Universal Workflow Research Articles

A-262 Novel Hepatitis C Virus External Quality Control that is Stable at Ambient Temperature and Suitable For Use in Low-Resource Settings

Abstract Background Notwithstanding the WHO’s initiative to eliminate viral hepatitis by 2030, there are currently 58 million individuals infected with Hepatitis C Virus (HCV). 73% of infected individuals live in low- and middle-income countries (LMIC) where conventional diagnostics are inaccessible due to high costs and lack of trained personnel. The emergence of low-complexity Point of Care tests is critical for improving accessibility and reducing the spread of infection. Additionally, there is a need for external quality controls (EQC) that monitor the accuracy of test results. Given that LMIC have limited access to laboratory equipment, EQC must have simplified handling procedures and storage conditions. Unfortunately, these materials are not available at scale. Microbix strived to develop HCV EQC swab formulations that are stable at ambient temperature. Since this format deviates from standard HCV diagnostic workflows, we sought to establish a simple yet reproducible workflow that can be followed by laboratories worldwide. Methods Microbix developed HCV swab-based EQC that are stable when stored at 2-30°C. The contrived specimens are formulated with protected synthetic HCV whole-genome nucleic acid and human cells. The formulation was quantified via ddPCR and benchmarked against the WHO HCV standard using Xpert® HCV Viral Load Fingerstick Assay. Sample performance was evaluated with various elution buffers (PrimeStore® MTM, eNAT®, TE buffer, Microbix’s proprietary buffer) and handling procedures that require minimal use of laboratory equipment. Each EQC workflow was assessed based on its ability to consistently demonstrate a viral load of 100-200 IU/mL when tested on Cepheid’s platform. Results The EQC tested positive for HCV when eluted in each buffer and processed using a hand-mixing procedure. Only the workflows that used PrimeStore® MTM or eNAT® consistently reported a viral load between 100-200 IU/mL. Conclusions Microbix developed an HCV swab-based EQC that is stable at ambient temperature; however, we observed that consistent elution conditions are imperative for achieving reproducible results. Our findings demonstrate that a universal workflow should be followed to standardize results across testing sites as deviations in elution buffers, volumes, and handling procedures can influence test outcomes.

Analysis of mutation‐originated gain‐of‐glycosylation using mass spectrometry‐based N‐glycoproteomics

RationaleA general N‐glycoproteomics analysis pipeline has been established for characterization of mutation‐related gain‐of‐glycosylation (GoG) at intact N‐glycopeptide molecular level, generating comprehensive site and structure information of N‐glycosylation.MethodsThis study focused on mutation‐originated GoG using a mass spectrometry‐based N‐glycoproteomics analysis workflow. In brief, GoG intact N‐glycopeptide databases were built, consisting of 2701 proteins (potential GoG N‐glycosites and amino acids derived from MUTAGEN, VARIANT and VAR_SEQ in UniProt) and 6709 human N‐glycans (≤50 sequence isomers per monosaccharide composition). We employed the site‐ and structure‐specific N‐glycoproteomics workflow utilizing intact N‐glycopeptides search engine GPSeeker to identify GoG intact N‐glycopeptides from parental breast cancer stem cells (MCF‐7 CSCs) and adriamycin‐resistant breast cancer stem cells (MCF‐7/ADR CSCs).ResultsWith the criteria of spectrum‐level false discovery rate control of ≤1%, we identified 87 and 94 GoG intact N‐glycopeptides corresponding to 37 and 35 intact N‐glycoproteins from MCF‐7 CSCs and MCF‐7/ADR CSCs, respectively. Micro‐heterogeneity and macro‐heterogeneity of N‐glycosylation from GoG intact N‐glycoproteins with VAR_SEQ and VARIANT were found in both MCF‐7 CSCs and MCF‐7/ADR CSCs systems.ConclusionsThe integration of site‐ and structure‐specific N‐glycoproteomics approach, conjugating with GoG characterization, provides a universal workflow for revealing comprehensive N‐glycosite and N‐glycan structure information of GoG. The analysis of mutation‐originated GoG can be extended to GoG characterization of other N‐glycoproteome systems including complex clinical tissues and body fluids.

Clinical applications of metagenomics next-generation sequencing in infectious diseases.

Infectious diseases are a great threat to human health. Rapid and accurate detection of pathogens is important in the diagnosis and treatment of infectious diseases. Metagenomics next-generation sequencing (mNGS) is an unbiased and comprehensive approach for detecting all RNA and DNA in a sample. With the development of sequencing and bioinformatics technologies, mNGS is moving from research to clinical application, which opens a new avenue for pathogen detection. Numerous studies have revealed good potential for the clinical application of mNGS in infectious diseases, especially in difficult-to-detect, rare, and novel pathogens. However, there are several hurdles in the clinical application of mNGS, such as: (1) lack of universal workflow validation and quality assurance; (2) insensitivity to high-host background and low-biomass samples; and (3) lack of standardized instructions for mass data analysis and report interpretation. Therefore, a complete understanding of this new technology will help promote the clinical application of mNGS to infectious diseases. This review briefly introduces the history of next-generation sequencing, mainstream sequencing platforms, and mNGS workflow, and discusses the clinical applications of mNGS to infectious diseases and its advantages and disadvantages.

The Shelf Life of Milk-A Novel Concept for the Identification of Marker Peptides Using Multivariate Analysis.

The quality of food is influenced by several factors during production and storage. When using marker compounds, different steps in the production chain, as well as during storage, can be monitored. This might enable an optimum prediction of food's shelf life and avoid food waste. Especially, proteoforms and peptides thereof can serve as indicators for exogenous influences. The development of a proteomics-based workflow for detecting and identifying differences in the proteome is complex and time-consuming. The aim of the study was to develop a fast and universal workflow with ultra-high temperature (UHT) milk as a proteinaceous model food with expectable changes in protein/peptide composition. To find an optimum shelf life without sticking to a theoretically fixed best-before date, new evaluation and analytical methods are needed. Consequently, a modeling approach was used to monitor the shelf life of the milk after it was treated thermally and stored. The different peptide profiles determined with high-resolution mass spectrometry (HRMS) showed a significant difference depending on the preparation method of the samples. Potential marker peptides were determined using orthogonal projections to latent structures discriminant analysis (OPLSDA) and principal component analysis (PCA) following a typical proteomics protocol with tryptic hydrolysis. An additional Python-based algorithm enabled the identification of eight potential tryptic marker peptides (with mass spectrometric structural indications m/z 885.4843, m/z 639.3500, m/z 635.8622, m/z 634.3570, m/z 412.7191, m/z 623.2967, m/z 880.4767, and m/z 692.4041), indicating the effect of the heat treatment. The developed workflow is flexible and can be easily adapted to different research questions in the field of peptide analysis. In particular, the process of feature identification can be carried out with significantly less effort than with conventional methods.

Optimized structure design of asymmetrical Mg alloy cerebrovascular stent with high flexibility

In the treatment of cerebral artery stenosis via stent intervention, it is required that the stent can pass through the tortuous blood vessel with high curvature to reach the lesion position smoothly, and the damage to the artery should be as small as possible. This determines that the coronary artery stent cannot be directly applied to the diseased cerebrovascular, but a specialized cerebrovascular stent with high flexibility should be specifically designed. Differing from the commonly employed symmetrical structure, in this work, an asymmetrical and unequal-heigh stent structure was designed, which helps to improve the flexibility of the stent and reduces the self-contact phenomenon that occurs after the ordinary stent is bent. To balance the comprehensive properties of the stent, multi-objective optimization on the stent structure was carried out. The optimized stent structure shows better radial strength and flexibility and does not significantly affect equivalent plastic strain after stent expansion and volume average stress. In addition, this work provides a universal workflow for the customized stent structure.

A universal workflow for creation, validation, and generalization of detailed neuronal models

Detailed single-neuron modeling is widely used to study neuronal functions. While cellular and functional diversity across the mammalian cortex is vast, most of the available computational tools focus on a limited set of specific features characteristic of a single neuron. Here, we present a generalized automated workflow for the creation of robust electrical models and illustrate its performance by building cell models for the rat somatosensory cortex. Each model is based on a 3D morphological reconstruction and a set of ionic mechanisms. We use an evolutionary algorithm to optimize neuronal parameters to match the electrophysiological features extracted from experimental data. Then we validate the optimized models against additional stimuli and assess their generalizability on a population of similar morphologies. Compared to the state-of-the-art canonical models, our models show 5-fold improved generalizability. This versatile approach can be used to build robust models of any neuronal type.

Sustainable strategies for waterborne electrospinning of biocompatible nanofibers based on soy protein isolate

Electrospun nanofibers have gained great interest in many fields of research from water and air filtration or food packaging to medical use as scaffolds for tissue engineering, drug delivery systems and wound bandages. Proteins such as soy protein isolate (SPI) are biodegradable and safe polymers that can be purified from renewable and sustainable sources, and are thus interesting as building blocks for sustainable and biocompatible nanofiber-based materials. Sufficient solvent evaporation and intermolecular entanglement are required for efficient nanofiber formation. Electrospinning of proteins is therefore often achieved using organic solvents, strong bases or surfactants, which limits the safety, sustainability and usability of protein-based nanofibers. In this work, green and biocompatible electrospun nanofibers with a high content of SPI (up to 75% (w/w)) were fabricated with polyethylene oxide (PEO) as a co-spinning polymer and with water being the only solvent, thus avoiding use of any organic solvent, strong base or surfactant. A thorough biophysical assessment based on microscopy and spectroscopies, and a rheological profiling of SPI suggested that disassembly of larger structures into smaller in the SPI suspension and increase of SPI solubility improved the electrospinnability of SPI. The content of SPI in the nanofibers affected the morphology as visualized by scanning electron microscopy, brittleness assessed by dynamic mechanical analysis, and aqueous stability of the nanofibers, which are key parameters for the future use of SPI-based nanofibers. The biocompatibility of the electrospun SPI/PEO nanofibers was demonstrated by exposure of human epithelial cell monolayers (TR146) to the nanofibers without loss of cell viability. We propose that the presented strategies can serve as a universal workflow for waterborne electrospinning of other proteins or protein isolates.

ALIBY: ALFA Nanobody-Based Toolkit for Imaging and Biochemistry in Yeast.

ABSTRACTSpecialized epitope tags continue to be integral components of various biochemical and cell biological applications such as fluorescence microscopy, immunoblotting, immunoprecipitation, and protein purification. However, until recently, no single tag could offer this complete set of functionalities on its own. Here, we present a plasmid-based toolkit named ALIBY (ALFA toolkit for imaging and biochemistry in yeast) that provides a universal workflow to adopt the versatile ALFA tag/NbALFA system within the well-established model organism Saccharomyces cerevisiae. The kit comprises tagging plasmids for labeling a protein of interest with the ALFA tag and detection plasmids encoding fluorescent-protein-tagged NbALFA for live-cell imaging purposes. We demonstrate the suitability of ALIBY for visualizing the spatiotemporal localization of yeast proteins (i.e., the cytoskeleton, nucleus, centrosome, mitochondria, vacuole, endoplasmic reticulum, exocyst, and divisome) in live cells. Our approach has yielded an excellent signal-to-noise ratio without off-target effects or any effect on cell growth. In summary, our yeast-specific toolkit aims to simplify and further advance the live-cell imaging of differentially abundant yeast proteins while also being suitable for biochemical applications.IMPORTANCE In yeast research, conventional fluorescent protein tags and small epitope tags are widely used to study the spatiotemporal dynamics and activity of proteins. Although proven to be efficient, these tags lack the versatility for use across different cell biological and biochemical studies of a given protein of interest. Therefore, there is an urgent need for a unified platform for visualization and biochemical and functional analyses of proteins of interest in yeast. Here, we have engineered ALIBY, a plasmid-based toolkit that expands the benefits of the recently developed ALFA tag/NbALFA system to studies in the well-established model organism Saccharomyces cerevisiae. We demonstrate that ALIBY provides a simple and versatile strain construction workflow for long-duration live-cell imaging and biochemical applications in yeast.

BIM-driven data augmentation method for semantic segmentation in superpoint-based deep learning network

This paper describes a universal workflow to synthesize point clouds containing both geometry and color information by utilizing the IFC model or its 3D geometry model to automatically generate annotated point clouds for semantic segmentation in deep learning. In our experiments, we selected 44 scenes from the S3DIS dataset to rebuild BIM models and synthesize point clouds, replaced training datasets in different proportions with synthetic point clouds, and fed the mixed datasets to a superpoint-based network. The training results show that increasing the appropriate proportion of synthetic point clouds in the training dataset can significantly improve the semantic segmentation performance. Furthermore, we extend our experiments to two other state-of-the-art networks and another similar dataset, ScanNet, and the experimental results illustrate that the synthetic point clouds can be applied to augmenting the limited and low-quality annotated point clouds for deep learning and boost the automatic remodeling work in the architectural field.

Universal workflow of artificial intelligence for energy saving

Artificial intelligence (AI) controls are commonly used to save energy. However, excessive diversity in technological development has resulted in the inability to provide consistent energy-saving effects. Therefore, this study analysed 164 academic papers, with a total of 113 AI methods applied in six different fields of application. A universal workflow was developed to identify workable AI technologies for energy saving.The concept of a universal workflow originates from machine learning (ML). To approach an ML problem, a workflow is constructed to assist researchers in defining their problem and assembling a dataset. In this study, the developed universal workflow adopted a hierarchical structure to guide users to choose learning, optimisation, and control tools to achieve energy saving. Based on the data from various studies, the developed workflow provides qualitative and quantitative energy-saving effects for application in diverse fields.Universal workflow has contributed to the development of ML for commercial applications, and this research is also targeted to facilitate the commercial application of AI in the field of energy saving. Through a comprehensive analysis of experimental data, the universal workflow can confirm 35% energy cost saving in the building; 25% energy saving of the heating, ventilation and air conditioning equipment; 50% artificial lighting system energy saving; up to 70% reduction of information transfer and communication power; a continuous output of 30% peak power from the renewable energy device to the microgrid; and 20% power demand reduction in the factory. Corresponding to the choice of application technology, to the qualitative and quantitative benefits, and to the difference in control response, the universal workflow developed in this study provides a workable method to assist the use of AI in various applications. With workable design guidelines, the acceleration of commercial applications of AI for energy saving can be expected.

A review of detrital zircon data treatment, and launch of a new tool ‘Dezirteer’ along with the suggested universal workflow

Overwhelming numbers of detrital zircon (dZr) U—Pb ages have been acquired all over the globe in the last few decades, opening new horizons for employing big data approaches. However, several impediments such as frequent publication of heavily filtered data tables with omitted analyses, failure to cite the logic on "best age" computation, and generally the lack of uniformity among data treatment approaches delay the employment of this growing volume of data to the full extent. We have developed Dezirteer software to address some of the impediments. The program runs on any OS as a Python package and can be installed in Windows via an executable installer. Dezirteer imports U-Th-Pb LA-ICPMS geochronology data (either as .csv files from Iolite or Glitter, or from a manually-filled template). First, it allows the user to define and apply filters (by elevated discordance, analytical uncertainty, and U concentration). Next, the user defines computations (discordance calculation, type of Pb-correction, choosing "best age"), and Dezirteer applies them on dZr datasets. Finally, Dezirteer exports data and manipulations on them, unequivocally separated. Dezirteer permits to quickly assess the results of filters and computations visually (concordia, probability density curves, kernel density estimates, histograms, and cumulative diagrams) and numerically (Kolmogoroff — Smirnov statistics, Likeness, and Similarity coefficients, peaks locations). Thus, our program can be used as a substitute for several existing software packages and provides some unique functionality. We propose several guidelines for publishing U-Th-Pb dZr data to increase the data's trustworthiness and usability and improve the transparency of manipulations on these data. Most importantly, dZr data must be published before extensive filtering and interpretation, while all further filtering and computational aspects should be described. Such an approach will significantly simplify the use of global dZr data by the scientific community and step forward towards employing big data approaches in dZr studies.

Simulation of dynamic recrystallization behavior of hot extruded Mg-Zn-Y-Nd alloy tubes by the finite element method

The biodegradability and biocompatibility of magnesium alloys make them potential materials for manufacturing cardiovascular stents after multipass deformation and processing. The fabrication of Mg tubes is the most important step of the production procedure. In this work, the constitutive equation of this alloy was established by isothermal hot compression testing. A series of relevant models of dynamic recrystallization kinetics and grain growth processes were also established. Based on these models, a simulation utilizing the finite element method was employed to investigate the flow behaviors of a Mg-Zn-Y-Nd alloy during hot extrusion. The simulation results of the effective strain and grain size of the processed alloy show agreement with the experiments. Finally, a universal workflow is presented that facilitates the optimization of the manufacturing process of Mg tubes by the finite element method.

Improving depression screening in HIV positive pregnant women

IntroductionDepression is a common complication of pregnancy and the postpartum period. Up to 70% percent of women report depressive symptoms during their pregnancy, and approximately 10-16% meet full criteria for major depressive disorder. Women with a history of perinatal or non-perinatal major depression are likely to relapse during pregnancy. Research shows that exposure to untreated depression and stress can have negative consequences on the birth outcome and child development. Given the harmful effects of this disease on both the mother and child, it is essential that all pregnant patients be screened for depression. Literature review did not reflect many studies that focus on depression screening in this population, let alone in pregnant patients with Human Immunodeficiency Virus (HIV). Our study focuses on the impact the mandatory screening tool had on the incidence of depression screening in pregnant HIV patients.Objectives- Gain understanding of the Family Focused HIV Health Care Program for Women - Understand the importance of a mandatory screening tool for depressionMethodsUsing standardized Quality Improvement tools Implementation of screening tool in notes & enforcing a hard stop in the medical recordsResultsWe noted both qualitative & quantitative improvement in depression screening. Qualitatively the screening has been standardized by creating a universal workflow by the inclusion of screening tools (PHQ2 and PHQ9) in Electronic Medical records. Quantitatively there has been a 34.9% improvement in screening by the case managers in the post interventional quarter.ConclusionsSignificant improvement noted in the incidence of depression screening by implementation a mandatory screening tool

From outcrop scanlines to discrete fracture networks, an integrative workflow

Understanding fractures and fracture networks is essential for the investigation and use of subsurface reservoirs. The aim is to predict the fractures and the fracture network when there is no direct access to subsurface images available. This article presents a universal workflow to numerically compute a discrete fracture network by combining the 1D scanline survey method, processed with the newly written SkaPy script, together with the multiple point statistic method (MPS). This workflow is applied to a potential geothermal site in Mexico called Acoculco. We use Las Minas outcrops and quarries as surface analogues for the Acoculco reservoir, as Las Minas and Acoculco are both formed by the influence of a plutonic intrusion into the Jurassic–Cretaceous carbonate sequence of the Sierra Madre Oriental in the Trans-Mexican volcanic belt (TMVB). The intrusion is associated with contact metamorphism and metasomatic phenomena, providing the basis for the mining activities at Las Minas. The results obtained using this workflow demonstrate the feasibility of the approach, which presents a solution combining the efficiency of data processing and an interpretation-driven approach to build realistic discrete fracture networks. This workflow can be used in the process of estimating the permeability of a fracture controlled reservoir, with using only scanline surveys data as input. This is essential in the process of evaluating the feasibility to develop an enhanced geothermal system.

The contamination of valsartan and other sartans, Part 2: Untargeted screening reveals contamination with amides additionally to known nitrosamine impurities

The recent incidences of contaminated valsartan drug products gave rise to review the suitability of current impurity profiling workflows implemented at authorities and pharmaceutical companies. The major drawback of targeted impurity profiling, where a considerable amount of prior knowledge about possible contaminants is necessary, is the fact that unexpected impurities are overlooked easily. Here, a generic untargeted approach was applied on sartan containing drug products. The untargeted workflow allowed for the discrimination of different batches, different production sites, and differences after changes in the production process. The presented universal workflow makes use of LC-HRMS/MS and multivariate analysis for the interpretation of the data. Sartan samples contaminated with N-nitrosodimethylamine could be very well discriminated from N-nitrosodimethylamine-free samples using the procedure. Furthermore, untargeted approaches revealed two new impurities in various sartans drug products: valeramide and N,N-dimethylvaleramide.

Profiling embryonic stem cell differentiation by MALDI TOF mass spectrometry: development of a reproducible and robust sample preparation workflow.

MALDI TOF mass spectrometry (MS) is widely used to characterise and biotype bacterial samples, but a complementary method for profiling of mammalian cells is still underdeveloped. Current approaches vary dramatically in their sample preparation methods and are not suitable for high-throughput studies. In this work, we present a universal workflow for mammalian cell MALDI TOF MS analysis and apply it to distinguish ground-state naïve and differentiating mouse embryonic stem cells (mESCs), which can be used as a model for drug discovery. We employed a systematic approach testing many parameters to evaluate how efficiently and reproducibly each method extracted unique mass features from four different human cell lines. These data enabled us to develop a unique mammalian cell MALDI TOF workflow involving a freeze-thaw cycle, methanol fixing and a CHCA matrix to generate spectra that robustly phenotype different cell lines and are highly reproducible in peak identification across replicate spectra. We applied our optimised workflow to distinguish naïve and differentiating populations using multivariate analysis and reproducibly identify unique features. We were also able to demonstrate the compatibility of our optimised method for current automated liquid handling technologies. Consequently, our MALDI TOF MS profiling method enables identification of unique features and robust phenotyping of mESC differentiation in under 1 hour from culture to analysis, which is significantly faster and cheaper when compared with conventional methods such as qPCR. This method has the potential to be automated and can in the future be applied to profile other cell types and expanded towards cellular MALDI TOF MS screening assays.

Research and implementation of a universal workflow model to evaluate the soil fertility based on OGC Web Service

ABSTRACTA method based on workflow technology and Open Geospatial Consortium (OGC) specification is proposed to establish a universal workflow conceptual model in the network environment. In this paper, the soil fertility evaluation conceptual model was developed as an evaluation method of soil fertility by analyzing the GIS-based fertility evaluation method and extracting the dynamic variable to verify the feasibility model. This validation process involves determining the instantiation of the conceptual model. The proposed conceptual model achieved the following goals. All data acquisition and processing functions were packaged into an OGC-compliant service model; these service models were organized into a processing chain in a certain order on the workflow platform by Petri-Net; the fertility evaluation was realized on the workflow platform by calling the processing chain. Results showed that processing functions and data can be shared in the network environment, and the network workflow model can be realized by the workflow technology. The successful implementation of fertility evaluation proved the feasibility of the network-based universal workflow conceptual model. In addition, the flexibility of our modeling method is demonstrated by reconstructing the workflow model.

Identifying conserved genomic elements and designing universal bait sets to enrich them

Summary Targeted enrichment of conserved genomic regions is a popular method for collecting large amounts of sequence data from non‐model taxa for phylogenetic, phylogeographic and population genetic studies. For example, two available bait sets each allow enrichment of thousands of orthologous loci from >20 000 species (Faircloth et al. Systematic Biology, 61, 717–726, 2012; Molecular Ecology Resources, 15, 489–501, 2015). Unfortunately, few open‐source workflows are available to identify conserved genomic elements shared among divergent taxa and to design enrichment baits targeting these regions. Those that do exist require extensive bioinformatics expertise and significant amounts of time to use. These shortcomings limit the application of targeted enrichment methods to additional organismal groups. Here, I describe a universal workflow for identifying conserved genomic regions in available genomic data and for designing targeted enrichment baits to collect data from these conserved regions. These methods require less expertise, less time and better use commonly available information to identify conserved loci and design baits to capture them. I apply this computational approach to the understudied arthropod groups Arachnida, Coleoptera, Diptera, Hemiptera or Lepidoptera to identify thousands of conserved loci in each group and design target enrichment baits to capture these loci. I then use in silico analyses to demonstrate that targeted enrichment of the conserved loci can be used to reconstruct the accepted relationships among genome sequences from the focal arthropod orders. The software workflow I created allowed me to identify thousands of conserved loci in five diverse arthropod groups and design sequence capture baits to target them. This suite of capture bait designs should enable collection of phylogenomic data from >900 000 arthropod species. Although the examples in this manuscript focus on understudied arthropod groups, the approach I describe is applicable to all organismal groups having some form of pre‐existing genomic information (e.g. other invertebrates, plants, fungi and microbes). Finally, the documentation, design steps, software code and bait sets developed here are available under an open‐source license for restriction‐free testing, use, and additional modification by any research group.

Workflow management system based on WEB technology

Through the analysis of workflow management system based on Web, the work, following WFMC workflow model, proposed a universal workflow management system with the combination of specific application requirements of enterprises. Workflow management system based on Web was described from system function, software structure, system structure, workflow engine and security. The actual case of the design of aeronautical structure showed that workflow system performance can be greatly improved by using Web technology.

An Integrated Workflow To Assess Technical and Biological Variability of Cell Population Frequencies in Human Peripheral Blood by Flow Cytometry.

In the context of large-scale human system immunology studies, controlling for technical and biological variability is crucial to ensure that experimental data support research conclusions. In this study, we report on a universal workflow to evaluate both technical and biological variation in multiparameter flow cytometry, applied to the development of a 10-color panel to identify all major cell populations and T cell subsets in cryopreserved PBMC. Replicate runs from a control donation and comparison of different gating strategies assessed the technical variability associated with each cell population and permitted the calculation of a quality control score. Applying our panel to a large collection of PBMC samples, we found that most cell populations showed low intraindividual variability over time. In contrast, certain subpopulations such as CD56 T cells and Temra CD4 T cells were associated with high interindividual variability. Age but not gender had a significant effect on the frequency of several populations, with a drastic decrease in naive T cells observed in older donors. Ethnicity also influenced a significant proportion of immune cell population frequencies, emphasizing the need to account for these covariates in immune profiling studies. We also exemplify the usefulness of our workflow by identifying a novel cell-subset signature of latent tuberculosis infection. Thus, our study provides a universal workflow to establish and evaluate any flow cytometry panel in systems immunology studies.