Recent advances in robotic protein sample preparation for clinical analysis and other biomedical applications

Liquid-liquid phase separation-related signature predicts prognosis and therapeutic response in esophageal adenocarcinoma

BACKGROUND

Esophageal adenocarcinoma is a leading cause of mortality worldwide. New evidence indicates that liquid-liquid phase separation is related to malignancies. The current study aims at exploring the functions of liquid-liquid phase separation within esophageal adenocarcinoma. Patients within the TCGA dataset were classified using liquid-liquid phase separation-related genes. Significantly differentially expressed genes and prognostic factors for overall survival have been screened by Cox regression. Based on the liquid-liquid phase separation score, the construction of a prognostic model and liquid-liquid phase separation signature was constructed. Tumor mutation burden and drug sensitivity were analyzed in two groups: high liquid-liquid phase separation scores, and low liquid-liquid phase separation scores. According to liquid-liquid phase separation, some small-molecule compounds targeting esophageal adenocarcinoma were screened. The results were verified in vitro with an external cohort.

RESULTS

87 samples are involved, and 61 liquid-liquid phase separation-related genes may influence esophageal adenocarcinoma by changing DNA conformation and metabolism. Meanwhile, based on a high liquid-liquid phase separation score and low score group including 43 patients, it is found that the result significantly lowered the 5-year overall survival to 32.6 %, compared to 64.8 % in the low-score group of 44 patients with p < 0.001. The high score group had an average TIDE score of 0.27 versus 0.14 in the low-score group, with p = 0.003. The median tumor mutation burden was 9.1 mutations/Mb in the high-score group versus 6.4 mutations/Mb in the low-score group, with p = 0.011. The predictive model worked very well, with area under the curve values of 0.82, 0.79, and 0.76 for 1-, 3-, and 5-year survival, respectively. Liquid-liquid phase separation has been validated as an effective prognostic biomarker and drug sensitivity predictor.

SIGNIFICANCE

Liquid-liquid phase separation is potentially implicated in esophageal adenocarcinoma and works as a prognostic biomarker assessment of vulnerability to LLPS, which could help develop individualized therapies by showing how one is situated about various medications where responses vary across the body.

Magnetically Actuated Soft Microrobot with Environmental Adaptative Multimodal Locomotion Towards Targeted Delivery

The development of environmentally adaptive solutions for magnetically actuated microrobots to enable targeted delivery in complex and confined fluid environments presents a significant challenge. Inspired by the natural locomotion of crucian carp, a barbell-shaped soft microrobot (MBS2M) is proposed. A mechano-electromagnetic hybrid actuation system is developed to generate oscillating magnetic fields to manipulate the microrobot. The MBS2M can seamlessly transition between three fundamental locomotion modes: fast navigation (FN), high-precision navigation (HPN), and fixed-point rotation (FPR). Moreover, the MBS2M can move in reverse without turning. The multimodal locomotion endows the MBS2M's adaptability in diverse environments. It can smoothly pass through confined channels, climb over obstacles, overcome gravity for vertical motion, track complex pathways, traverse viscous environments, overcome low fluid resistance, and navigate complex spaces mimicking in vivo environments. Additionally, the MBS2M is capable of drug loading and release in response to ultrasound excitation. In an ex vivo porcine liver vein, the microrobot demonstrated targeted navigation under ultrasound guidance, showcasing its potential for specialized in vivo tasks.

Automated multiplexed affinity-based enrichment of peptides for LC-MS/MS plasma proteomics

Plasma proteomics offers high potential for biomarker discovery, as plasma is collected through a minimally invasive procedure and constitutes the most complex human-derived proteome. However, the wide dynamic range poses a significant challenge. Here, we propose a semi-automated method based on the use of multiple single chain variable fragment antibodies, each enriching for peptides found in up to a few hundred proteins. This approach allows for the analysis of a complementary fraction compared to full proteome analysis. Proteins from pooled plasma were extracted and digested before testing the performance of 29 different antibodies with the aim of reproducibly maximizing peptide enrichment. Our results demonstrate the enrichment of 3662 peptides not detected in neat plasma or negative controls. Moreover, most antibodies were able to enrich for at least 155 peptides across different levels of abundance in plasma. To further reduce analysis time, a combination of antibodies was used in a multiplexed setting. Repeated sample analyses showed low coefficients of variation, and the method is flexible in terms of affinity binders. It does not impose drastic increases in instrument time, thus showing excellent potential for usage in large scale discovery projects.

Blood proteomics of COVID-19 infection: An update

Despite significant progress in understanding SARS-CoV-2 and its impact, a deeper comprehension of the molecular changes in the host following infection is still lacking. Proteomic analysis of COVID-19 infected patients can provide valuable data about the events and mechanisms related to the initial, progression, and terminal stages of the disease. Such information can lead to better prevention, treatment, and convalescence strategies. In this review, we discuss blood proteomic studies based on mass spectrometry in COVID-19 patients. The analysis focuses on various blood components including plasma, platelets, serum, red blood cells, and peripheral blood mononuclear cells. Scientific papers published since 2022 are covered, with approaches categorised based on whether they use in-gel, in-solution, or on-beads/on-filter digestion modes. Additionally, candidate protein biomarkers related to COVID-19 are surveyed and discussed.

Evaluation of PAC and FASP Performance: DIA-Based Quantitative Proteomic Analysis

The aim of this study was to compare filter-aided sample preparation (FASP) and protein aggregation capture (PAC) starting from a three-species protein mix (Human, Soybean and Pisum sativum) and two different starting amounts (1 and 10 µg). Peptide mixtures were analyzed by data-independent acquisition (DIA) and raw files were processed by three commonly used software: Spectronaut, MaxDIA and DIA-NN. Overall, the highest number of proteins (mean value of 5491) were identified by PAC (10 µg), while the lowest number (4855) was identified by FASP (1 µg). The latter experiment displayed the worst performance in terms of both specificity (0.73) and precision (0.24). Other tested conditions showed better diagnostic accuracy, with specificity values of 0.95-0.99 and precision values between 0.61 and 0.86. In order to provide guidance on the data analysis pipeline, the accuracy diagnostic of three software was investigated: (i) the highest sensitivity was obtained with Spectronaut (median of 0.67) highlighting the ability of Spectronaut to quantify low-abundance proteins, (ii) the best precision value was obtained by MaxDIA (median of 0.84), but with a reduced number of identifications compared to Spectronaut and DIA-NN data, and (iii) the specificity values were similar (between 0.93 and 0.99). The data are available on ProteomeXchange with the identifier PXD044349.

Automation and Computerization of (Bio)sensing Systems

Sensing systems necessitate automation to reduce human effort, increase reproducibility, and enable remote sensing. In this perspective, we highlight different types of sensing systems with elements of automation, which are based on flow injection and sequential injection analysis, microfluidics, robotics, and other prototypes addressing specific real-world problems. Finally, we discuss the role of computer technology in sensing systems. Automated flow injection and sequential injection techniques offer precise and efficient sample handling and dependable outcomes. They enable continuous analysis of numerous samples, boosting throughput, and saving time and resources. They enhance safety by minimizing contact with hazardous chemicals. Microfluidic systems are enhanced by automation to enable precise control of parameters and increase of analysis speed. Robotic sampling and sample preparation platforms excel in precise execution of intricate, repetitive tasks such as sample handling, dilution, and transfer. These platforms enhance efficiency by multitasking, use minimal sample volumes, and they seamlessly integrate with analytical instruments. Other sensor prototypes utilize mechanical devices and computer technology to address real-world issues, offering efficient, accurate, and economical real-time solutions for analyte identification and quantification in remote areas. Computer technology is crucial in modern sensing systems, enabling data acquisition, signal processing, real-time analysis, and data storage. Machine learning and artificial intelligence enhance predictions from the sensor data, supporting the Internet of Things with efficient data management.

Metabolomic Profiling of Hormonal Contraceptive Use in Young Females Using a Commercially Available LC-MS/MS Kit

Oral hormonal contraceptive users carry the risk of venous thrombosis and increased mortality. This study aimed to comprehensively profile the serum metabolome of participants using a combination of drospirenone (DRSP) and ethinyl estradiol (EE) containing oral contraceptives (COCs). The MxP Quant 500 kit for liquid chromatography mass tandem spectrometry (LC-MS/MS) was used to analyse the 22 controls and 44 COC users (22 on a low EE dose (DRSP/20EE) and 22 on a higher EE dose (DRSP/30EE)). The kit's results were compared to our internally developed untargeted and targeted metabolomics methods previously applied to this cohort. Of the 630 metabolites included in the method, 277 provided desirable results (consistently detected above their detection limits), and of these, 5 had p-values < 0.05, including betaine, glutamine, cortisol, glycine, and choline. Notably, these variations were observed between the control and COC groups, rather than among the two COC groups. Partial least squares-discriminant analysis revealed 49 compounds with VIP values ≥ 1, including amino acids and their derivatives, ceramides, phosphatidylcholines, and triglycerides, among others. Ten differential compounds were consistent with our previous studies, reinforcing the notion of COCs inducing a prothrombotic state and increased oxidative stress. Although only a limited number of compounds were deemed usable, these were quantified with high reliability and facilitated the identification of meaningful biological differences among the sample groups. In addition to substantiating known drug-induced variations, new hypotheses were also generated.

Automation of an atomic force microscope via Arduino

The Atomic Force Microscopy is a very versatile technique that allows to characterize surfaces by acquiring topographies with sub-nanometer resolution. This technique often overcomes the problems and capabilities of electron microscopy when characterizing few nanometers thin coatings over solid substrates. They are expensive, in the half million dollar range for standard units, and therefore it is often difficult to upgrade to new units with improved characteristics. One of these improvements, motorization and automation of the measurements is very interesting to sample different parts of a substrate in an unattended way. Here we report a low cost upgrade under 60 $ to a Dimension 3000 AFM based on a control unit using an Arduino Leonardo. It enables to acquire dozens or hundreds of images automatically by mimicking keyboard shortcuts and interfacing the AFM PCI card.

Modern automated microextraction procedures for bioanalytical, environmental, and food analyses

Sample preparation frequently is considered the most critical stage of the analytical workflow. It affects the analytical throughput and costs; moreover, it is the primary source of error and possible sample contamination. To increase efficiency, productivity, and reliability, while minimizing costs and environmental impacts, miniaturization and automation of sample preparation are necessary. Nowadays, several types of liquid-phase and solid-phase microextractions are available, as well as different automatization strategies. Thus, this review summarizes recent developments in automated microextractions coupled with liquid chromatography, from 2016 to 2022. Therefore, outstanding technologies and their main outcomes, as well as miniaturization and automation of sample preparation, are critically analyzed. Focus is given to main microextraction automation strategies, such as flow techniques, robotic systems, and column-switching approaches, reviewing their applications to the determination of small organic molecules in biological, environmental, and food/beverage samples.

Enrichment and detection of VEGF165 in blood samples on a microfluidic chip integrated with multifunctional units

In this paper, a multifunctional microfluidic chip integrated with a centrifugal separation zone, aqueous two-phase system (ATPS) mixing zone and enrichment detection zone was proposed and fabricated. An automatic and efficient separation and quantitative analysis method for vascular endothelial growth factor 165 (VEGF₁₆₅) in whole blood samples was established with the designed microfluidic chip. A blood sample was divided into blood cells and plasma in the centrifugation zone. In the ATPS mixing zone, plasma was mixed with PEG/KH₂PO₄ aqueous two-phase solution containing Apt-Au NP nanoprobes. In the enrichment detection zone, the mixture was separated on CN140 modified with a ZnO NP-anti VEGF₁₆₅ nanostructure. The VEGF₁₆₅ captured by Apt-Au NPs was distributed in the PEG phase, concentrated at the front of CN140 and combined with anti-VEGF₁₆₅ to form a sandwich structure. The sensitive detection of VEGF₁₆₅ was achieved through fluorescence resonance energy transfer between rhodamine B and Au NPs on the nanoprobe. Under the optimized rotation program, capillary and centrifugal forces propelled the fluid in the whole process of pretreatment and detection. The detection linear range was between 1 pg mL^-1 and 50 ng mL^-1, the detection limit of VEGF₁₆₅ in blood was 0.22 pg mL^-1 and the enrichment efficiency was 983. It was illustrated that a convenient and reliable way for detection of tumor markers based on the multifunctional microfluidic chip was provided and it has a potential value for early screening and prognosis of clinical cancer.

A rapid and convenient enzyme digestion method for the analysis of N-glycans using exoglycosidase-impregnated polyacrylamide gels fabricated in an automatic pipette tip

Efficient enzymatic digestion methods are critical for the characterization and identification of glycans. Glycan hydrolysis enzymes are widely utilized for the identification of glycoprotein or glycolipid glycans. The commonly utilized in solution glycan hydrolysis methods require several hours of incubation with enzymes for complete removal of their target monosaccharides. To develop an efficient and simple method for the rapid release of monosaccharides from glycoprotein glycans, we fabricated exoglycosidase-impregnated acrylamide gels in an automatic pipette tip. Our automated enzymatic reactors are based on the simple photochemical copolymerization of monomers comprising acrylamide and methylene-bis-acrylamide-containing enzymes with an azobis compound functioning as the photocatalytic initiator. After filling the tip of the automatic pipette with these acrylamide solutions, polymerization of the acrylamide gel solution was performed by irradiation with a LED. The immobilized enzymes maintained their activities in the pipette tips and their action was completed by fully automatic pipetting for 10 to 30 min. We utilized 8-aminopyrene-1, 3, 6-trisulfonic acid (APTS)-labeled glycans as a substrate and measured by capillary electrophoresis (CE) before and after enzymatic digestion. We demonstrated that this method exhibited quantitative enzymatic and specific cleavage of monosaccharides from glycoprotein glycans.

Bottom-Up Proteomics: Advancements in Sample Preparation

Liquid chromatography–tandem mass spectrometry (LC–MS/MS)-based proteomics is a powerful technique for profiling proteomes of cells, tissues, and body fluids. Typical bottom-up proteomic workflows consist of the following three major steps: sample preparation, LC–MS/MS analysis, and data analysis. LC–MS/MS and data analysis techniques have been intensively developed, whereas sample preparation, a laborious process, remains a difficult task and the main challenge in different applications. Sample preparation is a crucial stage that affects the overall efficiency of a proteomic study; however, it is prone to errors and has low reproducibility and throughput. In-solution digestion and filter-aided sample preparation are the typical and widely used methods. In the past decade, novel methods to improve and facilitate the entire sample preparation process or integrate sample preparation and fractionation have been reported to reduce time, increase throughput, and improve reproducibility. In this review, we have outlined the current methods used for sample preparation in proteomics, including on-membrane digestion, bead-based digestion, immobilized enzymatic digestion, and suspension trapping. Additionally, we have summarized and discussed current devices and methods for integrating different steps of sample preparation and peptide fractionation.

Vending-Machine-Style Skin Excretion Sensing

Skin metabolites show huge potential for use in clinical diagnostics. However, skin sampling and analysis workflows are tedious and time-consuming. Here, we demonstrate a vending-machine-style skin excretion sensing platform based on hydrogel-assisted sampling of skin metabolites. In this sensing platform, a sampling probe with hydrogel is held by a robotic arm. The robotic arm manoeuvres the probe to press it onto the forearm of a human subject. Due to the highly hydrophilic nature of the hydrogel, water-soluble metabolites─released by skin─are collected into the hydrogel, leaving behind the nonpolar metabolites. The probe is then inserted into a custom-made open port sampling interface coupled to an electrospray ion source of a high-resolution quadrupole-time-of-flight mass spectrometer. Metabolites in the hydrogel are immediately extracted by a solvent liquid junction in the interface and analyzed using the mass spectrometer. The ion current of the target analyte is displayed on a customized graphical user interface, which can also be used to control the key components of the analytical platform. The automated sampling and analysis workflow starts after the user inserts coins or presents an insurance card, presses a button, and extends an arm on the sampling area. The platform relies on low-cost mechanical and electronic modules (a robotic arm, a single-board computer, and two microcontroller boards). The limits of detection for standard analytes─arginine, citrulline, and histidine─embedded in agarose gel beds were 148, 205, and 199 nM, respectively. Various low-molecular-weight metabolites from human skin have been identified with the high-resolution mass spectrometer.

Mass Spectrometric-Based Proteomics for Biomarker Discovery in Osteosarcoma: Current Status and Future Direction

Due to a lack of novel therapies and biomarkers, the clinical outcomes of osteosarcoma patients have not significantly improved for decades. The advancement of mass spectrometry (MS), peptide quantification, and downstream pathway analysis enables the investigation of protein profiles across a wide range of input materials, from cell culture to long-term archived clinical specimens. This can provide insight into osteosarcoma biology and identify candidate biomarkers for diagnosis, prognosis, and stratification of chemotherapy response. In this review, we provide an overview of proteomics studies of osteosarcoma, indicate potential biomarkers that might be promising therapeutic targets, and discuss the challenges and opportunities of mass spectrometric-based proteomics in future osteosarcoma research.

Proteomics-Based Transporter Identification by the PICK Method: Involvement of TM7SF3 and LHFPL6 in Proton-Coupled Organic Cation Antiport at the Blood-Brain Barrier

A proton-coupled organic cation (H⁺/OC) antiporter working at the blood–brain barrier (BBB) in humans and rodents is thought to be a promising candidate for the efficient delivery of cationic drugs to the brain. Therefore, it is important to identify the molecular entity that exhibits this activity. Here, for this purpose, we established the Proteomics-based Identification of transporter by Crosslinking substrate in Keyhole (PICK) method, which combines photo-affinity labeling with comprehensive proteomics analysis using SWATH-MS. Using preselected criteria, the PICK method generated sixteen candidate proteins. From these, knockdown screening in hCMEC/D3 cells, an in vitro BBB model, identified two proteins, TM7SF3 and LHFPL6, as candidates for the H⁺/OC antiporter. We synthesized a novel H⁺/OC antiporter substrate for functional analysis of TM7SF3 and LHFPL6 in hCMEC/D3 cells and HEK293 cells. The results suggested that both TM7SF3 and LHFPL6 are components of the H⁺/OC antiporter.

Current Insights on the Impact of Proteomics in Respiratory Allergies

Respiratory allergies affect humans worldwide, causing extensive morbidity and mortality. They include allergic rhinitis (AR), asthma, pollen food allergy syndrome (PFAS), aspirin-exacerbated respiratory disease (AERD), and nasal polyps (NPs). The study of respiratory allergic diseases requires new technologies for early and accurate diagnosis and treatment. Omics technologies provide the tools required to investigate DNA, RNA, proteins, and other molecular determinants. These technologies include genomics, transcriptomics, proteomics, and metabolomics. However, proteomics is one of the main approaches to studying allergic disorders' pathophysiology. Proteins are used to indicate normal biological processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention. In this field, the principal goal of proteomics has been to discover new proteins and use them in precision medicine. Multiple technologies have been applied to proteomics, but that most used for identifying, quantifying, and profiling proteins is mass spectrometry (MS). Over the last few years, proteomics has enabled the establishment of several proteins for diagnosing and treating respiratory allergic diseases.

Comprehensive Genomic Profiling of Circulating Tumor DNA in Patients with Previously Treated Metastatic Colorectal Cancer: Analysis of a Real-World Healthcare Claims Database

We used a real-world database (GuardantINFORM^TM) to analyze the treatment choices for patients with mCRC who underwent next-generation sequencing of circulating tumor DNA (ctDNA) using a commercially available test (Guardant360^®) after first- or second-line therapy. From 18,875 patients with claims for CRC, 1064 had confirmed metastatic disease and sufficient histories for analysis (median age 59 years, 44.8% female, 44.5% left-sided). ctDNA was detectable for 997/1064 (93.7%) patients. Clinically actionable molecular profiles were present for 507/1064 (47.7%) patients, including those who had not received targeted therapy in the previous line (410/926, 44.3%). Second- or third-line targeted therapies were administered to 338/1064 patients (31.8%) and were considered matched for 193/338 (57.1%) patients. Therapies administered after testing were informed by the ctDNA results in 56.7% of patients overall (603/1064). Time to treatment discontinuation was most favorable for patients with a clinically actionable ctDNA profile who received matched therapy. This analysis demonstrates the real-world clinical value of plasma-based comprehensive genomic profiling for selecting appropriate molecular-targeted therapies in mCRC patients with disease progression after first- or second-line therapy.

Automatic Programmable Bioreactor with pH Monitoring System for Tissue Engineering Application

Tissue engineering technology has been advanced and applied to various applications in the past few years. The presence of a bioreactor is one key factor to the successful development of advanced tissue engineering products. In this work, we developed a programmable bioreactor with a controlling program that allowed each component to be automatically operated. Moreover, we developed a new pH sensor for non-contact and real-time pH monitoring. We demonstrated that the prototype bioreactor could facilitate automatic cell culture of L929 cells. It showed that the cell viability was greater than 80% and cell proliferation was enhanced compared to that of the control obtained by a conventional cell culture procedure. This result suggests the possibility of a system that could be potentially useful for medical and industrial applications, including cultured meat, drug testing, etc.

Open source fraction collector/MALDI spotter for proteomics

We describe a complete open-source hardware/software solution for high performance thermostatted peptide fraction collection to support mass spectrometry experiments with complex proteomes. The instrument is easy to assemble using parts readily available through retail channels at a fraction of the cost compared to typical commercial systems. Control software is written in Python allowing for rapid customization. We demonstrate several useful applications, including the automated deposition of LC separated peptides for matrix-assisted laser desorption ionization mass spectrometry (MALDI-MS) as well as collection and concatenation of peptide fractions from nanoflow HPLC separations.

Human peripheral blood mononuclear cells: A review of recent proteomic applications

Human peripheral blood mononuclear cells (PBMCs) represent a sentinel blood sample which reacts to different pathophysiological stimuli in the form of immunological responses/immunophenotypic changes. The study of molecular content of PBMCs can provide better understanding of immune processes giving the possibility of monitoring the health conditions of the host organism. Proteomic analysis of PBMCs can achieve mentioned goal as important immune-related biomarkers are easily accessible for analysis. PBMCs have been gaining attention in different research areas including preclinical or clinical investigations. In this review, recent applications of proteomic analysis of PBMCs are described and discussed. Approaches are divided based on different proteomic workflows such as in-gel, in-solution and on-filter modes. The effect of various diseases such as autoimmune, cancer, neurodegenerative, viral, metabolic, and various immune stimulations such as radiation, vaccine, corticosteroids over PBMCs proteome, are described with emphasis on promising protein biomarker candidates. This article is protected by copyright. All rights reserved.

Proteomics-Based Identification of Interaction Partners of the Xenobiotic Detoxification Enzyme FMO3 Reveals Involvement in Urea Cycle

The hepatic xenobiotic metabolizing enzyme flavin-containing monooxygenase 3 (FMO3) has been implicated in the development of cardiometabolic disease primarily due to its enzymatic product trimethylamine-N oxide (TMAO), which has recently been shown to be associated with multiple chronic diseases, including kidney and coronary artery diseases. Although TMAO may have causative roles as a pro-inflammatory mediator, the possibility for roles in metabolic disease for FMO3, irrespective of TMAO formation, does exist. We hypothesized that FMO3 may interact with other proteins known to be involved in cardiometabolic diseases and that modulating the expression of FMO3 may impact on these interaction partners. Here, we combine a co-immunoprecipitation strategy coupled to unbiased proteomic workflow to report a novel protein:protein interaction network for FMO3. We identified 51 FMO3 protein interaction partners, and through gene ontology analysis, have identified urea cycle as an enriched pathway. Using mice deficient in FMO3 on two separate backgrounds, we validated and further investigated expressional and functional associations between FMO3 and the identified urea cycle genes. FMO3-deficient mice showed hepatic overexpression of carbamoylphosphate synthetase (CPS1), the rate-limiting gene of urea cycle, and increased hepatic urea levels, especially in mice of FVB (Friend leukemia virus B strain) background. Finally, overexpression of FMO3 in murine AML12 hepatocytes led to downregulation of CPS1. Although there is past literature linking TMAO to urea cycle, this is the first published work showing that FMO3 and CPS1 may directly interact, implicating a role for FMO3 in chronic kidney disease irrespective of TMAO formation.

Comparative Phosphoproteomics of Neuro-2a Cells under Insulin Resistance Reveals New Molecular Signatures of Alzheimer's Disease

Insulin in the brain is a well-known critical factor in neuro-development and regulation of adult neurogenesis in the hippocampus. The abnormality of brain insulin signaling is associated with the aging process and altered brain plasticity, and could promote neurodegeneration in the late stage of Alzheimer’s disease (AD). The precise molecular mechanism of the relationship between insulin resistance and AD remains unclear. The development of phosphoproteomics has advanced our knowledge of phosphorylation-mediated signaling networks and could elucidate the molecular mechanisms of certain pathological conditions. Here, we applied a reliable phosphoproteomic approach to Neuro2a (N2a) cells to identify their molecular features under two different insulin-resistant conditions with clinical relevance: inflammation and dyslipidemia. Despite significant difference in overall phosphoproteome profiles, we found molecular signatures and biological pathways in common between two insulin-resistant conditions. These include the integrin and adenosine monophosphate-activated protein kinase pathways, and we further verified these molecular targets by subsequent biochemical analysis. Among them, the phosphorylation levels of acetyl-CoA carboxylase and Src were reduced in the brain from rodent AD model 5xFAD mice. This study provides new molecular signatures for insulin resistance in N2a cells and possible links between the molecular features of insulin resistance and AD.

Nano liquid chromatography, 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 mass spectrometry 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 liquid chromatography , the types of columns employed, and strategies for multi-dimensionality of separations, which is 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 towards 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.

Clinical Implications of MiR128, Angiotensin I Converting Enzyme and Vascular Endothelial Growth Factor Gene Abnormalities and Their Association with T2D

Type 2 DM (T2D) results from the interaction of the genetic and environmental risk factors. Vascular endothelial growth factor (VEGF), angiotensin I-converting enzyme (ACE), and MicroRNAs (MiRNAs) are involved in important physiological processes. Gene variations in VEGF, ACE and MiRNA genes are associated with diseases. In this study we investigated the associations of the VEGF-2578 C/A (rs699947), VEGF-2549 insertion/deletion (I/D), and ACE I/D rs4646994 and Mir128a (rs11888095) gene variations with T2D using the amplification refractory mutation system PCR (ARMS-PCR) and mutation specific PCR (MSP). We screened 122 T2D cases and 126 healthy controls (HCs) for the rs699947, and 133 T2D cases and 133 HCs for the VEGF I/D polymorphism. For the ACE I/D we screened 152 cases and 150 HCs, and we screened 129 cases and 112 HCs for the Mir128a (rs11888095). The results showed that the CA genotype of the VEGF rs699947 and D allele of the VEGF I/D polymorphisms were associated with T2D with OR =2.01, p-value = 0.011, and OR = 2.42, p-value = 0.010, respectively. The result indicated the D allele of the ACE ID was protective against T2D with OR = 0.10, p-value = 0.0001, whereas the TC genotype and the T allele of the Mir128a (rs11888095) were associated with increased risk to T2D with OR = 3.16, p-value = 0.0001, and OR = 1.68, p-value = 0.01, respectively. We conclude that the VEGF (rs699947), VEGF I/D and Mir128a (rs11888095) are potential risk loci for T2D, and that the D allele of the ACE ID polymorphism may be protective against T2D. These results help in identification and stratification for the individuals that at risk for T2D. However, future well-designed studies in different populations and with larger sample sizes are required. Moreover, studies to examine the effects of these polymorphisms on VEGF and ACE proteins are recommended.

Standardized high-throughput biomonitoring using DNA metabarcoding: Strategies for the adoption of automated liquid handlers

Reliable and comprehensive monitoring data are required to trace and counteract biodiversity loss. High-throughput metabarcoding using DNA extracted from community samples (bulk) or from water or sediment (environmental DNA) has revolutionized biomonitoring, given the capability to assess biodiversity across the tree of life rapidly with feasible effort and at a modest price. DNA metabarcoding can be upscaled to process hundreds of samples in parallel. However, while automated high-throughput analysis workflows are well-established in the medical sector, manual sample processing still predominates in biomonitoring laboratory workflows limiting the upscaling and standardization for routine monitoring applications. Here we present an automated, scalable, and reproducible metabarcoding workflow to extract DNA from bulk samples, perform PCR and library preparation on a liquid handler. Key features are the independent sample replication throughout the workflow and the use of many negative controls for quality assurance and quality control. We generated two datasets: i) a validation dataset consisting of 42 individual arthropod specimens of different species, and ii) a routine monitoring dataset consisting of 60 stream macroinvertebrate bulk samples. As a marker, we used the mitochondrial COI gene. Our results show that the developed single-deck workflow is free of laboratory-derived contamination and produces highly consistent results. Minor deviations between replicates are mostly due to stochastic differences for low abundant OTUs. Thus, we successfully demonstrated that robotic liquid handling can be used reliably from DNA extraction to final library preparation on a single deck, thereby substantially increasing throughput, reducing costs, and increasing data robustness for biodiversity assessments and monitoring.

Comparison of Design Approaches for Low-Cost Sampling Mechanisms in Open-Source Chemical Instrumentation

Robotic positioning systems are used in a variety of chemical instruments, primarily for liquid handling purposes, such as autosamplers from vials or well plates. Here, two approaches to the design of open-source autosampler positioning systems for use with 96-well plates are described and compared. The first system, a 3-axis design similar to many low-cost 3D printers that are available on the market, is constructed using an aluminum design and stepper motors. The other system relies upon a series of 3D printed parts to achieve movement with a series of linker arms based on Selective Compliance Assembly Robot Arm (SCARA) design principles. Full printer design files, assembly instructions, software, and user directions are included for both samplers. The positioning precision of the 3-axis system is better than the SCARA mechanism due to finer motor control, albeit with a slightly higher cost of materials. Based on the improved precision of this approach, the 3-axis autosampler system was used to demonstrate the generation of a segmented flow droplet stream from adjacent wells within a 96-well plate.

Automation of single-cell proteomic sample preparation

Molecular heterogeneity exists at different spatial scales in biological samples and is an important parameter in the development of pathologies and resistances to therapies. When aiming to reach molecular heterogeneity of cells at extremely low spatial scales, single-cell analysis can be the ultimate choice. Proteomics performed in bulk population of cells (macroproteomics) is prone to mask molecular heterogeneity. Mass spectrometry-based single cell proteomics (SCP-MS) is the right solution to overcome this issue. Three main problems can be identified using SCP-MS: (i) analytical loss during sample preparation, (ii) inefficient microinjection/delivery of proteins/peptides from samples to MS and (iii) low analytical throughput. Technologies for automation of SCP have recently gained attention to improve methods accuracy, sensitivity, throughput and in-depth and low-biased proteome analysis. In this minireview, we therefore overview the state-of-the-art of automation of SCP-MS sample preparation approaches.

Sample Preparation and Diagnostic Methods for a Variety of Settings: A Comprehensive Review

Sample preparation is an essential step for nearly every type of biochemical analysis in use today. Among the most important of these analyses is the diagnosis of diseases, since their treatment may rely greatly on time and, in the case of infectious diseases, containing their spread within a population to prevent outbreaks. To address this, many different methods have been developed for use in the wide variety of settings for which they are needed. In this work, we have reviewed the literature and report on a broad range of methods that have been developed in recent years and their applications to point-of-care (POC), high-throughput screening, and low-resource and traditional clinical settings for diagnosis, including some of those that were developed in response to the coronavirus disease 2019 (COVID-19) pandemic. In addition to covering alternative approaches and improvements to traditional sample preparation techniques such as extractions and separations, techniques that have been developed with focuses on integration with smart devices, laboratory automation, and biosensors are also discussed.

Review of Methodological Approaches to Human Milk Small Extracellular Vesicle Proteomics

Proteomics can map extracellular vesicles (EVs), including exosomes, across disease states between organisms and cell types. Due to the diverse origin and cargo of EVs, tailoring methodological and analytical techniques can support the reproducibility of results. Proteomics scans are sensitive to in-sample contaminants, which can be retained during EV isolation procedures. Contaminants can also arise from the biological origin of exosomes, such as the lipid-rich environment in human milk. Human milk (HM) EVs and exosomes are emerging as a research interest in health and disease, though the experimental characterization and functional assays remain varied. Past studies of HM EV proteomes have used data-dependent acquisition methods for protein detection, however, improvements in data independent acquisition could allow for previously undetected EV proteins to be identified by mass spectrometry. Depending on the research question, only a specific population of proteins can be compared and measured using isotope and other labelling techniques. In this review, we summarize published HM EV proteomics protocols and suggest a methodological workflow with the end-goal of effective and reproducible analysis of human milk EV proteomes.

A Semiautomated Paramagnetic Bead-Based Platform for Isobaric Tag Sample Preparation

The development of streamlined and high-throughput sample processing workflows is important for capitalizing on emerging advances and innovations in mass spectrometry-based applications. While the adaptation of new technologies and improved methodologies is fast paced, automation of upstream sample processing often lags. Here we have developed and implemented a semiautomated paramagnetic bead-based platform for isobaric tag sample preparation. We benchmarked the robot-assisted platform by comparing the protein abundance profiles of six common parental laboratory yeast strains in triplicate TMTpro16-plex experiments against an identical set of experiments in which the samples were manually processed. Both sets of experiments quantified similar numbers of proteins and peptides with good reproducibility. Using these data, we constructed an interactive website to explore the proteome profiles of six yeast strains. We also provide the community with open-source templates for automating routine proteomics workflows on an opentrons OT-2 liquid handler. The robot-assisted platform offers a versatile and affordable option for reproducible sample processing for a wide range of protein profiling applications.

Microfluidic Magnetic Analyte Delivery Technique for Separation, Enrichment, and Fluorescence Detection of Ultratrace Biomarkers

A microfluidic magnetic analyte delivery (μMAD) technique was developed to realize sample preparation and ultrasensitive biomarker detection. A simply designed microfluidic device was employed to carry out this technique, including a poly(dimethylsiloxane)-glass hybrid microchip having four straight rectangular channels and a permanent magnet. In the μMAD process, functionalized magnetic beads (MBs) were used to recognize and isolate analytes from a complex sample matrix, deliver analytes into tiny microchannels, and preconcentrate analytes in the magnetic trapping/detection region for in situ fluorescence detection. In the feasibility study and sensitivity optimization, horseradish peroxidase-labeled MBs were used, and critical parameters for the signal amplification performance of μMAD were carefully evaluated. At optimized conditions, a sensitivity improvement of at least 2 orders of magnitude was achieved. As a proof of concept, μMAD was combined with the enzyme-linked immunosorbent assay (ELISA), while carcinoembryonic antigen (CEA), prostate-specific antigen (PSA), and interleukin 6 (IL-6) were selected as model biomarkers. The limits of detection (LODs) of μMAD-ELISA were as low as 0.29 pg/mL for CEA, 0.047 pg/mL for PSA, and 0.021 pg/mL for IL-6, which corresponded to an over 200-fold reduction compared to their commercial ELISA results. Meanwhile, μMAD-ELISA revealed high selectivity and reproducibility. In clinical sample analysis, good accuracy was acquired for human serum analysis relative to commercial ELISA kits, and satisfied recoveries of 85.1-102% with RSDs of 1.7-9.8% for IL-6 and 84.7-113% with RSDs of 3.2-8.3% for interferon-γ were obtained. This ultrasensitive and easy operation technique provides a valuable approach for trace-level biomarker detection for practical applications.

Integrated Proteomic and Metabolomic Analysis of the Testes Characterizes BDE-47-Induced Reproductive Toxicity in Mice

A representative congener of polybrominated diphenyl ethers in the environment, 2,2',4,4'-tetrabromodiphenyl ether (BDE-47), is associated with male reproductive toxicity, yet the underlying mechanisms remain largely unclear. In this study, mice were administered environmentally relevant concentrations of BDE-47 for six weeks. Histopathological observations showed that BDE-47 induced inflammatory reactions and damaged the testes. By conducting an integrated proteomic and metabolomic analysis coupled with a bioinformatic analysis using ingenuity pathway analysis (IPA) methods, we found that BDE-47 mainly affected the molecules involved in free radical scavenging, cell death and survival, neurological disease, and inflammatory response. IPA canonical pathways showed inflammatory and apoptosis pathways, including hepatic fibrosis/hepatic stellate cell activation, the GP6 signaling pathway, tight junction signaling, acute phase response signaling, LXR/RXR activation, unfolded protein response, and FXR/RXR activation, which are related to male reproductive toxicity. Key transcriptional regulator networks were activated via a focus on upstream regulator analysis. The expression of MYC and Clu as the core transcriptional factor and targeted protein, respectively, was verified. It is further proposed that MYC may contribute to the etiology of male reproductive toxicity. These findings will improve our understanding of the mechanisms responsible for BDE-47-induced male reproductive toxicity, which may promote the discovery of useful biomarkers indicative of BDE-47 exposure.

Investigation of the lipidomic changes in differentiated glioblastoma cells after drug treatment using MALDI-MS

Lipids differences between tumor and normal tissue have been proved to be of diagnostic and therapeutic significance. The research of lipidomics in tumor is more and more important. Mass spectrometry like matrix-assisted laser desorption ionization-mass spectrometry (MALDI-MS) can be more convenient and informative for lipids researching in biological and clinical researches. Most of malignant tumors like glioblastoma are characterized by incomplete differentiation, so differentiation therapy has made important progress in tumor treatment. Lipid profiles changes after therapy are worthy investigating. In our study, glioblastoma cell line U87-MG cells were treated by inducers of sodium phenylbutyrate (SPB) and all-trans retinoic acid (ATRA). The changes in lipids on cell membrane were profiled by MALDI-MS. The differentiation degree was assessed by cell proliferation, cell cycle, morphology and protein expression before MALDI-MS analysis. Comparing the inducer treated and untreated U87-MG cells, reduced proliferation rate, blocked cell cycle, benign nucleus morphology and changed expression of protein CD133 and glial fibrillary acidic protein (GFAP), were found after drug treatment. Moreover, the lipids of cell membrane presented distinguished differences in the drug treated cells. Most of the glycerophosphocholines (PC) with an increasing abundance are unsaturated PCs (PC (38:1), 816 m/z; PC (36:1), 788 m/z; PC (31:1), 725 m/z), and those decreasing are saturated PCs (PC (32:0), 734 m/z). These results provide the lipidomic differentiation which may be a significant guidance for evaluating the therapeutic effect of tumor therapy.

Alterations of the Platelet Proteome in Lung Cancer: Accelerated F13A1 and ER Processing as New Actors in Hypercoagulability

Simple Summary

The risk of venous thromboembolism in cancer is nine times higher than in the general population and the second leading cause of death in these patients. Tissue factor and downstream plasmatic coagulation cascade are largely responsible for the risk of thrombosis in cancer. In recent years, it has been increasingly recognised that platelets also play a central role in tumour growth and cancer-associated thrombosis. The underlying molecular mechanisms are largely unknown. In order to comprehensively investigate the biochemical changes in platelets from cancers with high risk of thrombosis, we examined the platelet proteome of brain and lung cancer patients in comparison to sex and age-matched healthy controls. However, we only found alterations in lung cancer, where some of these platelet proteins directly promote thrombosis. One example is the increased amount of the enzyme protein disulfide isomerase, which is clinically investigated as an antithrombotic drug target of the plant-based flavonol quercetin.

Abstract

In order to comprehensively expose cancer-related biochemical changes, we compared the platelet proteome of two types of cancer with a high risk of thrombosis (22 patients with brain cancer, 19 with lung cancer) to 41 matched healthy controls using unbiased two-dimensional differential in-gel electrophoresis. The examined platelet proteome was unchanged in patients with brain cancer, but considerably affected in lung cancer with 15 significantly altered proteins. Amongst these, the endoplasmic reticulum (ER) proteins calreticulin (CALR), endoplasmic reticulum chaperone BiP (HSPA5) and protein disulfide-isomerase (P4HB) were significantly elevated. Accelerated conversion of the fibrin stabilising factor XIII was detected in platelets of patients with lung cancer by elevated levels of a coagulation factor XIII (F13A1) 55 kDa fragment. A significant correlation of this F13A1 cleavage product with plasma levels of the plasmin–α-2-antiplasmin complex and D-dimer suggests its enhanced degradation by the fibrinolytic system. Protein association network analysis showed that lung cancer-related proteins were involved in platelet degranulation and upregulated ER protein processing. As a possible outcome, plasma FVIII, an immediate end product for ER-mediated glycosylation, correlated significantly with the ER-executing chaperones CALR and HSPA5. These new data on the differential behaviour of platelets in various cancers revealed F13A1 and ER chaperones as potential novel diagnostic and therapeutic targets in lung cancer patients.

Endoplasmic Reticulum Subproteome Analysis Reveals Underlying Defense Mechanisms of Wheat Seedling Leaves under Salt Stress

Salt stress is the second most important abiotic stress factor in the world, which seriously affects crop growth, development and grain production. In this study, we performed the first integrated physiological and endoplasmic reticulum (ER) proteome analysis of wheat seedling leaves under salt stress using a label-free-based quantitative proteomic approach. Salt stress caused significant decrease in seedling height, root length, relative water content and chlorophyll content of wheat seedling leaves, indicating that wheat seedling growth was significantly inhibited under salt stress. The ER proteome analysis identified 233 ER-localized differentially accumulated proteins (DAPs) in response to salt stress, including 202 upregulated and 31 downregulated proteins. The upregulated proteins were mainly involved in the oxidation-reduction process, transmembrane transport, the carboxylic acid metabolic process, stress response, the arbohydrate metabolic process and proteolysis, while the downregulated proteins mainly participated in the metabolic process, biological regulation and the cellular process. In particular, salt stress induced significant upregulation of protein disulfide isomerase-like proteins and heat shock proteins and significant downregulation of ribosomal protein abundance. Further transcript expression analysis revealed that half of the detected DAP genes showed a consistent pattern with their protein levels under salt stress. A putative metabolic pathway of ER subproteome of wheat seedling leaves in response to salt stress was proposed, which reveals the potential roles of wheat ER proteome in salt stress response and defense.

Omics and Artificial Intelligence to Improve In Vitro Fertilization (IVF) Success: A Proposed Protocol

The prediction of in vitro fertilization (IVF) outcome is an imperative achievement in assisted reproduction, substantially aiding infertile couples, health systems and communities. To date, the assessment of infertile couples depends on medical/reproductive history, biochemical indications and investigations of the reproductive tract, along with data obtained from previous IVF cycles, if any. Our project aims to develop a novel tool, integrating omics and artificial intelligence, to propose optimal treatment options and enhance treatment success rates. For this purpose, we will proceed with the following: (1) recording subfertile couples’ lifestyle and demographic parameters and previous IVF cycle characteristics; (2) measurement and evaluation of metabolomics, transcriptomics and biomarkers, and deep machine learning assessment of the oocyte, sperm and embryo; (3) creation of artificial neural network models to increase objectivity and accuracy in comparison to traditional techniques for the improvement of the success rates of IVF cycles following an IVF failure. Therefore, “omics” data are a valuable parameter for embryo selection optimization and promoting personalized IVF treatment. “Omics” combined with predictive models will substantially promote health management individualization; contribute to the successful treatment of infertile couples, particularly those with unexplained infertility or repeated implantation failures; and reduce multiple gestation rates.

A New Era of Neuro-Oncology Research Pioneered by Multi-Omics Analysis and Machine Learning

Although the incidence of central nervous system (CNS) cancers is not high, it significantly reduces a patient’s quality of life and results in high mortality rates. A low incidence also means a low number of cases, which in turn means a low amount of information. To compensate, researchers have tried to increase the amount of information available from a single test using high-throughput technologies. This approach, referred to as single-omics analysis, has only been partially successful as one type of data may not be able to appropriately describe all the characteristics of a tumor. It is presently unclear what type of data can describe a particular clinical situation. One way to solve this problem is to use multi-omics data. When using many types of data, a selected data type or a combination of them may effectively resolve a clinical question. Hence, we conducted a comprehensive survey of papers in the field of neuro-oncology that used multi-omics data for analysis and found that most of the papers utilized machine learning techniques. This fact shows that it is useful to utilize machine learning techniques in multi-omics analysis. In this review, we discuss the current status of multi-omics analysis in the field of neuro-oncology and the importance of using machine learning techniques.

Proteomics in Forensic Analysis: Applications for Human Samples

Proteomics, the large-scale study of all proteins of an organism or system, is a powerful tool for studying biological systems. It can provide a holistic view of the physiological and biochemical states of given samples through identification and quantification of large numbers of peptides and proteins. In forensic science, proteomics can be used as a confirmatory and orthogonal technique for well-built genomic analyses. Proteomics is highly valuable in cases where nucleic acids are absent or degraded, such as hair and bone samples. It can be used to identify body fluids, ethnic group, gender, individual, and estimate post-mortem interval using bone, muscle, and decomposition fluid samples. Compared to genomic analysis, proteomics can provide a better global picture of a sample. It has been used in forensic science for a wide range of sample types and applications. In this review, we briefly introduce proteomic methods, including sample preparation techniques, data acquisition using liquid chromatography-tandem mass spectrometry, and data analysis using database search, spectral library search, and de novo sequencing. We also summarize recent applications in the past decade of proteomics in forensic science with a special focus on human samples, including hair, bone, body fluids, fingernail, muscle, brain, and fingermark, and address the challenges, considerations, and future developments of forensic proteomics.

Proteome of Stored RBC Membrane and Vesicles from Heterozygous Beta Thalassemia Donors

Genetic characteristics of blood donors may impact the storability of blood products. Despite higher basal stress, red blood cells (RBCs) from eligible donors that are heterozygous for beta-thalassemia traits (βThal⁺) possess a differential nitrogen-related metabolism, and cope better with storage stress compared to the control. Nevertheless, not much is known about how storage impacts the proteome of membrane and extracellular vesicles (EVs) in βThal⁺. For this purpose, RBC units from twelve βThal⁺ donors were studied through proteomics, immunoblotting, electron microscopy, and functional ELISA assays, versus units from sex- and aged-matched controls. βThal⁺ RBCs exhibited less irreversible shape modifications. Their membrane proteome was characterized by different levels of structural, lipid raft, transport, chaperoning, redox, and enzyme components. The most prominent findings include the upregulation of myosin proteoforms, arginase-1, heat shock proteins, and protein kinases, but the downregulation of nitrogen-related transporters. The unique membrane proteome was also mirrored, in part, to that of βThal⁺ EVs. Network analysis revealed interesting connections of membrane vesiculation with storage and stress hemolysis, along with proteome control modulators of the RBC membrane. Our findings, which are in line with the mild but consistent oxidative stress these cells experience in vivo, provide insight into the physiology and aging of stored βThal⁺ RBCs.

N-Glycomics of Cerebrospinal Fluid: Method Comparison

Cerebrospinal fluid (CSF) contains valuable biological and neurological information. However, its glycomics analysis is hampered due to the low amount of protein in the biofluid, as has been demonstrated by other glycomics studies using a substantial amount of CSF. In this work, we investigated different N-glycan sample preparation approaches to develop a more sensitive method. These methods, one with an increased amount of buffer solution during the N-glycan release step with a lower amount of sample volume and the other with Filter-Aided N-Glycan Separation (FANGS), were compared with recent work to demonstrate their effectiveness. It was demonstrated that an increased amount of buffer solution showed higher intensity in comparison to the previously published method and FANGS. This suggested that digestion efficiency during the N-glycan release step was not in an optimal condition from the previously published method, and that there is a substantial loss of sample with FANGS when preparing N-glycans from CSF.

Microproteomic sample preparation

Multiple applications of proteomics in life and health science, pathology and pharmacology, require handling size-limited cell and tissue samples. During proteomic sample preparation, analyte loss in these samples arises when standard procedures are used. Thus, specific considerations have to be taken into account for processing, that are summarised under the term microproteomics (μPs). Microproteomic workflows include: sampling (e.g., flow cytometry, laser capture microdissection), sample preparation (possible disruption of cells or tissue pieces via lysis, protein extraction, digestion in bottom-up approaches, and sample clean-up) and analysis (chromatographic or electrophoretic separation, mass spectrometric measurements and statistical/bioinformatic evaluation). All these steps must be optimised to reach wide protein dynamic ranges and high numbers of identifications. Under optimal conditions, sampling is adapted to the studied sample types and nature, sample preparation isolates and enriches the whole protein content, clean-up removes salts and other interferences such as detergents or chaotropes, and analysis identifies as many analytes as the instrumental throughput and sensitivity allow. In the suggested review, we present and discuss the current state in μP applications for processing of small number of cells (cell μPs) and microscopic tissue regions (tissue μPs).

Circulating tumor DNA analysis for tumor diagnosis

Tumor is a kind of abnormal organism generated by the proliferation and differentiation of cells in the body under the action of various initiating and promoting factors, which seriously threatens human life and health. Tumorigenesis is a gradual process that involves multistage reactions and the accumulation of mutations. Gene mutation usually occurs during tumorigenesis, and can be used for tumor diagnosis. Early diagnosis is the most effective way to improve the cure rate and reduce the mortality rate. Among the peripheral blood circulating tumor DNA (ctDNA), gene mutation in keeping with tumor cells can be detected, which can potentially replace tumor tissue section for early diagnosis. It has been considered as a liquid biopsy marker with good clinical application prospect. However, the high fragmentation and low concentration of ctDNA in blood result in the difficulty of tumor stage determination. Therefore, high sensitive and specific mutation detection methods have been developed to detect trace mutant ctDNA. At present, the approaches include digital PCR (dPCR), Bead, Emulsion, Amplification and Magnetic (BEAMing), Next Generation Sequencing (NGS), Amplification Refractory Mutation System (ARMS), etc. In this paper, the principle, characteristics, latest progress and application prospects of these methods are reviewed, which will facilitate researchers to choose appropriate ctDNA detection approaches.

Microheterogeneity and preanalytical stability of protein biomarkers of inflammation and renal function

Protein biomarker microheterogeneity has attracted increasing attention in epidemiological and clinical research studies. Knowledge concerning the preanalytical stability of proteins is paramount to assess the biological significance of their proteoforms. We investigated the stability of the inflammatory markers C-reactive protein (CRP), serum amyloid A (SAA), and calprotectin (S100A8/9), and the renal function marker, cystatin C (CnC). In total 16 proteoforms were quantified by immuno-MALDI-TOF MS in EDTA plasma and serum samples from 15 healthy volunteers. Prior to analysis blood samples were stored at either room temperature from 1 h up to 8 days, or underwent up to 9 consecutive freeze/thaw cycles. Pearson's correlation coefficient and t-test, intra-class correlation coefficient (ICC), and Autoregressive Integrated Moving-Average (ARIMA) models were used to investigate the stability of proteoform concentrations and distributions in blood. Plasma and serum concentrations of CRP and SAA proteoforms were highly stable during room temperature exposure and repeated freeze/thaw cycles, demonstrating excellent reproducibility (ICC > 0.75), no serial dependency in ARIMA models, and stable distribution of proteoforms. Stability analyses for proteoforms of S100A8/9 and CnC identified only minor preanalytical changes in concentrations and distributions, and none of the proteoforms were produced during prolonged exposure to room temperature or repeated freezing/thawing. The four proteins and their proteoforms are stable during sub-optimal sample handling, and represent robust biomarker candidates for future biobank studies aimed at investigating the microheterogeneity of SAA, S100A8/9, and CnC in relation to inflammation, renal dysfunction and various clinical outcomes.

Development of a Microplate Platform for High-Throughput Sample Preparation Based on Microwave Metasurfaces

Sample preparation is one of the most time-consuming steps in diagnostic assays, particularly those involving biological samples. In this paper we report the results of finite-difference time-domain (FDTD) simulations and thermographic imaging experiments carried out with the intent of designing a microplate for rapid, high-throughput sample preparation to aid diagnostic assays. This work is based on devices known as microwave lysing triangles (MLTs) that have been proven capable of rapid sample preparation when irradiated in a standard microwave cavity. FDTD software was used to model a microplate platform as a polystyrene substrate with an array of various passive scattering elements (PSEs) of different sizes, shapes, and interelement spacings in a 2.45 GHz field identical to that of a common microwave oven. Based on the FDTD modeling, several PSE arrays were fabricated by cutting PSEs out of aluminum foil and adhering them to the bottom of regular polystyrene microplates to make prototypes. Each prototype microplate was then irradiated in a microwave cavity for a range of different times, powers, and source angles and the heating effects were observed via a forward looking infrared (FLIR) camera. Based on the results, two prototype microplate platforms have been shown to demonstrate electromagnetic and thermal enhancements similar to those seen with MLTs as well as tunable thermal responses to radio frequency (RF) irradiation.

Automation of Immunoglobulin Glycosylation Analysis

The development of reliable, affordable, high-resolution glycomics technologies that can be used for many samples in a high-throughput manner are essential for both the optimization of glycosylation in the biopharmaceutical industry as well as for the advancement of clinical diagnostics based on glycosylation biomarkers. We will use this chapter to review the sample preparation processes that have been used on liquid-handling robots to obtain high-quality glycomics data for both biopharmaceutical and clinical antibody samples. This will focus on glycoprotein purification, followed by glycan or glycopeptide generation, derivatization and enrichment. The use of liquid-handling robots for glycomics studies on other sample types beyond antibodies will not be discussed here. We will summarize our thoughts on the current status of the field and explore the benefits and challenges associated with developing and using automated platforms for sample preparation. Finally, the future outlook for the automation of glycomics will be discussed along with a projected impact on the field in general.

Hydrogen-Deuterium Exchange Mass Spectrometry: A Novel Structural Biology Approach to Structure, Dynamics and Interactions of Proteins and Their Complexes

Hydrogen/Deuterium eXchange Mass Spectrometry (HDX-MS) is a rapidly evolving technique for analyzing structural features and dynamic properties of proteins. It may stand alone or serve as a complementary method to cryo-electron-microscopy (EM) or other structural biology approaches. HDX-MS is capable of providing information on individual proteins as well as large protein complexes. Owing to recent methodological advancements and improving availability of instrumentation, HDX-MS is becoming a routine technique for some applications. When dealing with samples of low to medium complexity and sizes of less than 150 kDa, conformation and ligand interaction analyses by HDX-MS are already almost routine applications. This is also well supported by the rapid evolution of the computational (software) background that facilitates the analysis of the obtained experimental data. HDX-MS can cope at times with analytes that are difficult to tackle by any other approach. Large complexes like viral capsids as well as disordered proteins can also be analyzed by this method. HDX-MS has recently become an established tool in the drug discovery process and biopharmaceutical development, as it is now also capable of dissecting post-translational modifications and membrane proteins. This mini review provides the reader with an introduction to the technique and a brief overview of the most common applications. Furthermore, the most challenging likely applications, the analyses of glycosylated and membrane proteins, are also highlighted.

Insight to Functional Conformation and Noncovalent Interactions of Protein-Protein Assembly Using MALDI Mass Spectrometry

Noncovalent interactions are the keys to the structural organization of biomolecule e.g., proteins, glycans, lipids in the process of molecular recognition processes e.g., enzyme-substrate, antigen-antibody. Protein interactions lead to conformational changes, which dictate the functionality of that protein-protein complex. Besides biophysics techniques, noncovalent interaction and conformational dynamics, can be studied via mass spectrometry (MS), which represents a powerful tool, due to its low sample consumption, high sensitivity, and label-free sample. In this review, the focus will be placed on Matrix-Assisted Laser Desorption Ionization Mass Spectrometry (MALDI-MS) and its role in the analysis of protein-protein noncovalent assemblies exploring the relationship within noncovalent interaction, conformation, and biological function.

Elevating Chemistry Research with a Modern Electronics Toolkit

With the rapid development of high technology, chemical science is not as it used to be a century ago. Many chemists acquire and utilize skills that are well beyond the traditional definition of chemistry. The digital age has transformed chemistry laboratories. One aspect of this transformation is the progressing implementation of electronics and computer science in chemistry research. In the past decade, numerous chemistry-oriented studies have benefited from the implementation of electronic modules, including microcontroller boards (MCBs), single-board computers (SBCs), professional grade control and data acquisition systems, as well as field-programmable gate arrays (FPGAs). In particular, MCBs and SBCs provide good value for money. The application areas for electronic modules in chemistry research include construction of simple detection systems based on spectrophotometry and spectrofluorometry principles, customizing laboratory devices for automation of common laboratory practices, control of reaction systems (batch- and flow-based), extraction systems, chromatographic and electrophoretic systems, microfluidic systems (classical and nonclassical), custom-built polymerase chain reaction devices, gas-phase analyte detection systems, chemical robots and drones, construction of FPGA-based imaging systems, and the Internet-of-Chemical-Things. The technology is easy to handle, and many chemists have managed to train themselves in its implementation. The only major obstacle in its implementation is probably one's imagination.