekeeping gene studies. The provided tables here comprise of detailed chromosomal location, detection breadth, normalized expression level, exon count, total exon length, and total intron length of each concerned gene and their related transcripts. We hope this information can help researchers better understand the differences in gene ontology-bias we discussed (Zhang et al., 2015) [1] and can encourage further improvement on these two technology platforms.

Do housekeeping genes exist?

The searching of human housekeeping (HK) genes has been a long quest since the emergence of transcriptomics, and is instrumental for us to understand the structure of genome and the fundamentals of biological processes. The resolved genes are frequently used in evolution studies and as normalization standards in quantitative gene-expression analysis. Within the past 20 years, more than a dozen HK-gene studies have been conducted, yet none of them sampled human tissues completely. We believe an integration of these results will help remove false positive genes owing to the inadequate sampling. Surprisingly, we only find one common gene across 15 examined HK-gene datasets comprising 187 different tissue and cell types. Our subsequent analyses suggest that it might not be appropriate to rigidly define HK genes as expressed in all tissue types that have diverse developmental, physiological, and pathological states. It might be beneficial to use more robustly identified HK functions for filtering criteria, in which the representing genes can be a subset of genome. These genes are not necessarily the same, and perhaps need not to be the same, everywhere in our body.

Glycopeptide capture for cell surface proteomics.

Cell surface proteins, including extracellular matrix proteins, participate in all major cellular processes and functions, such as growth, differentiation, and proliferation. A comprehensive characterization of these proteins provides rich information for biomarker discovery, cell-type identification, and drug-target selection, as well as helping to advance our understanding of cellular biology and physiology. Surface proteins, however, pose significant analytical challenges, because of their inherently low abundance, high hydrophobicity, and heavy post-translational modifications. Taking advantage of the prevalent glycosylation on surface proteins, we introduce here a high-throughput glycopeptide-capture approach that integrates the advantages of several existing N-glycoproteomics means. Our method can enrich the glycopeptides derived from surface proteins and remove their glycans for facile proteomics using LC-MS. The resolved N-glycoproteome comprises the information of protein identity and quantity as well as their sites of glycosylation. This method has been applied to a series of studies in areas including cancer, stem cells, and drug toxicity. The limitation of the method lies in the low abundance of surface membrane proteins, such that a relatively large quantity of samples is required for this analysis compared to studies centered on cytosolic proteins.