High-resolution quantitative profiling of tRNA abundance and modification status in eukaryotes by mim-tRNAseq.

Measurements of cellular tRNA abundance are hampered by pervasive blocks to cDNA synthesis at modified nucleosides and the extensive similarity among tRNA genes. We overcome these limitations with modification-induced misincorporation tRNA sequencing (mim-tRNAseq), which combines a workflow for full-length cDNA library construction from endogenously modified tRNA with a comprehensive and user-friendly computational analysis toolkit. Our method accurately captures tRNA abundance and modification status in yeast, fly, and human cells and is applicable to any organism with a known genome. We applied mim-tRNAseq to discover a dramatic heterogeneity of tRNA isodecoder pools among diverse human cell lines and a surprising interdependence of modifications at distinct sites within the same tRNA transcript.

Spatially Resolved Top-Down Proteomics of Tissue Sections Based on a Microfluidic Nanodroplet Sample Preparation Platform.

Conventional proteomic approaches measure the averaged signal from mixed cell populations or bulk tissues, leading to the dilution of signals arising from subpopulations of cells that might serve as important biomarkers. Recent developments in bottom-up proteomics have enabled spatial mapping of cellular heterogeneity in tissue microenvironments. However, bottom-up proteomics cannot unambiguously define and quantify proteoforms, which are intact (i.e., functional) forms of proteins capturing genetic variations, alternatively spliced transcripts and posttranslational modifications. Herein, we described a spatially resolved top-down proteomics (TDP) platform for proteoform identification and quantitation directly from tissue sections. The spatial TDP platform consisted of a nanodroplet processing in one pot for trace samples-based sample preparation system and an laser capture microdissection-based cell isolation system. We improved the nanodroplet processing in one pot for trace samples sample preparation by adding benzonase in the extraction buffer to enhance the coverage of nucleus proteins. Using ∼200 cultured cells as test samples, this approach increased total proteoform identifications from 493 to 700; with newly identified proteoforms primarily corresponding to nuclear proteins. To demonstrate the spatial TDP platform in tissue samples, we analyzed laser capture microdissection-isolated tissue voxels from rat brain cortex and hypothalamus regions. We quantified 509 proteoforms within the union of top-down mass spectrometry-based proteoform identification and characterization and TDPortal identifications to match with features from protein mass extractor. Several proteoforms corresponding to the same gene exhibited mixed abundance profiles between two tissue regions, suggesting potential posttranslational modification-specific spatial distributions. The spatial TDP workflow has prospects for biomarker discovery at proteoform level from small tissue sections.

On the excessive use of coefficient of variation as a metric of quantitation quality in proteomics.

The coefficient of variation (CV) is often used in proteomics as a proxy to characterize the performance of a quantitation method and/or the related software. In this note, we question the excessive reliance on this metric in quantitative proteomics that may result in erroneous conclusions. We support this note using a ground-truth Human-Yeast-E. coli dataset demonstrating in a number of cases that erroneous data processing methods may lead to a low CV which has nothing to do with these methods' performances in quantitation.

Assessing the precision of a detergent-assisted cartridge precipitation workflow for non-targeted quantitative proteomics.

Detergent-based workflows incorporating sodium dodecyl sulfate (SDS) necessitate additional steps for detergent removal ahead of mass spectrometry (MS). These steps may lead to variable protein recovery, inconsistent enzyme digestion efficiency, and unreliable MS signals. To validate a detergent-based workflow for quantitative proteomics, we herein evaluate the precision of a bottom-up sample preparation strategy incorporating cartridge-based protein precipitation with organic solvent to deplete SDS. The variance of data-independent acquisition (SWATH-MS) data was isolated from sample preparation error by modelling the variance as a function of peptide signal intensity. Our SDS-assisted cartridge workflow yield a coefficient of variance (CV) of 13%-14%. By comparison, conventional (detergent-free) in-solution digestion increased the CV to 50%; in-gel digestion provided lower CVs between 14% and 20%. By filtering peptides predicting to display lower precision, we further enhance the validity of data in global comparative proteomics. These results demonstrate the detergent-based precipitation workflow is a reliable approach for in depth, label-free quantitative proteome analysis.

Deep quantitative proteomics of North American Pacific coast star tunicate (Botryllus schlosseri).

Botryllus schlosseri, is a model marine invertebrate for studying immunity, regeneration, and stress-induced evolution. Conditions for validating its predicted proteome were optimized using nanoElute® 2 deep-coverage LCMS, revealing up to 4930 protein groups and 20,984 unique peptides per sample. Spectral libraries were generated and filtered to remove interferences, low-quality transitions, and only retain proteins with >3 unique peptides. The resulting DIA assay library enabled label-free quantitation of 3426 protein groups represented by 22,593 unique peptides. Quantitative comparisons of single systems from a laboratory-raised with two field-collected populations revealed (1) a more unique proteome in the laboratory-raised population, and (2) proteins with high/low individual variabilities in each population. DNA repair/replication, ion transport, and intracellular signaling processes were distinct in laboratory-cultured colonies. Spliceosome and Wnt signaling proteins were the least variable (highly functionally constrained) in all populations. In conclusion, we present the first colonial tunicate's deep quantitative proteome analysis, identifying functional protein clusters associated with laboratory conditions, different habitats, and strong versus relaxed abundance constraints. These results empower research on B. schlosseri with proteomics resources and enable quantitative molecular phenotyping of changes associated with transfer from in situ to ex situ and from in vivo to in vitro culture conditions.

Robust, Precise, and Deep Proteome Profiling Using a Small Mass Range and Narrow Window Data-Independent-Acquisition Scheme.

In recent years, a plethora of different data-independent acquisition methods have been developed for proteomics to cover a wide range of requirements. Current deep proteome profiling methods rely on fractionations, elaborate chromatography, and mass spectrometry setups or display suboptimal quantitative precision. We set out to develop an easy-to-use one shot DIA method that achieves high quantitative precision and high proteome coverage. We achieve this by focusing on a small mass range of 430-670 m/z using small isolation windows without overlap. With this new method, we were able to quantify >9200 protein groups in HEK lysates with an average coefficient of variance of 3.2%. To demonstrate the power of our newly developed narrow mass range method, we applied it to investigate the effect of PGC-1α knockout on the skeletal muscle proteome in mice. Compared to a standard data-dependent acquisition method, we could double proteome coverage and, most importantly, achieve a significantly higher quantitative precision, as compared to a previously proposed DIA method. We believe that our method will be especially helpful in quantifying low abundant proteins in samples with a high dynamic range. All raw and result files are available at massive.ucsd.edu (MSV000092186).

Use of Nonhuman Sera as a Highly Cost-Effective Internal Standard for Quantitation of Multiple Human Proteins Using Species-Specific Tryptic Peptides: Applicability in Clinical LC-MS Analyses.

Quantitation of proteins using liquid chromatography-tandem mass spectrometry (LC-MS/MS) is complex, with a multiplicity of options ranging from label-free techniques to chemically and metabolically labeling proteins. Increasingly, for clinically relevant analyses, stable isotope-labeled (SIL) internal standards (ISs) represent the "gold standard" for quantitation due to their similar physiochemical properties to the analyte, wide availability, and ability to multiplex to several peptides. However, the purchase of SIL-ISs is a resource-intensive step in terms of cost and time, particularly for screening putative biomarker panels of hundreds of proteins. We demonstrate an alternative strategy utilizing nonhuman sera as the IS for quantitation of multiple human proteins. We demonstrate the effectiveness of this strategy using two high abundance clinically relevant analytes, vitamin D binding protein [Gc globulin] (DBP) and albumin (ALB). We extend this to three putative risk markers for cardiovascular disease: plasma protease C1 inhibitor (SERPING1), annexin A1 (ANXA1), and protein kinase, DNA-activated catalytic subunit (PRKDC). The results show highly specific, reproducible, and linear measurement of the proteins of interest with comparable precision and accuracy to the gold standard SIL-IS technique. This approach may not be applicable to every protein, but for many proteins it can offer a cost-effective solution to LC-MS/MS protein quantitation.

Cytoplasmic Shotgun Proteomic Points to Key Proteins and Pathways in Temozolomide-Resistant Glioblastoma Multiforme.

Temozolomide (TMZ) is the first line of chemotherapy to treat primary brain tumors of the type glioblastoma multiforme (GBM). TMZ resistance (TMZR) is one of the main barriers to successful treatment and is a principal factor in relapse, resulting in a poor median survival of 15 months. The present paper focuses on proteomic analyses of cytosolic fractions from TMZ-resistant (TMZR) LN-18 cells. The experimental workflow includes an easy, cost-effective, and reproducible method to isolate subcellular fraction of cytosolic (CYTO) proteins, mitochondria, and plasma membrane proteins for proteomic studies. For this study, enriched cytoplasmic fractions were analyzed in replicates by nanoflow liquid chromatography tandem high-resolution mass spectrometry (nLC-MS/MS), and proteins identified were quantified using a label-free approach (LFQ). Statistical analysis of control (CTRL) and temozolomide-resistant (TMZR) proteomes revealed proteins that appear to be differentially controlled in the cytoplasm. The functions of these proteins are discussed as well as their roles in other cancers and TMZ resistance in GBM. Key proteins are also described through biological processes related to gene ontology (GO), molecular functions, and cellular components. For protein-protein interactions (PPI), network and pathway involvement analyses have been performed, highlighting the roles of key proteins in the TMZ resistance phenotypes. This study provides a detailed insight into methods of subcellular fractionation for proteomic analysis of TMZ-resistant GBM cells and the potential to apply this approach to future large-scale studies. Several key proteins, protein-protein interactions (PPI), and pathways have been identified, underlying the TMZ resistance phenotype and highlighting the proteins' biological functions.

Accuracy of quantitative viral secondary standards: a re-examination.

Interlaboratory agreement of viral load assays depends on the accuracy and uniformity of quantitative calibrators. Previous work demonstrated poor agreement of secondary cytomegalovirus (CMV) standards with nominal values. This study re-evaluated this issue among commercially produced secondary standards for both BK virus (BKV) and CMV, using digital polymerase chain reaction (dPCR) to compare the materials from three different manufacturers. Overall, standards showed an improved agreement compared to prior work, against nominal values in both log10 copies/mL and log10 international unit (IU)/mL, with bias from manufacturer-assigned nominal values of 0.0-0.9 log10 units (either copies or IU)/mL. Standards normalized to IU and those values assigned by dPCR rather than by real-time PCR (qPCR) showed better agreement with nominal values. The latter reinforces prior conclusions regarding the utility of using such methods for quantitative value assignment in reference materials. Quantitative standards have improved over the last several years, and the remaining bias from nominal values might be further reduced by universal implementation of dPCR methods for value assignment, normalized to IU. IMPORTANCE: Interlaboratory agreement of viral load assays depends on accuracy and uniformity of quantitative calibrators. Previous work, published in JCM several years ago, demonstrated poor agreement of secondary cytomegalovirus (CMV) standards with nominal values. This study re-evaluated this issue among commercially produced secondary standards for both BK virus (BKV) and CMV, using digital polymerase chain reaction (dPCR) to compare the materials from three different manufacturers. Overall, standards showed an improved agreement compared to prior work, against nominal values, indicating a substantial improvement in the production of accurate secondary viral standards, while supporting the need for further work in this area and for the broad adaption of international unit (IU) as a reporting standard for quantitative viral load results.

Deciphering a proteomic signature for the early detection of breast cancer from breast milk: the role of quantitative proteomics.

INTRODUCTION: Breast cancer is one of the most prevalent cancers among women in the United States. Current research regarding breast milk has been focused on the composition and its role in infant growth and development. There is little information about the proteins, immune cells, and epithelial cells present in breast milk which can be indicative of the emergence of BC cells and tumors. AREAS COVERED: We summarize all breast milk studies previously done in our group using proteomics. These studies include 1D-PAGE and 2D-PAGE analysis of breast milk samples, which include within woman and across woman comparisons to identify dysregulated proteins in breast milk and the roles of these proteins in both the development of BC and its diagnosis. Our projected outlook for the use of milk for cancer detection is also discussed. EXPERT OPINION: Analyzing the samples by multiple methods allows one to interrogate a set of samples with various biochemical methods that complement each other, thus providing a more comprehensive proteome. Complementing methods like 1D-PAGE, 2D-PAGE, in-solution digestion and proteomics analysis with PTM-omics, peptidomics, degradomics, or interactomics will provide a better understanding of the dysregulated proteins, but also the modifications or interactions between these proteins.

Recent advances in mass spectrometry analysis of neuropeptides.

Due to their involvement in numerous biochemical pathways, neuropeptides have been the focus of many recent research studies. Unfortunately, classic analytical methods, such as western blots and enzyme-linked immunosorbent assays, are extremely limited in terms of global investigations, leading researchers to search for more advanced techniques capable of probing the entire neuropeptidome of an organism. With recent technological advances, mass spectrometry (MS) has provided methodology to gain global knowledge of a neuropeptidome on a spatial, temporal, and quantitative level. This review will cover key considerations for the analysis of neuropeptides by MS, including sample preparation strategies, instrumental advances for identification, structural characterization, and imaging; insightful functional studies; and newly developed absolute and relative quantitation strategies. While many discoveries have been made with MS, the methodology is still in its infancy. Many of the current challenges and areas that need development will also be highlighted in this review.

Mass spectrometry in ocular drug research.

Mass spectrometry (MS) has been proven as an excellent tool in ocular drug research allowing analyzes from small samples and low concentrations. This review begins with a short introduction to eye physiology and ocular pharmacokinetics and the relevance of advancing ophthalmic treatments. The second part of the review consists of an introduction to ocular proteomics, with special emphasis on targeted absolute quantitation of membrane transporters and metabolizing enzymes. The third part of the review deals with liquid chromatography-MS (LC-MS) and MS imaging (MSI) methods used in the analysis of drugs and metabolites in ocular samples. The sensitivity and speed of LC-MS make simultaneous quantitation of various drugs and metabolites possible in minute tissue samples, even though ocular sample preparation requires careful handling. The MSI methodology is on the verge of becoming as important as LC-MS in ocular pharmacokinetic studies, since the spatial resolution has reached the level, where cell layers can be separated, and quantitation with isotope-labeled standards has come more reliable. MS will remain in the foreseeable future as the main analytical method that will progress our understanding of ocular pharmacokinetics.

Absolute quantitation of human wild-type DNAI1 protein in lung tissue using a nanoLC-PRM-MS-based targeted proteomics approach coupled with immunoprecipitation.

BACKGROUND: Dynein axonemal intermediate chain 1 protein (DNAI1) plays an essential role in cilia structure and function, while its mutations lead to primary ciliary dyskinesia (PCD). Accurate quantitation of DNAI1 in lung tissue is crucial for comprehensive understanding of its involvement in PCD, as well as for developing the potential PCD therapies. However, the current protein quantitation method is not sensitive enough to detect the endogenous level of DNAI1 in complex biological matrix such as lung tissue. METHODS: In this study, a quantitative method combining immunoprecipitation with nanoLC-MS/MS was developed to measure the expression level of human wild-type (WT) DNAI1 protein in lung tissue. To our understanding, it is the first immunoprecipitation (IP)-MS based method for absolute quantitation of DNAI1 protein in lung tissue. The DNAI1 quantitation was achieved through constructing a standard curve with recombinant human WT DNAI1 protein spiked into lung tissue matrix. RESULTS: This method was qualified with high sensitivity and accuracy. The lower limit of quantitation of human DNAI1 was 4 pg/mg tissue. This assay was successfully applied to determine the endogenous level of WT DNAI1 in human lung tissue. CONCLUSIONS: The results clearly demonstrate that the developed assay can accurately quantitate low-abundance WT DNAI1 protein in human lung tissue with high sensitivity, indicating its high potential use in the drug development for DNAI1 mutation-caused PCD therapy.

Sorting and simultaneous quantitation of intact mixed-cell samples via capillary isotachophoresis.

A great need currently exists for rapid, inexpensive, and accurate methods for microbial analysis in the medical, food, industrial, and water quality fields. Here, a novel capillary isotachophoresis (CITP) method is presented for the focusing, sorting, and quantitation of intact cells in mixed samples based on their electrophoretic mobility ranges. Using a series of ion spacers dissolved in the sample, this technique results in several efficient cell peaks in the electropherogram corresponding to specific cell electrophoretic mobility ranges. The concentrations of different species in mixed-cell samples are determined from the cell peak areas and the known peak response factors for the cell species using a series of linear equations. Method design and optimization are discussed, including the choice of running buffer, pH, and ion spacers. Mixed-cell samples of up to four different species were focused and quantified as a proof-of-principle of the method. When sample cell concentrations were toward the middle of the linear response range, accuracies between 1% and 11% and relative standard deviations of 1%-14% were obtained, depending on the number of cell species in the mixture. This work provides a useful basis for future studies of cell quantitation using CITP, which could be potentially applied to a variety of fields including cell growth studies, microbial contamination testing, and sterility testing.

A novel SPE-LC-MRM strategy for serum demethylzeylasteral quantitation developed with an 18O-labeled internal standard.

Natural bioactive compounds (NBCs) are widely used in clinical treatment. For example, Tripterygium wilfordii Hook f. is commonly known in China as Lei-Gong-Teng which means thunder god vine. This herb is widely distributed in Eastern and Southern China, Korea, and Japan. The natural bioactive compounds of this herb can be extracted and made into tripterygium glycoside tablets. It is one of the most commonly used and effective traditional Chinese herbal medicines against rheumatoid arthritis (RA), nephrotic syndrome (NS), autoimmune hepatis (AIH), and so on. However, many NBCs are difficult to reliably quantify in the serum due to the effects of matrix and RSD. In addition, the targeted compound's internal standard (IS) is rarely sold due to the complex isotope internal standard synthesis pathway. In this study, a new quantitation method for 18O labeling combined with off-line SPE was formulated. We contrasted the recoveries and matrix effects of various separation methods in order to choose the best method. Furthermore, we optimized the conditions for SPE loading and washing. An isotopic internal standard was prepared by the 16O/18O exchanging reaction in order to eliminate the matrix effects. The method's accuracy and precision met the requirements for method validation. The recovery of this method was close to 60%. The relative standard deviation (RSD) of the high-concentration sample was 2%, and the limit of detection (LOD) was 1 ng/mL. This method could be used to analyze the clinical serum concentration of demethylzeylasteral. Sixty samples were collected from 10 patients with diabetes nephropathy. The quantitation results of demethylzeylasteral in patients' serum obtained using this method exhibited a correlation between therapeutic drug monitoring (TDM) and decreased urinary protein. This work may have broad implications for the study of drug metabolism in vivo and the clinical application of low-abundance and difficult-to-quantify NBCs.

15N metabolic labeling-TMT multiplexing approach to facilitate the quantitation of glycopeptides derived from cell lines.

The study of glycoproteomics presents a set of unique challenges, primarily due to the low abundance of glycopeptides and their intricate heterogeneity, which is specific to each site. Glycoproteins play a crucial role in numerous biological functions, including cell signaling, adhesion, and intercellular communication, and are increasingly recognized as vital markers in the diagnosis and study of various diseases. Consequently, a quantitative approach to glycopeptide research is essential. One effective strategy to address this need is the use of multiplex glycopeptide labeling. By harnessing the synergies of 15N metabolic labeling via the isotopic detection of amino sugars with glutamine (IDAWG) technique for glycan parts and tandem mass tag (TMT)pro labeling for peptide backbones, we have developed a method that allows for the accurate quantification and comparison of multiple samples simultaneously. The adoption of the liquid chromatography-synchronous precursor selection (LC-SPS-MS3) technique minimizes fragmentation interference, enhancing data reliability, as shown by a 97% TMT labeling efficiency. This method allows for detailed, high-throughput analysis of 32 diverse samples from 231BR cell lines, using both 14N and 15N glycopeptides at a 1:1 ratio. A key component of our methodology was the precise correction for isotope and TMTpro distortions, significantly improving quantification accuracy to less than 5% distortion. This breakthrough enhances the efficiency and accuracy of glycoproteomic studies, increasing our understanding of glycoproteins in health and disease. Its applicability to various cancer cell types sets a new standard in quantitative glycoproteomics, enabling deeper investigation into glycopeptide profiles.

Establishment of a targeted analysis method for gangliosides in mouse tissues by HILIC-ESI-MS/MS.

Gangliosides play an imperative role in cell signaling, neuronal recovery, apoptosis, and other physiological processes. For example, GM3 can regulate hypothalamic leptin resistance and control energy homeostasis, GD3 can mediate cell proliferation and differentiation and induce apoptosis, and GQ1b can stimulate neurogenesis. Therefore, the present study sought to establish and optimize the targeted analysis method for ganglioside subclasses and their molecular species using hydrophilic interaction liquid chromatography-triple quadrupole-MS/MS (HILIC-QQQ-MS/MS). Additionally, the fragmentation pattern of different ganglioside subclasses and their retention time patterns were analyzed, providing more accurate qualitative results. The limit of quantitation (LOQ) was as low as 10-4 ng. Moreover, the molecular species of gangliosides in the liver, cortex, and hypothalamus of C57BL/6 mice were analyzed using the established method. A total of 23 ganglioside subclasses with 164 molecular species, including 40 O-acetylated ganglioside molecular species and 28 NeuGc ganglioside molecular species, were identified using the semi-quantitative analysis method of an external standard curve corrected by an internal standard. In addition to NeuGc gangliosides, the contents of ganglioside subclasses were more abundant in the mouse brain than those in the mouse liver; especially, the contents of unsaturated gangliosides in the hypothalamus were much higher than those in the liver. Among them, O-acetylated gangliosides were detected only in the cortex and hypothalamus at a concentration of up to 100 µg/mg protein (40 molecular species). Overall, the proposed method expanded the detectable number of ganglioside subclasses and molecular species in biological samples and provided more opportunities for further study of the biological functions of gangliosides.

A novel method to assess copy number variations in melanocytic neoplasms: Droplet digital PCR for precise quantitation of MYC and MYB genes.

INTRODUCTION: While most melanocytic neoplasms can be classified as either benign or malignant by histopathology alone, ancillary molecular diagnostic tests can be necessary to establish the correct diagnosis in challenging cases. Currently, the detection of copy number variations (CNVs) by fluorescence in situ hybridization and chromosomal microarray (CMA) are the most popular methods, but remain expensive and inaccessible. We aim to develop a relatively inexpensive, fast, and accessible molecular assay to detect CNVs relevant to melanoma using droplet digital polymerase chain reaction (ddPCR) technology. METHODS: In this proof-of-concept study, we evaluated CNVs in MYC and MYB genes from 73 cases of benign nevi, borderline melanocytic lesions, and primary and metastatic melanoma at our institution from 2015 to 2022. A multiplexed ddPCR assay and CMA were performed on each sample, and the results were compared. RESULTS: Concordance analysis of ddPCR with CMA for quantification of MYC and MYB CNVs revealed a sensitivity and specificity of 89% and 86% for MYC and 83% and 74% for MYB, respectively. CONCLUSION: We demonstrate the first use of a multiplexed ddPCR assay to identify CNVs in melanocytic neoplasms. With further improvement and validation, ddPCR may represent a low-cost and rapid tool to aid in the diagnosis of histopathologically ambiguous melanocytic tumors.

Stress-induced changes in CARF expression serve as a quantitative predictive measure of cell proliferation fate.

Discovery of CARF (Collaborator of ARF)/CDKN2AIP as an ARF-interacting protein that promotes ARF-p53-p21WAF1 signaling and cellular senescence, initially established its role in genomic stress. Multiple reports further unraveled its role in regulation of senescence, growth arrest, apoptosis, or malignant transformation of cells in response to a variety of stress conditions in cultured human cells. It has been established as an essential protein. Whereas CARF-compromised cells undergo apoptosis, its enrichment has been recorded in a variety of cancer cells and has been associated with malignant transformation. We earlier demonstrated its role in stress-induced cell phenotypes that ranged from growth arrest, apoptosis, or malignant transformation. In the present study, we assessed the molecular mechanism of quantitative impact of change in CARF expression level on these cell fates. Stress-induced changes in CARF expression were assessed quantitatively with proteins involved in proteotoxicity, oxidative, genotoxic, and cytotoxic stress. These comparative quantitative analyses confirmed that (i) CARF responds to diverse stresses in a quantitative manner, (ii) its expression level serves as a reliable predictive measure of cell fates (iii) it correlates more with the DNA damage and MDA levels than the oxidative and proteotoxic signatures and (iv) CARF-expression based quantitative assay may be recruited for stress diagnostic applications.

Normics: Proteomic Normalization by Variance and Data-Inherent Correlation Structure.

Several algorithms for the normalization of proteomic data are currently available, each based on a priori assumptions. Among these is the extent to which differential expression (DE) can be present in the dataset. This factor is usually unknown in explorative biomarker screens. Simultaneously, the increasing depth of proteomic analyses often requires the selection of subsets with a high probability of being DE to obtain meaningful results in downstream bioinformatical analyses. Based on the relationship of technical variation and (true) biological DE of an unknown share of proteins, we propose the "Normics" algorithm: Proteins are ranked based on their expression level-corrected variance and the mean correlation with all other proteins. The latter serves as a novel indicator of the non-DE likelihood of a protein in a given dataset. Subsequent normalization is based on a subset of non-DE proteins only. No a priori information such as batch, clinical, or replicate group is necessary. Simulation data demonstrated robust and superior performance across a wide range of stochastically chosen parameters. Five publicly available spike-in and biologically variant datasets were reliably and quantitively accurately normalized by Normics with improved performance compared to standard variance stabilization as well as median, quantile, and LOESS normalizations. In complex biological datasets Normics correctly determined proteins as being DE that had been cross-validated by an independent transcriptome analysis of the same samples. In both complex datasets Normics identified the most DE proteins. We demonstrate that combining variance analysis and data-inherent correlation structure to identify non-DE proteins improves data normalization. Standard normalization algorithms can be consolidated against high shares of (one-sided) biological regulation. The statistical power of downstream analyses can be increased by focusing on Normics-selected subsets of high DE likelihood.