Bioinertization of NanoLC/MS/MS Systems by Depleting Metal Ions From the Mobile Phases for Phosphoproteomics.

We have successfully developed a bioinertized nanoflow LC/MS/MS (nanoLC/MS/MS) system for the highly sensitive analysis of phosphopeptides by depleting metal ions from the mobile phase. We found that not only direct contact of phosphopeptides with metal components, but also indirect contact with nanoLC pumps through the mobile phase causes significant losses during the recovery of phosphopeptides. Moreover, electrospray ionization was adversely affected by the mobile phase containing multiple metal ions as well as by the sample solvents contaminated with metal ions used in immobilized metal ion affinity chromatography for phosphopeptide enrichment. To solve these problems, metal ions were depleted by inserting an online metal ion removal device containing metal-chelating membranes between the gradient mixer and the autosampler. As a result, the peak areas of the identified phosphopeptides increased an average of 9.9-fold overall and 77-fold for multiply phosphorylated peptides with the insertion of the online metal ion removal system. This strategy would be applicable to the highly sensitive analysis of other phosphorylated biomolecules by microscale-LC/MS/MS.

Label free quantitative proteomic profiling of serum samples of intellectually disabled young patients revealed dysregulation of complement coagulation and cholesterol cascade systems.

Intellectual disability is a heterogeneous disorder, diagnosed using intelligence quotient (IQ) score criteria. Currently, no specific clinical test is available to diagnose the disease and its subgroups due to inadequate understanding of the pathophysiology. Therefore, current study was designed to explore the molecular mechanisms involved in disease perturbation, and to identify potential biomarkers for disease diagnosis and prognosis. A total of 250 participants were enrolled in this study, including 200 intellectually disabled (ID) subjects from the subgroups (mild, moderate, and severe) with age and gender matched healthy controls (n = 50). Initially, IQ testing score and biochemical profile of each subject was generated, followed by label-free quantitative proteomics of subgroups of IQ and healthy control group through nano-LC/MS- mass spectrometry. A total of 310 proteins were identified, among them198 proteins were common among all groups. Statistical analysis (ANOVA) of the subgroups of ID showed 142 differentially expressed proteins, in comparison to healthy control group. From these, 120 proteins were found to be common among all subgroups. The remaining 22 proteins were categorized as exclusive proteins found only in disease subgroups. Furthermore, the hierarchical cluster analysis (HCL) of common significant proteins was also performed, followed by PANTHER protein classification and GO functional enrichment analysis. Results provides that the datasets of differentially expressed proteins, belong to the categories of immune / defense proteins, transfer carrier proteins, apolipoproteins, complement proteins, protease inhibitors, hemoglobin proteins etc., they are known to involvein immune system, and complement and coagulation pathway cascade and cholesterol metabolism pathway. Exclusively expressed 22 proteins were found to be disease stage specific and strong PPI network specifically those that have significant role in platelets activation and degranulation, such as Filamin A (FLNA). Furthermore, to validate the mass spectrometric findings, four highly significant proteins (APOA4, SAP, FLNA, and SERPING) were quantified by ELISA in all the study subjects. AUROC analysis showed a significant association of APOA4 (0.830), FLNA (0.958), SAP (0.754) and SERPING (0.600) with the disease. Apolipoprotein A4 (APOA4) has a significant role in cholesterol transport, and in modulation of glucose and lipid metabolism in the CNS. Similarly, FLNA has a crucial role in the nervous system, especially in the functioning of synaptic network. Therefore, both APOA4, and FLNA proteins represent good potential for candidate biomarkers for the diagnosis and prognosis of the intellectual disability. Overall, serum proteome of ID patients provides valuable information of proteins/pathways that are altered during ID progression.

Proteomic Analysis of Rap1A GTPase Signaling-Deficient C57BL/6 Mouse Pancreas and Functional Studies Identify an Essential Role of Rap1A in Pancreas Physiology.

Ras-related Rap1A GTPase is implicated in pancreas ß-cell insulin secretion and is stimulated by the cAMP sensor Epac2, a guanine exchange factor and activator of Rap1 GTPase. In this study, we examined the differential proteomic profiles of pancreata from C57BL/6 Rap1A-deficient (Null) and control wild-type (WT) mice with nanoLC-ESI-MS/MS to assess targets of Rap1A potentially involved in insulin regulation. We identified 77 overlapping identifier proteins in both groups, with 8 distinct identifier proteins in Null versus 56 distinct identifier proteins in WT mice pancreata. Functional enrichment analysis showed four of the eight Null unique proteins, ERO1-like protein ß (Ero1lß), triosephosphate isomerase (TP1), 14-3-3 protein γ, and kallikrein-1, were exclusively involved in insulin biogenesis, with roles in insulin metabolism. Specifically, the mRNA expression of Ero1lß and TP1 was significantly (p < 0.05) increased in Null versus WT pancreata. Rap1A deficiency significantly affected glucose tolerance during the first 15-30 min of glucose challenge but showed no impact on insulin sensitivity. Ex vivo glucose-stimulated insulin secretion (GSIS) studies on isolated Null islets showed significantly impaired GSIS. Furthermore, in GSIS-impaired islets, the cAMP-Epac2-Rap1A pathway was significantly compromised compared to the WT. Altogether, these studies underscore an essential role of Rap1A GTPase in pancreas physiological function.

Development of a Simple and Stable NanoESI Spray System Using Suction Wind from the MS Inlet.

Improving the reproducibility of proteome analysis systems presents a challenge; therefore, in this study, we developed a new insertion spray ionization (InSpIon) system wherein an InSpIon tube was designed with a spray tip inserted into the tube. This system stabilized the spray and subsequently improved the reproducibility of the analysis.

Enantiomeric analysis of drugs in water samples by using liquid-liquid microextraction and nano-liquid chromatography.

The nano-LC technique is increasingly used for both fast studies on enantiomeric analysis and test beds of novel stationary phases due to the small volumes involved and the short conditioning and analysis times. In this study, the enantioseparation of 10 drugs from different families was carried out by nano-LC, utilizing silica with immobilized amylose tris(3-chloro-5-methylphenylcarbamate) column. The effect on chiral separation caused by the addition of different salts to the mobile phase was evaluated. To simultaneously separate as many enantiomers as possible, the effect of buffer concentration in the mobile phase was studied, and, to increase the sensitivity, a liquid-liquid microextraction based on the use of isoamyl acetate as sustainable extraction solvent was applied to pre-concentrate four chiral drugs from tap and environmental waters, achieving satisfactory recoveries (>70%).

Open tubular liquid chromatography: Recent advances and future trends.

Nano-liquid chromatography (nanoLC) is gaining significant attention as a primary analytical technique across various scientific domains. Unlike conventional high-performance LC, nanoLC utilizes columns with inner diameters (i.ds.) usually ranging from 10 to 150 µm and operates at mobile phase flow rates between 10 and 1000 nl/min, offering improved chromatographic performance and detectability. Currently, most exploration of nanoLC has focused on particle-packed columns. Although open tubular LC (OTLC) can provide superior performance, optimized OTLC columns require very narrow i.ds. (< 10 µm) and demand challenging instrumentation. At the moment, these challenges have limited the success of OTLC. Nevertheless, remarkable progress has been made in developing and utilizing OTLC systems featuring narrow columns (< 2 µm). Additionally, significant efforts have been made to explore larger columns (10-75 µm i.d), demonstrating practical applicability in many situations. Due to their perceived advantages, interest in OTLC has resurged in the last two decades. This review provides an updated outlook on the latest developments in OTLC, focusing on instrumental challenges, achievements, and advancements in column technology. Moreover, it outlines selected applications that illustrate the potential of OTLC for performing targeted and untargeted studies.

Untargeted Lipidomic Profiling of Aged Human Retina With and Without Age-Related Macular Degeneration (AMD).

The molecular characterization of extracellular deposits is crucial to understanding the clinical progression of AMD. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis is a powerful analytical discovery tool capable of identifying lipids in an untargeted manner. NanoLC-MS/MS is an analytical tool capable of identifying lipids with high sensitivity and minimum sample usage. Hence, the purpose of this study was to compare retina lipid identification from RPE-choroid samples using high flow LC-MS/MS and nanoLC-MS/MS. Manually dissected paraformaldehyde-fixed human donor tissues sections were used for LC-MS/MS and nanoLC-MS/MS analysis. Lipids were extracted with MeOH/MTBE/CHCl3 (MMC) and were analyzed by LC-MS/MS and nanoLC-MS/MS using negative and positive ionization modes. Untargeted lipidomics using LC-MS/MS identified 215 lipids from 4 lipid classes and 15 subclasses. We observed a 78% increase in lipid identifications using nanoLC-MS/MS with lipid numbers totaling 384. The nanoLC-MS/MS method is expected to provide extensive lipid identifications from small retina samples, e.g., from drusen and drusenoid deposits in aged and AMD eyes, and could help elucidate how lipids are involved in extracellular deposit formation in AMD.

Regulatory Effects of ABA and GA on the Expression of Conglutin Genes and LAFL Network Genes in Yellow Lupine (Lupinus luteus L.) Seeds.

The maturation of seeds is a process of particular importance both for the plant itself by assuring the survival of the species and for the human population for nutritional and economic reasons. Controlling this process requires a strict coordination of many factors at different levels of the functioning of genetic and hormonal changes as well as cellular organization. One of the most important examples is the transcriptional activity of the LAFL gene regulatory network, which includes LEAFY COTYLEDON1 (LEC1) and LEC1-LIKE (L1L) and ABSCISIC ACID INSENSITIVE3 (ABI3), FUSCA3 (FUS3), and LEC2 (LEAFY COTYLEDON2), as well as hormonal homeostasis-of abscisic acid (ABA) and gibberellins (GA) in particular. From the nutritional point of view, the key to seed development is the ability of seeds to accumulate large amounts of proteins with different structures and properties. The world's food deficit is mainly related to shortages of protein, and taking into consideration the environmental changes occurring on Earth, it is becoming necessary to search for a way to obtain large amounts of plant-derived protein while maintaining the diversity of its origin. Yellow lupin, whose storage proteins are conglutins, is one of the plant species native to Europe that accumulates large amounts of this nutrient in its seeds. In this article we have shown the key changes occurring in the developing seeds of the yellow-lupin cultivar Taper by means of modern molecular biology techniques, including RNA-seq, chromatographic techniques and quantitative PCR analysis. We identified regulatory genes fundamental to the seed-filling process, as well as genes encoding conglutins. We also investigated how exogenous application of ABA and GA3 affects the expression of LlLEC2, LlABI3, LlFUS3, and genes encoding ß- and δ-conglutins and whether it results in the amount of accumulated seed storage proteins. The research shows that for each species, even related plants, very specific changes can be identified. Thus the analysis and possibility of using such an approach to improve and stabilize yields requires even more detailed and extended research.

Nano-Liquid Chromatography with a New Monolithic Column for the Analysis of Coenzyme Q10 in Pistachio Samples.

Coenzyme Q10 (CoQ10) is a vital substance found throughout body. It helps convert food into energy and is eaten small amounts in foods. CoQ10 has gained great interest in recent years as a potential candidate for the treatment of various diseases. The content of CoQ10 in food samples is a crucial quality index for foods. Therefore, the development of sensitive separation and quantification method for determining the amount of CoQ10 in various samples, especially in foods, is an important issue, especially for food nutrition. In this study, a new, miniaturized monolithic column was developed and applied for the determination of CoQ10 in pistachio samples by nano-liquid chromatography (nano-LC). The monolithic column with a 50 µm i.d. was prepared by in situ polymerization using laurylmethacrylate (LMA) as the main monomer and ethylene dimethacrylate (EDMA) as the crosslinker. Methanol (MeOH) and polyethyleneglycol (PEG) were used as porogenic solvents. The final monolithic column was characterized by using scanning electron microscopy (SEM) and chromatographic analyses. The monolithic column with a 50 µm i.d. was applied to the analysis of CoQ10 in pistachio samples in nano-LC. This analytical method was validated by means of sensitivity, linearity, precision, recovery, and repeatability. The LOD and LOQ values were 0.05 and 0.48 µg/kg, respectively. The developed method using the monolithic column was optimized to achieve very sensitive analyses of CoQ10 content in the food samples. The applicability of the method was successfully demonstrated by the analysis of CoQ10 in pistachio samples.

Data-Dependent Acquisition with Precursor Coisolation Improves Proteome Coverage and Measurement Throughput for Label-Free Single-Cell Proteomics.

We combined efficient sample preparation and ultra-low-flow liquid chromatography with a newly developed data acquisition and analysis scheme termed wide window acquisition (WWA) to quantify >3,000 proteins from single cells in rapid label-free analyses. WWA employs large isolation windows to intentionally co-isolate and co-fragment adjacent precursors along with the selected precursor. Optimized WWA increased the number of MS2-identified proteins by ≈40 % relative to standard data-dependent acquisition. For a 40-min LC gradient operated at ≈15 nL/min, we identified an average of 3,524 proteins per single-cell-sized aliquot of protein digest. Reducing the active gradient to 20 min resulted in a modest 10 % decrease in proteome coverage. Using this platform, we compared protein expression between single HeLa cells having an essential autophagy gene, atg9a, knocked out, with their isogenic WT parental line. Similar proteome coverage was observed, and 268 proteins were significantly up- or downregulated. Protein upregulation primarily related to innate immunity, vesicle trafficking and protein degradation.

Deep Single-Shot NanoLC-MS Proteome Profiling with a 1500 Bar UHPLC System, Long Fully Porous Columns, and HRAM MS.

This study demonstrates how the latest ultrahigh-performance liquid chromatography (UHPLC) technology can be combined with high-resolution accurate-mass (HRAM) mass spectrometry (MS) and long columns packed with fully porous particles to improve bottom-up proteomics analysis with nanoflow liquid chromatography-mass spectrometry (nanoLC-MS) methods. The increased back pressures from the UHPLC system enabled the use of 75 µm I.D. × 75 cm columns packed with 2 µm particles at a typical 300 nL/min flow rate as well as elevated and reduced flow rates. The constant pressure pump operation at 1500 bar reduced sample loading and column washing/equilibration stages and overall overhead time, which maximizes MS utilization time. The versatility of flow rate optimization to balance the sensitivity, throughput with sample loading amount, and capability of using longer gradients contributes to a greater number of peptide and protein identifications for single-shot bottom-up proteomics experiments. The routine proteome profiling and precise quantification of >7000 proteins with single-shot nanoLC-MS analysis open possibilities for large-scale discovery studies with a deep dive into the protein level alterations. Data are available via ProteomeXchange with identifier PXD035665.

TMT based deep proteome analysis of buffalo mammary epithelial cells and identification of novel protein signatures during lactogenic differentiation.

The lactating mammary gland harbours numerous matured alveoli with their lumen surrounded by differentiated mammary epithelial cells (MECs), which are exclusively involved in milk synthesis and secretion. Buffalo (Bubalus bubalis) is the second major milk-producing animal, and its physiology is different from cattle. The complete protein machinery involved in MECs differentiation is still not defined in ruminants, in particular, buffalo. Therefore, we have studied the differential expression of regulated proteins in the in vitro grown buffalo MECs (BuMECs) at different time points (on 3, 6, 12, and 15 days) of their differentiation in the presence of lactogenic hormones. TMT-based MS analysis identified 4,934 proteins; of them, 681 were differentially expressed proteins (DEPs). The principal component analysis suggested a highly heterogeneous expression of DEPs at the four-time points of hormone treatment, with most of them (307) attained the highest expression on 12 days. Bioinformatics analysis revealed the association of DEPs with 24 KEGG pathways. We observed few new proteins, namely ABCA13, IVL, VPS37, CZIB, RFX7, Rab5, TTLL12, SMEK1, GDI2, and TMEM131 in BuMECs. The function of one of the highly upregulated proteins, namely involucrin in the differentiation of BuMECs was confirmed based on biochemical inhibition assay. The results further conclude that the proteins with higher abundance can be considered as the potential biomarkers for differentiation, and they may have a significant association with the lactation process in buffalo too. The proteome dataset obtained can be used to understand the species-specific variations among other lactating animals.

An integrative-omics analysis of an industrial clavulanic acid-overproducing Streptomyces clavuligerus.

Clavulanic acid (CA) is a clinically important secondary metabolite used to treat infectious diseases. We aimed to decipher complex regulatory mechanisms acting in CA biosynthesis by analyzing transcriptome- and proteome-wide alterations in an industrial CA overproducer Streptomyces clavuligerus strain, namely DEPA and its wild-type counterpart NRRL3585. A total of 924 differentially expressed genes (DEGs) and 271 differentially produced proteins (DPPs) were obtained by RNA-seq and nanoLC-MS/MS analyses, respectively. In particular, CA biosynthetic genes, namely, car (cad), cas2, oat2, pah, bls, ceas2, orf12, and claR, a cluster situated regulatory (CSR) gene, were significantly upregulated as shown by RNA-seq. Enzymes of clavam biosynthesis were downregulated considerably in the DEPA strain, while the genes involved in the arginine biosynthesis, one of the precursors of CA pathway, were overexpressed. However, the biosynthesis of the other CA precursor, glyceraldehyde-3-phosphate (G3P), was not affected. CA overproduction in the DEPA strain was correlated with BldD, BldG, BldM, and BldN (AdsA) overrepresentation. In addition, TetR, WhiB, and Xre family transcriptional regulators were shown to be significantly overrepresented. Several uncharacterized/unknown proteins differentially expressed in the DEPA strain await further studies for functional characterization. Correlation analysis indicated an acceptable degree of consistency between the transcriptome and proteome data. The study represents the first integrative-omics analysis in a CA overproducer S. clavuligerus strain, providing insights into the critical control points and potential rational engineering targets for a purposeful increase of CA yields in strain improvement. KEY POINTS: ∙ Transcriptome and proteome-wide alterations in industrial CA overproducer strain DEPA ∙ An acceptable degree of consistency between the transcriptome and proteome data ∙ New targets to be exploited for rational engineering.

An in-depth Comparison of the Pediatric and Adult Urinary N-glycomes.

We performed an in-depth characterization and comparison of the pediatric and adult urinary glycomes using a nanoLC-MS/MS based glycomics method, which included normal healthy pediatric (1-10 years, n = 21) and adult (21-50 years, n = 22) individuals. A total of 116 N-glycan compositions were identified, and 46 of them could be reproducibly quantified. We performed quantitative comparisons of the 46 glycan compositions between different age and sex groups. The results showed significant quantitative changes between the pediatric and adult cohorts. The pediatric urinary N-glycome was found to contain a higher level of high-mannose (HM), asialylated/afucosylated glycans (excluding HM), neutral fucosylated and agalactosylated glycans, and a lower level of trisialylated glycans compared with the adult. We further analyzed gender-associated glycan changes in the pediatric and adult group, respectively. In the pediatric group, there was almost no difference of glycan levels between males and females. In adult, the majority of glycans were more abundant in males than females, except the high-mannose and tetrasialylated glycans. These findings highlight the importance to consider age-matching and adult sex-matching for urinary glycan studies. The identified normal pediatric and adult urinary glycomes can serve as a baseline reference for comparisons to other disease states affected by glycosylation.

Single-cell Proteomics: Progress and Prospects.

MS-based proteome profiling has become increasingly comprehensive and quantitative, yet a persistent shortcoming has been the relatively large samples required to achieve an in-depth measurement. Such bulk samples, typically comprising thousands of cells or more, provide a population average and obscure important cellular heterogeneity. Single-cell proteomics capabilities have the potential to transform biomedical research and enable understanding of biological systems with a new level of granularity. Recent advances in sample processing, separations and MS instrumentation now make it possible to quantify >1000 proteins from individual mammalian cells, a level of coverage that required an input of thousands of cells just a few years ago. This review discusses important factors and parameters that should be optimized across the workflow for single-cell and other low-input measurements. It also highlights recent developments that have advanced the field and opportunities for further development.

Nano-LC: An updated review.

Low-flow chromatography has a rich history of innovation but has yet to reach widespread implementation in bioanalytical applications. Improvements in pump technology, microfluidic connections, and nano-electrospray sources for MS have laid the groundwork for broader application, and innovation in this space has accelerated in recent years. This article reviews the instrumentation used for nano-flow LC, the types of columns employed, and strategies for multidimensionality of separations, which are key to the future state of the technique to the high-throughput needs of modern bioanalysis. An update of the current applications where nano-LC is widely used, such as proteomics and metabolomics, is discussed. But the trend toward biopharmaceutical development of increasingly complex, targeted, and potent therapeutics for the safe treatment of disease drives the need for ultimate selectivity and sensitivity of our analytical platforms for targeted quantitation in a regulated space. The selectivity needs are best addressed by mass spectrometric detection, especially at high resolutions, and exquisite sensitivity is provided by nano-electrospray ionization as the technology continues to evolve into an accessible, robust, and easy-to-use platform.

Hydrophobic AEROSIL®R972 Fumed Silica Nanoparticles Incorporated Monolithic Nano-Columns for Small Molecule and Protein Separation by Nano-Liquid Chromatography.

A new feature of hydrophobic fumed silica nanoparticles (HFSNPs) when they apply to the preparation of monolithic nano-columns using narrow monolithic fused silica capillary columns (e.g., 50-µm inner diameter) was presented. The monolithic nano-columns were synthesized by an in-situ polymerization using butyl methacrylate (BMA) and ethylene dimethacrylate (EDMA) at various concentrations of AEROSIL®R972, called HFSNPs. Dimethyl formamide (DMF) and water were used as the porogenic solvents. These columns (referred to as HFSNP monoliths) were successfully characterized by using scanning electron microscopy (SEM) and reversed-phase nano-LC using alkylbenzenes and polyaromatic hydrocarbons as solute probes. The reproducibility values based on run-to-run, column-to-column and batch-to-batch were found as 2.3%, 2.48% and 2.99% (n = 3), respectively. The optimized column also indicated promising hydrophobic interactions under reversed-phase conditions, while the feasibility of the column allowed high efficiency and high throughput nano-LC separations. The potential of the final HFSNP monolith in relation to intact protein separation was successfully demonstrated using six intact proteins, including ribonuclease A, cytochrome C, carbonic anhydrase isozyme II, lysozyme, myoglobin, and α-chymotrypsinogen A in nano-LC. The results showed that HFSNP-based monolithic nanocolumns are promising materials and are powerful tools for sensitive separations.

RawBeans: A Simple, Vendor-Independent, Raw-Data Quality-Control Tool.

Every laboratory performing mass-spectrometry-based proteomics strives to generate high-quality data. Among the many factors that impact the outcome of any experiment in proteomics is the LC-MS system performance, which should be monitored within each specific experiment and also long term. This process is termed quality control (QC). We present an easy-to-use tool that rapidly produces a visual, HTML-based report that includes the key parameters needed to monitor the LC-MS system performance, with a focus on monitoring the performance within an experiment. The tool, named RawBeans, generates a report for individual files or for a set of samples from a whole experiment. We anticipate that it will help proteomics users and experts evaluate raw data quality independent of data processing. The tool is available at https://bitbucket.org/incpm/prot-qc/downloads. The mass-spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the data set identifier PXD022816.

Uromodulin Isolation and Its N-Glycosylation Analysis by NanoLC-MS/MS.

The glycoprotein uromodulin (UMOD) is the most abundant protein in urine, and N-glycans are critical for many biological functions of UMOD. Comprehensive glycan profiling of UMOD provides valuable information to understand the exact mechanisms of glycan-regulated functions. To perform comprehensive glycosylation analysis of UMOD from urine samples with limited volumes, we developed a streamlined workflow that included UMOD isolation from 5 mL of urine from 6 healthy adult donors (3 males and 3 females) and a glycosylation analysis using a highly sensitive and reproducible nanoLC-MS/MS based glycomics approach. In total, 212 N-glycan compositions were identified from the purified UMOD, and 17% were high-mannose glycans, 2% were afucosylated/asialylated, 3% were neutral fucosylated, 28% were sialylated (with no fucose), 46% were fucosylated and sialylated, and 4% were sulfated. We found that isolation of UMOD resulted in a significant decrease in the relative quantity of high-mannose and sulfated glycans with a significant increase of neutral fucosylated glycans in the UMOD-depleted urine relative to the undepleted urine, but depletion had little impact on the sialylated glycans. To our knowledge, this is the first study to perform comprehensive N-glycan profiling of UMOD using nanoLC-MS/MS. This analytical workflow would be very beneficial for studies with limited sample size, such as pediatric studies, and can be applied to larger patient cohorts not only for UMOD interrogation but also for global glycan analysis.

Simple and Efficient Microsolid-Phase Extraction Tip-Based Sample Preparation Workflow to Enable Sensitive Proteomic Profiling of Limited Samples (200 to 10,000 Cells).

In-depth LC-MS-based proteomic profiling of limited biological and clinical samples, such as rare cells or tissue sections from laser capture microdissection or microneedle biopsies, has been problematic due, in large, to the inefficiency of sample preparation and attendant sample losses. To address this issue, we developed on-microsolid-phase extraction tip (OmSET)-based sample preparation for limited biological samples. OmSET is simple, efficient, reproducible, and scalable and is a widely accessible method for processing ∼200 to 10,000 cells. The developed method benefits from minimal sample processing volumes (1-3 µL) and conducting all sample processing steps on-membrane within a single microreactor. We first assessed the feasibility of using micro-SPE tips for nanogram-level amounts of tryptic peptides, minimized the number of required sample handling steps, and reduced the hands-on time. We then evaluated the capability of OmSET for quantitative analysis of low numbers of human monocytes. Reliable and reproducible label-free quantitation results were obtained with excellent correlations between protein abundances and the amounts of starting material (R2 = 0.93) and pairwise correlations between sample processing replicates (R2 = 0.95) along with the identification of approximately 300, 1800, and 2000 protein groups from injected ∼10, 100, and 500 cell equivalents, resulting from processing approximately 200, 2000, and 10,000 cells, respectively.